Best AI papers explained

529 Odcinki

1. Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework

   Opublikowany: 31.03.2025
2. Why MCP won

   Opublikowany: 31.03.2025
3. SWEET-RL: Training LLM Agents for Collaborative Reasoning

   Opublikowany: 31.03.2025
4. TheoryCoder: Bilevel Planning with Synthesized World Models

   Opublikowany: 30.03.2025
5. Driving Forces in AI: Scaling to 2025 and Beyond (Jason Wei, OpenAI)

   Opublikowany: 29.03.2025
6. Expert Demonstrations for Sequential Decision Making under Heterogeneity

   Opublikowany: 28.03.2025
7. TextGrad: Backpropagating Language Model Feedback for Generative AI Optimization

   Opublikowany: 27.03.2025
8. MemReasoner: Generalizing Language Models on Reasoning-in-a-Haystack Tasks

   Opublikowany: 27.03.2025
9. RAFT: In-Domain Retrieval-Augmented Fine-Tuning for Language Models

   Opublikowany: 27.03.2025
10. Inductive Biases for Exchangeable Sequence Modeling

    Opublikowany: 26.03.2025
11. InverseRLignment: LLM Alignment via Inverse Reinforcement Learning

    Opublikowany: 26.03.2025
12. Prompt-OIRL: Offline Inverse RL for Query-Dependent Prompting

    Opublikowany: 26.03.2025
13. Alignment from Demonstrations for Large Language Models

    Opublikowany: 25.03.2025
14. Q♯: Distributional RL for Optimal LLM Post-Training

    Opublikowany: 18.03.2025
15. Scaling Test-Time Compute Without Verification or RL is Suboptimal

    Opublikowany: 14.03.2025
16. Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

    Opublikowany: 14.03.2025
17. Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning

    Opublikowany: 14.03.2025
18. Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback

    Opublikowany: 14.03.2025
19. Revisiting Superficial Alignment Hypothesis

    Opublikowany: 14.03.2025
20. Diagnostic uncertainty: teaching language Models to describe open-ended uncertainty

    Opublikowany: 14.03.2025