53 citations · 119 across the 20 of their papers we have counts for
9 papers · 1 filter
Open Multimodal Retrieval-Augmented Factual Image Generation
Yang Tian, Fan Liu, Jingyuan Zhang +3
Large Multimodal Models (LMMs) have achieved remarkable progress in generating photorealistic and prompt-aligned images, but they often produce outputs that contradict verifiable k…
OFFSET: Segmentation-based Focus Shift Revision for Composed Image Retrieval
Zhiwei Chen, Yupeng Hu, Zixu Li +3
Composed Image Retrieval (CIR) represents a novel retrieval paradigm that is capable of expressing users' intricate retrieval requirements flexibly. It enables the user to give a m…
CoRe-MMRAG: Cross-Source Knowledge Reconciliation for Multimodal RAG
Yang Tian, Fan Liu, Jingyuan Zhang +3
Multimodal Retrieval-Augmented Generation (MMRAG) has been introduced to enhance Multimodal Large Language Models by incorporating externally retrieved multimodal knowledge, but it…
KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction
Han Liu, Keyan Ding, Peilin Chen +4
Accurate prediction of protein-ligand binding affinity is critical for drug discovery. While recent deep learning approaches have demonstrated promising results, they often rely so…
Mitigating Hallucination Through Theory-Consistent Symmetric Multimodal Preference Optimization
Wenqi Liu, Xuemeng Song, Jiaxi Li +4
Direct Preference Optimization (DPO) has emerged as an effective approach for mitigating hallucination in Multimodal Large Language Models (MLLMs). Although existing methods have a…
FineCIR: Explicit Parsing of Fine-Grained Modification Semantics for Composed Image Retrieval
Zixu Li, Zhiheng Fu, Yupeng Hu +3
Composed Image Retrieval (CIR) facilitates image retrieval through a multimodal query consisting of a reference image and modification text. The reference image defines the retriev…
Fine-grained Textual Inversion Network for Zero-Shot Composed Image Retrieval
Haoqiang Lin, Haokun Wen, Xuemeng Song +3
Composed Image Retrieval (CIR) allows users to search target images with a multimodal query, comprising a reference image and a modification text that describes the user's modifica…
A Comprehensive Survey on Composed Image Retrieval
Xuemeng Song, Haoqiang Lin, Haokun Wen +3
Composed Image Retrieval (CIR) is an emerging yet challenging task that allows users to search for target images using a multimodal query, comprising a reference image and a modifi…
TIME: Temporal-Sensitive Multi-Dimensional Instruction Tuning and Robust Benchmarking for Video-LLMs
Yunxiao Wang, Meng Liu, Wenqi Liu +7
Video large language models have achieved remarkable performance in tasks such as video question answering, however, their temporal understanding remains suboptimal. To address thi…