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Fengyun Rao

2 papers indexed

arxivcs.CV2026-07-08

MMAgent-R$^2$: Learning to Rerank and Reject for Agentic mRAG

Tao Zhang, Ziqi Zhang, Zongyang Ma, Yuxin Yang, Bing Li, Chunfeng Yuan, et al.

Knowledge-based Visual Question Answering (KB-VQA) requires models to retrieve visual entities matching the query image from large-scale encyclopedic knowledge bases and answer related questions. Existing multimodal Retrieval Augmented Generation (mRAG) methods rely on global vis…

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arxivcs.CVcs.AI2026-07-07

Segmentation before Answering: Pixel Grounding for MLLM Visual Reasoning

Yake Wei, Yuan Wang, Fengyun Rao, Jing Lyu, Di Hu

Recent advancements in Multimodal Large Language Models (MLLMs) have evolved from static perception to interleaved visual-language reasoning, often referred to as ``thinking with images''. A basic operation in this reasoning process is to zoom in on regions of interest (often rep…

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