Best AI papers explained

550 Episodes

1. Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities

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

   Published: 7/20/2025
3. Language Model Personalization via Reward Factorization

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

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

   Published: 7/17/2025
6. Soft Best-of-n Sampling for Model Alignment

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

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

   Published: 7/15/2025
9. Probing Foundation Models for World Models

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

    Published: 7/14/2025
11. Interpretable Reward Modeling with Active Concept Bottlenecks

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

    Published: 7/14/2025
13. A Collectivist, Economic Perspective on AI

    Published: 7/14/2025
14. Textual Bayes: Quantifying Uncertainty in LLM-Based Systems

    Published: 7/12/2025
15. The Winner's Curse in Data-Driven Decisions

    Published: 7/11/2025
16. SPIRAL: Self-Play for Reasoning Through Zero-Sum Games

    Published: 7/11/2025
17. Beyond Statistical Learning: Exact Learning Is Essential for General Intelligence

    Published: 7/11/2025
18. Aligning Learning and Endogenous Decision-Making

    Published: 7/11/2025
19. Reliable Statistical Inference with Synthetic Data from Large Language Models

    Published: 7/11/2025
20. Multi-Turn Reinforcement Learning from Human Preference Feedback

    Published: 7/10/2025