A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
J. Kirchner, Yining Chen, Harri Edwards, et al.
Proposes legibility training via a Prover-Verifier Game to make LLM chain-of-thought reasoning easier for humans to verify, improving trust in model outputs.
Aayush Karan, Yilun Du
Proposes a simple iterative sampling algorithm that elicits reasoning from base LLMs at inference time, matching or outperforming RL post-training on single-shot tasks without additional training or verifiers.
Unknown
V-STaR iteratively improves LLM reasoning by training a DPO verifier on correct and incorrect solutions, boosting generator and verifier performance.
Unknown
OmniMath introduces a comprehensive Olympiad-level math benchmark with 4428 problems across 33 sub-domains and 10 difficulty levels, using GPT-4o and an open-source verifier OmniJudge for rigorous evaluation.
Unknown
Nover introduces verifier-free reinforcement learning for language models, eliminating the need for large verifier models and their computational costs.
Unknown
This paper proposes Double-Helix Co-Training, a method that iteratively improves a computer-use agent generator and an LLM-based verifier to provide accurate reward signals for reinforcement learning.