13 papers
ConsultMind:Towards Automated Diagnostic Consultation via Uncertainty-Aware Reasoning
Xiao Sun, Yuming Yang, Yun Chen +9
Diagnostic consultation is an online sequential decision-making process in which clinicians gather evidence through patient interaction until a diagnosis is sufficiently supported.…
GeoForge: Non-Parametric Self-Evolving Agents for Earth-Observation Reasoning
Xin Xiao, Jiang Zhong, Junnan Zhu +4
Earth observation (EO) agents construct scientifically valid tool workflows and ground their conclusions in current geospatial evidence. This is challenging because EO workflows ar…
MentalHospital: A Virtual Environment for Evaluating Psychiatric Clinical Encounters
Yuming Yang, Xiao Sun, Yuanwei Zou +6
Large language models (LLMs) have shown strong performance on isolated psychiatric tasks, including dialogue, diagnosis, and treatment planning, yet existing benchmarks rarely simu…
Lung-R1: A Knowledge Graph-Guided LLM for Pulmonary Diagnostic Reasoning
Haoyang Zeng, Yuanxi Fu, Rongzhen Li +11
Diagnosing pulmonary diseases requires integrating heterogeneous evidence amid phenotypic variability and cross-disease overlap. Although large language models (LLMs) have shown pr…
MentalSeek-Dx: Towards Progressive Hypothetico-Deductive Reasoning for Real-world Psychiatric Diagnosis
Xiao Sun, Yuming Yang, Junnan Zhu +3
Mental health disorders represent a burgeoning global public health challenge. While Large Language Models (LLMs) have demonstrated potential in psychiatric assessment, their clini…
CFVBench: A Comprehensive Video Benchmark for Fine-grained Multimodal Retrieval-Augmented Generation
Kaiwen Wei, Xiao Liu, Jie Zhang +11
Multimodal Retrieval-Augmented Generation (MRAG) enables Multimodal Large Language Models (MLLMs) to generate responses with external multimodal evidence, and numerous video-based…
T2R-bench: A Benchmark for Generating Article-Level Reports from Real World Industrial Tables
Jie Zhang, Changzai Pan, Kaiwen Wei +12
Extensive research has been conducted to explore the capabilities of large language models (LLMs) in table reasoning. However, the essential task of transforming tables information…
From Past To Path: Masked History Learning for Next-Item Prediction in Generative Recommendation
KaiWen Wei, Kejun He, Xiaomian Kang +7
Generative recommendation, which directly generates item identifiers, has emerged as a promising paradigm for recommendation systems. However, its potential is fundamentally constr…
Learning to Shop Like Humans: A Review-driven Retrieval-Augmented Recommendation Framework with LLMs
Kaiwen Wei, Jinpeng Gao, Jiang Zhong +3
Large language models (LLMs) have shown strong potential in recommendation tasks due to their strengths in language understanding, reasoning and knowledge integration. These capabi…
MIRAGE: Scaling Test-Time Inference with Parallel Graph-Retrieval-Augmented Reasoning Chains
Kaiwen Wei, Rui Shan, Dongsheng Zou +4
Large reasoning models (LRMs) have shown significant progress in test-time scaling through chain-of-thought prompting. Current approaches like search-o1 integrate retrieval augment…
FLEKE: Federated Locate-then-Edit Knowledge Editing
Zongkai Zhao, Guozeng Xu, Xiuhua Li +2
Locate-then-Edit Knowledge Editing (LEKE) is a key technique for updating large language models (LLMs) without full retraining. However, existing methods assume a single-user setti…
Benchmarking Multimodal RAG through a Chart-based Document Question-Answering Generation Framework
Yuming Yang, Jiang Zhong, Li Jin +7
Multimodal Retrieval-Augmented Generation (MRAG) enhances reasoning capabilities by integrating external knowledge. However, existing benchmarks primarily focus on simple image-tex…
Latent Distribution Decoupling: A Probabilistic Framework for Uncertainty-Aware Multimodal Emotion Recognition
Jingwang Huang, Jiang Zhong, Qin Lei +5
Multimodal multi-label emotion recognition (MMER) aims to identify the concurrent presence of multiple emotions in multimodal data. Existing studies primarily focus on improving fu…