activity
20242026
collaborators

7 papers

cs.CV2026

TruthLens: Object Hallucination Detection via Self-Evaluating Truthfulness Scores in LVLMs

Yanqi Wu, Runhe Lai, Xinhua Lu +5

Despite the remarkable progress of large vision language models (LVLMs), object hallucination remains a fundamental challenge that hinders their trustworthy deployment. A key findi…

cs.LG2026

Instruction Lens Score: Your Instruction Contributes a Powerful Object Hallucination Detector for Multimodal Large Language Models

Runhe Lai, Xinhua Lu, Yanqi Wu +3

Multimodal large language models (MLLMs) have achieved remarkable progress, yet the object hallucination remains a critical challenge for reliable deployment. In this paper, we pre…

cs.CV2025

OnlineHOI: Towards Online Human-Object Interaction Generation and Perception

Yihong Ji, Yunze Liu, Yiyao Zhuo +4

The perception and generation of Human-Object Interaction (HOI) are crucial for fields such as robotics, AR/VR, and human behavior understanding. However, current approaches model…

cs.CV2025

VReST: Enhancing Reasoning in Large Vision-Language Models through Tree Search and Self-Reward Mechanism

Congzhi Zhang, Jiawei Peng, Zhenglin Wang +5

Large Vision-Language Models (LVLMs) have shown exceptional performance in multimodal tasks, but their effectiveness in complex visual reasoning is still constrained, especially wh…

cs.CV2025

MuseFace: Text-driven Face Editing via Diffusion-based Mask Generation Approach

Xin Zhang, Siting Huang, Xiangyang Luo +5

Face editing modifies the appearance of face, which plays a key role in customization and enhancement of personal images. Although much work have achieved remarkable success in tex…

cs.AI2025

From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with Multi-modalities

Shixin Jiang, Jiafeng Liang, Jiyuan Wang +6

To tackle complex tasks in real-world scenarios, more researchers are focusing on Omni-MLLMs, which aim to achieve omni-modal understanding and generation. Beyond the constraints o…