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20242026
most citedFin-PRM: A Domain-Specialized Process Reward Model for Financial Reasoning in Large Language Models

2 citations · 3 across the 12 of their papers we have counts for

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6 papers · 1 filter

cs.CL2025

CARE: Cognitive-reasoning Augmented Reinforcement for Emotional Support Conversation

Jie Zhu, Yuanchen Zhou, Shuo Jiang +5

Emotional Support Conversation (ESC) plays a vital role in alleviating psychological stress and providing emotional value through dialogue. While recent studies have largely focuse…

cs.CL2025★ 2 cited

Fin-PRM: A Domain-Specialized Process Reward Model for Financial Reasoning in Large Language Models

Jie Zhu, Yuanchen Zhou, Shuo Jiang +4

Process Reward Models (PRMs) supervise intermediate reasoning steps in large language models (LLMs), but existing PRMs are mainly trained on general-domain data and struggle with t…

cs.CL2025

Evaluating, Synthesizing, and Enhancing for Customer Support Conversation

Jie Zhu, Huaixia Dou, Junhui Li +4

Effective customer support requires not only accurate problem solving but also structured and empathetic communication aligned with professional standards. However, existing dialog…

cs.CL2025

MFinMeeting: A Multilingual, Multi-Sector, and Multi-Task Financial Meeting Understanding Evaluation Dataset

Jie Zhu, Junhui Li, Yalong Wen +3

Recent breakthroughs in large language models (LLMs) have led to the development of new benchmarks for evaluating their performance in the financial domain. However, current financ…

cs.AI2025★ 1 cited

DianJin-R1: Evaluating and Enhancing Financial Reasoning in Large Language Models

Jie Zhu, Qian Chen, Huaixia Dou +4

Effective reasoning remains a core challenge for large language models (LLMs) in the financial domain, where tasks often require domain-specific knowledge, precise numerical calcul…

cs.CL2025

Speech Translation Refinement using Large Language Models

Huaixia Dou, Xinyu Tian, Xinglin Lyu +3

Recent advancements in large language models (LLMs) have demonstrated their remarkable capabilities across various language tasks. Inspired by the success of text-to-text translati…