26 citations · 67 across the 21 of their papers we have counts for
23 papers
ParaAgent: Reinforcing Parallel Acting in Open-World Tool Environments
Shengbin Yue, Hongru Wang, Siyuan Wang +3
Language model agents are increasingly deployed in open-world tool environments, which require balancing exploring unknown capabilities and exploiting known ones. Existing methods…
ObGynLongBench: Revealing the Evidence-to-EHR Gap in Longitudinal EHR Decision-Making
Jun Xiang, Zhijie Bao, Rong Hu +3
The application of large language models (LLMs) to personalized medical assistants has garnered growing interest. However, existing medical benchmarks largely rely on static questi…
RIDGE: Region-Informed Derivative-Guided Evidence Selection for Long Video Understanding
Shanqing Xu, Meng Luo, Mengchen Qian +7
Long videos contain far more visual content than Large Vision-Language Models (LVLMs) can process under a fixed visual-token budget, making frame selection essential. Existing quer…
DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding
Hao Yan, Yuliang Liu, Xingchen Liu +5
Existing Multimodal Large Language Models (MLLMs) suffer from significant performance degradation on the long document understanding task as document length increases. This stems f…
Benchmarking Real-Time Question Answering via Executable Code Workflows
Wenjie Zhou, Yuan Gao, Xin Zhou +5
Retrieving real-time information is a fundamental capability for search-integrated agents in real-world applications. However, existing benchmarks are predominantly static and ther…
Construction of Knowledge Graph based on Language Model
Qiubai Zhu, Qingwang Wang, Haibin Yuan +2
Knowledge Graph (KG) can effectively integrate valuable information from massive data, and thus has been rapidly developed and widely used in many fields. Traditional KG constructi…
STRIDE: Strategic Iterative Decision-Making for Retrieval-Augmented Multi-Hop Question Answering
Wei Chen, Lili Zhao, Zhi Zheng +2
Multi-hop question answering (MHQA) enables accurate answers to complex queries by retrieving and reasoning over evidence dispersed across multiple documents. Existing MHQA approac…
Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models
Haoyi Sun, Xiaoxiao Wang, Ning Mao +5
Vision-Language Models (VLMs) have shown remarkable capabilities in joint vision-language understanding, but their large scale poses significant challenges for deployment in resour…
MedRCube: A Multidimensional Framework for Fine-Grained and In-Depth Evaluation of MLLMs in Medical Imaging
Zhijie Bao, Fangke Chen, Licheng Bao +4
The potential of Multimodal Large Language Models (MLLMs) in domain of medical imaging raise the demands of systematic and rigorous evaluation frameworks that are aligned with the…
Doc-V*:Coarse-to-Fine Interactive Visual Reasoning for Multi-Page Document VQA
Yuanlei Zheng, Pei Fu, Hang Li +9
Multi-page Document Visual Question Answering requires reasoning over semantics, layouts, and visual elements in long, visually dense documents. Existing OCR-free methods face a tr…
SpeechMedAssist: Efficiently and Effectively Adapting Speech Language Models for Medical Consultation
Sirry Chen, Jieyi Wang, Wei Chen +1
Medical consultations are intrinsically speech-centric. However, most prior works focus on long-text-based interactions, which are cumbersome and patient-unfriendly. Recent advance…
Ready Jurist One: Benchmarking Language Agents for Legal Intelligence in Dynamic Environments
Zheng Jia, Shengbin Yue, Wei Chen +5
The gap between static benchmarks and the dynamic nature of real-world legal practice poses a key barrier to advancing legal intelligence. To this end, we introduce J1-ENVS, the fi…
InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models
Jing Ding, Kai Feng, Binbin Lin +6
The application of large language models (LLMs) has achieved remarkable success in various fields, but their effectiveness in specialized domains like the Chinese insurance industr…
MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration
Lai Wei, Wenkai Wang, Xiaoyu Shen +5
In recent advancements, multimodal large language models (MLLMs) have been fine-tuned on specific medical image datasets to address medical visual question answering (Med-VQA) task…
Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks
Shengbin Yue, Siyuan Wang, Wei Chen +2
Recent advancements in Large Language Models (LLMs) have led to significant breakthroughs in various natural language processing tasks. However, generating factually consistent res…
Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering
Shujian Jiao, Bingxuan Li, Lei Wang +4
Proteins are essential to life's processes, underpinning evolution and diversity. Advances in sequencing technology have revealed millions of proteins, underscoring the need for so…
AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator
Zhihao Fan, Jialong Tang, Wei Chen +5
Artificial intelligence has significantly advanced healthcare, particularly through large language models (LLMs) that excel in medical question answering benchmarks. However, their…
CauESC: A Causal Aware Model for Emotional Support Conversation
Wei Chen, Hengxu Lin, Qun Zhang +4
Emotional Support Conversation aims at reducing the seeker's emotional distress through supportive response. Existing approaches have two limitations: (1) They ignore the emotion c…
K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning
Wei Chen, Gang Zhao, Xiaojin Zhang +3
Automatic psychological counseling requires mass of professional knowledge that can be found in online counseling forums. Motivated by this, we propose K-ESConv, a novel prompt lea…
DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning
Wei Chen, Qiushi Wang, Zefei Long +8
We propose Multiple Experts Fine-tuning Framework to build a financial large language model (LLM), DISC-FinLLM. Our methodology improves general LLMs by endowing them with multi-tu…
DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services
Shengbin Yue, Wei Chen, Siyuan Wang +8
We propose DISC-LawLLM, an intelligent legal system utilizing large language models (LLMs) to provide a wide range of legal services. We adopt legal syllogism prompting strategies…
DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultation
Zhijie Bao, Wei Chen, Shengze Xiao +6
We propose DISC-MedLLM, a comprehensive solution that leverages Large Language Models (LLMs) to provide accurate and truthful medical response in end-to-end conversational healthca…
Hierarchical Reinforcement Learning for Automatic Disease Diagnosis
Cheng Zhong, Kangenbei Liao, Wei Chen +5
Motivation: Disease diagnosis oriented dialogue system models the interactive consultation procedure as Markov Decision Process and reinforcement learning algorithms are used to so…