Best AI papers explained

150 Episodes

1. GOAT: Generative Adversarial Training for Human-AI Coordination

   Published: 4/27/2025
2. π0.5: Generalization in Robotic Manipulation via Diverse Data

   Published: 4/27/2025
3. NoWag: Unified Compression for Large Language Models

   Published: 4/26/2025
4. Optimal Tool Calls in Language Model Reasoning

   Published: 4/26/2025
5. Data Selection for Empirical Risk Minimization

   Published: 4/26/2025
6. LoRe: Low-Rank Reward Modeling for Personalized LLMs

   Published: 4/26/2025
7. ParaPO: Reducing Language Model Verbatim Reproduction

   Published: 4/26/2025
8. Test-Time RL: Self-Evolving LLMs via Majority Voting Rewards

   Published: 4/25/2025
9. Tina: Tiny LoRA Reasoning Models

   Published: 4/25/2025
10. Evaluating large language models in theory of mind tasks

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

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

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

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

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

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

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

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

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

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

    Published: 4/24/2025