6 papers
Before Thinking, Learn to Decide: Proactive Routing for Efficient Visual Reasoning
Yinan Zhou, Haokun Lin, Yichen Wu +7
Large multimodal models have achieved strong reasoning on complex visual tasks, but their inference efficiency is often restricted by long chains of thought. A promising solution i…
Beyond Semantic Search: Towards Referential Anchoring in Composed Image Retrieval
Yuxin Yang, Yinan Zhou, Yuxin Chen +6
Composed Image Retrieval (CIR) has demonstrated significant potential by enabling flexible multimodal queries that combine a reference image and modification text. However, CIR inh…
MedREK: Retrieval-Based Editing for Medical LLMs with Key-Aware Prompts
Shujun Xia, Haokun Lin, Yichen Wu +9
LLMs hold great promise for healthcare applications, but the rapid evolution of medical knowledge and errors in training data often cause them to generate outdated or inaccurate in…
DOGR: Towards Versatile Visual Document Grounding and Referring
Yinan Zhou, Yuxin Chen, Haokun Lin +6
With recent advances in Multimodal Large Language Models (MLLMs), grounding and referring capabilities have gained increasing attention for achieving detailed understanding and fle…
DetailFusion: A Dual-branch Framework with Detail Enhancement for Composed Image Retrieval
Yuxin Yang, Yinan Zhou, Yuxin Chen +8
Composed Image Retrieval (CIR) aims to retrieve target images from a gallery based on a reference image and modification text as a combined query. Recent approaches focus on balanc…
Scale Up Composed Image Retrieval Learning via Modification Text Generation
Yinan Zhou, Yaxiong Wang, Haokun Lin +3
Composed Image Retrieval (CIR) aims to search an image of interest using a combination of a reference image and modification text as the query. Despite recent advancements, this ta…