3 papers
cs.AI2026
FADE: Mitigating Hallucinations by Reducing Language-Prior Dominance in Large Vision-Language Models
Yichen Guo, Kai Tang, Fenglai Lin +5
Despite the impressive capabilities of Large Vision-Language Models (LVLMs), they remain susceptible to hallucination, generating content inconsistent with the input image. Recent…
cs.AI2026
TOPS: First-Principles Visual Token Pruning via Constructing Token Optimal Preservation Sets for Efficient MLLM Inference
Tinghao Wang, Yichen Guo, Rui Huang +11
Multimodal large language models (MLLMs) have achieved strong multimodal reasoning capabilities, but their efficiency is limited by the large number of visual tokens, which introdu…
eess.IV2025
FSAR-Cap: A Fine-Grained Two-Stage Annotated Dataset for SAR Image Captioning
Jinqi Zhang, Lamei Zhang, Bin Zou
Synthetic Aperture Radar (SAR) image captioning enables scene-level semantic understanding and plays a crucial role in applications such as military intelligence and urban planning…