Best AI papers explained
Un podcast de Enoch H. Kang
522 Épisodes
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DINOv3: Vision Models for Self-Supervised Learning
Publié: 15/08/2025 -
Agent Lightning: Training Any AI Agents with Reinforcement Learning
Publié: 14/08/2025 -
Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier
Publié: 14/08/2025 -
From Model Weights to Agent Workflows: Charting the New Frontier of Optimization in Large Language Models
Publié: 12/08/2025 -
Is Chain-of-Thought Reasoning a Mirage?
Publié: 12/08/2025 -
Agentic Web: Weaving the Next Web with AI Agents
Publié: 11/08/2025 -
The Assimilation-Accommodation Gap in LLM Intelligence
Publié: 10/08/2025 -
The Minimalist AI Kernel: A New Frontier in Reasoning
Publié: 06/08/2025 -
Statistical Rigor for Interpretable AI
Publié: 06/08/2025 -
Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value
Publié: 04/08/2025 -
A foundation model to predict and capture human cognition
Publié: 04/08/2025 -
Generative Recommendation with Semantic IDs: A Practitioner’s Handbook
Publié: 04/08/2025 -
Hierarchical Reasoning Model
Publié: 04/08/2025 -
Test-time Offline Reinforcement Learning on Goal-related Experience
Publié: 04/08/2025 -
Interpreting Chain of Thought: A Walkthrough and Discussion
Publié: 04/08/2025 -
The wall confronting large language models
Publié: 04/08/2025 -
COLLABLLM: LLMs From Passive to Collaborative
Publié: 31/07/2025 -
A decade's battle on dataset bias: are we there yet?
Publié: 29/07/2025 -
GEPA: Generative Feedback for AI System Optimization
Publié: 29/07/2025 -
From AI-Curious to AI-First: Engineering Production AI Systems
Publié: 28/07/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
