“‘Claude AI’ Tag”,2022-08-04 (Anthropic, AI mode collapse)⁠:

Bibliography for tag ai/nn/transformer/gpt/claude, most recent first: 3 related tags, 74 annotations, & 128 links (parent).

• See Also
• Gwern
  • “Statistical Notes”, Gwern2014
• Links
  • “Business Spending on AI Surged 500% This Year to $13.8 Billion”
  • “Hidden Persuaders: LLMs’ Political Leaning and Their Influence on Voters”, Potter 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”, Krebs2024
  • “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”, Schluntz2024
  • “System Prompts”, Anthropic2024
  • “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”, Wiggers2024
  • “Anthropic’s Latest Claude AI Model Pulls ahead of Rivals from OpenAI and Google”, Knight2024
  • “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”, Levy2024
  • “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”, Lemkin2024
  • “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”, Paech2023
  • “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
  • “On the Impossibility of Superintelligent Rubik’s Cube Solvers”, Gwern 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”, Knight2023
  • “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
  • “A General Language Assistant As a Laboratory for Alignment”, Askell et al 2021
  • “The Perception of Rhythm in Language”, Cutler1994
  • “In AI We Trust, Part II [Claude-3 Opus Predicting Supreme Court Decisions]”, Unikowsky2024
  • “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”
  • “Janus”
  • “The Neruda Factory”, Jenn2024
  • “Claude, Read the Chevron PDF”, Cowen & Claude-3 2024
  • “Claude Sonnet 3.5, Economist”
  • “How Anthropic Built Artifacts”, Orosz2024
  • “On Claude 3.5 Sonnet”
  • “Claude’s Dark Spiritual AI Futurism”
  • “European Parliament Revolutionizes Archive Access With Claude AI”, Anthropic2024
  • “Introducing ‘Computer Use’, a New Claude 3.5 Sonnet, and Claude 3.5 Haiku”, Anthropic2024
  • “Introducing Claude 3.5”
  • “Fine-Tune Claude 3 Haiku in Amazon Bedrock”
  • “Claude 3.5 Sonnet on GitHub Copilot”
  • “Claude’s Character”, Anthropic2024
  • “Developing a Computer Use Model”, Anthropic2024
  • “How I Use Claude”, Balwit2024
  • “Websim, Worldsim, and The Summer of Simulative AI”
  • “How Good Are LLMs at Doing ML on an Unknown Dataset?”
  • “A Poem Is All You Need: Jailbreaking ChatGPT, Meta & More”
  • “AI Will Increase the Quantity—And Quality—Of Phishing Scams”
  • QiaochuYuan
  • Wikipedia
• Miscellaneous
• Bibliography