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2025​

  • Equipping agents for the real world with Agent Skills — article=anthropic-agent-skills@2026-08-30

2024​

  • Gemma: Open Models Based on Gemini Research and Technology — paper=gemma-open-models-based-on-gemini-research-and@arXiv:2403.08295v4
  • Mixtral of Experts — paper=mixtral-of-experts@arXiv:2401.04088v1
  • Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone — paper=phi-3-technical-report-a-highly-capable-language@arXiv:2404.14219v4
  • Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training — paper=sleeper-agents-training-deceptive-llms-that-persist-through@arXiv:2401.05566v3
  • The Llama 3 Herd of Models — paper=the-llama-3-herd-of-models@arXiv:2407.21783v3

2023​

  • Gemini: A Family of Highly Capable Multimodal Models — paper=gemini-a-family-of-highly-capable-multimodal-models@arXiv:2312.11805v5
  • GPT-4 Technical Report — paper=gpt-4-technical-report@arXiv:2303.08774v6
  • Llama 2: Open Foundation and Fine-Tuned Chat Models — paper=llama-2-open-foundation-and-fine-tuned-chat@arXiv:2307.09288v2
  • LLaMA: Open and Efficient Foundation Language Models — paper=llama-open-and-efficient-foundation-language-models@arXiv:2302.13971v1
  • Mistral 7B — paper=mistral-7b@arXiv:2310.06825v1

2022​

  • Hierarchical Text-Conditional Image Generation with CLIP Latents — paper=hierarchical-text-conditional-image-generation-with-clip-latents@arXiv:2204.06125v1
  • PaLM: Scaling Language Modeling with Pathways — paper=palm-scaling-language-modeling-with-pathways@arXiv:2204.02311v5
  • Robust Speech Recognition via Large-Scale Weak Supervision — paper=robust-speech-recognition-via-large-scale-weak-supervision@arXiv:2212.04356v1
  • Scaling Instruction-Finetuned Language Models — paper=scaling-instruction-finetuned-language-models@arXiv:2210.11416v5
  • Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback — paper=training-a-helpful-and-harmless-assistant-with-reinforcement@arXiv:2204.05862v1

2021​

  • Evaluating Large Language Models Trained on Code — paper=evaluating-large-language-models-trained-on-code@arXiv:2107.03374v2
  • Finetuned Language Models Are Zero-Shot Learners — paper=finetuned-language-models-are-zero-shot-learners@arXiv:2109.01652v5
  • Zero-Shot Text-to-Image Generation — paper=zero-shot-text-to-image-generation@arXiv:2102.12092v2

2019​

  • Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer — paper=exploring-the-limits-of-transfer-learning-with-a@arXiv:1910.10683v4