Best AI papers explained

Podcast autorstwa Enoch H. Kang

550 Odcinki

Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing
Opublikowany: 27.11.2025
Prompted Policy Search: Reinforcement Learning through Linguistic and Numerical Reasoning in LLMs
Opublikowany: 27.11.2025
Ilya Sutskever – We're moving from the age of scaling to the age of research
Opublikowany: 26.11.2025
Cognitive Foundations for Reasoning and Their Manifestation in LLMs
Opublikowany: 26.11.2025
Natural emergent misalignment from reward hacking in production RL
Opublikowany: 25.11.2025
Evolution Strategies at the Hyperscale
Opublikowany: 25.11.2025
The Path Not Taken: RLVR Provably Learns Off the Principals
Opublikowany: 23.11.2025
Back to Basics: Let Denoising Generative Models Denoise
Opublikowany: 23.11.2025
LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization
Opublikowany: 22.11.2025
Black-Box On-Policy Distillation of Large Language Models
Opublikowany: 20.11.2025
Solving a million step LLM task with zero errors
Opublikowany: 20.11.2025
Not All Thoughts Matter: Selective Attention for Efficient Reasoning
Opublikowany: 19.11.2025
Sample-Efficient Parametric Learning from Natural Language
Opublikowany: 19.11.2025
Bayesian Optimization in Language space: An Eval-Efficient AI Self-Improvement Framework
Opublikowany: 18.11.2025
Context Engineering: Sessions, Memory
Opublikowany: 16.11.2025
The Era of Agentic Organization: Learning to Organize with Language Models
Opublikowany: 15.11.2025
Understanding neural networks through sparse circuits
Opublikowany: 14.11.2025
Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
Opublikowany: 14.11.2025
Multi-Agent Evolve: LLM Self-Improvement Through Co-Evolution
Opublikowany: 14.11.2025
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
Opublikowany: 14.11.2025

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550 Odcinki

Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing

Prompted Policy Search: Reinforcement Learning through Linguistic and Numerical Reasoning in LLMs

Ilya Sutskever – We're moving from the age of scaling to the age of research

Cognitive Foundations for Reasoning and Their Manifestation in LLMs

Natural emergent misalignment from reward hacking in production RL

Evolution Strategies at the Hyperscale

The Path Not Taken: RLVR Provably Learns Off the Principals

Back to Basics: Let Denoising Generative Models Denoise

LLM Prompt Duel Optimizer: Efficient Label-Free Prompt Optimization

Black-Box On-Policy Distillation of Large Language Models

Solving a million step LLM task with zero errors

Not All Thoughts Matter: Selective Attention for Efficient Reasoning

Sample-Efficient Parametric Learning from Natural Language

Bayesian Optimization in Language space: An Eval-Efficient AI Self-Improvement Framework

Context Engineering: Sessions, Memory

The Era of Agentic Organization: Learning to Organize with Language Models

Understanding neural networks through sparse circuits

Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning

Multi-Agent Evolve: LLM Self-Improvement Through Co-Evolution

LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics