essay paper synonym

Synonyms of essay

• as in article
• as in attempt
• as in to attempt
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Thesaurus Definition of essay

 (Entry 1 of 2)

Synonyms & Similar Words

• dissertation
• composition
• prolegomenon
• undertaking
• trial and error
• experimentation

Thesaurus Definition of essay  (Entry 2 of 2)

• have a go at
• try one's hand (at)

Antonyms & Near Antonyms

Synonym Chooser

How does the verb essay differ from other similar words?

Some common synonyms of essay are attempt , endeavor , strive , and try . While all these words mean "to make an effort to accomplish an end," essay implies difficulty but also suggests tentative trying or experimenting.

When might attempt be a better fit than essay ?

While the synonyms attempt and essay are close in meaning, attempt stresses the initiation or beginning of an effort.

Where would endeavor be a reasonable alternative to essay ?

Although the words endeavor and essay have much in common, endeavor heightens the implications of exertion and difficulty.

When is strive a more appropriate choice than essay ?

While in some cases nearly identical to essay , strive implies great exertion against great difficulty and specifically suggests persistent effort.

How do try and attempt relate to one another, in the sense of essay ?

Try is often close to attempt but may stress effort or experiment made in the hope of testing or proving something.

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“Essay.” Merriam-Webster.com Thesaurus , Merriam-Webster, https://www.merriam-webster.com/thesaurus/essay. Accessed 11 Apr. 2024.

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Synonyms of 'essay' in British English

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Word Choice

What this handout is about.

This handout can help you revise your papers for word-level clarity, eliminate wordiness and avoid clichés, find the words that best express your ideas, and choose words that suit an academic audience.

Introduction

Writing is a series of choices. As you work on a paper, you choose your topic, your approach, your sources, and your thesis; when it’s time to write, you have to choose the words you will use to express your ideas and decide how you will arrange those words into sentences and paragraphs. As you revise your draft, you make more choices. You might ask yourself, “Is this really what I mean?” or “Will readers understand this?” or “Does this sound good?” Finding words that capture your meaning and convey that meaning to your readers is challenging. When your instructors write things like “awkward,” “vague,” or “wordy” on your draft, they are letting you know that they want you to work on word choice. This handout will explain some common issues related to word choice and give you strategies for choosing the best words as you revise your drafts.

As you read further into the handout, keep in mind that it can sometimes take more time to “save” words from your original sentence than to write a brand new sentence to convey the same meaning or idea. Don’t be too attached to what you’ve already written; if you are willing to start a sentence fresh, you may be able to choose words with greater clarity.

For tips on making more substantial revisions, take a look at our handouts on reorganizing drafts and revising drafts .

“Awkward,” “vague,” and “unclear” word choice

So: you write a paper that makes perfect sense to you, but it comes back with “awkward” scribbled throughout the margins. Why, you wonder, are instructors so fond of terms like “awkward”? Most instructors use terms like this to draw your attention to sentences they had trouble understanding and to encourage you to rewrite those sentences more clearly.

Difficulties with word choice aren’t the only cause of awkwardness, vagueness, or other problems with clarity. Sometimes a sentence is hard to follow because there is a grammatical problem with it or because of the syntax (the way the words and phrases are put together). Here’s an example: “Having finished with studying, the pizza was quickly eaten.” This sentence isn’t hard to understand because of the words I chose—everybody knows what studying, pizza, and eating are. The problem here is that readers will naturally assume that first bit of the sentence “(Having finished with studying”) goes with the next noun that follows it—which, in this case, is “the pizza”! It doesn’t make a lot of sense to imply that the pizza was studying. What I was actually trying to express was something more like this: “Having finished with studying, the students quickly ate the pizza.” If you have a sentence that has been marked “awkward,” “vague,” or “unclear,” try to think about it from a reader’s point of view—see if you can tell where it changes direction or leaves out important information.

Sometimes, though, problems with clarity are a matter of word choice. See if you recognize any of these issues:

• Misused words —the word doesn’t actually mean what the writer thinks it does. Example : Cree Indians were a monotonous culture until French and British settlers arrived. Revision: Cree Indians were a homogenous culture.
• Words with unwanted connotations or meanings. Example : I sprayed the ants in their private places. Revision: I sprayed the ants in their hiding places.
• Using a pronoun when readers can’t tell whom/what it refers to. Example : My cousin Jake hugged my brother Trey, even though he didn’t like him very much. Revision: My cousin Jake hugged my brother Trey, even though Jake doesn’t like Trey very much.
• Jargon or technical terms that make readers work unnecessarily hard. Maybe you need to use some of these words because they are important terms in your field, but don’t throw them in just to “sound smart.” Example : The dialectical interface between neo-Platonists and anti-disestablishment Catholics offers an algorithm for deontological thought. Revision : The dialogue between neo-Platonists and certain Catholic thinkers is a model for deontological thought.
• Loaded language. Sometimes we as writers know what we mean by a certain word, but we haven’t ever spelled that out for readers. We rely too heavily on that word, perhaps repeating it often, without clarifying what we are talking about. Example : Society teaches young girls that beauty is their most important quality. In order to prevent eating disorders and other health problems, we must change society. Revision : Contemporary American popular media, like magazines and movies, teach young girls that beauty is their most important quality. In order to prevent eating disorders and other health problems, we must change the images and role models girls are offered.

Sometimes the problem isn’t choosing exactly the right word to express an idea—it’s being “wordy,” or using words that your reader may regard as “extra” or inefficient. Take a look at the following list for some examples. On the left are some phrases that use three, four, or more words where fewer will do; on the right are some shorter substitutes:

Keep an eye out for wordy constructions in your writing and see if you can replace them with more concise words or phrases.

In academic writing, it’s a good idea to limit your use of clichés. Clichés are catchy little phrases so frequently used that they have become trite, corny, or annoying. They are problematic because their overuse has diminished their impact and because they require several words where just one would do.

The main way to avoid clichés is first to recognize them and then to create shorter, fresher equivalents. Ask yourself if there is one word that means the same thing as the cliché. If there isn’t, can you use two or three words to state the idea your own way? Below you will see five common clichés, with some alternatives to their right. As a challenge, see how many alternatives you can create for the final two examples.

Try these yourself:

Writing for an academic audience

When you choose words to express your ideas, you have to think not only about what makes sense and sounds best to you, but what will make sense and sound best to your readers. Thinking about your audience and their expectations will help you make decisions about word choice.

Some writers think that academic audiences expect them to “sound smart” by using big or technical words. But the most important goal of academic writing is not to sound smart—it is to communicate an argument or information clearly and convincingly. It is true that academic writing has a certain style of its own and that you, as a student, are beginning to learn to read and write in that style. You may find yourself using words and grammatical constructions that you didn’t use in your high school writing. The danger is that if you consciously set out to “sound smart” and use words or structures that are very unfamiliar to you, you may produce sentences that your readers can’t understand.

When writing for your professors, think simplicity. Using simple words does not indicate simple thoughts. In an academic argument paper, what makes the thesis and argument sophisticated are the connections presented in simple, clear language.

Keep in mind, though, that simple and clear doesn’t necessarily mean casual. Most instructors will not be pleased if your paper looks like an instant message or an email to a friend. It’s usually best to avoid slang and colloquialisms. Take a look at this example and ask yourself how a professor would probably respond to it if it were the thesis statement of a paper: “Moulin Rouge really bit because the singing sucked and the costume colors were nasty, KWIM?”

Selecting and using key terms

When writing academic papers, it is often helpful to find key terms and use them within your paper as well as in your thesis. This section comments on the crucial difference between repetition and redundancy of terms and works through an example of using key terms in a thesis statement.

Repetition vs. redundancy

These two phenomena are not necessarily the same. Repetition can be a good thing. Sometimes we have to use our key terms several times within a paper, especially in topic sentences. Sometimes there is simply no substitute for the key terms, and selecting a weaker term as a synonym can do more harm than good. Repeating key terms emphasizes important points and signals to the reader that the argument is still being supported. This kind of repetition can give your paper cohesion and is done by conscious choice.

In contrast, if you find yourself frustrated, tiredly repeating the same nouns, verbs, or adjectives, or making the same point over and over, you are probably being redundant. In this case, you are swimming aimlessly around the same points because you have not decided what your argument really is or because you are truly fatigued and clarity escapes you. Refer to the “Strategies” section below for ideas on revising for redundancy.

Building clear thesis statements

Writing clear sentences is important throughout your writing. For the purposes of this handout, let’s focus on the thesis statement—one of the most important sentences in academic argument papers. You can apply these ideas to other sentences in your papers.

A common problem with writing good thesis statements is finding the words that best capture both the important elements and the significance of the essay’s argument. It is not always easy to condense several paragraphs or several pages into concise key terms that, when combined in one sentence, can effectively describe the argument.

However, taking the time to find the right words offers writers a significant edge. Concise and appropriate terms will help both the writer and the reader keep track of what the essay will show and how it will show it. Graders, in particular, like to see clearly stated thesis statements. (For more on thesis statements in general, please refer to our handout .)

Example : You’ve been assigned to write an essay that contrasts the river and shore scenes in Mark Twain’s Huckleberry Finn. You work on it for several days, producing three versions of your thesis:

Version 1 : There are many important river and shore scenes in Huckleberry Finn.

Version 2 : The contrasting river and shore scenes in Huckleberry Finn suggest a return to nature.

Version 3 : Through its contrasting river and shore scenes, Twain’s Huckleberry Finn suggests that to find the true expression of American democratic ideals, one must leave “civilized” society and go back to nature.

Let’s consider the word choice issues in these statements. In Version 1, the word “important”—like “interesting”—is both overused and vague; it suggests that the author has an opinion but gives very little indication about the framework of that opinion. As a result, your reader knows only that you’re going to talk about river and shore scenes, but not what you’re going to say. Version 2 is an improvement: the words “return to nature” give your reader a better idea where the paper is headed. On the other hand, they still do not know how this return to nature is crucial to your understanding of the novel.

Finally, you come up with Version 3, which is a stronger thesis because it offers a sophisticated argument and the key terms used to make this argument are clear. At least three key terms or concepts are evident: the contrast between river and shore scenes, a return to nature, and American democratic ideals.

By itself, a key term is merely a topic—an element of the argument but not the argument itself. The argument, then, becomes clear to the reader through the way in which you combine key terms.

Strategies for successful word choice

• Be careful when using words you are unfamiliar with. Look at how they are used in context and check their dictionary definitions.
• Be careful when using the thesaurus. Each word listed as a synonym for the word you’re looking up may have its own unique connotations or shades of meaning. Use a dictionary to be sure the synonym you are considering really fits what you are trying to say.
• Under the present conditions of our society, marriage practices generally demonstrate a high degree of homogeneity.
• In our culture, people tend to marry others who are like themselves. (Longman, p. 452)
• Before you revise for accurate and strong adjectives, make sure you are first using accurate and strong nouns and verbs. For example, if you were revising the sentence “This is a good book that tells about the Revolutionary War,” think about whether “book” and “tells” are as strong as they could be before you worry about “good.” (A stronger sentence might read “The novel describes the experiences of a soldier during the Revolutionary War.” “Novel” tells us what kind of book it is, and “describes” tells us more about how the book communicates information.)
• Try the slash/option technique, which is like brainstorming as you write. When you get stuck, write out two or more choices for a questionable word or a confusing sentence, e.g., “questionable/inaccurate/vague/inappropriate.” Pick the word that best indicates your meaning or combine different terms to say what you mean.
• Look for repetition. When you find it, decide if it is “good” repetition (using key terms that are crucial and helpful to meaning) or “bad” repetition (redundancy or laziness in reusing words).
• Write your thesis in five different ways. Make five different versions of your thesis sentence. Compose five sentences that express your argument. Try to come up with four alternatives to the thesis sentence you’ve already written. Find five possible ways to communicate your argument in one sentence to your reader. (We’ve just used this technique—which of the last five sentences do you prefer?)Whenever we write a sentence we make choices. Some are less obvious than others, so that it can often feel like we’ve written the sentence the only way we know how. By writing out five different versions of your thesis, you can begin to see your range of choices. The final version may be a combination of phrasings and words from all five versions, or the one version that says it best. By literally spelling out some possibilities for yourself, you will be able to make better decisions.
• Read your paper out loud and at… a… slow… pace. You can do this alone or with a friend, roommate, TA, etc. When read out loud, your written words should make sense to both you and other listeners. If a sentence seems confusing, rewrite it to make the meaning clear.
• Instead of reading the paper itself, put it down and just talk through your argument as concisely as you can. If your listener quickly and easily comprehends your essay’s main point and significance, you should then make sure that your written words are as clear as your oral presentation was. If, on the other hand, your listener keeps asking for clarification, you will need to work on finding the right terms for your essay. If you do this in exchange with a friend or classmate, rest assured that whether you are the talker or the listener, your articulation skills will develop.
• Have someone not familiar with the issue read the paper and point out words or sentences they find confusing. Do not brush off this reader’s confusion by assuming they simply doesn’t know enough about the topic. Instead, rewrite the sentences so that your “outsider” reader can follow along at all times.
• Check out the Writing Center’s handouts on style , passive voice , and proofreading for more tips.

Questions to ask yourself

• Am I sure what each word I use really means? Am I positive, or should I look it up?
• Have I found the best word or just settled for the most obvious, or the easiest, one?
• Am I trying too hard to impress my reader?
• What’s the easiest way to write this sentence? (Sometimes it helps to answer this question by trying it out loud. How would you say it to someone?)
• What are the key terms of my argument?
• Can I outline out my argument using only these key terms? What others do I need? Which do I not need?
• Have I created my own terms, or have I simply borrowed what looked like key ones from the assignment? If I’ve borrowed the terms, can I find better ones in my own vocabulary, the texts, my notes, the dictionary, or the thesaurus to make myself clearer?
• Are my key terms too specific? (Do they cover the entire range of my argument?) Can I think of specific examples from my sources that fall under the key term?
• Are my key terms too vague? (Do they cover more than the range of my argument?)

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Anson, Chris M., and Robert A. Schwegler. 2010. The Longman Handbook for Writers and Readers , 6th ed. New York: Longman.

Cook, Claire Kehrwald. 1985. Line by Line: How to Improve Your Own Writing . Boston: Houghton Mifflin.

Grossman, Ellie. 1997. The Grammatically Correct Handbook: A Lively and Unorthodox Review of Common English for the Linguistically Challenged . New York: Hyperion.

Houghton Mifflin. 1996. The American Heritage Book of English Usage: A Practical and Authoritative Guide to Contemporary English . Boston: Houghton Mifflin.

O’Conner, Patricia. 2010. Woe Is I: The Grammarphobe’s Guide to Better English in Plain English , 3rd ed. New York: Penguin Publishing Group.

Tarshis, Barry. 1998. How to Be Your Own Best Editor: The Toolkit for Everyone Who Writes . New York: Three Rivers Press.

Williams, Joseph, and Joseph Bizup. 2017. Style: Lessons in Clarity and Grace , 12th ed. Boston: Pearson.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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• The four main types of essay | Quick guide with examples

The Four Main Types of Essay | Quick Guide with Examples

Published on September 4, 2020 by Jack Caulfield . Revised on July 23, 2023.

An essay is a focused piece of writing designed to inform or persuade. There are many different types of essay, but they are often defined in four categories: argumentative, expository, narrative, and descriptive essays.

Argumentative and expository essays are focused on conveying information and making clear points, while narrative and descriptive essays are about exercising creativity and writing in an interesting way. At university level, argumentative essays are the most common type. 

In high school and college, you will also often have to write textual analysis essays, which test your skills in close reading and interpretation.

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Table of contents

Argumentative essays, expository essays, narrative essays, descriptive essays, textual analysis essays, other interesting articles, frequently asked questions about types of essays.

An argumentative essay presents an extended, evidence-based argument. It requires a strong thesis statement —a clearly defined stance on your topic. Your aim is to convince the reader of your thesis using evidence (such as quotations ) and analysis.

Argumentative essays test your ability to research and present your own position on a topic. This is the most common type of essay at college level—most papers you write will involve some kind of argumentation.

The essay is divided into an introduction, body, and conclusion:

• The introduction provides your topic and thesis statement
• The body presents your evidence and arguments
• The conclusion summarizes your argument and emphasizes its importance

The example below is a paragraph from the body of an argumentative essay about the effects of the internet on education. Mouse over it to learn more.

A common frustration for teachers is students’ use of Wikipedia as a source in their writing. Its prevalence among students is not exaggerated; a survey found that the vast majority of the students surveyed used Wikipedia (Head & Eisenberg, 2010). An article in The Guardian stresses a common objection to its use: “a reliance on Wikipedia can discourage students from engaging with genuine academic writing” (Coomer, 2013). Teachers are clearly not mistaken in viewing Wikipedia usage as ubiquitous among their students; but the claim that it discourages engagement with academic sources requires further investigation. This point is treated as self-evident by many teachers, but Wikipedia itself explicitly encourages students to look into other sources. Its articles often provide references to academic publications and include warning notes where citations are missing; the site’s own guidelines for research make clear that it should be used as a starting point, emphasizing that users should always “read the references and check whether they really do support what the article says” (“Wikipedia:Researching with Wikipedia,” 2020). Indeed, for many students, Wikipedia is their first encounter with the concepts of citation and referencing. The use of Wikipedia therefore has a positive side that merits deeper consideration than it often receives.

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An expository essay provides a clear, focused explanation of a topic. It doesn’t require an original argument, just a balanced and well-organized view of the topic.

Expository essays test your familiarity with a topic and your ability to organize and convey information. They are commonly assigned at high school or in exam questions at college level.

The introduction of an expository essay states your topic and provides some general background, the body presents the details, and the conclusion summarizes the information presented.

A typical body paragraph from an expository essay about the invention of the printing press is shown below. Mouse over it to learn more.

The invention of the printing press in 1440 changed this situation dramatically. Johannes Gutenberg, who had worked as a goldsmith, used his knowledge of metals in the design of the press. He made his type from an alloy of lead, tin, and antimony, whose durability allowed for the reliable production of high-quality books. This new technology allowed texts to be reproduced and disseminated on a much larger scale than was previously possible. The Gutenberg Bible appeared in the 1450s, and a large number of printing presses sprang up across the continent in the following decades. Gutenberg’s invention rapidly transformed cultural production in Europe; among other things, it would lead to the Protestant Reformation.

A narrative essay is one that tells a story. This is usually a story about a personal experience you had, but it may also be an imaginative exploration of something you have not experienced.

Narrative essays test your ability to build up a narrative in an engaging, well-structured way. They are much more personal and creative than other kinds of academic writing . Writing a personal statement for an application requires the same skills as a narrative essay.

A narrative essay isn’t strictly divided into introduction, body, and conclusion, but it should still begin by setting up the narrative and finish by expressing the point of the story—what you learned from your experience, or why it made an impression on you.

Mouse over the example below, a short narrative essay responding to the prompt “Write about an experience where you learned something about yourself,” to explore its structure.

Since elementary school, I have always favored subjects like science and math over the humanities. My instinct was always to think of these subjects as more solid and serious than classes like English. If there was no right answer, I thought, why bother? But recently I had an experience that taught me my academic interests are more flexible than I had thought: I took my first philosophy class.

Before I entered the classroom, I was skeptical. I waited outside with the other students and wondered what exactly philosophy would involve—I really had no idea. I imagined something pretty abstract: long, stilted conversations pondering the meaning of life. But what I got was something quite different.

A young man in jeans, Mr. Jones—“but you can call me Rob”—was far from the white-haired, buttoned-up old man I had half-expected. And rather than pulling us into pedantic arguments about obscure philosophical points, Rob engaged us on our level. To talk free will, we looked at our own choices. To talk ethics, we looked at dilemmas we had faced ourselves. By the end of class, I’d discovered that questions with no right answer can turn out to be the most interesting ones.

The experience has taught me to look at things a little more “philosophically”—and not just because it was a philosophy class! I learned that if I let go of my preconceptions, I can actually get a lot out of subjects I was previously dismissive of. The class taught me—in more ways than one—to look at things with an open mind.

A descriptive essay provides a detailed sensory description of something. Like narrative essays, they allow you to be more creative than most academic writing, but they are more tightly focused than narrative essays. You might describe a specific place or object, rather than telling a whole story.

Descriptive essays test your ability to use language creatively, making striking word choices to convey a memorable picture of what you’re describing.

A descriptive essay can be quite loosely structured, though it should usually begin by introducing the object of your description and end by drawing an overall picture of it. The important thing is to use careful word choices and figurative language to create an original description of your object.

Mouse over the example below, a response to the prompt “Describe a place you love to spend time in,” to learn more about descriptive essays.

On Sunday afternoons I like to spend my time in the garden behind my house. The garden is narrow but long, a corridor of green extending from the back of the house, and I sit on a lawn chair at the far end to read and relax. I am in my small peaceful paradise: the shade of the tree, the feel of the grass on my feet, the gentle activity of the fish in the pond beside me.

My cat crosses the garden nimbly and leaps onto the fence to survey it from above. From his perch he can watch over his little kingdom and keep an eye on the neighbours. He does this until the barking of next door’s dog scares him from his post and he bolts for the cat flap to govern from the safety of the kitchen.

With that, I am left alone with the fish, whose whole world is the pond by my feet. The fish explore the pond every day as if for the first time, prodding and inspecting every stone. I sometimes feel the same about sitting here in the garden; I know the place better than anyone, but whenever I return I still feel compelled to pay attention to all its details and novelties—a new bird perched in the tree, the growth of the grass, and the movement of the insects it shelters…

Sitting out in the garden, I feel serene. I feel at home. And yet I always feel there is more to discover. The bounds of my garden may be small, but there is a whole world contained within it, and it is one I will never get tired of inhabiting.

Though every essay type tests your writing skills, some essays also test your ability to read carefully and critically. In a textual analysis essay, you don’t just present information on a topic, but closely analyze a text to explain how it achieves certain effects.

Rhetorical analysis

A rhetorical analysis looks at a persuasive text (e.g. a speech, an essay, a political cartoon) in terms of the rhetorical devices it uses, and evaluates their effectiveness.

The goal is not to state whether you agree with the author’s argument but to look at how they have constructed it.

The introduction of a rhetorical analysis presents the text, some background information, and your thesis statement; the body comprises the analysis itself; and the conclusion wraps up your analysis of the text, emphasizing its relevance to broader concerns.

The example below is from a rhetorical analysis of Martin Luther King Jr.’s “I Have a Dream” speech . Mouse over it to learn more.

King’s speech is infused with prophetic language throughout. Even before the famous “dream” part of the speech, King’s language consistently strikes a prophetic tone. He refers to the Lincoln Memorial as a “hallowed spot” and speaks of rising “from the dark and desolate valley of segregation” to “make justice a reality for all of God’s children.” The assumption of this prophetic voice constitutes the text’s strongest ethical appeal; after linking himself with political figures like Lincoln and the Founding Fathers, King’s ethos adopts a distinctly religious tone, recalling Biblical prophets and preachers of change from across history. This adds significant force to his words; standing before an audience of hundreds of thousands, he states not just what the future should be, but what it will be: “The whirlwinds of revolt will continue to shake the foundations of our nation until the bright day of justice emerges.” This warning is almost apocalyptic in tone, though it concludes with the positive image of the “bright day of justice.” The power of King’s rhetoric thus stems not only from the pathos of his vision of a brighter future, but from the ethos of the prophetic voice he adopts in expressing this vision.

Literary analysis

A literary analysis essay presents a close reading of a work of literature—e.g. a poem or novel—to explore the choices made by the author and how they help to convey the text’s theme. It is not simply a book report or a review, but an in-depth interpretation of the text.

Literary analysis looks at things like setting, characters, themes, and figurative language. The goal is to closely analyze what the author conveys and how.

The introduction of a literary analysis essay presents the text and background, and provides your thesis statement; the body consists of close readings of the text with quotations and analysis in support of your argument; and the conclusion emphasizes what your approach tells us about the text.

Mouse over the example below, the introduction to a literary analysis essay on Frankenstein , to learn more.

Mary Shelley’s Frankenstein is often read as a crude cautionary tale about the dangers of scientific advancement unrestrained by ethical considerations. In this reading, protagonist Victor Frankenstein is a stable representation of the callous ambition of modern science throughout the novel. This essay, however, argues that far from providing a stable image of the character, Shelley uses shifting narrative perspectives to portray Frankenstein in an increasingly negative light as the novel goes on. While he initially appears to be a naive but sympathetic idealist, after the creature’s narrative Frankenstein begins to resemble—even in his own telling—the thoughtlessly cruel figure the creature represents him as. This essay begins by exploring the positive portrayal of Frankenstein in the first volume, then moves on to the creature’s perception of him, and finally discusses the third volume’s narrative shift toward viewing Frankenstein as the creature views him.

If you want to know more about AI tools , college essays , or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

• Ad hominem fallacy
• Post hoc fallacy
• Appeal to authority fallacy
• False cause fallacy
• Sunk cost fallacy

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• Write a College Essay
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At high school and in composition classes at university, you’ll often be told to write a specific type of essay , but you might also just be given prompts.

Look for keywords in these prompts that suggest a certain approach: The word “explain” suggests you should write an expository essay , while the word “describe” implies a descriptive essay . An argumentative essay might be prompted with the word “assess” or “argue.”

The vast majority of essays written at university are some sort of argumentative essay . Almost all academic writing involves building up an argument, though other types of essay might be assigned in composition classes.

Essays can present arguments about all kinds of different topics. For example:

• In a literary analysis essay, you might make an argument for a specific interpretation of a text
• In a history essay, you might present an argument for the importance of a particular event
• In a politics essay, you might argue for the validity of a certain political theory

An argumentative essay tends to be a longer essay involving independent research, and aims to make an original argument about a topic. Its thesis statement makes a contentious claim that must be supported in an objective, evidence-based way.

An expository essay also aims to be objective, but it doesn’t have to make an original argument. Rather, it aims to explain something (e.g., a process or idea) in a clear, concise way. Expository essays are often shorter assignments and rely less on research.

The key difference is that a narrative essay is designed to tell a complete story, while a descriptive essay is meant to convey an intense description of a particular place, object, or concept.

Narrative and descriptive essays both allow you to write more personally and creatively than other kinds of essays , and similar writing skills can apply to both.

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Caulfield, J. (2023, July 23). The Four Main Types of Essay | Quick Guide with Examples. Scribbr. Retrieved April 10, 2024, from https://www.scribbr.com/academic-essay/essay-types/

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100+ Useful Words and Phrases to Write a Great Essay

By: Author Sophia

Posted on Last updated: October 25, 2023

Sharing is caring!

How to Write a Great Essay in English! This lesson provides 100+ useful words, transition words and expressions used in writing an essay. Let’s take a look!

The secret to a successful essay doesn’t just lie in the clever things you talk about and the way you structure your points.

Useful Words and Phrases to Write a Great Essay

Overview of an essay.

Useful Phrases for Proficiency Essays

Developing the argument

• The first aspect to point out is that…
• Let us start by considering the facts.
• The novel portrays, deals with, revolves around…
• Central to the novel is…
• The character of xxx embodies/ epitomizes…

The other side of the argument

• It would also be interesting to see…
• One should, nevertheless, consider the problem from another angle.
• Equally relevant to the issue are the questions of…
• The arguments we have presented… suggest that…/ prove that…/ would indicate that…
• From these arguments one must…/ could…/ might… conclude that…
• All of this points to the conclusion that…
• To conclude…

Ordering elements

• Firstly,…/ Secondly,…/ Finally,… (note the comma after all these introductory words.)
• As a final point…
• On the one hand, …. on the other hand…
• If on the one hand it can be said that… the same is not true for…
• The first argument suggests that… whilst the second suggests that…
• There are at least xxx points to highlight.

Adding elements

• Furthermore, one should not forget that…
• In addition to…
• Moreover…
• It is important to add that…

Accepting other points of view

• Nevertheless, one should accept that…
• However, we also agree that…

Personal opinion

• We/I personally believe that…
• Our/My own point of view is that…
• It is my contention that…
• I am convinced that…
• My own opinion is…

Others’ opinions

• According to some critics… Critics:
• believe that
• suggest that
• are convinced that
• point out that
• emphasize that
• contend that
• go as far as to say that
• argue for this

Introducing examples

• For example…
• For instance…
• To illustrate this point…

Introducing facts

• It is… true that…/ clear that…/ noticeable that…
• One should note here that…

Saying what you think is true

• This leads us to believe that…
• It is very possible that…
• In view of these facts, it is quite likely that…
• Doubtless,…
• One cannot deny that…
• It is (very) clear from these observations that…
• All the same, it is possible that…
• It is difficult to believe that…

Accepting other points to a certain degree

• One can agree up to a certain point with…
• Certainly,… However,…
• It cannot be denied that…

Emphasizing particular points

• The last example highlights the fact that…
• Not only… but also…
• We would even go so far as to say that…

Moderating, agreeing, disagreeing

• By and large…
• Perhaps we should also point out the fact that…
• It would be unfair not to mention the fact that…
• One must admit that…
• We cannot ignore the fact that…
• One cannot possibly accept the fact that…

Consequences

• From these facts, one may conclude that…
• That is why, in our opinion, …
• Which seems to confirm the idea that…
• Thus,…/ Therefore,…
• Some critics suggest…, whereas others…
• Compared to…
• On the one hand, there is the firm belief that… On the other hand, many people are convinced that…

How to Write a Great Essay | Image 1

How to Write a Great Essay | Image 2

Phrases For Balanced Arguments

Introduction

• It is often said that…
• It is undeniable that…
• It is a well-known fact that…
• One of the most striking features of this text is…
• The first thing that needs to be said is…
• First of all, let us try to analyze…
• One argument in support of…
• We must distinguish carefully between…
• The second reason for…
• An important aspect of the text is…
• It is worth stating at this point that…
• On the other hand, we can observe that…
• The other side of the coin is, however, that…
• Another way of looking at this question is to…
• What conclusions can be drawn from all this?
• The most satisfactory conclusion that we can come to is…
• To sum up… we are convinced that…/ …we believe that…/ …we have to accept that…

How to Write a Great Essay | Image 3

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• Cambridge Dictionary +Plus

Meaning of essay in English

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• I want to finish off this essay before I go to bed .
• His essay was full of spelling errors .
• Have you given that essay in yet ?
• Have you handed in your history essay yet ?
• I'd like to discuss the first point in your essay.
• boilerplate
• composition
• dissertation
• essay question
• peer review
• go after someone
• go all out idiom
• go down swinging/fighting idiom
• go for it idiom
• go for someone
• shoot the works idiom
• smarten (someone/something) up
• smarten up your act idiom
• square the circle idiom
• step on the gas idiom

essay | American Dictionary

Examples of essay, collocations with essay.

These are words often used in combination with essay .

Click on a collocation to see more examples of it.

Translations of essay

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Word of the Day

a type of singing in which four, usually male, voices in close combination perform popular romantic songs, especially from the 1920s and 1930s

Alike and analogous (Talking about similarities, Part 1)

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Difference Between an Essay & a Paper

Jennifer brozak.

Whether you’re in middle school, high school or toiling away at college, paper writing is a fundamental facet of schooling. While essays and other forms of creative writing are common in English classes, you’ll also need to understand how to write informative pieces, such as research or term papers. By understanding the difference between the various types of writing styles, you’ll be able to draft compelling prose that is appropriate for any given assignment.

Explore this article

• What Is an Essay?
• What Is a Research Paper?
• What Is the Difference Between a Research Paper and Term Paper?
• Avoid Getting a Free Essay Writer

1 What Is an Essay?

One of the most common forms of writing is the essay. Starting in your later elementary school years and into middle school, you’ll likely be exposed to the five-paragraph essay, which is a fundamental starting point for creating longer-length writing assignments as you move upward through the higher grades. While they’re typically shorter pieces of writing (often under 1,000 words), they allow teachers to evaluate students on different writing, reading and analysis skills, including the art of persuasion and exposition.

Essays can take on many forms: They can be narrative, or tell a story; expository, or require investigation and evidential support; descriptive, in which a student is required to describe, creatively, a person, place or object; and finally, persuasive, in which a student is asked to argue a specific position on a particular topic.

As a whole, paper essay writing typically allows for more creativity than more formal writing styles, such as research papers.

2 What Is a Research Paper?

The phrase “research paper” can conjure anxiety in even the most adequate student writers. However, this need not be the case. In fact, it’s helpful to think of a research paper as an inflated essay. The structure will basically be the same, but you’ll need a thesis statement (which is not required in some forms of essay writing), significant research and evidence to support your ideas. You’ll also be required to include several credible sources in your paper, which will be listed on a reference page. And consider this: If you choose a subject you’re interested in researching, writing an informative paper can actually be quite a rewarding experience.

3 What Is the Difference Between a Research Paper and Term Paper?

Teachers, especially college professors, sometimes refer to longer research papers as “term papers,” which are similar in their structure and format. They’re expanded essays that will require evidence and credible sources to support your ideas. The difference lies in the subject matter. Research papers may allow you to cover a topic outside of the general subject matter (such as writing a persuasive research paper about global warming in an English class), while term papers will focus solely on the subject matter discussed in the course. High-quality research and term paper examples can be found on numerous sites, such as the Purdue University Online Writing Lab.

4 Avoid Getting a Free Essay Writer

A note of caution about submitting any writing assignment: While the Internet abounds with sources to help you in your quest to write the perfect paper, avoid using “essay generators” or hiring a free essay writer or buying papers from a database. Even if you’re procrastinating and panicking about finishing your assignment, it’s always better to turn in your own work. Not only do many teachers utilize online plagiarism checkers, but they also learn to recognize a student’s specific writing style over the course of an academic year. While it’s perfectly fine to use a term paper example as a guideline, it’s always better to submit your own paper or essay with minor errors than to attempt to pass off someone else’s writing as your own.

• 1 SUNY Empire State College: Research Writing: Elements and Steps
• 2 Enago Academy: How to Avoid Plagiarism in Research Papers (Part1 )

About the Author

Jennifer Brozak earned her state teaching certificate in Secondary English and Communications from St. Vincent College in Latrobe, Pa., and her bachelor's degree in journalism from the University of Pittsburgh. A former high school English teacher, Jennifer enjoys writing articles about parenting and education and has contributed to Reader's Digest, Mamapedia, Shmoop and more.

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Tips on Writing on Unlined Paper

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He turned that down — “I immediately thought back to college and writing term papers at the very last minute,” Redick recalled — but when Wojnarowski asked him to try a podcast, he gave it a go.

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Amanda Hoover

Students Are Likely Writing Millions of Papers With AI

Students have submitted more than 22 million papers that may have used generative AI in the past year, new data released by plagiarism detection company Turnitin shows.

A year ago, Turnitin rolled out an AI writing detection tool that was trained on its trove of papers written by students as well as other AI-generated texts. Since then, more than 200 million papers have been reviewed by the detector, predominantly written by high school and college students. Turnitin found that 11 percent may contain AI-written language in 20 percent of its content, with 3 percent of the total papers reviewed getting flagged for having 80 percent or more AI writing. (Turnitin is owned by Advance, which also owns Condé Nast, publisher of WIRED.) Turnitin says its detector has a false positive rate of less than 1 percent when analyzing full documents.

ChatGPT’s launch was met with knee-jerk fears that the English class essay would die . The chatbot can synthesize information and distill it near-instantly—but that doesn’t mean it always gets it right. Generative AI has been known to hallucinate , creating its own facts and citing academic references that don’t actually exist. Generative AI chatbots have also been caught spitting out biased text on gender and race . Despite those flaws, students have used chatbots for research, organizing ideas, and as a ghostwriter . Traces of chatbots have even been found in peer-reviewed, published academic writing .

Teachers understandably want to hold students accountable for using generative AI without permission or disclosure. But that requires a reliable way to prove AI was used in a given assignment. Instructors have tried at times to find their own solutions to detecting AI in writing, using messy, untested methods to enforce rules , and distressing students. Further complicating the issue, some teachers are even using generative AI in their grading processes.

Detecting the use of gen AI is tricky. It’s not as easy as flagging plagiarism, because generated text is still original text. Plus, there’s nuance to how students use gen AI; some may ask chatbots to write their papers for them in large chunks or in full, while others may use the tools as an aid or a brainstorm partner.

Students also aren't tempted by only ChatGPT and similar large language models. So-called word spinners are another type of AI software that rewrites text, and may make it less obvious to a teacher that work was plagiarized or generated by AI. Turnitin’s AI detector has also been updated to detect word spinners, says Annie Chechitelli, the company’s chief product officer. It can also flag work that was rewritten by services like spell checker Grammarly, which now has its own generative AI tool . As familiar software increasingly adds generative AI components, what students can and can’t use becomes more muddled.

Detection tools themselves have a risk of bias. English language learners may be more likely to set them off; a 2023 study found a 61.3 percent false positive rate when evaluating Test of English as a Foreign Language (TOEFL) exams with seven different AI detectors. The study did not examine Turnitin’s version. The company says it has trained its detector on writing from English language learners as well as native English speakers. A study published in October found that Turnitin was among the most accurate of 16 AI language detectors in a test that had the tool examine undergraduate papers and AI-generated papers.

Lauren Goode

Karen Williams

William Turton

Schools that use Turnitin had access to the AI detection software for a free pilot period, which ended at the start of this year. Chechitelli says a majority of the service’s clients have opted to purchase the AI detection. But the risks of false positives and bias against English learners have led some universities to ditch the tools for now. Montclair State University in New Jersey announced in November that it would pause use of Turnitin’s AI detector. Vanderbilt University and Northwestern University did the same last summer.

“This is hard. I understand why people want a tool,” says Emily Isaacs, executive director of the Office of Faculty Excellence at Montclair State. But Isaacs says the university is concerned about potentially biased results from AI detectors, as well as the fact that the tools can’t provide confirmation the way they can with plagiarism. Plus, Montclair State doesn’t want to put a blanket ban on AI, which will have some place in academia. With time and more trust in the tools, the policies could change. “It’s not a forever decision, it’s a now decision,” Isaacs says.

Chechitelli says the Turnitin tool shouldn’t be the only consideration in passing or failing a student. Instead, it’s a chance for teachers to start conversations with students that touch on all of the nuance in using generative AI. “People don’t really know where that line should be,” she says.

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Announcing the NeurIPS 2023 Paper Awards 

Communications Chairs 2023 2023 Conference awards , neurips2023

By Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine and Comms Chair, Sahra Ghalebikesabi 

We are honored to announce the award-winning papers for NeurIPS 2023! This year’s prestigious awards consist of the Test of Time Award plus two Outstanding Paper Awards in each of these three categories: 

• Two Outstanding Main Track Papers 
• Two Outstanding Main Track Runner-Ups 
• Two Outstanding Datasets and Benchmark Track Papers  

This year’s organizers received a record number of paper submissions. Of the 13,300 submitted papers that were reviewed by 968 Area Chairs, 98 senior area chairs, and 396 Ethics reviewers 3,540  were accepted after 502 papers were flagged for ethics reviews . 

We thank the awards committee for the main track: Yoav Artzi, Chelsea Finn, Ludwig Schmidt, Ricardo Silva, Isabel Valera, and Mengdi Wang. For the Datasets and Benchmarks track, we thank Sergio Escalera, Isabelle Guyon, Neil Lawrence, Dina Machuve, Olga Russakovsky, Hugo Jair Escalante, Deepti Ghadiyaram, and Serena Yeung. Conflicts of interest were taken into account in the decision process.

Congratulations to all the authors! See Posters Sessions Tue-Thur in Great Hall & B1-B2 (level 1).

Outstanding Main Track Papers

Privacy Auditing with One (1) Training Run Authors: Thomas Steinke · Milad Nasr · Matthew Jagielski

Poster session 2: Tue 12 Dec 5:15 p.m. — 7:15 p.m. CST, #1523

Oral: Tue 12 Dec 3:40 p.m. — 4:40 p.m. CST, Room R06-R09 (level 2)

Abstract: We propose a scheme for auditing differentially private machine learning systems with a single training run. This exploits the parallelism of being able to add or remove multiple training examples independently. We analyze this using the connection between differential privacy and statistical generalization, which avoids the cost of group privacy. Our auditing scheme requires minimal assumptions about the algorithm and can be applied in the black-box or white-box setting. We demonstrate the effectiveness of our framework by applying it to DP-SGD, where we can achieve meaningful empirical privacy lower bounds by training only one model. In contrast, standard methods would require training hundreds of models.

Are Emergent Abilities of Large Language Models a Mirage? Authors: Rylan Schaeffer · Brando Miranda · Sanmi Koyejo

Poster session 6: Thu 14 Dec 5:00 p.m. — 7:00 p.m. CST, #1108

Oral: Thu 14 Dec 3:20 p.m. — 3:35 p.m. CST, Hall C2 (level 1) 

Abstract: Recent work claims that large language models display emergent abilities, abilities not present in smaller-scale models that are present in larger-scale models. What makes emergent abilities intriguing is two-fold: their sharpness, transitioning seemingly instantaneously from not present to present, and their unpredictability , appearing at seemingly unforeseeable model scales. Here, we present an alternative explanation for emergent abilities: that for a particular task and model family, when analyzing fixed model outputs, emergent abilities appear due to the researcher’s choice of metric rather than due to fundamental changes in model behavior with scale. Specifically, nonlinear or discontinuous metrics produce apparent emergent abilities, whereas linear or continuous metrics produce smooth, continuous, predictable changes in model performance. We present our alternative explanation in a simple mathematical model, then test it in three complementary ways: we (1) make, test and confirm three predictions on the effect of metric choice using the InstructGPT/GPT-3 family on tasks with claimed emergent abilities, (2) make, test and confirm two predictions about metric choices in a meta-analysis of emergent abilities on BIG-Bench; and (3) show how to choose metrics to produce never-before-seen seemingly emergent abilities in multiple vision tasks across diverse deep networks. Via all three analyses, we provide evidence that alleged emergent abilities evaporate with different metrics or with better statistics, and may not be a fundamental property of scaling AI models.

Outstanding Main Track Runner-Ups

Scaling Data-Constrained Language Models Authors : Niklas Muennighoff · Alexander Rush · Boaz Barak · Teven Le Scao · Nouamane Tazi · Aleksandra Piktus · Sampo Pyysalo · Thomas Wolf · Colin Raffel

Poster session 2: Tue 12 Dec 5:15 p.m. — 7:15 p.m. CST, #813

Oral: Tue 12 Dec 3:40 p.m. — 4:40 p.m. CST, Hall C2 (level 1)  

Abstract : The current trend of scaling language models involves increasing both parameter count and training dataset size. Extrapolating this trend suggests that training dataset size may soon be limited by the amount of text data available on the internet. Motivated by this limit, we investigate scaling language models in data-constrained regimes. Specifically, we run a large set of experiments varying the extent of data repetition and compute budget, ranging up to 900 billion training tokens and 9 billion parameter models. We find that with constrained data for a fixed compute budget, training with up to 4 epochs of repeated data yields negligible changes to loss compared to having unique data. However, with more repetition, the value of adding compute eventually decays to zero. We propose and empirically validate a scaling law for compute optimality that accounts for the decreasing value of repeated tokens and excess parameters. Finally, we experiment with approaches mitigating data scarcity, including augmenting the training dataset with code data or removing commonly used filters. Models and datasets from our 400 training runs are freely available at https://github.com/huggingface/datablations .

Direct Preference Optimization: Your Language Model is Secretly a Reward Model Authors: Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn

Poster session 6: Thu 14 Dec 5:00 p.m. — 7:00 p.m. CST, #625

Oral: Thu 14 Dec 3:50 p.m. — 4:05 p.m. CST, Ballroom A-C (level 2)  

Abstract: While large-scale unsupervised language models (LMs) learn broad world knowledge and some reasoning skills, achieving precise control of their behavior is difficult due to the completely unsupervised nature of their training. Existing methods for gaining such steerability collect human labels of the relative quality of model generations and fine-tune the unsupervised LM to align with these preferences, often with reinforcement learning from human feedback (RLHF). However, RLHF is a complex and often unstable procedure, first fitting a reward model that reflects the human preferences, and then fine-tuning the large unsupervised LM using reinforcement learning to maximize this estimated reward without drifting too far from the original model. In this paper, we leverage a mapping between reward functions and optimal policies to show that this constrained reward maximization problem can be optimized exactly with a single stage of policy training, essentially solving a classification problem on the human preference data. The resulting algorithm, which we call Direct Preference Optimization (DPO), is stable, performant, and computationally lightweight, eliminating the need for fitting a reward model, sampling from the LM during fine-tuning, or performing significant hyperparameter tuning. Our experiments show that DPO can fine-tune LMs to align with human preferences as well as or better than existing methods. Notably, fine-tuning with DPO exceeds RLHF’s ability to control sentiment of generations and improves response quality in summarization and single-turn dialogue while being substantially simpler to implement and train.

Outstanding Datasets and Benchmarks Papers

In the dataset category : 

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Authors:  Sungduk Yu · Walter Hannah · Liran Peng · Jerry Lin · Mohamed Aziz Bhouri · Ritwik Gupta · Björn Lütjens · Justus C. Will · Gunnar Behrens · Julius Busecke · Nora Loose · Charles Stern · Tom Beucler · Bryce Harrop · Benjamin Hillman · Andrea Jenney · Savannah L. Ferretti · Nana Liu · Animashree Anandkumar · Noah Brenowitz · Veronika Eyring · Nicholas Geneva · Pierre Gentine · Stephan Mandt · Jaideep Pathak · Akshay Subramaniam · Carl Vondrick · Rose Yu · Laure Zanna · Tian Zheng · Ryan Abernathey · Fiaz Ahmed · David Bader · Pierre Baldi · Elizabeth Barnes · Christopher Bretherton · Peter Caldwell · Wayne Chuang · Yilun Han · YU HUANG · Fernando Iglesias-Suarez · Sanket Jantre · Karthik Kashinath · Marat Khairoutdinov · Thorsten Kurth · Nicholas Lutsko · Po-Lun Ma · Griffin Mooers · J. David Neelin · David Randall · Sara Shamekh · Mark Taylor · Nathan Urban · Janni Yuval · Guang Zhang · Mike Pritchard

Poster session 4: Wed 13 Dec 5:00 p.m. — 7:00 p.m. CST, #105 

Oral: Wed 13 Dec 3:45 p.m. — 4:00 p.m. CST, Ballroom A-C (level 2)

Abstract: Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climate simulators that can sidestep Moore’s Law by outsourcing compute-hungry, short, high-resolution simulations to ML emulators. However, this hybrid ML-physics simulation approach requires domain-specific treatment and has been inaccessible to ML experts because of lack of training data and relevant, easy-to-use workflows. We present ClimSim, the largest-ever dataset designed for hybrid ML-physics research. It comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. It consists of 5.7 billion pairs of multivariate input and output vectors that isolate the influence of locally-nested, high-resolution, high-fidelity physics on a host climate simulator’s macro-scale physical state. The dataset is global in coverage, spans multiple years at high sampling frequency, and is designed such that resulting emulators are compatible with downstream coupling into operational climate simulators. We implement a range of deterministic and stochastic regression baselines to highlight the ML challenges and their scoring. The data (https://huggingface.co/datasets/LEAP/ClimSim_high-res) and code (https://leap-stc.github.io/ClimSim) are released openly to support the development of hybrid ML-physics and high-fidelity climate simulations for the benefit of science and society.   

In the benchmark category :

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Authors: Boxin Wang · Weixin Chen · Hengzhi Pei · Chulin Xie · Mintong Kang · Chenhui Zhang · Chejian Xu · Zidi Xiong · Ritik Dutta · Rylan Schaeffer · Sang Truong · Simran Arora · Mantas Mazeika · Dan Hendrycks · Zinan Lin · Yu Cheng · Sanmi Koyejo · Dawn Song · Bo Li

Poster session 1: Tue 12 Dec 10:45 a.m. — 12:45 p.m. CST, #1618  

Oral: Tue 12 Dec 10:30 a.m. — 10:45 a.m. CST, Ballroom A-C (Level 2)

Abstract: Generative Pre-trained Transformer (GPT) models have exhibited exciting progress in capabilities, capturing the interest of practitioners and the public alike. Yet, while the literature on the trustworthiness of GPT models remains limited, practitioners have proposed employing capable GPT models for sensitive applications to healthcare and finance – where mistakes can be costly. To this end, this work proposes a comprehensive trustworthiness evaluation for large language models with a focus on GPT-4 and GPT-3.5, considering diverse perspectives – including toxicity, stereotype bias, adversarial robustness, out-of-distribution robustness, robustness on adversarial demonstrations, privacy, machine ethics, and fairness. Based on our evaluations, we discover previously unpublished vulnerabilities to trustworthiness threats. For instance, we find that GPT models can be easily misled to generate toxic and biased outputs and leak private information in both training data and conversation history. We also find that although GPT-4 is usually more trustworthy than GPT-3.5 on standard benchmarks, GPT-4 is more vulnerable given jailbreaking system or user prompts, potentially due to the reason that GPT-4 follows the (misleading) instructions more precisely. Our work illustrates a comprehensive trustworthiness evaluation of GPT models and sheds light on the trustworthiness gaps. Our benchmark is publicly available at https://decodingtrust.github.io/.

Test of Time

This year, following the usual practice, we chose a NeurIPS paper from 10 years ago to receive the Test of Time Award, and “ Distributed Representations of Words and Phrases and their Compositionality ” by Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean, won. 

Published at NeurIPS 2013 and cited over 40,000 times, the work introduced the seminal word embedding technique word2vec. Demonstrating the power of learning from large amounts of unstructured text, the work catalyzed progress that marked the beginning of a new era in natural language processing.

Greg Corrado and Jeffrey Dean will be giving a talk about this work and related research on Tuesday, 12 Dec at 3:05 – 3:25 pm CST in Hall F.  

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Reflections on the neurips 2023 ethics review process, neurips newsletter – november 2023.

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Memory in Exile: 80 Years since the Liberation of the Nazi Camps, Special issue of Word and Text

Memory in Exile: 80 Years since the Liberation of the Nazi Camps

Special issue of Word and Text , publication in December 2025

In 2025 there will be 80 years since the Nazi camps were liberated.

As Dan Stone showed, citing as examples scenes from the Red Army’s films of the liberation of Majdanek and Auschwitz to the final scenes of Life is Beautiful and Schindler’s List , ‘[i]n the popular imagination, the liberation of the Nazi concentration camps was a joyous affair, bringing an end to the inmates’ torments’ ( The Liberation of the Camps: The End of the Holocaust and its Aftermath , 2015). Yet for many of the inmates who were still alive when the liberation armies entered the camps, and even for the witnesses of the Nazi crimes, the mental scars remained for life. American and British liberators reported how insanely hungry the inmates they found in Dachau, Buchenwald, Mauthausen or Bergen-Belsen were. Soviet soldiers reported on the mountains of shoes they found in Majdanek and the thousands of emaciated prisoners who hugged them and cried at the three camps that made up Auschwitz. ‘I remember their faces, especially their eyes which betrayed their ordeal,’ soldier Ivan Martynushkin declared in an interview for The Times of Israel (see Erin Blakemore, ‘The Shocking Liberation of Auschwitz: Soviets “Knew Nothing” as They Approached’, History , 2020, https://www.history.com/news/auschwitz-liberation-soviets-holocaust )

Time passed and the trials from Nuremberg (1945-1949) and of Adolf Eichmann (1961) ushered in the ‘era of Holocaust awareness’. This was followed by the establishment and proliferation of audio and video archives of survivors’ and witnesses’ oral testimonies in the United States, Europe, Israel, and Australia. The United Nations General Assembly resolution 60/7 (2005), urged all member states to ‘develop programmes that will inculcate future generations with the lessons of the Holocaust in order to help to prevent future acts of genocide’. In the ‘after testimony’, ‘post-witness’, ‘after memory’ or ‘post-testimonial era’ (see Jakob Lothe, Susan Rubin Suleiman and James Phelan, After Testimony: The Ethics and Aesthetics of Holocaust Narrative for the Future , 2012; Diana I. Popescu and Tanja Schult, Revisiting Holocaust Representation in the Post-Witness Era , 2015; Matthias Schwartz, Nina Weller and Heike Winkel, After Memory: World War II in Contemporary Eastern European Literatures ; 2021; Arleen Ionescu and Simona Mitroiu, ‘Holocaust Narratives in the Post-Testimonial Era’, Parallax , 2023), this challenge becomes more timely than ever, since direct witnesses passed away and acts of genocide have kept on being committed, as if the lessons of history are never learnt. It is as if our ‘memory is in exile’, to quote Elie Wiesel’s words from a 1985 interview with Roger Lipsey. When Lipsey asked Wiesel about his position as a witness, Wiesel replied that he did not consider himself privileged, as ‘We are all witnesses.’ Lipsey insisted that Wiesel witnessed things that most people did not see and asked for advice: ‘what is it we should remember?’ This is when Wiesel expressed his fear that ‘memory is in exile’, since it seemed to him that people forgot that they had to remember everything even what they could not remember (see Lipsey, Interview with Elie Wiesel, Parabola x:2 ‘Exile’ Issue (May 1985)). Remembering what cannot be remembered is akin to what Maurice Blanchot meant by the ‘immemorial’: ‘How can it be preserved even by thought? How can thought be made the keeper of the Holocaust where all was lost, including guardian thought?’ ( The Writing of the Disaster , 1995, 47), a concept that we are also interested in for this special issue.

Our issue proposes to deal with the notion of memory in exile. Topics of interest include (but are not limited to):

l  Representations of the Holocaust in literature, films, visual arts 80 years after

l  New perspectives on the representation of the Holocaust in canonical texts 80 years after (i.e. The Diary of Anne Frank , the memoirs of Elie Wiesel, Primo Levi, Victor Frankl, Gisella Perl, Charlotte Delbo, the poems of Paul Celan, Dan Pagis, etc.)

l  Recuperation of unknown or under-explored Holocaust memories 80 years after

l  Holocaust memory, language and cultural translation 80 years after

l  Holocaust memory from gender and sexuality studies perspectives in the 21st century

l  Holocaust memory and various generations’ perspectives 80 years after

l  Holocaust memory as a toolkit of resistance strategies in new situations of crisis

l  Holocaust memory in relation to other genocide memories in the 21st century

l  What do we remember about the liberation of the camps 80 years after? What did we forget?

l  How do we deal with Saul Friedländer’s suggestion to create ‘an integrated history of the Holocaust’ (1997) in an era when no firsthand witnesses remained?

l  What challenges do digital technologies/ platforms or A.I. pose for Holocaust memory nowadays?

l  How do recent scholarly categories of analysis like Emily Budick’s ‘implicated reader/ writer’ ( The Subject of Holocaust Fiction , 2015), Michael Rothberg’s ‘implicated subject’ ( The Implicated Subject: Beyond Victims and Perpetrators , 2019) or Mihaela Mihai’s ‘impure resistance’ ( Political Memory and the Aesthetics of Care: The Art of Complicity and Resistance , 2022) promote new directions of engagement with Holocaust memories in the 21st century?

l  Can we include other 20th or 21st century historical traumas in the notion of ‘memory in exile’?

l  Remembering Wiesel’s words: ‘We must always take sides. Neutrality helps the oppressor, never the victim. Silence encourages the tormentor, never the tormented.’ (Wiesel, Acceptance Speech for the Nobel Prize ), how can ‘intercontextual’ readings (Leona Toker, Gulag Literature and the Literature of Nazi Camps: An Intercontexual Reading , 2019) help develop solidarity with the victims of all genocides?

We welcome interdisciplinary approaches, ranging across Holocaust and trauma studies, memory studies, critical theory, literary and cultural studies, visual arts, as well as other relevant disciplines in the humanities.

Interested contributors should submit a 300-500 word abstract along with a short bio note (no more than 200 words) as attachments to the editors of this special issue of Word and Text , Arleen Ionescu, Feng Li, Dana Mihăilescu and Adrian Tudurachi ( arleenionescu@gmail .com; [email protected] ;  [email protected] ; [email protected] ) by 30 September 2024. We will notify authors whose proposals are accepted for publication by 31 October 2024. Articles (7500-10000 words) are expected by 31 March 2025. Every author who submits an article must adhere to the policies and guidelines of Word and Text :

https://jlsl.upg-ploiesti.ro/documente/documente/Submission_Guidelines_English_2021_2.pdf ; https://jlsl.upg-ploiesti.ro/documente/documente/Editorial_Policy_Reviewing_Avoiding_Conflict_of_Interest_and_Complaints.pdf