Best AI papers explained
A podcast by Enoch H. Kang
550 Episodio
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Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT
Pubblicato: 02/05/2025 -
Self-Consuming Generative Models with Curated Data
Pubblicato: 02/05/2025 -
Bootstrapping Language Models with DPO Implicit Rewards
Pubblicato: 02/05/2025 -
DeepSeek-Prover-V2: Advancing Formal Reasoning
Pubblicato: 01/05/2025 -
THINKPRM: Data-Efficient Process Reward Models
Pubblicato: 01/05/2025 -
Societal Frameworks and LLM Alignment
Pubblicato: 29/04/2025 -
Risks from Multi-Agent Advanced AI
Pubblicato: 29/04/2025 -
Causality-Aware Alignment for Large Language Model Debiasing
Pubblicato: 29/04/2025 -
Reward Models Evaluate Consistency, Not Causality
Pubblicato: 28/04/2025 -
Causal Rewards for Large Language Model Alignment
Pubblicato: 28/04/2025 -
Sycophancy to subterfuge: Investigating reward-tampering in large language models
Pubblicato: 28/04/2025 -
Bidirectional AI Alignment
Pubblicato: 28/04/2025 -
Why Do Multi-Agent LLM Systems Fail?
Pubblicato: 27/04/2025 -
LLMs as Greedy Agents: RL Fine-tuning for Decision-Making
Pubblicato: 27/04/2025 -
LLM Feedback Loops and the Lock-in Hypothesis
Pubblicato: 27/04/2025 -
Representational Alignment Drives Effective Teaching and Learning
Pubblicato: 27/04/2025 -
Adaptive Parallel Reasoning with Language Models
Pubblicato: 27/04/2025 -
AI: Rewiring the Flow of Ideas and Human Knowledge
Pubblicato: 27/04/2025 -
Learning and Equilibrium with Ranking Feedback
Pubblicato: 27/04/2025 -
Designing Human-AI Collaboration: A Sufficient-Statistic Approach
Pubblicato: 27/04/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
