3 papers
cs.CV2025
Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark
Ziming Cheng, Binrui Xu, Lisheng Gong +14
With enhanced capabilities and widespread applications, Multimodal Large Language Models (MLLMs) are increasingly required to process and reason over multiple images simultaneously…
cs.AI2025
Benchmarking Retrieval-Augmented Generation in Multi-Modal Contexts
Zhenghao Liu, Xingsheng Zhu, Tianshuo Zhou +5
With the rapid advancement of Multi-modal Large Language Models (MLLMs), their capability in understanding both images and text has greatly improved. However, their potential for l…
cs.IR2023
MARVEL: Unlocking the Multi-Modal Capability of Dense Retrieval via Visual Module Plugin
Tianshuo Zhou, Sen Mei, Xinze Li +5
This paper proposes Multi-modAl Retrieval model via Visual modulE pLugin (MARVEL), which learns an embedding space for queries and multi-modal documents to conduct retrieval. MARVE…