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#machine learning Preprint Sep 2026

Making LLMs Truly Forget: Deep Unlearning by Searching, Selecting, and Severing Knowledge Paths

While an unlearned language model may no longer recall a fact directly, the fact often remains recoverable through multi-hop reasoning over related knowledge. Most existing unlearning techniques overlook this vulnerability, targeting facts in isolation while leaving their supporting knowledge intact. To achieve true fo...

Jia-Lu Wang, Pei-Zhi Niu, Hao-Teng Yin et al. · 0 citations
#artificial intelligence Preprint Sep 2026

SEAD: A State-Based Perspective on Attack and Defense in Tool-Using Agents

Language-model agents increasingly use tools to act on external systems. Earlier actions can alter files, permissions, database records, or other state, making a later routine-looking action harmful. Yet the visible interaction may not reveal the underlying state needed to assess that action. We formulate attack and de...

Xin-Jie Shen, Jun-Ran Wang, Rong-Zhe Wei et al. · 0 citations

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