5 citations · 10 across the 8 of their papers we have counts for
Showing 2025Show all
3 papers · 1 filter
cs.AI2025
Boosting LLM Reasoning via Spontaneous Self-Correction
Xutong Zhao, Tengyu Xu, Xuewei Wang +11
While large language models (LLMs) have demonstrated remarkable success on a broad range of tasks, math reasoning remains a challenging one. One of the approaches for improving mat…
cs.AI2025
Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization
Zishun Yu, Tengyu Xu, Di Jin +9
Solving mathematics problems has been an intriguing capability of large language models, and many efforts have been made to improve reasoning by extending reasoning length, such as…
cs.LG2025★ 1 cited
Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback
Yen-Ting Lin, Di Jin, Tengyu Xu +11
Large language models (LLMs) have recently demonstrated remarkable success in mathematical reasoning. Despite progress in methods like chain-of-thought prompting and self-consisten…