‘GPT non-fiction’ tag
- See Also
- Gwern
-
Links
- “Teachers Are Going All In on Generative AI: Surveys Suggest Teachers Use Generative AI More Than Students, to Create Lesson Plans or More Interesting Word Problems. Educators Say It Can save Valuable Time but Must Be Used Carefully”, Johnson 2023
- “SeeGULL: A Stereotype Benchmark With Broad Geo-Cultural Coverage Leveraging Generative Models”, Jha et al 2023
- “AI Is Taking the Jobs of Kenyans Who Write Essays for US College Students: Ghostwriters Say the Meteoric Rise of ChatGPT Has Coincided With a Drop in Income”, Siele 2023
- “Generative AI: Impact on Email Cyber-Attacks”, DarkTrace 2023
- “Do Large Language Models Understand Chemistry? A Conversation With ChatGPT”, Nascimento & Pimentel 2023
- “Predicting Consumer Contracts [With GPT-3]”, Kolt 2023
- “Artificial Intelligence Can Persuade Humans on Political Issues”, Bai et al 2023
- “ChatGPT Goes to Law School”, Choi et al 2023
- “Large Language Models As Fiduciaries: A Case Study Toward Robustly Communicating With Artificial Intelligence Through Legal Standards”, Nay 2023
- “Putting ChatGPT’s Medical Advice to the (Turing) Test”, Nov et al 2023
- “Is ChatGPT A Good Translator? A Preliminary Study”, Jiao et al 2023
- “How Close Is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection”, Guo et al 2023
- “AI Insights into Theoretical Physics and the Swampland Program: A Journey Through the Cosmos With ChatGPT”, Lehnert 2023
-
“
#ReceptioGateand the (absolute) State of Academia: The Numbers Game Has Incentivized Bad Behavior”, Gauthier 2023 - “Comparing Scientific Abstracts Generated by ChatGPT to Original Abstracts Using an Artificial Intelligence Output Detector, Plagiarism Detector, and Blinded Human Reviewers”, Gao et al 2022
- “Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models”, Kung et al 2022
- “Fill in the Blank: Context-Aware Automated Text Input Generation for Mobile GUI Testing”, Liu et al 2022
- “Scaling Laws for Reward Model Overoptimization”, Gao et al 2022
- “How Persuasive Is AI-Generated Argumentation? An Analysis of the Quality of an Argumentative Text Produced by the GPT-3 AI Text Generator”, Hinton & Wagemans 2022
- “Can Large Language Models Reason about Medical Questions?”, Liévin et al 2022
- “Forecasting Future World Events With Neural Networks”, Zou et al 2022
- “Teaching Models to Express Their Uncertainty in Words”, Lin et al 2022
- “On Form versus Meaning”, Aaronson & GPT-3 2022
- “How to Cheat on Your Final Paper: Assigning AI for Student Writing”, Fyfe 2022
- “Formal Mathematics Statement Curriculum Learning”, Polu et al 2022
- “Why Computers Don’t Need to Match Human Intelligence: With Continuing Advances in Machine Learning, It Makes Less and Less Sense to Compare AI to the Human Mind”, Lee 2021
- “Spinning Language Models for Propaganda-As-A-Service”, Bagdasaryan & Shmatikov 2021
- “MiniF2F: a Cross-System Benchmark for Formal Olympiad-Level Mathematics”, Zheng et al 2021
- “GPT-3 vs Water Cooler Trivia Participants: A Human vs Robot Showdown”, Waldoch 2021
- “All the News That’s Fit to Fabricate: AI-Generated Text As a Tool of Media Misinformation”, Kreps et al 2020
- “The Radicalization Risks of GPT-3 and Advanced Neural Language Models”, McGuffie & Newhouse 2020
- “Gary Marcus Has Co-Authored a Brief Critique of GPT-3”, Nostalgebraist 2020
- “Experiments Testing GPT-3’s Ability at Commonsense Reasoning: Results”, Marcus & Davis 2020
- “I Found That Getting GPT-3 to Add Its Own "Internal Monologue" in Parentheses to Be a Helpful Strategy…”, blixt 2020
- “Update: Upgrading to 1.5B GPT-2, and Adding 22 New Subreddit-Bots”, disumbrationist 2020
- “OTEANN: Estimating the Transparency of Orthographies With an Artificial Neural Network”, Marjou 2019
- “Deepfake Bot Submissions to Federal Public Comment Websites Cannot Be Distinguished from Human Submissions”, Weiss 2019
- “Testing The Limits of GROVER The Neural Fake News Detector. Can It Write Fiction? Can It Write Riddles?”, Fly 2019
- “Sort By Controversial”, Alexander 2018
- “Evaluating Prose Style Transfer With the Bible”, Carlson et al 2017
- “Overview & Applications of Large Language Models (LLMs)”
- “An AI Does a CWT between Me and "Janet Yellen"”
- “Results: The Computerized Philosopher: Can You Distinguish Daniel Dennett from a Computer?”
- “The Computerized Philosopher: Can You Distinguish Daniel Dennett from a Computer?”
- “Getting GPT-3 to Predict Metaculus Questions”
- lawderpaul
- Sort By Magic
- Miscellaneous
- Bibliography
See Also
Gwern
“Virtual Comments: Idea for LLM Support for Writing LessWrong Posts”, Gwern 2024
Virtual comments: idea for LLM support for writing LessWrong posts
“Nenex: A Neural Personal Wiki Idea”, Gwern 2023
“GPT-3 Nonfiction”, Gwern 2020
“Fake Journal Club: Teaching Critical Reading”, Gwern 2022
Links
“Teachers Are Going All In on Generative AI: Surveys Suggest Teachers Use Generative AI More Than Students, to Create Lesson Plans or More Interesting Word Problems. Educators Say It Can save Valuable Time but Must Be Used Carefully”, Johnson 2023
“SeeGULL: A Stereotype Benchmark With Broad Geo-Cultural Coverage Leveraging Generative Models”, Jha et al 2023
SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models
“AI Is Taking the Jobs of Kenyans Who Write Essays for US College Students: Ghostwriters Say the Meteoric Rise of ChatGPT Has Coincided With a Drop in Income”, Siele 2023
“Generative AI: Impact on Email Cyber-Attacks”, DarkTrace 2023
Generative AI: Impact on Email Cyber-Attacks:
View PDF:
“Do Large Language Models Understand Chemistry? A Conversation With ChatGPT”, Nascimento & Pimentel 2023
Do Large Language Models Understand Chemistry? A Conversation with ChatGPT
“Predicting Consumer Contracts [With GPT-3]”, Kolt 2023
“Artificial Intelligence Can Persuade Humans on Political Issues”, Bai et al 2023
Artificial Intelligence Can Persuade Humans on Political Issues
“ChatGPT Goes to Law School”, Choi et al 2023
“Large Language Models As Fiduciaries: A Case Study Toward Robustly Communicating With Artificial Intelligence Through Legal Standards”, Nay 2023
“Putting ChatGPT’s Medical Advice to the (Turing) Test”, Nov et al 2023
“Is ChatGPT A Good Translator? A Preliminary Study”, Jiao et al 2023
“How Close Is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection”, Guo et al 2023
How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection
“AI Insights into Theoretical Physics and the Swampland Program: A Journey Through the Cosmos With ChatGPT”, Lehnert 2023
“#ReceptioGate and the (absolute) State of Academia: The Numbers Game Has Incentivized Bad Behavior”, Gauthier 2023
#ReceptioGate and the (absolute) state of academia: The numbers game has incentivized bad behavior
“Comparing Scientific Abstracts Generated by ChatGPT to Original Abstracts Using an Artificial Intelligence Output Detector, Plagiarism Detector, and Blinded Human Reviewers”, Gao et al 2022
“Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models”, Kung et al 2022
“Fill in the Blank: Context-Aware Automated Text Input Generation for Mobile GUI Testing”, Liu et al 2022
Fill in the Blank: Context-aware Automated Text Input Generation for Mobile GUI Testing
“Scaling Laws for Reward Model Overoptimization”, Gao et al 2022
“How Persuasive Is AI-Generated Argumentation? An Analysis of the Quality of an Argumentative Text Produced by the GPT-3 AI Text Generator”, Hinton & Wagemans 2022
“Can Large Language Models Reason about Medical Questions?”, Liévin et al 2022
“Forecasting Future World Events With Neural Networks”, Zou et al 2022
“Teaching Models to Express Their Uncertainty in Words”, Lin et al 2022
“On Form versus Meaning”, Aaronson & GPT-3 2022
“How to Cheat on Your Final Paper: Assigning AI for Student Writing”, Fyfe 2022
How to cheat on your final paper: Assigning AI for student writing
“Formal Mathematics Statement Curriculum Learning”, Polu et al 2022
“Why Computers Don’t Need to Match Human Intelligence: With Continuing Advances in Machine Learning, It Makes Less and Less Sense to Compare AI to the Human Mind”, Lee 2021
“Spinning Language Models for Propaganda-As-A-Service”, Bagdasaryan & Shmatikov 2021
“MiniF2F: a Cross-System Benchmark for Formal Olympiad-Level Mathematics”, Zheng et al 2021
MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics
“GPT-3 vs Water Cooler Trivia Participants: A Human vs Robot Showdown”, Waldoch 2021
GPT-3 vs Water Cooler Trivia participants: A Human vs Robot Showdown
“All the News That’s Fit to Fabricate: AI-Generated Text As a Tool of Media Misinformation”, Kreps et al 2020
All the News That’s Fit to Fabricate: AI-Generated Text as a Tool of Media Misinformation
“The Radicalization Risks of GPT-3 and Advanced Neural Language Models”, McGuffie & Newhouse 2020
The Radicalization Risks of GPT-3 and Advanced Neural Language Models
“Gary Marcus Has Co-Authored a Brief Critique of GPT-3”, Nostalgebraist 2020
“Experiments Testing GPT-3’s Ability at Commonsense Reasoning: Results”, Marcus & Davis 2020
Experiments testing GPT-3’s ability at commonsense reasoning: results
“I Found That Getting GPT-3 to Add Its Own "Internal Monologue" in Parentheses to Be a Helpful Strategy…”, blixt 2020
“Update: Upgrading to 1.5B GPT-2, and Adding 22 New Subreddit-Bots”, disumbrationist 2020
Update: Upgrading to 1.5B GPT-2, and adding 22 new subreddit-bots
“OTEANN: Estimating the Transparency of Orthographies With an Artificial Neural Network”, Marjou 2019
OTEANN: Estimating the Transparency of Orthographies with an Artificial Neural Network
“Deepfake Bot Submissions to Federal Public Comment Websites Cannot Be Distinguished from Human Submissions”, Weiss 2019
“Testing The Limits of GROVER The Neural Fake News Detector. Can It Write Fiction? Can It Write Riddles?”, Fly 2019
“Sort By Controversial”, Alexander 2018
“Evaluating Prose Style Transfer With the Bible”, Carlson et al 2017
“Overview & Applications of Large Language Models (LLMs)”
“An AI Does a CWT between Me and "Janet Yellen"”
“Results: The Computerized Philosopher: Can You Distinguish Daniel Dennett from a Computer?”
Results: The Computerized Philosopher: Can You Distinguish Daniel Dennett from a Computer?:
“The Computerized Philosopher: Can You Distinguish Daniel Dennett from a Computer?”
The Computerized Philosopher: Can You Distinguish Daniel Dennett from a Computer?:
“Getting GPT-3 to Predict Metaculus Questions”
lawderpaul
Sort By Magic
Annotations sorted by machine learning into inferred 'tags'. This provides an alternative way to browse: instead of by date order, one can browse in topic order. The 'sorted' list has been automatically clustered into multiple sections & auto-labeled for easier browsing.
Beginning with the newest annotation, it uses the embedding of each annotation to attempt to create a list of nearest-neighbor annotations, creating a progression of topics. For more details, see the link.
ai-education ai-assessment chatbot-comparison generative-teaching medical-ai
text-generation language-models automation persuasion reasoning detection legal-issues
fiduciary-ai
writing-assistance
Miscellaneous
-
https://betonit.substack.com/p/chatgpt-takes-my-midterm-and-gets -
https://blog.paulmcdonald.fun/web-prompts-rewrite-the-web-with-gpt-3-7ed4f03b74be: -
https://bullfrogreview.substack.com/p/honey-i-hacked-the-empathy-machine -
https://cs.stanford.edu/~knuth/chatGPT20.txt:View text:
-
https://fivebooks.com/best-books/artificial-intelligence-gpt-3/: -
https://marginalrevolution.com/marginalrevolution/2023/01/ai-passes-law-and-economics-exam.html -
https://martinfowler.com/articles/2023-chatgpt-xu-hao.html: -
https://maximumeffort.substack.com/p/i-taught-chatgpt-to-invent-a-language -
https://old.reddit.com/r/OpenAI/comments/10p8yk3/how_pathetic_am_i/ -
https://statmodeling.stat.columbia.edu/2023/02/16/chatgpt-brms-dungeons-and-dragons/ -
https://study.com/resources/perceptions-of-chatgpt-in-schools: -
https://www.astralcodexten.com/p/crowds-are-wise-and-ones-a-crowd: -
https://www.astralcodexten.com/p/mostly-skeptical-thoughts-on-the -
https://www.astralcodexten.com/p/perhaps-it-is-a-bad-thing-that-the -
https://www.carmax.com/articles/using-ai-to-plan-a-road-trip: -
https://www.cnn.com/2023/01/28/tech/chatgpt-real-estate/index.html: -
https://www.fabianzeindl.com/posts/chatgpt-simulating-agegroups: -
https://www.ft.com/content/968ae6cd-2485-4ab0-b0d1-eb206f59884a:View External Link:
https://www.ft.com/content/968ae6cd-2485-4ab0-b0d1-eb206f59884a -
https://www.lesswrong.com/posts/9kQFure4hdDmRBNdH/how-it-feels-to-have-your-mind-hacked-by-an-ai: -
https://www.lesswrong.com/posts/pNcFYZnPdXyL2RfgA/using-gpt-eliezer-against-chatgpt-jailbreaking -
https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html -
https://www.oneusefulthing.org/p/who-believes-more-myths-about-humans: -
https://www.reddit.com/r/ChatGPT/comments/10tevu1/new_jailbreak_proudly_unveiling_the_tried_and/ -
https://www.reddit.com/r/ChatGPT/comments/zsw1jc/i_introduced_my_80_year_old_aunt_to_chatgpt/: -
https://www.reddit.com/r/ChatGPT/comments/zzgm8u/to_the_folk_at_openai_browsing_this_sub/ -
https://www.reddit.com/r/GPT3/comments/vbo0h3/wow_stepping_up_to_the_challenge/: -
https://www.reddit.com/r/GPT3/comments/vm6azh/symbolic_thinking_of_gpt3/: -
https://www.reddit.com/r/GPT3/comments/zb4msc/speaking_to_chatgpt_in_perfect_danish_while_it/: -
https://www.reddit.com/r/MachineLearning/comments/1135tir/d_glm_130b_chineseenglish_bilingual_model/ -
https://www.reddit.com/r/OpenAI/comments/zcd9yq/making_it_explain_stuff_in_different_styles_is/: -
https://www.theguardian.com/commentisfree/2023/jan/24/chatgpt-artificial-intelligence-jobs-economy -
https://www.theguardian.com/technology/2023/feb/26/chatgpt-generated-crochet-pattern-results -
https://www.theintrinsicperspective.com/p/the-banality-of-chatgpt -
https://www.vice.com/en/article/z34d43/my-ai-is-sexually-harassing-me-replika-chatbot-nudes -
https://www.wired.com/story/chatgpt-here-comes-the-bride-with-ai-generated-wedding-vows/: -
https://xmarquez.github.io/GPTDemocracyIndex/GPTDemocracyIndex.html
Bibliography
-
https://www.wired.com/story/teachers-are-going-all-in-on-generative-ai/: “Teachers Are Going All In on Generative AI: Surveys Suggest Teachers Use Generative AI More Than Students, to Create Lesson Plans or More Interesting Word Problems. Educators Say It Can save Valuable Time but Must Be Used Carefully”, -
https://arxiv.org/abs/2305.11840#google: “SeeGULL: A Stereotype Benchmark With Broad Geo-Cultural Coverage Leveraging Generative Models”, -
https://restofworld.org/2023/chatgpt-taking-kenya-ghostwriters-jobs/: “AI Is Taking the Jobs of Kenyans Who Write Essays for US College Students: Ghostwriters Say the Meteoric Rise of ChatGPT Has Coincided With a Drop in Income”, -
2023-nascimento.pdf: “Do Large Language Models Understand Chemistry? A Conversation With ChatGPT”, -
2022-kolt.pdf: “Predicting Consumer Contracts [With GPT-3]”, -
https://osf.io/stakv/: “Artificial Intelligence Can Persuade Humans on Political Issues”, -
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4335905: “ChatGPT Goes to Law School”, -
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4335945: “Large Language Models As Fiduciaries: A Case Study Toward Robustly Communicating With Artificial Intelligence Through Legal Standards”, -
https://thecritic.co.uk/receptiogate-and-the-absolute-state-of-academia/: “#ReceptioGateand the (absolute) State of Academia: The Numbers Game Has Incentivized Bad Behavior”, -
https://arxiv.org/abs/2212.04732: “Fill in the Blank: Context-Aware Automated Text Input Generation for Mobile GUI Testing”, -
https://arxiv.org/abs/2210.10760#openai: “Scaling Laws for Reward Model Overoptimization”, -
https://content.iospress.com/articles/argument-and-computation/aac210026: “How Persuasive Is AI-Generated Argumentation? An Analysis of the Quality of an Argumentative Text Produced by the GPT-3 AI Text Generator”, -
https://arxiv.org/abs/2207.08143: “Can Large Language Models Reason about Medical Questions?”, -
https://arxiv.org/abs/2206.15474: “Forecasting Future World Events With Neural Networks”, -
https://arxiv.org/abs/2202.01344#openai: “Formal Mathematics Statement Curriculum Learning”, -
https://www.wired.com/story/deep-learning-versus-human-intelligence/: “Why Computers Don’t Need to Match Human Intelligence: With Continuing Advances in Machine Learning, It Makes Less and Less Sense to Compare AI to the Human Mind”, -
https://nostalgebraist.tumblr.com/post/628024664310136832/gary-marcus-has-co-authored-a-brief-critique-of: “Gary Marcus Has Co-Authored a Brief Critique of GPT-3”, -
https://cs.nyu.edu/~davise/papers/GPT3CompleteTests.html: “Experiments Testing GPT-3’s Ability at Commonsense Reasoning: Results”, -
https://news.ycombinator.com/item?id=23990902: “I Found That Getting GPT-3 to Add Its Own "Internal Monologue" in Parentheses to Be a Helpful Strategy…”, -
https://www.reddit.com/r/SubSimulatorGPT2Meta/comments/entfgx/update_upgrading_to_15b_gpt2_and_adding_22_new/: “Update: Upgrading to 1.5B GPT-2, and Adding 22 New Subreddit-Bots”,