3 papers
cs.CV2025
Improving VQA Reliability: A Dual-Assessment Approach with Self-Reflection and Cross-Model Verification
Xixian Wu, Yang Ou, Pengchao Tian +4
Vision-language models (VLMs) have demonstrated significant potential in Visual Question Answering (VQA). However, the susceptibility of VLMs to hallucinations can lead to overconf…
cs.CV2025
Diving into Mitigating Hallucinations from a Vision Perspective for Large Vision-Language Models
Weihang Wang, Xinhao Li, Ziyue Wang +5
Object hallucination in Large Vision-Language Models (LVLMs) significantly impedes their real-world applicability. As the primary component for accurately interpreting visual infor…
cs.CV2025
MX-Font++: Mixture of Heterogeneous Aggregation Experts for Few-shot Font Generation
Weihang Wang, Duolin Sun, Jielei Zhang +1
Few-shot Font Generation (FFG) aims to create new font libraries using limited reference glyphs, with crucial applications in digital accessibility and equity for low-resource lang…