Best AI papers explained

153 Episodes

1. Optimal Prediction Sets for Enhanced Human-AI Accuracy

   Published: 4/24/2025
2. Self-Correction via Reinforcement Learning for Language Models

   Published: 4/24/2025
3. Tractable Multi-Agent Reinforcement Learning through Behavioral Economics

   Published: 4/24/2025
4. Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement

   Published: 4/24/2025
5. Iterative Nash Policy Optimization for Language Model Alignment

   Published: 4/24/2025
6. SycEval: Benchmarking LLM Sycophancy in Mathematics and Medicine

   Published: 4/23/2025
7. Stack AI: Democratizing Enterprise AI Development

   Published: 4/22/2025
8. Evaluating Modern Recommender Systems: Challenges and Future Directions

   Published: 4/22/2025
9. AI in the Enterprise: Seven Lessons from Frontier Companies by OpenAI

   Published: 4/22/2025
10. Discussion: Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

    Published: 4/21/2025
11. AI Agent Protocols and Human Preference

    Published: 4/21/2025
12. Cross-Environment Cooperation for Zero-Shot Multi-Agent Coordination

    Published: 4/20/2025
13. Sutton and Silver: The Era of Experience: Learning Beyond Human Data

    Published: 4/19/2025
14. Sample, Don't Search: Rethinking Test-Time Alignment for Language Models

    Published: 4/19/2025
15. AI Agents: Echoes of Past Technology Pivots?

    Published: 4/19/2025
16. Minimalist LLM Reasoning: Rejection Sampling to Reinforcement

    Published: 4/19/2025
17. Securing the Model Context Protocol in Enterprise Environments

    Published: 4/19/2025
18. Improving Multi-Turn Tool Use with Reinforcement Learning

    Published: 4/19/2025
19. Cultural Knowledge Conservation and Control in Large Language Models

    Published: 4/19/2025
20. Data Quality, Repetition, and Scaling of Language Models

    Published: 4/18/2025