3 citations · 9 across the 12 of their papers we have counts for
6 papers · 1 filter
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…