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cs.CV2026

OmniMapBench: Benchmarking Visual-Centric Reasoning on Diverse Map Documents

Yang Chen, Yunwen Li, Yufan Shen +6

Recent advancements in LVLMs necessitate robust benchmarks for complex, visually grounded reasoning. A critical limitation is identified in many document understanding benchmarks:…

cs.CV2026

Investigating Redundancy in Multimodal Large Language Models with Multiple Vision Encoders

Yizhou Wang, Song Mao, Yang Chen +8

Recent multimodal large language models (MLLMs) increasingly integrate multiple vision encoders to improve performance on various benchmarks, assuming that diverse pretraining obje…

cs.CV2025

Aligning Vision to Language: Annotation-Free Multimodal Knowledge Graph Construction for Enhanced LLMs Reasoning

Junming Liu, Siyuan Meng, Yanting Gao +7

Multimodal reasoning in Large Language Models (LLMs) struggles with incomplete knowledge and hallucination artifacts, challenges that textual Knowledge Graphs (KGs) only partially…

cs.CV2025

MELLA: Bridging Linguistic Capability and Cultural Groundedness for Low-Resource Language MLLMs

Yufei Gao, Jiaying Fei, Nuo Chen +4

Multimodal Large Language Models (MLLMs) perform strongly in high-resource languages, yet often produce fluent but culturally "thin" descriptions in low-resource settings. We argue…

cs.CV2025

Learning Only with Images: Visual Reinforcement Learning with Reasoning, Rendering, and Visual Feedback

Yang Chen, Yufan Shen, Wenxuan Huang +7

Multimodal Large Language Models (MLLMs) exhibit impressive performance across various visual tasks. Subsequent investigations into enhancing their visual reasoning abilities have…