1 citations · 1 across the 5 of their papers we have counts for
5 papers
DAG-Math: Graph-of-Thought Guided Mathematical Reasoning in LLMs
Yuanhe Zhang, Ilja Kuzborskij, Jason D. Lee +2
Large Language Models (LLMs) demonstrate strong performance on mathematical problems when prompted with Chain-of-Thought (CoT), yet it remains unclear whether this success stems fr…
Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension
Yijun Dong, Yicheng Li, Yunai Li +2
Weak-to-strong (W2S) generalization is a type of finetuning (FT) where a strong (large) student model is trained on pseudo-labels generated by a weak teacher. Surprisingly, W2S FT…
Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
Qian Yu, Yining Wang, Baihe Huang +2
Optimization of convex functions under stochastic zeroth-order feedback has been a major and challenging question in online learning. In this work, we consider the problem of optim…
An Information-Theoretic Analysis of In-Context Learning
Hong Jun Jeon, Jason D. Lee, Qi Lei +1
Previous theoretical results pertaining to meta-learning on sequences build on contrived assumptions and are somewhat convoluted. We introduce new information-theoretic tools that…
Towards Optimal Statistical Watermarking
Baihe Huang, Hanlin Zhu, Banghua Zhu +4
We study statistical watermarking by formulating it as a hypothesis testing problem, a general framework which subsumes all previous statistical watermarking methods. Key to our fo…