Best AI papers explained

Podcast készítő Enoch H. Kang

550 Epizód

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

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550 Epizód

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