Best AI papers explained

203 Episodes

1. AI Agent Protocols and Human Preference

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

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

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

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

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

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

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

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

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

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

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

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

    Published: 4/14/2025
14. RL Post-training Amplifies Pretraining Behaviors in Language Models

    Published: 4/14/2025
15. Fast Adaptation of Behavioral Foundation Models

    Published: 4/14/2025
16. Proprietary Reward Models: Sustaining Advantage in Agentic AI

    Published: 4/13/2025
17. Why Multi-Agent LLM Systems Fail: A Comprehensive Study

    Published: 4/12/2025
18. Play2Prompt: Zero-Shot Tool Instruction Optimization via Tool Play

    Published: 4/12/2025
19. Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

    Published: 4/12/2025
20. API and GUI Agents: Divergence, Convergence, and Hybrid Approaches

    Published: 4/12/2025