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cs.AI2026
One Token per Multimodal Evidence: Latent Memory for Resource-Constrained QA
Zhi Zheng, Ziqiao Meng, Hao Luan +2
External memory effectively grounds large language models (LLMs) and vision-language models (VLMs)-based question answering (QA) in relevant multimodal evidence. However, existing…
cs.AI2026
Are We Evaluating the Edit Locality of LLM Model Editing Properly?
Wei Liu, Haomei Xu, Hongkai Liu +5
Model editing has recently emerged as a popular paradigm for efficiently updating knowledge in LLMs. A central desideratum of updating knowledge is to balance editing efficacy, i.e…
cs.AI2025
Is Model Editing Built on Sand? Revealing Its Illusory Success and Fragile Foundation
Wei Liu, Haomei Xu, Bingqing Liu +6
Large language models (LLMs) inevitably encode outdated or incorrect knowledge. Updating, deleting, and forgetting such knowledge is important for alignment, safety, and other issu…