3 papers
cs.AI2026
Learning to Generate Formally Verifiable Step-by-Step Logic Reasoning via Structured Formal Intermediaries
Luoxin Chen, Yichi Zhou, Huishuai Zhang
Large language models (LLMs) have recently demonstrated impressive performance on complex, multi-step reasoning tasks, especially when post-trained with outcome-rewarded reinforcem…
cs.AI2025
Solving Formal Math Problems by Decomposition and Iterative Reflection
Yichi Zhou, Jianqiu Zhao, Yongxin Zhang +14
General-purpose Large Language Models (LLMs) have achieved remarkable success in intelligence, performing comparably to human experts on complex reasoning tasks such as coding and…
cs.LG2025
AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training
Huishuai Zhang, Bohan Wang, Luoxin Chen
We introduce AdamS, a simple yet effective alternative to Adam for large language model (LLM) pretraining and post-training. By leveraging a novel denominator, i.e., the root of we…