5 papers · 1 filter
Who Bridges Safety? Identifying and Targeting Cross-Lingual Shared Safety Pathways
Shuyi Miao, Wangjie Qiu, Pengyang Shao +4
Uncovering the internal mechanisms underlying the safety capabilities of large language models (LLMs) is crucial for developing trustworthy artificial intelligence. Currently, mech…
Hidden APIs in Language Models: Discovering Reusable Causal Interfaces from Forked Futures
SiYuan Ma, Yiqin Luo, Zhangji +8
Identical language-model answers can arise from hidden states that support different future computations, so current-answer probes do not establish a reusable internal interface. W…
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, le…
InduceKV: Fixed-Footprint Continual Adaptation of Multimodal LLMs via Inducing KV Memories
Qianyu Chen, Ziteng Feng, Canran Xiao +1
Multimodal large language models must adapt to evolving tasks and domains, yet continual improvement under bounded deployment footprint remains difficult because repeated parameter…
Seeing through the Conflict: Transparent Knowledge Conflict Handling in Retrieval-Augmented Generation
Hua Ye, Siyuan Chen, Ziqi Zhong +4
Large language models (LLMs) equipped with retrieval--the Retrieval-Augmented Generation (RAG) paradigm--should combine their parametric knowledge with external evidence, yet in pr…