Best AI papers explained
A podcast by Enoch H. Kang
550 Episodes
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Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models
Published: 5/27/2025 -
Improved Techniques for Training Score-Based Generative Models
Published: 5/27/2025 -
Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator
Published: 5/27/2025 -
AlphaEvolve: A coding agent for scientific and algorithmic discovery
Published: 5/27/2025 -
Harnessing the Universal Geometry of Embeddings
Published: 5/27/2025 -
Goal Inference using Reward-Producing Programs in a Novel Physics Environment
Published: 5/27/2025 -
Trial-Error-Explain In-Context Learning for Personalized Text Generation
Published: 5/27/2025 -
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Published: 5/27/2025 -
Test-Time Reinforcement Learning (TTRL)
Published: 5/27/2025 -
Interpreting Emergent Planning in Model-Free Reinforcement Learning
Published: 5/26/2025 -
Agentic Reward Modeling_Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems
Published: 5/26/2025 -
Beyond Reward Hacking: Causal Rewards for Large LanguageModel Alignment
Published: 5/26/2025 -
Learning How Hard to Think: Input-Adaptive Allocation of LM Computation
Published: 5/26/2025 -
Highlighting What Matters: Promptable Embeddings for Attribute-Focused Image Retrieval
Published: 5/26/2025 -
UFT: Unifying Supervised and Reinforcement Fine-Tuning
Published: 5/26/2025 -
Understanding High-Dimensional Bayesian Optimization
Published: 5/26/2025 -
Inference time alignment in continuous space
Published: 5/25/2025 -
Efficient Test-Time Scaling via Self-Calibration
Published: 5/25/2025 -
Conformal Prediction via Bayesian Quadrature
Published: 5/25/2025 -
Predicting from Strings: Language Model Embeddings for Bayesian Optimization
Published: 5/25/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
