5 citations · 5 across the 6 of their papers we have counts for
9 papers
MS-Eval: Benchmarking Sub-Agent Delegation and Orchestration in MCP-Intensive Working Scenarios
Bowen Ding, Qixin Wang, Lexing Ruan +4
LLM agents are increasingly integrated into real-world works, yet they must handle diverse domain-specific tools and complex multi-sub-task problems that sequential tool invocation…
ProAS: A Progress-Aware Advantage Shaping Framework for Multi-Turn Agentic Reinforcement Learning
Bowen Ding, Mingda Wan, Yuhan Chen +7
Reinforcement learning (RL) has emerged as the primary paradigm for optimizing Large Language Model (LLM) agents, yet efficient critic-free algorithms (e.g., GRPO) suffer from a fu…
Rethinking Expert Trajectory Utilization in LLM Post-training for Mathematical Reasoning
Bowen Ding, Yuhan Chen, Jiayang Lyv +9
Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) dominate the post-training landscape for mathematical reasoning, yet differ fundamentally in their reliance on expert t…
Do Thinking Tokens Help or Trap? Towards More Efficient Large Reasoning Model
Bowen Ding, Yuhan Chen, Futing Wang +2
Large Reasoning Models (LRMs) excel at solving complex problems but face an overthinking dilemma. When handling simple tasks, they often produce verbose responses overloaded with t…
CPathAgent: An Agent-based Foundation Model for Interpretable High-Resolution Pathology Image Analysis Mimicking Pathologists' Diagnostic Logic
Yuxuan Sun, Yixuan Si, Chenglu Zhu +5
Recent advances in computational pathology have led to the emergence of numerous foundation models. These models typically rely on general-purpose encoders with multi-instance lear…
Baichuan-Omni-1.5 Technical Report
Yadong Li, Jun Liu, Tao Zhang +89
We introduce Baichuan-Omni-1.5, an omni-modal model that not only has omni-modal understanding capabilities but also provides end-to-end audio generation capabilities. To achieve f…
Baichuan-Omni Technical Report
Yadong Li, Haoze Sun, Mingan Lin +23
The salient multimodal capabilities and interactive experience of GPT-4o highlight its critical role in practical applications, yet it lacks a high-performing open-source counterpa…
A Rationale-centric Counterfactual Data Augmentation Method for Cross-Document Event Coreference Resolution
Bowen Ding, Qingkai Min, Shengkun Ma +3
Based on Pre-trained Language Models (PLMs), event coreference resolution (ECR) systems have demonstrated outstanding performance in clustering coreferential events across document…
Evaluating Open-QA Evaluation
Cunxiang Wang, Sirui Cheng, Qipeng Guo +7
This study focuses on the evaluation of the Open Question Answering (Open-QA) task, which can directly estimate the factuality of large language models (LLMs). Current automatic ev…