Best AI papers explained

437 Episodo

1. LLM Economist: Large Population Models and Mechanism Design in Multi-Agent Generative Simulacra

   Publicado: 28/7/2025
2. Microsoft's Blueprint: AI, Quantum, and the Agentic Future

   Publicado: 26/7/2025
3. Zuckerberg's AI Vision Analyzed

   Publicado: 26/7/2025
4. Inside Claude: Scaling, Agency, and Interpretability

   Publicado: 26/7/2025
5. Personalized language modeling from personalized human feedback

   Publicado: 26/7/2025
6. Position: Empowering Time Series Reasoning with Multimodal LLMs

   Publicado: 25/7/2025
7. An empirical risk minimization approach for offline inverse RL and Dynamic Discrete Choice models

   Publicado: 22/7/2025
8. Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities

   Publicado: 22/7/2025
9. The Invisible Leash: Why RLVR May Not Escape Its Origin

   Publicado: 20/7/2025
10. Language Model Personalization via Reward Factorization

    Publicado: 20/7/2025
11. Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions

    Publicado: 18/7/2025
12. Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective

    Publicado: 17/7/2025
13. Soft Best-of-n Sampling for Model Alignment

    Publicado: 16/7/2025
14. On Temporal Credit Assignment and Data-Efficient Reinforcement Learning

    Publicado: 15/7/2025
15. Bradley–Terry and Multi-Objective Reward Modeling Are Complementary

    Publicado: 15/7/2025
16. Probing Foundation Models for World Models

    Publicado: 15/7/2025
17. GenAI-Powered Statistical Inference (with Unstructured Data)

    Publicado: 14/7/2025
18. Interpretable Reward Modeling with Active Concept Bottlenecks

    Publicado: 14/7/2025
19. PrefillOnly: An Inference Engine for Prefill-only Workloads in Large Language Model Applications

    Publicado: 14/7/2025
20. A Collectivist, Economic Perspective on AI

    Publicado: 14/7/2025