3 papers indexed
Chengzhen Yu, Canran Xiao, Siyuan Ma, Yang Liu
Vision-language alignment powers open-vocabulary recognition, retrieval, and LVLM grounding, yet natural captions are often underspecified, making similarity brittle and overly confident under paraphrase and omitted details. We aim to learn representations whose matching is stabl…
Qianyu Chen, Canran Xiao, Runxuan Tang
Multimodal large language models must continually adapt to evolving tasks and domains, yet standard continual learning metrics mainly measure whether old answers remain correct, leaving the stability of multimodal grounding largely unexamined. We study this overlooked failure mod…
Qianyu Chen, Ziteng Feng, Canran Xiao, Runxuan Tang
Multimodal large language models must adapt to evolving tasks and domains, yet continual improvement under bounded deployment footprint remains difficult because repeated parameter updates or growing replay stores can accumulate adaptation state over time. We study fixed-footprin…