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cs.LG2025
Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization
Yu Huang, Zixin Wen, Aarti Singh +2
The ability to reason lies at the core of artificial intelligence (AI), and challenging problems usually call for deeper and longer reasoning to tackle. A crucial question about AI…
stat.ML2025
Statistical and Algorithmic Foundations of Reinforcement Learning
Yuejie Chi, Yuxin Chen, Yuting Wei
As a paradigm for sequential decision making in unknown environments, reinforcement learning (RL) has received a flurry of attention in recent years. However, the explosion of mode…
cs.LG2025
Transformers Meet In-Context Learning: A Universal Approximation Theory
Gen Li, Yuchen Jiao, Yu Huang +2
Large language models are capable of in-context learning, the ability to perform new tasks at test time using a handful of input-output examples, without parameter updates. We deve…