1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Distilling Tool Knowledge into Language Models via Back-Translated Traces
Xingyue Huang, Xianglong Hu, Zifeng Ding +9
Large language models (LLMs) often struggle with mathematical problems that require exact computation or multi-step algebraic reasoning. Tool-integrated reasoning (TIR) offers a pr…
cs.CL2025
Training Domain Draft Models for Speculative Decoding: Best Practices and Insights
Fenglu Hong, Ravi Raju, Jonathan Lingjie Li +5
Speculative decoding is an effective method for accelerating inference of large language models (LLMs) by employing a small draft model to predict the output of a target model. How…
cs.LG2024★ 1 cited
SubgoalXL: Subgoal-based Expert Learning for Theorem Proving
Xueliang Zhao, Lin Zheng, Haige Bo +3
Formal theorem proving, a field at the intersection of mathematics and computer science, has seen renewed interest with advancements in large language models (LLMs). This paper int…