Best AI papers explained

440 Episodes

1. Interpretable Reward Modeling with Active Concept Bottlenecks

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

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

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

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

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

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

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

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

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

    Published: 7/10/2025
11. Provably Learning from Language Feedback

    Published: 7/9/2025
12. Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learners

    Published: 7/5/2025
13. Why Neural Network Can Discover Symbolic Structures with Gradient-based Training: An Algebraic and Geometric Foundation

    Published: 7/5/2025
14. Causal Abstraction with Lossy Representations

    Published: 7/4/2025
15. The Winner's Curse in Data-Driven Decisions

    Published: 7/4/2025
16. Embodied AI Agents: Modeling the World

    Published: 7/4/2025
17. Beyond Statistical Learning: Exact Learning Is Essential for General Intelligence

    Published: 7/4/2025
18. What Has a Foundation Model Found? Inductive Bias Reveals World Models

    Published: 7/4/2025
19. Language Bottleneck Models: A Framework for Interpretable Knowledge Tracing and Beyond

    Published: 7/3/2025
20. Learning to Explore: An In-Context Learning Approach for Pure Exploration

    Published: 7/3/2025