Best AI papers explained
Un pódcast de Enoch H. Kang
550 Episodo
-
Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing
Publicado: 27/11/2025 -
Prompted Policy Search: Reinforcement Learning through Linguistic and Numerical Reasoning in LLMs
Publicado: 27/11/2025 -
Ilya Sutskever – We're moving from the age of scaling to the age of research
Publicado: 26/11/2025 -
Cognitive Foundations for Reasoning and Their Manifestation in LLMs
Publicado: 26/11/2025 -
Natural emergent misalignment from reward hacking in production RL
Publicado: 25/11/2025 -
Evolution Strategies at the Hyperscale
Publicado: 25/11/2025 -
The Path Not Taken: RLVR Provably Learns Off the Principals
Publicado: 23/11/2025 -
Back to Basics: Let Denoising Generative Models Denoise
Publicado: 23/11/2025 -
LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization
Publicado: 22/11/2025 -
Black-Box On-Policy Distillation of Large Language Models
Publicado: 20/11/2025 -
Solving a million step LLM task with zero errors
Publicado: 20/11/2025 -
Not All Thoughts Matter: Selective Attention for Efficient Reasoning
Publicado: 19/11/2025 -
Sample-Efficient Parametric Learning from Natural Language
Publicado: 19/11/2025 -
Bayesian Optimization in Language space: An Eval-Efficient AI Self-Improvement Framework
Publicado: 18/11/2025 -
Context Engineering: Sessions, Memory
Publicado: 16/11/2025 -
The Era of Agentic Organization: Learning to Organize with Language Models
Publicado: 15/11/2025 -
Understanding neural networks through sparse circuits
Publicado: 14/11/2025 -
Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
Publicado: 14/11/2025 -
Multi-Agent Evolve: LLM Self-Improvement Through Co-Evolution
Publicado: 14/11/2025 -
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
Publicado: 14/11/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
