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20242026
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cs.CV2026

Reliability-Prioritized Fine-Grained Generation in Multimodal Large

Xiaomeng Fan, Wei Wu, Yuwei Wu +9

Multimodal large language models (MLLMs) are increasingly expected to generate fine-grained descriptions of visual content. However, we observe and theoretically show that generati…

cs.CV2026

AdaptMMBench: Benchmarking Adaptive Multimodal Reasoning for Mode Selection and Reasoning Process

Xintong Zhang, Xiaowen Zhang, Jingrong Wu +8

Adaptive multimodal reasoning has emerged as a promising frontier in Vision-Language Models (VLMs), aiming to dynamically modulate between tool-augmented visual reasoning and text…

cs.CV2025

Modality Alignment across Trees on Heterogeneous Hyperbolic Manifolds

Wei Wu, Xiaomeng Fan, Yuwei Wu +4

Modality alignment is critical for vision-language models (VLMs) to effectively integrate information across modalities. However, existing methods extract hierarchical features fro…

cs.CV2025

Geometry-aware Distance Measure for Diverse Hierarchical Structures in Hyperbolic Spaces

Pengxiang Li, Yuwei Wu, Zhi Gao +5

Learning in hyperbolic spaces has attracted increasing attention due to its superior ability to model hierarchical structures of data. Most existing hyperbolic learning methods use…

cs.CV2025

A Set-to-Set Distance Measure in Hyperbolic Space

Pengxiang Li, Wei Wu, Zhi Gao +6

We propose a hyperbolic set-to-set distance measure for computing dissimilarity between sets in hyperbolic space. While point-to-point distances in hyperbolic space effectively cap…

cs.CV2025

Multi-Sourced Compositional Generalization in Visual Question Answering

Chuanhao Li, Wenbo Ye, Zhen Li +2

Compositional generalization is the ability of generalizing novel compositions from seen primitives, and has received much attention in vision-and-language (V\&L) recently. Due to…

cs.CV2025

Iterative Tool Usage Exploration for Multimodal Agents via Step-wise Preference Tuning

Pengxiang Li, Zhi Gao, Bofei Zhang +8

Multimodal agents, which integrate a controller e.g., a vision language model) with external tools, have demonstrated remarkable capabilities in tackling complex multimodal tasks.…

cs.CV2024

FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models

Pengxiang Li, Zhi Gao, Bofei Zhang +6

Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction. In this paper, we build FIRE, a feedback-refinemen…