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Runxuan Tang

2 papers indexed

arxivcs.AI2026-07-02

Hidden Forgetting in Continual Multimodal Learning: When Accuracy Survives but Grounding Fails

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…

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arxivcs.AI2026-07-02

InduceKV: Fixed-Footprint Continual Adaptation of Multimodal LLMs via Inducing KV Memories

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…

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