3 citations · 9 across the 12 of their papers we have counts for
12 papers
Baichuan-M4: A Clinical-Grade Medical Agent System for Continuous Care
Aiyuan Yang, Canbin Piao, Chengfeng Dou +25
Baichuan-M4 is Baichuan Intelligence's clinical-grade medical large model, designed for continuous care rather than single-turn medical question answering. It is built as a coordin…
Do We Really Need External Tools to Mitigate Hallucinations? SIRA: Shared-Prefix Internal Reconstruction of Attribution
Tian Qin, Junzhe Chen, Yuqing Shi +3
Large vision-language models (LVLMs) often hallucinate when language priors dominate weak or ambiguous visual evidence. Existing contrastive decoding methods mitigate this problem…
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…
SkinFlow: Efficient Information Transmission for Open Dermatological Diagnosis via Dynamic Visual Encoding and Staged RL
Lijun Liu, Linwei Chen, Zhishou Zhang +7
General-purpose Large Vision-Language Models (LVLMs), despite their massive scale, often falter in dermatology due to "diffuse attention" - the inability to disentangle subtle path…
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…
Baichuan-M2: Scaling Medical Capability with Large Verifier System
M2 Team, Chengfeng Dou, Chong Liu +31
As large language models (LLMs) advance in conversational and reasoning capabilities, their practical application in healthcare has become a critical research focus. However, there…
HierSearch: A Hierarchical Enterprise Deep Search Framework Integrating Local and Web Searches
Jiejun Tan, Zhicheng Dou, Yan Yu +4
Recently, large reasoning models have demonstrated strong mathematical and coding abilities, and deep search leverages their reasoning capabilities in challenging information retri…
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…
TOD-DA: Towards Boosting the Robustness of Task-oriented Dialogue Modeling on Spoken Conversations
Xin Tian, Xinxian Huang, Dongfeng He +11
Task-oriented dialogue systems have been plagued by the difficulties of obtaining large-scale and high-quality annotated conversations. Furthermore, most of the publicly available…