Best AI papers explained
A podcast by Enoch H. Kang
544 Episodes
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The Path Not Taken: RLVR Provably Learns Off the Principals
Published: 11/23/2025 -
Back to Basics: Let Denoising Generative Models Denoise
Published: 11/23/2025 -
LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization
Published: 11/22/2025 -
Black-Box On-Policy Distillation of Large Language Models
Published: 11/20/2025 -
Solving a million step LLM task with zero errors
Published: 11/20/2025 -
Not All Thoughts Matter: Selective Attention for Efficient Reasoning
Published: 11/19/2025 -
Sample-Efficient Parametric Learning from Natural Language
Published: 11/19/2025 -
Bayesian Optimization in Language space: An Eval-Efficient AI Self-Improvement Framework
Published: 11/18/2025 -
Context Engineering: Sessions, Memory
Published: 11/16/2025 -
The Era of Agentic Organization: Learning to Organize with Language Models
Published: 11/15/2025 -
Understanding neural networks through sparse circuits
Published: 11/14/2025 -
Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
Published: 11/14/2025 -
Multi-Agent Evolve: LLM Self-Improvement Through Co-Evolution
Published: 11/14/2025 -
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
Published: 11/14/2025 -
PREFDISCO: Evaluating Proactive Personalization through Interactive Preference Discovery
Published: 11/12/2025 -
Reusing pre-training data at test time is a compute multiplier
Published: 11/10/2025 -
Scaling Agent Learning via Experience Synthesis
Published: 11/9/2025 -
Continuous Autoregressive Language Models
Published: 11/8/2025 -
Toward a Theory of Agents as Tool-Use Decision-Makers
Published: 11/7/2025 -
Nested Learning: The Illusion of Deep Learning Architectures
Published: 11/5/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
