Direct Preference Optimization with Unobserved Preference Heterogeneity: The Necessity of Ternary Preferences

The Coverage Principle: How Pre-Training Enables Post-Training

The Era of Real-World Human Interaction: RL from User Conversations

Agent Learning via Early Experience

Demystifying the Mechanisms Behind Emergent Exploration in Goal-conditioned RL

Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model Behavior

A Definition of AGI

Provably Learning from Language Feedback

In-Context Learning for Pure Exploration

On the Role of Preference Variance in Preference Optimization

Training LLM Agents to Empower Humans

Richard Sutton Declares LLMs a Dead End

Demystifying Reinforcement Learning in Agentic Reasoning

Emergent coordination in multi-agent language models

Learning-to-measure: in-context active feature acquisition

Andrej Karpathy's insights: AGI, Intelligence, and Evolution

Front-Loading Reasoning: The Synergy between Pretraining and Post-Training Data

Representation-Based Exploration for Language Models: From Test-Time to Post-Training

The attacker moves second: stronger adaptive attacks bypass defenses against LLM jail- Breaks and prompt injections

When can in-context learning generalize out of task distribution?