Best AI papers explained

481 Episodes

1. Evaluating large language models in theory of mind tasks

   Published: 4/25/2025
2. QUEST: Quality Sampling for Machine Translation

   Published: 4/24/2025
3. Offline Preference Learning via Simulated Trajectory Feedback

   Published: 4/24/2025
4. Reasoning Elicitation in Language Models via Counterfactual Feedback

   Published: 4/24/2025
5. Eliciting Human Preferences with Language Models

   Published: 4/24/2025
6. Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning

   Published: 4/24/2025
7. γ-Bench: Evaluating LLMs in Multi-Agent Games

   Published: 4/24/2025
8. DRAFT: Self-Driven LLM Tool Mastery via Documentation Refinement

   Published: 4/24/2025
9. Optimal Prediction Sets for Enhanced Human-AI Accuracy

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

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

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

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

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

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

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

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

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

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

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

    Published: 4/20/2025