Best AI papers explained
A podcast by Enoch H. Kang
421 Episodes
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Agent Lightning: Training Any AI Agents with Reinforcement Learning
Published: 8/14/2025 -
Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier
Published: 8/14/2025 -
From Model Weights to Agent Workflows: Charting the New Frontier of Optimization in Large Language Models
Published: 8/12/2025 -
Is Chain-of-Thought Reasoning a Mirage?
Published: 8/12/2025 -
Agentic Web: Weaving the Next Web with AI Agents
Published: 8/11/2025 -
The Assimilation-Accommodation Gap in LLM Intelligence
Published: 8/10/2025 -
The Minimalist AI Kernel: A New Frontier in Reasoning
Published: 8/6/2025 -
Statistical Rigor for Interpretable AI
Published: 8/6/2025 -
Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value
Published: 8/4/2025 -
A foundation model to predict and capture human cognition
Published: 8/4/2025 -
Generative Recommendation with Semantic IDs: A Practitioner’s Handbook
Published: 8/4/2025 -
Hierarchical Reasoning Model
Published: 8/4/2025 -
Test-time Offline Reinforcement Learning on Goal-related Experience
Published: 8/4/2025 -
Interpreting Chain of Thought: A Walkthrough and Discussion
Published: 8/4/2025 -
The wall confronting large language models
Published: 8/4/2025 -
COLLABLLM: LLMs From Passive to Collaborative
Published: 7/31/2025 -
A decade's battle on dataset bias: are we there yet?
Published: 7/29/2025 -
GEPA: Generative Feedback for AI System Optimization
Published: 7/29/2025 -
From AI-Curious to AI-First: Engineering Production AI Systems
Published: 7/28/2025 -
Context Engineering: Beyond Simple Prompting to LLM Architecture
Published: 7/28/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.