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20242026
most citedAdvancing Large Multi-modal Models with Explicit Chain-of-Reasoning and Visual Question Generation

2 citations · 3 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

PixelEyes: Decoupling Perception and Reasoning for Pinpoint Visual Evidence Seeking

Dengxian Gong, Yuanzheng Wu, Haobo Yuan +11

This paper explores multi-turn visual reasoning and observes that MLLMs repeatedly fail to localize the target, leading to long, redundant trajectories. We attribute this failure t…

cs.CV2025

HyperVL: An Efficient and Dynamic Multimodal Large Language Model for Edge Devices

HyperAI Team, Yuchen Liu, Kaiyang Han +26

Current multimodal large lanauge models possess strong perceptual and reasoning capabilities, however high computational and memory requirements make them difficult to deploy direc…

cs.CV2025

Explainable AI-Generated Image Detection RewardBench

Michael Yang, Shijian Deng, William T. Doan +4

Conventional, classification-based AI-generated image detection methods cannot explain why an image is considered real or AI-generated in a way a human expert would, which reduces…

cs.CV2025

Can World Simulators Reason? Gen-ViRe: A Generative Visual Reasoning Benchmark

Xinxin Liu, Zhaopan Xu, Ming Li +3

While Chain-of-Thought (CoT) prompting enables sophisticated symbolic reasoning in LLMs, it remains confined to discrete text and cannot simulate the continuous, physics-governed d…

cs.CV2024★ 2 cited

Advancing Large Multi-modal Models with Explicit Chain-of-Reasoning and Visual Question Generation

Kohei Uehara, Nabarun Goswami, Hanqin Wang +10

The increasing demand for intelligent systems capable of interpreting and reasoning about visual content requires the development of large Vision-and-Language Models (VLMs) that ar…