- See Also
- Gwern
-
Links
- “Automated Social Science: Language Models As Scientist and Subjects”, Manning et al 2024
- “Enhancing Confidence Expression in Large Language Models Through Learning from Past Experience”, Han et al 2024
- “Is ChatGPT Transforming Academics’ Writing Style?”, Geng & Trotta 2024
- “From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples”, Vacareanu et al 2024
- “Election Workers Are Drowning in Records Requests. AI Chatbots Could Make It Worse: Experts Worry That Election Deniers Could Weaponize Chatbots to Overwhelm and Slow down Local Officials”, Elliott 2024
- “Visualization-Of-Thought Elicits Spatial Reasoning in Large Language Models”, Wu et al 2024
- “FABLES: Evaluating Faithfulness and Content Selection in Book-Length Summarization”, Kim et al 2024
- “Re-Evaluating GPT-4’s Bar Exam Performance”, Martínez 2024
- “A Peter Thiel-Backed AI Startup, Cognition Labs, Seeks $2 Billion Valuation: Funding round Could Increase Startup’s Valuation Nearly Sixfold in a Matter of Weeks, Reflecting AI Frenzy”, Jin 2024
- “Vulnerability Detection With Code Language Models: How Far Are We?”, Ding et al 2024
- “Gold-Medalist Coders Build an AI That Can Do Their Job for Them: A New Startup Called Cognition AI Can Turn a User’s Prompt into a Website or Video Game”, Vance 2024
- “Tokenization Counts: the Impact of Tokenization on Arithmetic in Frontier LLMs”, Singh & Strouse 2024
-
“
ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs”, Jiang et al 2024 - “Tasks That Language Models Don’t Learn”, Lee & Lim 2024
- “The Non-Effect of Sampling Temperature on Problem Solving in GPT-3.5/GPT-4”, Renze & Guven 2024
- “Better Call GPT, Comparing Large Language Models Against Lawyers”, Martin et al 2024
- “I Am a Strange Dataset: Metalinguistic Tests for Language Models”, Thrush et al 2024
- “GPT-4-V(ision) Is a Human-Aligned Evaluator for Text-To-3D Generation”, Wu et al 2024
- “Leveraging Large Language Models to Boost Dafny’s Developers Productivity”, Silva et al 2024
- “GPT-4 Passes the Bar Exam”, Katz et al 2024
- “Large Language Models Are Able to Downplay Their Cognitive Abilities to Fit the Persona They Simulate”, Milička et al 2024
- “WaveCoder: Widespread And Versatile Enhanced Instruction Tuning With Refined Data Generation”, Yu et al 2023
- “PRER: Modeling Complex Mathematical Reasoning via Large Language Model Based MathAgent”, Liao et al 2023
- “Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine”, Nori et al 2023
- “GPQA: A Graduate-Level Google-Proof Q&A Benchmark”, Rein et al 2023
- 42irrationalist @ "2023-11-19"
- “Llamas Know What GPTs Don’t Show: Surrogate Models for Confidence Estimation”, Shrivastava et al 2023
- “Comparing Humans, GPT-4, and GPT-4-V On Abstraction and Reasoning Tasks”, Mitchell et al 2023
- “The Impact of Large Language Models on Scientific Discovery: a Preliminary Study Using GPT-4”, AI4Science & Quantum 2023
- “Accuracy of a Vision-Language Model on Challenging Medical Cases”, Buckley et al 2023
- “Large Language Models Can Strategically Deceive Their Users When Put Under Pressure”, Scheurer et al 2023
- “Augmenting Large Language Models With Chemistry Tools”, Bran et al 2023
- “Branch-Solve-Merge Improves Large Language Model Evaluation and Generation”, Saha et al 2023
- “Eureka: Human-Level Reward Design via Coding Large Language Models”, Ma et al 2023
- “Set-Of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4-V”, Yang et al 2023
- “Large Language Model Prediction Capabilities: Evidence from a Real-World Forecasting Tournament”, Schoenegger & Park 2023
- “Data Contamination Through the Lens of Time”, Roberts et al 2023
- “Can GPT Models Be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on Mock CFA Exams”, Callanan et al 2023
- “Beyond Memorization: Violating Privacy Via Inference With Large Language Models”, Staab et al 2023
- “SWE-Bench: Can Language Models Resolve Real-World GitHub Issues?”, Jimenez et al 2023
- “Can a Computer Outfake a Human [personality]?”, Phillips & Robie 2023
- “Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models”, Zhou et al 2023
- “FreshLLMs: Refreshing Large Language Models With Search Engine Augmentation”, Vu et al 2023
- “Low-Resource Languages Jailbreak GPT-4”, Yong et al 2023
- “An Evolutionary Model of Personality Traits Related to Cooperative Behavior Using a Large Language Model”, Suzuki & Arita 2023
- “UltraFeedback: Boosting Language Models With High-Quality Feedback”, Cui et al 2023
- “Embers of Autoregression: Understanding Large Language Models Through the Problem They Are Trained to Solve”, McCoy et al 2023
- “The Cambridge Law Corpus: A Corpus for Legal AI Research”, Östling et al 2023
- “The Reversal Curse: LLMs Trained on "A Is B" Fail to Learn "B Is A"”, Berglund et al 2023
- “From Sparse to Dense: GPT-4 Summarization With Chain of Density (CoD) Prompting”, Adams et al 2023
- “Solving Challenging Math Word Problems Using GPT-4 Code Interpreter With Code-Based Self-Verification”, Zhou et al 2023
- “OpenAI Cribbed Our Tax Example, But Can GPT-4 Really Do Tax?”, Blair-Stanek et al 2023
- “Testing GPT-4 With Wolfram Alpha and Code Interpreter Plug-Ins on Math and Science Problems”, Davis & Aaronson 2023
- “The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domain”, Moskvichev et al 2023
- “OpenAI Worries About What Its Chatbot Will Say About People’s Faces: An Advanced Version of ChatGPT Can Analyze Images and Is Already Helping the Blind. But Its Ability to Put a Name to a Face Is One Reason the Public Doesn’t Have Access to It”, Hill 2023
- “GPT-4, an Artificial Intelligence Large Language Model, Exhibits High Levels of Accuracy on Dermatology Specialty Certificate Exam Questions”, Shetty et al 2023
- “Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events”, Gu et al 2023
- “Explaining Competitive-Level Programming Solutions Using LLMs”, Li et al 2023
- “LeanDojo: Theorem Proving With Retrieval-Augmented Language Models”, Yang et al 2023
- “ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews”, D’Arcy et al 2023
- “Evaluating Superhuman Models With Consistency Checks”, Fluri et al 2023
- “ChessGPT: Bridging Policy Learning and Language Modeling”, Feng et al 2023
- “Large Language Models As Tax Attorneys: A Case Study in Legal Capabilities Emergence”, Nay et al 2023
- “Can Large Language Models Democratize Access to Dual-Use Biotechnology?”, Soice et al 2023
- “Let’s Verify Step by Step”, Lightman et al 2023
- “GPT4GEO: How a Language Model Sees the World’s Geography”, Roberts et al 2023
- “LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-Based Representations”, Xu et al 2023
- “Learning to Generate Novel Scientific Directions With Contextualized Literature-Based Discovery”, Wang et al 2023
- “WikiChat: Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia”, Semnani et al 2023
- “How Language Model Hallucinations Can Snowball”, Zhang et al 2023
- “C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models”, Huang et al 2023
- “Large Language Models Can Be Used To Effectively Scale Spear Phishing Campaigns”, Hazell 2023
- “Boosting Theory-Of-Mind Performance in Large Language Models via Prompting”, Moghaddam & Honey 2023
- “Today Was the First Day That I Could Definitively Say That GPT-4 Has Saved Me a Substantial Amount of Tedious Work”, Tao 2023
- “Humans in Humans Out: On GPT Converging Toward Common Sense in Both Success and Failure”, Koralus & Wang-Maścianica 2023
- “Advances in Apparent Conceptual Physics Reasoning in GPT-4”, West 2023
- “Performance of ChatGPT on Free-Response, Clinical Reasoning Exams”, Strong et al 2023
- “How Well Do Large Language Models Perform in Arithmetic Tasks?”, Yuan et al 2023
- “GPT-4 Technical Report § Limitations: Calibration”, OpenAI 2023 (page 12 org openai)
- “Salesforce Announces Einstein GPT, the World’s First Generative AI for CRM”, Salesforce 2023
- “Large Language Models Are State-Of-The-Art Evaluators of Translation Quality”, Kocmi & Federmann 2023
- “Not What You’ve Signed up For: Compromising Real-World LLM-Integrated Applications With Indirect Prompt Injection”, Greshake et al 2023
- “Harvey, Which Uses AI to Answer Legal Questions, Lands Cash from OpenAI”, Wiggers 2022
- Sort By Magic
- Miscellaneous
- Link Bibliography
See Also
Gwern
“CQK Is The First Unused TLA”, Gwern 2023
Links
“Automated Social Science: Language Models As Scientist and Subjects”, Manning et al 2024
Automated Social Science: Language Models as Scientist and Subjects
“Enhancing Confidence Expression in Large Language Models Through Learning from Past Experience”, Han et al 2024
Enhancing Confidence Expression in Large Language Models Through Learning from Past Experience
“Is ChatGPT Transforming Academics’ Writing Style?”, Geng & Trotta 2024
“From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples”, Vacareanu et al 2024
“Election Workers Are Drowning in Records Requests. AI Chatbots Could Make It Worse: Experts Worry That Election Deniers Could Weaponize Chatbots to Overwhelm and Slow down Local Officials”, Elliott 2024
“Visualization-Of-Thought Elicits Spatial Reasoning in Large Language Models”, Wu et al 2024
Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models
“FABLES: Evaluating Faithfulness and Content Selection in Book-Length Summarization”, Kim et al 2024
FABLES: Evaluating faithfulness and content selection in book-length summarization
“Re-Evaluating GPT-4’s Bar Exam Performance”, Martínez 2024
“A Peter Thiel-Backed AI Startup, Cognition Labs, Seeks $2 Billion Valuation: Funding round Could Increase Startup’s Valuation Nearly Sixfold in a Matter of Weeks, Reflecting AI Frenzy”, Jin 2024
“Vulnerability Detection With Code Language Models: How Far Are We?”, Ding et al 2024
Vulnerability Detection with Code Language Models: How Far Are We?
“Gold-Medalist Coders Build an AI That Can Do Their Job for Them: A New Startup Called Cognition AI Can Turn a User’s Prompt into a Website or Video Game”, Vance 2024
“Tokenization Counts: the Impact of Tokenization on Arithmetic in Frontier LLMs”, Singh & Strouse 2024
Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs
“ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs”, Jiang et al 2024
ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs
“Tasks That Language Models Don’t Learn”, Lee & Lim 2024
“The Non-Effect of Sampling Temperature on Problem Solving in GPT-3.5/GPT-4”, Renze & Guven 2024
The Non-Effect of Sampling Temperature on Problem Solving in GPT-3.5/GPT-4
“Better Call GPT, Comparing Large Language Models Against Lawyers”, Martin et al 2024
Better Call GPT, Comparing Large Language Models Against Lawyers
“I Am a Strange Dataset: Metalinguistic Tests for Language Models”, Thrush et al 2024
I am a Strange Dataset: Metalinguistic Tests for Language Models
“GPT-4-V(ision) Is a Human-Aligned Evaluator for Text-To-3D Generation”, Wu et al 2024
GPT-4-V(ision) is a Human-Aligned Evaluator for Text-to-3D Generation
“Leveraging Large Language Models to Boost Dafny’s Developers Productivity”, Silva et al 2024
Leveraging Large Language Models to Boost Dafny’s Developers Productivity
“GPT-4 Passes the Bar Exam”, Katz et al 2024
“Large Language Models Are Able to Downplay Their Cognitive Abilities to Fit the Persona They Simulate”, Milička et al 2024
“WaveCoder: Widespread And Versatile Enhanced Instruction Tuning With Refined Data Generation”, Yu et al 2023
WaveCoder: Widespread And Versatile Enhanced Instruction Tuning with Refined Data Generation
“PRER: Modeling Complex Mathematical Reasoning via Large Language Model Based MathAgent”, Liao et al 2023
PRER: Modeling Complex Mathematical Reasoning via Large Language Model based MathAgent
“Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine”, Nori et al 2023
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
“GPQA: A Graduate-Level Google-Proof Q&A Benchmark”, Rein et al 2023
42irrationalist @ "2023-11-19"
“Llamas Know What GPTs Don’t Show: Surrogate Models for Confidence Estimation”, Shrivastava et al 2023
Llamas Know What GPTs Don’t Show: Surrogate Models for Confidence Estimation
“Comparing Humans, GPT-4, and GPT-4-V On Abstraction and Reasoning Tasks”, Mitchell et al 2023
Comparing Humans, GPT-4, and GPT-4-V On Abstraction and Reasoning Tasks
“The Impact of Large Language Models on Scientific Discovery: a Preliminary Study Using GPT-4”, AI4Science & Quantum 2023
The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4
“Accuracy of a Vision-Language Model on Challenging Medical Cases”, Buckley et al 2023
Accuracy of a Vision-Language Model on Challenging Medical Cases
“Large Language Models Can Strategically Deceive Their Users When Put Under Pressure”, Scheurer et al 2023
Large Language Models can Strategically Deceive their Users when Put Under Pressure
“Augmenting Large Language Models With Chemistry Tools”, Bran et al 2023
“Branch-Solve-Merge Improves Large Language Model Evaluation and Generation”, Saha et al 2023
Branch-Solve-Merge Improves Large Language Model Evaluation and Generation
“Eureka: Human-Level Reward Design via Coding Large Language Models”, Ma et al 2023
Eureka: Human-Level Reward Design via Coding Large Language Models
“Set-Of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4-V”, Yang et al 2023
Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4-V
“Large Language Model Prediction Capabilities: Evidence from a Real-World Forecasting Tournament”, Schoenegger & Park 2023
Large Language Model Prediction Capabilities: Evidence from a Real-World Forecasting Tournament
“Data Contamination Through the Lens of Time”, Roberts et al 2023
“Can GPT Models Be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on Mock CFA Exams”, Callanan et al 2023
Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams
“Beyond Memorization: Violating Privacy Via Inference With Large Language Models”, Staab et al 2023
Beyond Memorization: Violating Privacy Via Inference with Large Language Models
“SWE-Bench: Can Language Models Resolve Real-World GitHub Issues?”, Jimenez et al 2023
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
“Can a Computer Outfake a Human [personality]?”, Phillips & Robie 2023
“Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models”, Zhou et al 2023
Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
“FreshLLMs: Refreshing Large Language Models With Search Engine Augmentation”, Vu et al 2023
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation
“Low-Resource Languages Jailbreak GPT-4”, Yong et al 2023
“An Evolutionary Model of Personality Traits Related to Cooperative Behavior Using a Large Language Model”, Suzuki & Arita 2023
“UltraFeedback: Boosting Language Models With High-Quality Feedback”, Cui et al 2023
UltraFeedback: Boosting Language Models with High-quality Feedback
“Embers of Autoregression: Understanding Large Language Models Through the Problem They Are Trained to Solve”, McCoy et al 2023
“The Cambridge Law Corpus: A Corpus for Legal AI Research”, Östling et al 2023
“The Reversal Curse: LLMs Trained on "A Is B" Fail to Learn "B Is A"”, Berglund et al 2023
The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"
“From Sparse to Dense: GPT-4 Summarization With Chain of Density (CoD) Prompting”, Adams et al 2023
From Sparse to Dense: GPT-4 Summarization with Chain of Density (CoD) Prompting
“Solving Challenging Math Word Problems Using GPT-4 Code Interpreter With Code-Based Self-Verification”, Zhou et al 2023
“OpenAI Cribbed Our Tax Example, But Can GPT-4 Really Do Tax?”, Blair-Stanek et al 2023
OpenAI Cribbed Our Tax Example, But Can GPT-4 Really Do Tax?
“Testing GPT-4 With Wolfram Alpha and Code Interpreter Plug-Ins on Math and Science Problems”, Davis & Aaronson 2023
Testing GPT-4 with Wolfram Alpha and Code Interpreter plug-ins on math and science problems
“The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domain”, Moskvichev et al 2023
The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domain
“OpenAI Worries About What Its Chatbot Will Say About People’s Faces: An Advanced Version of ChatGPT Can Analyze Images and Is Already Helping the Blind. But Its Ability to Put a Name to a Face Is One Reason the Public Doesn’t Have Access to It”, Hill 2023
“GPT-4, an Artificial Intelligence Large Language Model, Exhibits High Levels of Accuracy on Dermatology Specialty Certificate Exam Questions”, Shetty et al 2023
“Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events”, Gu et al 2023
“Explaining Competitive-Level Programming Solutions Using LLMs”, Li et al 2023
Explaining Competitive-Level Programming Solutions using LLMs
“LeanDojo: Theorem Proving With Retrieval-Augmented Language Models”, Yang et al 2023
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
“ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews”, D’Arcy et al 2023
ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews
“Evaluating Superhuman Models With Consistency Checks”, Fluri et al 2023
“ChessGPT: Bridging Policy Learning and Language Modeling”, Feng et al 2023
“Large Language Models As Tax Attorneys: A Case Study in Legal Capabilities Emergence”, Nay et al 2023
Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence
“Can Large Language Models Democratize Access to Dual-Use Biotechnology?”, Soice et al 2023
Can large language models democratize access to dual-use biotechnology?
“Let’s Verify Step by Step”, Lightman et al 2023
“GPT4GEO: How a Language Model Sees the World’s Geography”, Roberts et al 2023
“LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-Based Representations”, Xu et al 2023
“Learning to Generate Novel Scientific Directions With Contextualized Literature-Based Discovery”, Wang et al 2023
Learning to Generate Novel Scientific Directions with Contextualized Literature-based Discovery
“WikiChat: Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia”, Semnani et al 2023
“How Language Model Hallucinations Can Snowball”, Zhang et al 2023
“C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models”, Huang et al 2023
C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
“Large Language Models Can Be Used To Effectively Scale Spear Phishing Campaigns”, Hazell 2023
Large Language Models Can Be Used To Effectively Scale Spear Phishing Campaigns
“Boosting Theory-Of-Mind Performance in Large Language Models via Prompting”, Moghaddam & Honey 2023
Boosting Theory-of-Mind Performance in Large Language Models via Prompting
“Today Was the First Day That I Could Definitively Say That GPT-4 Has Saved Me a Substantial Amount of Tedious Work”, Tao 2023
“Humans in Humans Out: On GPT Converging Toward Common Sense in Both Success and Failure”, Koralus & Wang-Maścianica 2023
Humans in Humans Out: On GPT Converging Toward Common Sense in both Success and Failure
“Advances in Apparent Conceptual Physics Reasoning in GPT-4”, West 2023
“Performance of ChatGPT on Free-Response, Clinical Reasoning Exams”, Strong et al 2023
Performance of ChatGPT on free-response, clinical reasoning exams
“How Well Do Large Language Models Perform in Arithmetic Tasks?”, Yuan et al 2023
How well do Large Language Models perform in Arithmetic tasks?
“GPT-4 Technical Report § Limitations: Calibration”, OpenAI 2023 (page 12 org openai)
“Salesforce Announces Einstein GPT, the World’s First Generative AI for CRM”, Salesforce 2023
Salesforce Announces Einstein GPT, the World’s First Generative AI for CRM
“Large Language Models Are State-Of-The-Art Evaluators of Translation Quality”, Kocmi & Federmann 2023
Large Language Models Are State-of-the-Art Evaluators of Translation Quality
“Not What You’ve Signed up For: Compromising Real-World LLM-Integrated Applications With Indirect Prompt Injection”, Greshake et al 2023
“Harvey, Which Uses AI to Answer Legal Questions, Lands Cash from OpenAI”, Wiggers 2022
Harvey, which uses AI to answer legal questions, lands cash from OpenAI
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.
gpt-applications
language-verification
language-optimization
languagemodels
gpt-law
legal-ai
Miscellaneous
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/doc/ai/nn/transformer/gpt/codex/2024-03-07-inflection-inflection25benchmarks.svg -
https://betonit.substack.com/p/gpt-4-takes-a-new-midterm-and-gets -
https://blog.matteskridge.com/business/gpt4-and-silicon-valley-bank/2023/03/19/: -
https://blog.mentat.ai/benchmarking-gpt-4-turbo-a-cautionary-tale -
https://blog.nawaz.org/posts/2024/Jan/llm-assisted-moderation/ -
https://chat.openai.com/share/04add58f-2052-4b60-ae2a-ab708c29088f -
https://chat.openai.com/share/312e82f0-cc5e-47f3-b368-b2c0c0f4ad3f -
https://clarifycapital.com/the-future-of-investment-pitching -
https://cookbook.openai.com/examples/tag_caption_images_with_gpt4v -
https://finedataproducts.com/posts/2024-03-10-tax-scenarios-with-ai/ -
https://generallyintelligent.substack.com/p/fine-tuning-mistral-7b-on-magic-the -
https://gist.github.com/Jessime/63f93215faed6f7109c6d62b7fef7fbc: -
https://gist.github.com/harryaskham/68a611bef777525991790bca2f2d324d -
https://github.com/E-xyza/Exonerate/blob/master/bench/reports/gpt-bench.md -
https://github.com/jujumilk3/leaked-system-prompts/blob/main/microsoft-bing-chat_20230209.md: -
https://github.com/jujumilk3/leaked-system-prompts/blob/main/openai-assistants-api_20231106.md: -
https://github.com/jujumilk3/leaked-system-prompts/blob/main/openai-chatgpt-ios_20230614.md: -
https://github.com/jujumilk3/leaked-system-prompts/blob/main/openai-chatgpt4-android_20240207.md: -
https://github.com/jujumilk3/leaked-system-prompts/blob/main/openai-chatgpt_20221201.md: -
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https://kenkantzer.com/lessons-after-a-half-billion-gpt-tokens/ -
https://koenvangilst.nl/blog/keeping-code-complexity-in-check -
https://lemire.me/blog/2023/03/22/can-gpt-pass-my-programming-courses/ -
https://matthewbarnett.substack.com/p/gpt-4-takes-bryan-caplans-midterm -
https://micahflee.com/2023/04/capturing-the-flag-with-gpt-4/ -
https://openai.com/blog/function-calling-and-other-api-updates#function-calling -
https://pslusarz.github.io/articles/2023/12/22/compare-ocr-tesseract-gpt4-nara-rolls.html: -
https://statmodeling.stat.columbia.edu/2023/04/18/chatgpt4-writes-stan-code-so-i-dont-have-to/ -
https://statmodeling.stat.columbia.edu/2023/08/20/bob-carpenter-thinks-gpt-4-is-awesome/ -
https://terrytao.wordpress.com/about/ai-generated-versions-of-the-ai-anthology-article/ -
https://twitter.com/AISafetyMemes/status/1762320288862314659: -
https://twitter.com/GrantSlatton/status/1740039795659956359: -
https://twitter.com/KevinAFischer/status/1646690838981005312 -
https://twitter.com/MasterTimBlais/status/1635701745727700999: -
https://twitter.com/MichaelTrazzi/status/1635743595989970945 -
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https://twitter.com/StudentInfosec/status/1640360234882310145 -
https://twitter.com/TheStalwart/status/1720475482171253104: -
https://twitter.com/_via_getty_/status/1635728855934836736: -
https://twitter.com/amuseddaman/status/1647367383022182400: -
https://twitter.com/bryanhpchiang/status/1639830383616487426: -
https://twitter.com/colin_fraser/status/1762351995296350592: -
https://twitter.com/fabianstelzer/status/1717131243861520569 -
https://twitter.com/kenshinsamurai9/status/1662510532585291779 -
https://twitter.com/krishnanrohit/status/1738617384276263356 -
https://twitter.com/mckaywrigley/status/1708153813583204394: -
https://twitter.com/mezaoptimizer/status/1725512396901433575 -
https://twitter.com/michael_nielsen/status/1769404321739972859: -
https://twitter.com/papayathreesome/status/1670170344953372676 -
https://villekuosmanen.medium.com/i-played-chess-against-chatgpt-4-and-lost-c5798a9049ca -
https://www.construction-physics.com/p/could-chatgpt-become-an-architect -
https://www.economist.com/business/2024/02/29/how-businesses-are-actually-using-generative-ai -
https://www.euractiv.com/section/politics/news/albania-to-speed-up-eu-accession-using-chatgpt/ -
https://www.lesswrong.com/posts/CkhJAxHeyFCg2EcET/are-language-models-good-at-making-predictions -
https://www.lesswrong.com/posts/KSroBnxCHodGmPPJ8/jailbreaking-gpt-4-s-code-interpreter -
https://www.lesswrong.com/posts/doPbyzPgKdjedohud/the-case-for-more-ambitious-language-model-evals -
https://www.oneusefulthing.org/p/it-is-starting-to-get-strange -
https://www.oneusefulthing.org/p/setting-time-on-fire-and-the-temptation: -
https://www.reddit.com/r/ChatGPT/comments/12a0ajb/i_gave_gpt4_persistent_memory_and_the_ability_to/ -
https://www.reddit.com/r/GPT3/comments/12ez822/neurosemantical_inversitis_prompt_still_works/ -
https://www.reddit.com/r/bing/comments/110eagl/the_customer_service_of_the_new_bing_chat_is/ -
https://www.reddit.com/r/duolingo/comments/18sx06i/big_layoff_at_duolingo/ -
https://www.reddit.com/r/freelanceWriters/comments/12ff5mw/it_happened_to_me_today/ -
https://www.reddit.com/r/singularity/comments/1atjz9v/ive_put_a_complex_codebase_into_a_single/ -
https://www.supersimple.io/blog/gpt-4-fine-tuning-early-access -
https://www.thebigquestions.com/2023/04/05/gpt-4-fails-economics/
Link Bibliography
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https://www.wired.com/story/ai-chatbots-foia-requests-election-workers/: “Election Workers Are Drowning in Records Requests. AI Chatbots Could Make It Worse: Experts Worry That Election Deniers Could Weaponize Chatbots to Overwhelm and Slow down Local Officials”, Vittoria Elliott -
https://link.springer.com/article/10.1007/s10506-024-09396-9: “Re-Evaluating GPT-4’s Bar Exam Performance”, Eric Martínez -
https://www.wsj.com/tech/ai/a-peter-thiel-backed-ai-startup-cognition-labs-seeks-2-billion-valuation-998fa39d: “A Peter Thiel-Backed AI Startup, Cognition Labs, Seeks $2 Billion Valuation: Funding round Could Increase Startup’s Valuation Nearly Sixfold in a Matter of Weeks, Reflecting AI Frenzy”, Berber Jin -
https://arxiv.org/abs/2403.18624: “Vulnerability Detection With Code Language Models: How Far Are We?”, -
https://www.bloomberg.com/news/articles/2024-03-12/cognition-ai-is-a-peter-thiel-backed-coding-assistant: “Gold-Medalist Coders Build an AI That Can Do Their Job for Them: A New Startup Called Cognition AI Can Turn a User’s Prompt into a Website or Video Game”, Ashlee Vance -
https://arxiv.org/abs/2402.14903: “Tokenization Counts: the Impact of Tokenization on Arithmetic in Frontier LLMs”, Aaditya K. Singh, D. J. Strouse -
https://arxiv.org/abs/2402.11753: “ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs”, Fengqing Jiang, Zhangchen Xu, Luyao Niu, Zhen Xiang, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran -
https://arxiv.org/abs/2402.11349: “Tasks That Language Models Don’t Learn”, Bruce W. Lee, JaeHyuk Lim -
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10894685/: “GPT-4 Passes the Bar Exam”, Daniel Martin Katz, Michael James Bommarito, Shang Gao, Pablo Arredondo -
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10936766/: “Large Language Models Are Able to Downplay Their Cognitive Abilities to Fit the Persona They Simulate”, Jiří Milička, Anna Marklová, Klára VanSlambrouck, Eva Pospíšilová, Jana Šimsová, Samuel Harvan, Ondřej Drobil -
https://arxiv.org/abs/2312.08926: “PRER: Modeling Complex Mathematical Reasoning via Large Language Model Based MathAgent”, Haoran Liao, Qinyi Du, Shaohua Hu, Hao He, Yanyan Xu, Jidong Tian, Yaohui Jin -
https://arxiv.org/abs/2311.16452#microsoft: “Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine”, -
https://arxiv.org/abs/2311.09247: “Comparing Humans, GPT-4, and GPT-4-V On Abstraction and Reasoning Tasks”, Melanie Mitchell, Alessandro B. Palmarini, Arseny Moskvichev -
https://arxiv.org/abs/2310.13014: “Large Language Model Prediction Capabilities: Evidence from a Real-World Forecasting Tournament”, Philipp Schoenegger, Peter S. Park -
https://arxiv.org/abs/2310.08678: “Can GPT Models Be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on Mock CFA Exams”, -
2023-phillips.pdf: “Can a Computer Outfake a Human [personality]?”, Jane Phillips, Chet Robie -
https://arxiv.org/abs/2310.04406: “Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models”, Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman, Haohan Wang, Yu-Xiong Wang -
https://arxiv.org/abs/2310.03214#google: “FreshLLMs: Refreshing Large Language Models With Search Engine Augmentation”, -
https://arxiv.org/abs/2310.01377: “UltraFeedback: Boosting Language Models With High-Quality Feedback”, Ganqu Cui, Lifan Yuan, Ning Ding, Guanming Yao, Wei Zhu, Yuan Ni, Guotong Xie, Zhiyuan Liu, Maosong Sun -
https://arxiv.org/abs/2309.12269: “The Cambridge Law Corpus: A Corpus for Legal AI Research”, -
https://arxiv.org/abs/2309.12288: “The Reversal Curse: LLMs Trained on "A Is B" Fail to Learn "B Is A"”, Lukas Berglund, Meg Tong, Max Kaufmann, Mikita Balesni, Asa Cooper Stickland, Tomasz Korbak, Owain Evans -
https://arxiv.org/abs/2309.04269: “From Sparse to Dense: GPT-4 Summarization With Chain of Density (CoD) Prompting”, Griffin Adams, Alexander Fabbri, Faisal Ladhak, Eric Lehman, Noémie Elhadad -
https://arxiv.org/abs/2308.07921: “Solving Challenging Math Word Problems Using GPT-4 Code Interpreter With Code-Based Self-Verification”, -
https://www.nytimes.com/2023/07/18/technology/openai-chatgpt-facial-recognition.html: “OpenAI Worries About What Its Chatbot Will Say About People’s Faces: An Advanced Version of ChatGPT Can Analyze Images and Is Already Helping the Blind. But Its Ability to Put a Name to a Face Is One Reason the Public Doesn’t Have Access to It”, Kashmir Hill -
https://arxiv.org/abs/2307.06439#microsoft: “Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events”, -
https://arxiv.org/abs/2306.15626: “LeanDojo: Theorem Proving With Retrieval-Augmented Language Models”, -
https://arxiv.org/abs/2306.12587: “ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews”, Mike D’Arcy, Alexis Ross, Erin Bransom, Bailey Kuehl, Jonathan Bragg, Tom Hope, Doug Downey -
https://arxiv.org/abs/2305.20050#openai: “Let’s Verify Step by Step”, -
https://arxiv.org/abs/2305.18354: “LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-Based Representations”, Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias B. Khalil -
https://arxiv.org/abs/2305.13534: “How Language Model Hallucinations Can Snowball”, Muru Zhang, Ofir Press, William Merrill, Alisa Liu, Noah Smith -
https://arxiv.org/abs/2305.06972: “Large Language Models Can Be Used To Effectively Scale Spear Phishing Campaigns”, Julian Hazell -
https://arxiv.org/abs/2304.11490: “Boosting Theory-Of-Mind Performance in Large Language Models via Prompting”, Shima Rahimi Moghaddam, Christopher J. Honey -
https://www.medrxiv.org/content/10.1101/2023.03.24.23287731.full: “Performance of ChatGPT on Free-Response, Clinical Reasoning Exams”, -
https://arxiv.org/abs/2304.02015#alibaba: “How Well Do Large Language Models Perform in Arithmetic Tasks?”, Zheng Yuan, Hongyi Yuan, Chuanqi Tan, Wei Wang, Songfang Huang -
https://arxiv.org/pdf/2303.08774.pdf#page=12&org=openai: “GPT-4 Technical Report § Limitations: Calibration”, OpenAI -
https://arxiv.org/abs/2302.14520: “Large Language Models Are State-Of-The-Art Evaluators of Translation Quality”, Tom Kocmi, Christian Federmann -
https://arxiv.org/abs/2302.12173: “Not What You’ve Signed up For: Compromising Real-World LLM-Integrated Applications With Indirect Prompt Injection”, Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, Christoph Endres, Thorsten Holz, Mario Fritz -
https://techcrunch.com/2022/11/23/harvey-which-uses-ai-to-answer-legal-questions-lands-cash-from-openai/: “Harvey, Which Uses AI to Answer Legal Questions, Lands Cash from OpenAI”, Kyle Wiggers