10 papers
MR-Bench: A Unified Benchmark for Evidence-Grounded Multimodal Metaphor Understanding
Hong Jiang, Junnan Zhu, Jingwang Huang +9
Multimodal metaphor understanding requires identifying cross-domain Target-Source mappings and inferring sentiment from visual and textual evidence. However, existing benchmarks la…
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…
From Reconstruction to Decision: A Post-Encoder Plug-in Adapter for Curvilinear Segmentation
Qin Lei, Jiang Zhong, Xin Xiao +2
Curvilinear object segmentation, including vessels and cracks, is challenging due to extreme spatial sparsity and topological fragility, where small local errors can cause severe s…
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…
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…
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…