2 citations · 2 across the 4 of their papers we have counts for
5 papers
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…
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…
Amplify Adjacent Token Differences: Enhancing Long Chain-of-Thought Reasoning with Shift-FFN
Yao Xu, Mingyu Xu, Fangyu Lei +7
Recently, models such as OpenAI-o1 and DeepSeek-R1 have demonstrated remarkable performance on complex reasoning tasks through Long Chain-of-Thought (Long-CoT) reasoning. Although…
Baichuan-M1: Pushing the Medical Capability of Large Language Models
Bingning Wang, Haizhou Zhao, Huozhi Zhou +39
The current generation of large language models (LLMs) is typically designed for broad, general-purpose applications, while domain-specific LLMs, especially in vertical fields like…
LLaSA: Large Language and Structured Data Assistant
Yao Xu, Shizhu He, Jiabei Chen +5
Structured data, such as tables, graphs, and databases, play a critical role in plentiful NLP tasks such as question answering and dialogue system. Recently, inspired by Vision-Lan…