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cs.LG2026
Unlocking Data Value in Finance: A Study on Distillation and Difficulty-Aware Training
Chuxue Cao, Honglin Lin, Zhanping Zhong +5
Large Language Models (LLMs) have demonstrated strong general capabilities, yet their deployment in finance remains challenging due to dense domain-specific terminology, stringent…
cs.LG2025
ScaleDiff: Scaling Difficult Problems for Advanced Mathematical Reasoning
Qizhi Pei, Zhuoshi Pan, Honglin Lin +6
Large Reasoning Models (LRMs) have shown impressive capabilities in complex problem-solving, often benefiting from training on difficult mathematical problems that stimulate intric…
cs.LG2025
LEMMA: Learning from Errors for MatheMatical Advancement in LLMs
Zhuoshi Pan, Yu Li, Honglin Lin +7
Large language models (LLMs) have demonstrated remarkable reasoning capability in solving mathematical problems. However, existing approaches primarily focus on improving the quali…