3 papers
cs.LG2026
Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domain
Yuan Yao, Jin Song, Huixia Li +3
Transfer learning aims to facilitate the learning of a target domain by transferring knowledge from a source domain. The source domain typically contains semantically meaningful sa…
cs.CV2025
SurveillanceVQA-589K: A Benchmark for Comprehensive Surveillance Video-Language Understanding with Large Models
Bo Liu, Pengfei Qiao, Minhan Ma +5
Understanding surveillance video content remains a critical yet underexplored challenge in vision-language research, particularly due to its real-world complexity, irregular event…
cs.CV2025
HiMix: Reducing Computational Complexity in Large Vision-Language Models
Xuange Zhang, Dengjie Li, Bo Liu +7
Benefiting from recent advancements in large language models and modality alignment techniques, existing Large Vision-Language Models(LVLMs) have achieved prominent performance acr…