Best AI papers explained

441 Episodo

1. Converging Predictions with Shared Information

   Publicado: 11/5/2025
2. Test-Time Alignment Via Hypothesis Reweighting

   Publicado: 11/5/2025
3. Rethinking Diverse Human Preference Learning through Principal Component Analysis

   Publicado: 11/5/2025
4. Active Statistical Inference

   Publicado: 10/5/2025
5. Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework

   Publicado: 10/5/2025
6. AI-Powered Bayesian Inference

   Publicado: 10/5/2025
7. Can Unconfident LLM Annotations Be Used for Confident Conclusions?

   Publicado: 9/5/2025
8. Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AI

   Publicado: 9/5/2025
9. Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

   Publicado: 9/5/2025
10. How to Evaluate Reward Models for RLHF

    Publicado: 9/5/2025
11. LLMs as Judges: Survey of Evaluation Methods

    Publicado: 9/5/2025
12. The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs

    Publicado: 9/5/2025
13. Limits to scalable evaluation at the frontier: LLM as Judge won’t beat twice the data

    Publicado: 9/5/2025
14. Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation

    Publicado: 9/5/2025
15. Accelerating Unbiased LLM Evaluation via Synthetic Feedback

    Publicado: 9/5/2025
16. Prediction-Powered Statistical Inference Framework

    Publicado: 9/5/2025
17. Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL

    Publicado: 9/5/2025
18. RM-R1: Reward Modeling as Reasoning

    Publicado: 9/5/2025
19. Reexamining the Aleatoric and Epistemic Uncertainty Dichotomy

    Publicado: 8/5/2025
20. Decoding Claude Code: Terminal Agent for Developers

    Publicado: 7/5/2025