Best AI papers explained

426 Episodes

1. Harnessing the Universal Geometry of Embeddings

   Published: 5/27/2025
2. Goal Inference using Reward-Producing Programs in a Novel Physics Environment

   Published: 5/27/2025
3. Trial-Error-Explain In-Context Learning for Personalized Text Generation

   Published: 5/27/2025
4. Reinforcement Learning for Reasoning in Large Language Models with One Training Example

   Published: 5/27/2025
5. Test-Time Reinforcement Learning (TTRL)

   Published: 5/27/2025
6. Interpreting Emergent Planning in Model-Free Reinforcement Learning

   Published: 5/26/2025
7. Agentic Reward Modeling_Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems

   Published: 5/26/2025
8. Beyond Reward Hacking: Causal Rewards for Large LanguageModel Alignment

   Published: 5/26/2025
9. Learning How Hard to Think: Input-Adaptive Allocation of LM Computation

   Published: 5/26/2025
10. Highlighting What Matters: Promptable Embeddings for Attribute-Focused Image Retrieval

    Published: 5/26/2025
11. UFT: Unifying Supervised and Reinforcement Fine-Tuning

    Published: 5/26/2025
12. Understanding High-Dimensional Bayesian Optimization

    Published: 5/26/2025
13. Inference time alignment in continuous space

    Published: 5/25/2025
14. Efficient Test-Time Scaling via Self-Calibration

    Published: 5/25/2025
15. Conformal Prediction via Bayesian Quadrature

    Published: 5/25/2025
16. Predicting from Strings: Language Model Embeddings for Bayesian Optimization

    Published: 5/25/2025
17. Self-Evolving Curriculum for LLM Reasoning

    Published: 5/25/2025
18. Online Decision-Focused Learning in Dynamic Environments

    Published: 5/25/2025
19. FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain

    Published: 5/25/2025
20. Reward Shaping from Confounded Offline Data

    Published: 5/25/2025