3 citations · 6 across the 11 of their papers we have counts for
6 papers · 1 filter
Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making
M3 Team, Chengfeng Dou, Fan Yang +15
We introduce Baichuan-M3, a medical-enhanced large language model engineered to shift the paradigm from passive question-answering to active, clinical-grade decision support. Addre…
DCPO: Dynamic Clipping Policy Optimization
Shihui Yang, Chengfeng Dou, Peidong Guo +4
Reinforcement Learning from Verifiable Rewards (RLVR) has emerged as a promising framework for enhancing the reasoning capabilities of large language models. However, existing appr…
Efficient Medical VIE via Reinforcement Learning
Lijun Liu, Ruiyang Li, Zhaocheng Liu +5
Visual Information Extraction (VIE) converts unstructured document images into structured formats like JSON, critical for medical applications such as report analysis and online co…
Baichuan4-Finance Technical Report
Hanyu Zhang, Boyu Qiu, Yuhao Feng +6
Large language models (LLMs) have demonstrated strong capabilities in language understanding, generation, and reasoning, yet their potential in finance remains underexplored due to…
Exploring the Inquiry-Diagnosis Relationship with Advanced Patient Simulators
Zhaocheng Liu, Quan Tu, Wen Ye +7
Recently, large language models have shown great potential to transform online medical consultation. Despite this, most research targets improving diagnostic accuracy with ample in…
Dialogue State Distillation Network with Inter-slot Contrastive Learning for Dialogue State Tracking
Jing Xu, Dandan Song, Chong Liu +5
In task-oriented dialogue systems, Dialogue State Tracking (DST) aims to extract users' intentions from the dialogue history. Currently, most existing approaches suffer from error…