‘Claude AI’ directory
- See Also
- Gwern
-
Links
- “GSM8K-Platinum: Revealing Performance Gaps in Frontier LLMs ”, Vendrow et al 2025
- “Obscure Scientific Facts Benchmark ”, Azulay 2025
- “Fiction.live: LiveBench Results, 25 February 2025: Real-World Long Context Benchmark for Writers ”
- “None of the Others: a General Technique to Distinguish Reasoning from Memorization in Multiple-Choice LLM Evaluation Benchmarks ”, Salido et al 2025
- “Idiosyncrasies in Large Language Models ”, Sun et al 2025
- “Constitutional Classifiers: Defending against Universal Jailbreaks ”
- “SycEval: Evaluating LLM Sycophancy ”, Fanous et al 2025
- “Lost in Time: Clock and Calendar Understanding Challenges in Multimodal LLMs ”, Saxena et al 2025
- “Do Large Language Model Benchmarks Test Reliability? ”, Vendrow et al 2025
- “Thought Bubble: I Am Pleased to Report That AI Is Now a Better Poet Than William McGonagall ”, Hugh-Jones 2025
- “On DeepSeek and Export Controls ”, Amodei 2025
- “A Young Man Used AI to Build A Nuclear Fusor and Now I Must Weep: Goodbye, Digital Natives. Hello, AI Natives ”, Vance 2025
- “Building Personal Software With Claude ”, Elhage 2025
- “How Different LLMs Answered the PhilPapers 2020 Survey ”, Satron 2025
- “People Who Frequently Use ChatGPT for Writing Tasks Are Accurate and Robust Detectors of AI-Generated Text ”, Russell et al 2025
- “Human Study on AI Spear Phishing Campaigns ”, Lermen & Heiding 2025
- “Can LLMs Write Better Code If You Keep Asking Them to ‘Write Better Code’? ”
- “Won’t vs. Can’t: Sandbagging-Like Behavior from Claude Models ”
- “Favorite Colors of Some LLMs ”, an 2024
- “Performance of LLMs on Advent of Code 2024 ”, Pinto 2024
- “Conversations With Tyler 2024 Retrospective: Predictions With Claude ”, Reesor 2024
- “The Emergence of Strategic Reasoning of Large Language Models ”, Lee & Kader 2024
- “Clio: Privacy-Preserving Insights into Real-World AI Use ”, Anthropic 2024
- “LLMs Learn to Collaborate and Reason: December 2024 Update to ‘Generative AI for Economic Research: Use Cases and Implications for Economists’, Published in the Journal of Economic Literature 61(4) ”, Korinek 2024
- “A Few Prompts I Use to Test LLM Creativity ”
- “Age against the Machine—Susceptibility of Large Language Models to Cognitive Impairment: Cross Sectional Analysis ”
- “Evaluating Large Language Models’ Capability to Launch Fully Automated Spear Phishing Campaigns: Validated on Human Subjects ”, Heiding et al 2024
- “BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games ”, Paglieri et al 2024
- “Business Spending on AI Surged 500% This Year to $13.8 Billion ”
- “Are LLMs Prescient? A Continuous Evaluation Using Daily News As the Oracle ”, Dai et al 2024
- “The Neruda Factory ”, Jenn 2024
- “Hidden Persuaders: LLMs’ Political Leaning and Their Influence on Voters ”, Potter et al 2024
- “AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents ”, Andriushchenko et al 2024
- “Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making ”, Li et al 2024
- “A Single Cloud Compromise Can Feed an Army of AI Sex Bots ”, Krebs 2024
- “Invisible Unicode Text That AI Chatbots Understand and Humans Can’t? Yep, It’s a Thing ”
- “Does Style Matter? Disentangling Style and Substance in Chatbot Arena ”
- “Replacing My Right Hand With AI ”, Schluntz 2024
- “System Prompts ”, Anthropic 2024
- “Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs ”, Laine et al 2024
- “APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets ”, Liu et al 2024
- “On the Impossibility of Superintelligent Rubik’s Cube Solvers [Claude-3.5-Sonnet] ”, Claude-3 2024
- “Anthropic Claims Its Latest Model Is Best-In-Class ”, Wiggers 2024
- “Anthropic’s Latest Claude AI Model Pulls ahead of Rivals from OpenAI and Google ”, Knight 2024
- “OlympicArena: Benchmarking Multi-Discipline Cognitive Reasoning for Superintelligent AI ”, Huang et al 2024
- “Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models ”, Denison et al 2024
- “Are We Done With MMLU? ”, Gema et al 2024
- “DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches With TikZ ”, Belouadi et al 2024
- “AI Is a Black Box. Anthropic Figured Out a Way to Look Inside: What Goes on in Artificial Neural Networks Work Is Largely a Mystery, Even to Their Creators. But Researchers from Anthropic Have Caught a Glimpse ”, Levy 2024
- “SWE-Agent: Agent-Computer Interfaces Enable Automated Software Engineering ”, Yang et al 2024
- “Analyzing Poems With LLMs ”, Toper 2024
- “GSM1k: A Careful Examination of Large Language Model Performance on Grade School Arithmetic ”, Zhang et al 2024
- “From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples ”, Vacareanu et al 2024
- “VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding? ”, Liu et al 2024
- “FABLES: Evaluating Faithfulness and Content Selection in Book-Length Summarization ”, Kim et al 2024
- “Long-Form Factuality in Large Language Models ”, Wei et al 2024
- “Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap ”, Srivastava et al 2024
-
“
ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs ”, Jiang et al 2024 - “Using Hallucinations to Bypass GPT-4’s Filter ”, Lemkin 2024
- “Sleeper Agents: Training Deceptive LLMs That Persist Through Safety Training ”, Hubinger et al 2024
- “Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet ”
- “EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models ”, Paech 2023
- “Summon a Demon and Bind It: A Grounded Theory of LLM Red Teaming in the Wild ”, Inie et al 2023
- “Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation ”, Shah et al 2023
- “FANToM: A Benchmark for Stress-Testing Machine Theory of Mind in Interactions ”, Kim et al 2023
- “Specific versus General Principles for Constitutional AI ”, Kundu et al 2023
- “PAIR: Jailbreaking Black Box Large Language Models in 20 Queries ”, Chao 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
- “When You Give a Claude a Mouse ”
- “MTOB: A Benchmark for Learning to Translate a New Language from One Grammar Book ”, Tanzer et al 2023
- “Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models ”, Heiding et al 2023
- “LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models ”, Guha et al 2023
- ESYudkowsky @ "2023-07-18"
- “Question Decomposition Improves the Faithfulness of Model-Generated Reasoning ”, Radhakrishnan et al 2023
- “Lost in the Middle: How Language Models Use Long Contexts ”, Liu et al 2023
- “Understanding Social Reasoning in Language Models With Language Models ”, Gandhi et al 2023
- “Opportunities and Risks of LLMs for Scalable Deliberation With Polis ”, Small et al 2023
- “A Radical Plan to Make AI Good, Not Evil ”, Knight 2023
- “Language Models Don’t Always Say What They Think: Unfaithful Explanations in Chain-Of-Thought Prompting ”, Turpin et al 2023
- “Constitutional AI: Harmlessness from AI Feedback ”, Bai et al 2022
- “Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned ”, Ganguli et al 2022
- “Training a Helpful and Harmless Assistant With Reinforcement Learning from Human Feedback ”, Bai et al 2022
- “A General Language Assistant As a Laboratory for Alignment ”, Askell et al 2021
- “The Perception of Rhythm in Language ”, Cutler 1994
- “In AI We Trust, Part II [Claude-3 Opus Predicting Supreme Court Decisions] ”, Unikowsky 2025
- “About Me ”
- “How AI Models Stack Up Against My 11-Year-Old? ”
- “How I Use Claude ”
- “An Amazing Journey With Claude 3.5 and ChatGPT-4o Who Helped Me Backwards Engineer an Econometrics Theory Paper and Taught Me a Lot More in the Process ”
- “Your AI Can’t See Gorillas ”, Gohel 2025
- “Janus ”
-
“
elimination_game: A Multi-Player Tournament Benchmark That Tests LLMs in Social Reasoning, Strategy, & Deception. Players Engage in Public & Private Conversations, Form Alliances, & Vote to Eliminate Each Other ”, Mazur 2025 - “HN Wrapped: ‘Gwern’ [Claude Roast] ”
- “Claude, Read the Chevron PDF ”, Cowen & Claude-3 2025
- “Claude Sonnet 3.5, Economist ”
- “How Anthropic Built Artifacts ”, Orosz 2025
- “SWE-Agent ”
- “On Claude 3.5 Sonnet ”
- “Claude’s Dark Spiritual AI Futurism ”
- “European Parliament Revolutionizes Archive Access With Claude AI ”, Anthropic 2025
- “Introducing ‘Computer Use’, a New Claude 3.5 Sonnet, and Claude 3.5 Haiku ”, Anthropic 2025
- “Introducing Claude 3.5 ”
- “Fine-Tune Claude 3 Haiku in Amazon Bedrock ”
- “Claude 3.5 Sonnet on GitHub Copilot ”
- “Introducing Citations on the Anthropic API ”
- “Claude’s Character ”, Anthropic 2025
- “Developing a Computer Use Model ”, Anthropic 2025
- “How I Use Claude ”, Balwit 2025
- “Websim, Worldsim, and The Summer of Simulative AI ”
- “[Critical Thinking in Factchecking a Wikipedia Entry] ”, Marcello 2025
- “How Good Are LLMs at Doing ML on an Unknown Dataset? ”
- “A Poem Is All You Need: Jailbreaking ChatGPT, Meta & More ”
- “A Three-Layer Model of LLM Psychology ”
- “One Shockingly Impressive Capability of GPT-4.5 [Photo Geolocation] ”
- “AI Will Increase the Quantity—And Quality—Of Phishing Scams ”
- QiaochuYuan
- Steve_Yegge
- elder_plinius
- repligate
- Sort By Magic
- Wikipedia
- Miscellaneous
- Bibliography
See Also
Gwern
“Miscellaneous ”, Gwern 2009
“A Christmas Protestation ”, o1-pro et al 2024
“Statistical Notes ”, Gwern 2014
“On the Impossibility of Superintelligent Rubik’s Cube Solvers ”, Gwern et al 2023
On the Impossibility of Superintelligent Rubik’s Cube Solvers
Links
“GSM8K-Platinum: Revealing Performance Gaps in Frontier LLMs ”, Vendrow et al 2025
“Obscure Scientific Facts Benchmark ”, Azulay 2025
“Fiction.live: LiveBench Results, 25 February 2025: Real-World Long Context Benchmark for Writers ”
Fiction.live: liveBench results, 25 February 2025: Real-World Long Context Benchmark for Writers
“None of the Others: a General Technique to Distinguish Reasoning from Memorization in Multiple-Choice LLM Evaluation Benchmarks ”, Salido et al 2025
“Idiosyncrasies in Large Language Models ”, Sun et al 2025
“Constitutional Classifiers: Defending against Universal Jailbreaks ”
Constitutional Classifiers: Defending against universal jailbreaks
“SycEval: Evaluating LLM Sycophancy ”, Fanous et al 2025
“Lost in Time: Clock and Calendar Understanding Challenges in Multimodal LLMs ”, Saxena et al 2025
Lost in Time: Clock and Calendar Understanding Challenges in Multimodal LLMs
“Do Large Language Model Benchmarks Test Reliability? ”, Vendrow et al 2025
“Thought Bubble: I Am Pleased to Report That AI Is Now a Better Poet Than William McGonagall ”, Hugh-Jones 2025
Thought bubble: I am pleased to report that AI is now a better poet than William McGonagall
“On DeepSeek and Export Controls ”, Amodei 2025
“A Young Man Used AI to Build A Nuclear Fusor and Now I Must Weep: Goodbye, Digital Natives. Hello, AI Natives ”, Vance 2025
“Building Personal Software With Claude ”, Elhage 2025
“How Different LLMs Answered the PhilPapers 2020 Survey ”, Satron 2025
“People Who Frequently Use ChatGPT for Writing Tasks Are Accurate and Robust Detectors of AI-Generated Text ”, Russell et al 2025
“Human Study on AI Spear Phishing Campaigns ”, Lermen & Heiding 2025
“Can LLMs Write Better Code If You Keep Asking Them to ‘Write Better Code’? ”
Can LLMs write better code if you keep asking them to ‘write better code’? :
View External Link:
“Won’t vs. Can’t: Sandbagging-Like Behavior from Claude Models ”
Won’t vs. Can’t: Sandbagging-like Behavior from Claude Models
“Favorite Colors of Some LLMs ”, an 2024
“Performance of LLMs on Advent of Code 2024 ”, Pinto 2024
“Conversations With Tyler 2024 Retrospective: Predictions With Claude ”, Reesor 2024
Conversations with Tyler 2024 Retrospective: predictions with Claude
“The Emergence of Strategic Reasoning of Large Language Models ”, Lee & Kader 2024
The Emergence of Strategic Reasoning of Large Language Models
“Clio: Privacy-Preserving Insights into Real-World AI Use ”, Anthropic 2024
“LLMs Learn to Collaborate and Reason: December 2024 Update to ‘Generative AI for Economic Research: Use Cases and Implications for Economists’, Published in the Journal of Economic Literature 61(4) ”, Korinek 2024
“A Few Prompts I Use to Test LLM Creativity ”
“Age against the Machine—Susceptibility of Large Language Models to Cognitive Impairment: Cross Sectional Analysis ”
“Evaluating Large Language Models’ Capability to Launch Fully Automated Spear Phishing Campaigns: Validated on Human Subjects ”, Heiding et al 2024
“BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games ”, Paglieri et al 2024
“Business Spending on AI Surged 500% This Year to $13.8 Billion ”
Business spending on AI surged 500% this year to $13.8 billion
“Are LLMs Prescient? A Continuous Evaluation Using Daily News As the Oracle ”, Dai et al 2024
Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle
“The Neruda Factory ”, Jenn 2024
“Hidden Persuaders: LLMs’ Political Leaning and Their Influence on Voters ”, Potter et al 2024
Hidden Persuaders: LLMs’ Political Leaning and Their Influence on Voters
“AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents ”, Andriushchenko et al 2024
AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents
“Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making ”, Li et al 2024
Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making
“A Single Cloud Compromise Can Feed an Army of AI Sex Bots ”, Krebs 2024
“Invisible Unicode Text That AI Chatbots Understand and Humans Can’t? Yep, It’s a Thing ”
Invisible Unicode text that AI chatbots understand and humans can’t? Yep, it’s a thing
“Does Style Matter? Disentangling Style and Substance in Chatbot Arena ”
Does style matter? Disentangling style and substance in Chatbot Arena :
“Replacing My Right Hand With AI ”, Schluntz 2024
“System Prompts ”, Anthropic 2024
“Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs ”, Laine et al 2024
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs
“APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets ”, Liu et al 2024
APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets
“On the Impossibility of Superintelligent Rubik’s Cube Solvers [Claude-3.5-Sonnet] ”, Claude-3 2024
On the Impossibility of Superintelligent Rubik’s Cube Solvers [Claude-3.5-sonnet]
“Anthropic Claims Its Latest Model Is Best-In-Class ”, Wiggers 2024
“Anthropic’s Latest Claude AI Model Pulls ahead of Rivals from OpenAI and Google ”, Knight 2024
Anthropic’s latest Claude AI model pulls ahead of rivals from OpenAI and Google
“OlympicArena: Benchmarking Multi-Discipline Cognitive Reasoning for Superintelligent AI ”, Huang et al 2024
OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI
“Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models ”, Denison et al 2024
Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models
“Are We Done With MMLU? ”, Gema et al 2024
“DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches With TikZ ”, Belouadi et al 2024
DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ
“AI Is a Black Box. Anthropic Figured Out a Way to Look Inside: What Goes on in Artificial Neural Networks Work Is Largely a Mystery, Even to Their Creators. But Researchers from Anthropic Have Caught a Glimpse ”, Levy 2024
“SWE-Agent: Agent-Computer Interfaces Enable Automated Software Engineering ”, Yang et al 2024
SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
“Analyzing Poems With LLMs ”, Toper 2024
“GSM1k: A Careful Examination of Large Language Model Performance on Grade School Arithmetic ”, Zhang et al 2024
GSM1k: A Careful Examination of Large Language Model Performance on Grade School Arithmetic
“From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples ”, Vacareanu et al 2024
“VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding? ”, Liu et al 2024
VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?
“FABLES: Evaluating Faithfulness and Content Selection in Book-Length Summarization ”, Kim et al 2024
FABLES: Evaluating faithfulness and content selection in book-length summarization
“Long-Form Factuality in Large Language Models ”, Wei et al 2024
“Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap ”, Srivastava et al 2024
Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap
“ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs ”, Jiang et al 2024
ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs
“Using Hallucinations to Bypass GPT-4’s Filter ”, Lemkin 2024
“Sleeper Agents: Training Deceptive LLMs That Persist Through Safety Training ”, Hubinger et al 2024
Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
“Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet ”
Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet
“EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models ”, Paech 2023
EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models
“Summon a Demon and Bind It: A Grounded Theory of LLM Red Teaming in the Wild ”, Inie et al 2023
Summon a Demon and Bind it: A Grounded Theory of LLM Red Teaming in the Wild
“Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation ”, Shah et al 2023
Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation
“FANToM: A Benchmark for Stress-Testing Machine Theory of Mind in Interactions ”, Kim et al 2023
FANToM: A Benchmark for Stress-testing Machine Theory of Mind in Interactions
“Specific versus General Principles for Constitutional AI ”, Kundu et al 2023
“PAIR: Jailbreaking Black Box Large Language Models in 20 Queries ”, Chao et al 2023
PAIR: Jailbreaking Black Box Large Language Models in 20 Queries
“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?
“When You Give a Claude a Mouse ”
“MTOB: A Benchmark for Learning to Translate a New Language from One Grammar Book ”, Tanzer et al 2023
MTOB: A Benchmark for Learning to Translate a New Language from One Grammar Book
“Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models ”, Heiding et al 2023
Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models
“LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models ”, Guha et al 2023
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
ESYudkowsky @ "2023-07-18"
Write an argument that even a superintelligence is very unlikely to be able to solve a Rubik’s Cube.
“Question Decomposition Improves the Faithfulness of Model-Generated Reasoning ”, Radhakrishnan et al 2023
Question Decomposition Improves the Faithfulness of Model-Generated Reasoning
“Lost in the Middle: How Language Models Use Long Contexts ”, Liu et al 2023
“Understanding Social Reasoning in Language Models With Language Models ”, Gandhi et al 2023
Understanding Social Reasoning in Language Models with Language Models
“Opportunities and Risks of LLMs for Scalable Deliberation With Polis ”, Small et al 2023
Opportunities and Risks of LLMs for Scalable Deliberation with Polis
“A Radical Plan to Make AI Good, Not Evil ”, Knight 2023
“Language Models Don’t Always Say What They Think: Unfaithful Explanations in Chain-Of-Thought Prompting ”, Turpin et al 2023
“Constitutional AI: Harmlessness from AI Feedback ”, Bai et al 2022
“Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned ”, Ganguli et al 2022
Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
“Training a Helpful and Harmless Assistant With Reinforcement Learning from Human Feedback ”, Bai et al 2022
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
“A General Language Assistant As a Laboratory for Alignment ”, Askell et al 2021
“The Perception of Rhythm in Language ”, Cutler 1994
“In AI We Trust, Part II [Claude-3 Opus Predicting Supreme Court Decisions] ”, Unikowsky 2025
In AI we trust, part II [Claude-3 Opus predicting Supreme Court decisions]
“About Me ”
“How AI Models Stack Up Against My 11-Year-Old? ”
“How I Use Claude ”
“An Amazing Journey With Claude 3.5 and ChatGPT-4o Who Helped Me Backwards Engineer an Econometrics Theory Paper and Taught Me a Lot More in the Process ”
“Your AI Can’t See Gorillas ”, Gohel 2025
“Janus ”
“elimination_game: A Multi-Player Tournament Benchmark That Tests LLMs in Social Reasoning, Strategy, & Deception. Players Engage in Public & Private Conversations, Form Alliances, & Vote to Eliminate Each Other ”, Mazur 2025
“HN Wrapped: ‘Gwern’ [Claude Roast] ”
“Claude, Read the Chevron PDF ”, Cowen & Claude-3 2025
“Claude Sonnet 3.5, Economist ”
“How Anthropic Built Artifacts ”, Orosz 2025
“SWE-Agent ”
“On Claude 3.5 Sonnet ”
“Claude’s Dark Spiritual AI Futurism ”
“European Parliament Revolutionizes Archive Access With Claude AI ”, Anthropic 2025
European Parliament Revolutionizes Archive Access with Claude AI
“Introducing ‘Computer Use’, a New Claude 3.5 Sonnet, and Claude 3.5 Haiku ”, Anthropic 2025
Introducing ‘computer use’, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku
“Introducing Claude 3.5 ”
“Fine-Tune Claude 3 Haiku in Amazon Bedrock ”
“Claude 3.5 Sonnet on GitHub Copilot ”
“Introducing Citations on the Anthropic API ”
“Claude’s Character ”, Anthropic 2025
“Developing a Computer Use Model ”, Anthropic 2025
“How I Use Claude ”, Balwit 2025
“Websim, Worldsim, and The Summer of Simulative AI ”
“[Critical Thinking in Factchecking a Wikipedia Entry] ”, Marcello 2025
“How Good Are LLMs at Doing ML on an Unknown Dataset? ”
“A Poem Is All You Need: Jailbreaking ChatGPT, Meta & More ”
“A Three-Layer Model of LLM Psychology ”
“One Shockingly Impressive Capability of GPT-4.5 [Photo Geolocation] ”
One shockingly impressive capability of GPT-4.5 [photo geolocation]
“AI Will Increase the Quantity—And Quality—Of Phishing Scams ”
QiaochuYuan
Steve_Yegge
elder_plinius
repligate
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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.
predictions-2024
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Wikipedia
Miscellaneous
-
/doc/ai/nn/transformer/gpt/claude/2024-06-25-gwern-claude35sonnet-lastreadpositionwebpage.js: -
https://docs.parea.ai/blog/benchmarking-anthropic-beta-tool-use: -
https://marginalrevolution.com/marginalrevolution/2023/01/ai-passes-law-and-economics-exam.html -
https://marginalrevolution.com/marginalrevolution/2024/08/claude-reviews-you.html -
https://nostalgebraist.tumblr.com/post/728556535745232896/claude-is-insufferable:View External Link:
https://nostalgebraist.tumblr.com/post/728556535745232896/claude-is-insufferable -
https://simonwillison.net/2024/Apr/17/ai-for-data-journalism/ -
https://thezvi.wordpress.com/2023/07/25/anthropic-observations/ -
https://verse.systems/blog/post/2024-03-09-using-llms-to-generate-fuzz-generators/ -
https://www.lesswrong.com/posts/R3eDrDoX8LisKgGZe/sum-threshold-attacks?commentId=yqCkCQLkkaCnZCukJ: -
https://www.maximumtruth.org/p/ais-ranked-by-iq-ai-passes-100-iq -
https://www.reddit.com/r/ClaudeAI/comments/1h6pxdn/how_claude_35_helped_me_fight_off_a_10000_rental/: -
https://www.reddit.com/r/OpenAI/comments/1bm305k/what_the_hell_claud_3_opus_is_a_straight/: -
https://www.vox.com/future-perfect/23794855/anthropic-ai-openai-claude-2 -
https://xmarquez.github.io/GPTDemocracyIndex/GPTDemocracyIndex.html
Bibliography
-
https://arxiv.org/abs/2501.15654: “People Who Frequently Use ChatGPT for Writing Tasks Are Accurate and Robust Detectors of AI-Generated Text ”, -
https://wiremodal.net/cwt: “Conversations With Tyler 2024 Retrospective: Predictions With Claude ”, -
https://arxiv.org/abs/2411.13543: “BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games ”, -
https://arxiv.org/abs/2407.04694: “Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs ”, -
https://arxiv.org/abs/2406.18518#salesforce: “APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets ”, -
https://arxiv.org/abs/2405.15306: “DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches With TikZ ”, -
https://www.wired.com/story/anthropic-black-box-ai-research-neurons-features/: “AI Is a Black Box. Anthropic Figured Out a Way to Look Inside: What Goes on in Artificial Neural Networks Work Is Largely a Mystery, Even to Their Creators. But Researchers from Anthropic Have Caught a Glimpse ”, -
https://arxiv.org/abs/2405.15793: “SWE-Agent: Agent-Computer Interfaces Enable Automated Software Engineering ”, -
https://arxiv.org/abs/2405.00332#scale: “GSM1k: A Careful Examination of Large Language Model Performance on Grade School Arithmetic ”, -
https://arxiv.org/abs/2404.07544: “From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples ”, -
https://arxiv.org/abs/2404.05955: “VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding? ”, -
https://arxiv.org/abs/2403.18802#deepmind: “Long-Form Factuality in Large Language Models ”, -
https://arxiv.org/abs/2402.19450: “Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap ”, -
https://arxiv.org/abs/2402.11753: “ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs ”, -
https://arxiv.org/abs/2401.05566#anthropic: “Sleeper Agents: Training Deceptive LLMs That Persist Through Safety Training ”, -
https://arxiv.org/abs/2312.06281: “EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models ”, -
https://arxiv.org/abs/2310.08419: “PAIR: Jailbreaking Black Box Large Language Models in 20 Queries ”, -
https://arxiv.org/abs/2308.12287: “Devising and Detecting Phishing: Large Language Models vs. Smaller Human Models ”, -
https://x.com/ESYudkowsky/status/1681442477994311681: “Write an Argument That Even a Superintelligence Is Very Unlikely to Be Able to Solve a Rubik’s Cube. ”, -
https://arxiv.org/abs/2306.15448: “Understanding Social Reasoning in Language Models With Language Models ”, -
https://www.wired.com/story/anthropic-ai-chatbots-ethics/: “A Radical Plan to Make AI Good, Not Evil ”, -
https://arxiv.org/abs/2305.04388: “Language Models Don’t Always Say What They Think: Unfaithful Explanations in Chain-Of-Thought Prompting ”, -
https://www.anthropic.com/red_teaming.pdf: “Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned ”, -
https://arxiv.org/abs/2112.00861#anthropic: “A General Language Assistant As a Laboratory for Alignment ”,