Best AI papers explained

150 Episodes

1. Diagnostic uncertainty: teaching language Models to describe open-ended uncertainty

   Published: 3/14/2025
2. Language Model Personalization via Reward Factorization

   Published: 3/14/2025
3. Is a Good Foundation Necessary for Efficient Reinforcement Learning? The Computational Role of the Base Model in Exploration

   Published: 3/14/2025
4. How Well do LLMs Compress Their Own Chain-of-Thought? A Token Complexity Approach

   Published: 3/14/2025
5. Can Large Language Models Extract Customer Needs as well as Professional Analysts?

   Published: 3/13/2025
6. Spurlens: finding spurious correlations in Multimodal llms

   Published: 3/13/2025
7. Improving test-time search with backtrack- Ing Improving test-time search with backtrack- Ing against in-context value verifiersagainst in-context value verifiers

   Published: 3/13/2025
8. Adaptive elicitation of latent information Using natural language

   Published: 3/13/2025
9. Document Valuation in LLM Summaries: A Cluster Shapley Approach

   Published: 3/13/2025
10. s1: simple test time scaling

    Published: 3/13/2025