Best AI papers explained

430 Episodes

1. Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    Published: 4/18/2025
18. Compute-Optimal Scaling Laws for Language Models Revisited

    Published: 4/18/2025
19. Concise Reasoning via Reinforcement Learning

    Published: 4/18/2025
20. Throughput Limits for LLM Inference and AI Agent Scheduling

    Published: 4/14/2025