AI RESEARCH
Unlocking Data Value in Finance: A Study on Distillation and Difficulty-Aware Training
arXiv CS.LG
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ArXi:2603.07223v1 Announce Type: new Large Language Models (LLMs) have nstrated strong general capabilities, yet their deployment in finance remains challenging due to dense domain-specific terminology, stringent numerical reasoning requirements, and low tolerance for factual errors. We conduct a controlled empirical study showing that in specialized vertical domains, performance is largely determined by the quality and difficulty/verifiability profile of post-