Best AI papers explained
A podcast by Enoch H. Kang
430 Episodes
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Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT
Published: 5/2/2025 -
Self-Consuming Generative Models with Curated Data
Published: 5/2/2025 -
Bootstrapping Language Models with DPO Implicit Rewards
Published: 5/2/2025 -
DeepSeek-Prover-V2: Advancing Formal Reasoning
Published: 5/1/2025 -
THINKPRM: Data-Efficient Process Reward Models
Published: 5/1/2025 -
Societal Frameworks and LLM Alignment
Published: 4/29/2025 -
Risks from Multi-Agent Advanced AI
Published: 4/29/2025 -
Causality-Aware Alignment for Large Language Model Debiasing
Published: 4/29/2025 -
Reward Models Evaluate Consistency, Not Causality
Published: 4/28/2025 -
Causal Rewards for Large Language Model Alignment
Published: 4/28/2025 -
Sycophancy to subterfuge: Investigating reward-tampering in large language models
Published: 4/28/2025 -
Bidirectional AI Alignment
Published: 4/28/2025 -
Why Do Multi-Agent LLM Systems Fail?
Published: 4/27/2025 -
LLMs as Greedy Agents: RL Fine-tuning for Decision-Making
Published: 4/27/2025 -
LLM Feedback Loops and the Lock-in Hypothesis
Published: 4/27/2025 -
Representational Alignment Drives Effective Teaching and Learning
Published: 4/27/2025 -
Adaptive Parallel Reasoning with Language Models
Published: 4/27/2025 -
AI: Rewiring the Flow of Ideas and Human Knowledge
Published: 4/27/2025 -
Learning and Equilibrium with Ranking Feedback
Published: 4/27/2025 -
Designing Human-AI Collaboration: A Sufficient-Statistic Approach
Published: 4/27/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.