4 papers · 1 filter
Open-Source Image Editing Models Are Zero-Shot Vision Learners
Wei Liu, Jiaxin Lin, Rui Chen
Recent studies have shown that large generative models can solve vision tasks they were not explicitly trained for. However, existing evidence relies on closed-source models~(Veo~3…
CAST: Mitigating Object Hallucination in Large Vision-Language Models via Caption-Guided Visual Attention Steering
Qiming Li, Zekai Ye, Xiaocheng Feng +9
Although Large Vision-Language Models (LVLMs) have demonstrated remarkable performance on downstream tasks, they frequently produce contents that deviate from visual information, l…
Not All Tokens See Equally: Perception-Grounded Policy Optimization for Large Vision-Language Models
Zekai Ye, Qiming Li, Xiaocheng Feng +6
While Reinforcement Learning from Verifiable Rewards (RLVR) has advanced reasoning in Large Vision-Language Models (LVLMs), prevailing frameworks suffer from a foundational methodo…
DinoDental: Benchmarking DINOv3 as a Unified Vision Encoder for Dental Image Analysis
Kun Tang, Xinquan Yang, Mianjie Zheng +6
The scarcity and high cost of expert annotations in dental imaging present a significant challenge for the development of AI in dentistry. DINOv3, a state-of-the-art, self-supervis…