1 citations · 1 across the 6 of their papers we have counts for
8 papers
Beyond Saying Less: Fine-Grained Alignment for Informative and Faithful Vision-Language Models
Xingming Long, Jie Zhang, Yuecong Min +2
Object hallucination remains a major challenge for large vision-language models. While off-policy preference optimization proves to be an effective solution, on-policy reinforcemen…
V-Gym: Enhancing Agentic Visual Reasoning via Skill-Data Co-Evolution
Bei Yan, Yuecong Min, Jie Zhang +3
Advances in multimodal understanding, reasoning, and tool use enable agents to tackle increasingly complex visual reasoning tasks. By distilling past execution experience into reus…
Mobile GUI Agent Privacy Personalization with Trajectory Induced Preference Optimization
Zhixin Lin, Jungang Li, Dongliang Xu +5
Mobile GUI agents powered by Multimodal Large Language Models (MLLMs) can execute complex tasks on mobile devices. Despite this progress, most existing systems still optimize task…
ACT Now: Preempting LVLM Hallucinations via Adaptive Context Integration
Bei Yan, Yuecong Min, Jie Zhang +2
Large Vision-Language Models (LVLMs) frequently suffer from severe hallucination issues. Existing mitigation strategies predominantly rely on isolated, single-step states to enhanc…
INFACT: A Diagnostic Benchmark for Induced Faithfulness and Factuality Hallucinations in Video-LLMs
Junqi Yang, Yuecong Min, Jie Zhang +2
Despite rapid progress, Video Large Language Models (Video-LLMs) remain unreliable due to hallucinations, which are outputs that contradict either video evidence (faithfulness) or…
T2VAttack: Adversarial Attack on Text-to-Video Diffusion Models
Changzhen Li, Yuecong Min, Jie Zhang +3
The rapid evolution of Text-to-Video (T2V) diffusion models has driven remarkable advancements in generating high-quality, temporally coherent videos from natural language descript…
SHALE: A Scalable Benchmark for Fine-grained Hallucination Evaluation in LVLMs
Bei Yan, Zhiyuan Chen, Yuecong Min +4
Despite rapid advances, Large Vision-Language Models (LVLMs) still suffer from hallucinations, i.e., generating content inconsistent with input or established world knowledge, whic…
A Survey of Multimodal Hallucination Evaluation and Detection
Zhiyuan Chen, Yuecong Min, Jie Zhang +4
Multi-modal Large Language Models (MLLMs) have emerged as a powerful paradigm for integrating visual and textual information, supporting a wide range of multi-modal tasks. However,…