activity
20242026
collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2026

Beyond the Eye: Efficient Multimodal Reasoning via Self-Regulated Implicit Visual Tools

Xiuwei Chen, Quanlin Chen, Wentao Hu +8

Recent multimodal large language models (MLLMs) have made remarkable progress on fine-grained perception tasks under the "Thinking with Images" (TwI) paradigm by iteratively perfor…

cs.CV2026

Latent Visual States for Efficient Multimodal Reasoning

Xiuwei Chen, Wentao Hu, Yongxin Wang +8

The integration of visual evidence has significantly enhanced the capabilities of large multimodal models. However, this integration predominantly relies on generating discrete out…

cs.CV2026

RADAR: Revealing Asymmetric Development of Abilities in MLLM Pre-training

Yunshuang Nie, Bingqian Lin, Minzhe Niu +7

Pre-trained Multi-modal Large Language Models (MLLMs) provide a knowledge-rich foundation for post-training by leveraging their inherent perception and reasoning capabilities to so…

cs.CV2026

Thinking with Geometry: Active Geometry Integration for Spatial Reasoning

Haoyuan Li, Qihang Cao, Tao Tang +6

Recent progress in spatial reasoning with Multimodal Large Language Models (MLLMs) increasingly leverages geometric priors from 3D encoders. However, most existing integration stra…

cs.CV2025

Can Atomic Step Decomposition Enhance the Self-structured Reasoning of Multimodal Large Models?

Kun Xiang, Zhili Liu, Zihao Jiang +13

In this paper, we address the challenging task of multimodal mathematical reasoning by incorporating the ability of "slow thinking" into multimodal large language models (MLLMs). O…

cs.CV2024

AtomThink: Multimodal Slow Thinking with Atomic Step Reasoning

Kun Xiang, Zhili Liu, Terry Jingchen Zhang +12

In this paper, we address the challenging task of multimodal reasoning by incorporating the notion of ``slow thinking'' into multimodal large language models (MLLMs). Our core idea…