6 papers
PsychēChat: An Empathic Framework Focused on Emotion Shift Tracking and Safety Risk Analysis in Psychological Counseling
Zhentao Xia, Yongqi Fan, Yuxiang Chu +4
Large language models (LLMs) have demonstrated notable advancements in psychological counseling. However, existing models generally do not explicitly model seekers' emotion shifts…
KG-o1: Enhancing Multi-hop Question Answering in Large Language Models via Knowledge Graph Integration
Nan Wang, Yongqi Fan, yansha zhu +6
Large Language Models (LLMs) face challenges in knowledge-intensive reasoning tasks like classic multi-hop question and answering, which involves reasoning across multiple facts. T…
TFRank: Think-Free Reasoning Enables Practical Pointwise LLM Ranking
Yongqi Fan, Xiaoyang Chen, Dezhi Ye +6
Reasoning-intensive ranking models built on Large Language Models (LLMs) have made notable progress. However, existing approaches often rely on large-scale LLMs and explicit Chain-…
LCDS: A Logic-Controlled Discharge Summary Generation System Supporting Source Attribution and Expert Review
Cheng Yuan, Xinkai Rui, Yongqi Fan +5
Despite the remarkable performance of Large Language Models (LLMs) in automated discharge summary generation, they still suffer from hallucination issues, such as generating inaccu…
MinosEval: Distinguishing Factoid and Non-Factoid for Tailored Open-Ended QA Evaluation with LLMs
Yongqi Fan, Yating Wang, Guandong Wang +4
Open-ended question answering (QA) is a key task for evaluating the capabilities of large language models (LLMs). Compared to closed-ended QA, it demands longer answer statements,…
CMQCIC-Bench: A Chinese Benchmark for Evaluating Large Language Models in Medical Quality Control Indicator Calculation
Guangya Yu, Yanhao Li, Zongying Jiang +9
Medical quality control indicators are essential to assess the qualifications of healthcare institutions for medical services. With the impressive performance of large language mod…