1 citations · 1 across the 6 of their papers we have counts for
6 papers
SABER: Stability-Aware Early Exit for LLM Reasoning via Adversarial Branch Probing
Wanli Cheng, Haiya Xiang, Juntao Li +2
Large Reasoning Models (LRMs) achieve strong reasoning capabilities, yet long-chain reasoning becomes inefficient once the intermediate answer stabilizes across reasoning steps: ad…
D-MOPD: Dynamic Domain ScheDuling for Efficient Multi-Teacher Distillation
Zechen Sun, Zhiwei Zhang, Fei Zhao +7
Multi-teacher on-policy distillation (MOPD) distills several domain-expert teachers into a single student by minimizing per-domain reverse-KL divergence on the student's own rollou…
IS-CoT: Breaking the Long-form Generation Collapse via Interleaved Structural Thinking
Zechen Sun, Yuyang Sun, Zecheng Tang +6
Generating coherent and controllable long-form content remains a persistent challenge for Large Language Models (LLMs). While reasoning-enhanced models have demonstrated success in…
OneEval: Benchmarking LLM Knowledge-intensive Reasoning over Diverse Knowledge Bases
Yongrui Chen, Zhiqiang Liu, Jing Yu +21
Large Language Models (LLMs) have demonstrated substantial progress on reasoning tasks involving unstructured text, yet their capabilities significantly deteriorate when reasoning…
CheMatAgent: Enhancing LLMs for Chemistry and Materials Science through Tree-Search Based Tool Learning
Mengsong Wu, YaFei Wang, Yidong Ming +7
Large language models (LLMs) have recently demonstrated promising capabilities in chemistry tasks while still facing challenges due to outdated pretraining knowledge and the diffic…
SELT: Self-Evaluation Tree Search for LLMs with Task Decomposition
Mengsong Wu, Di Zhang, Yuqiang Li +2
While Large Language Models (LLMs) have achieved remarkable success in a wide range of applications, their performance often degrades in complex reasoning tasks. In this work, we i…