3 papers
cs.CL2026
Unlearning Is Not Just Erasing: Temporal Decoupling via Generation Inequality
Xunlei Chen, Qirui Ye, Yuang Li +5
Large language models (LLMs) require effective unlearning to address privacy regulations and safety concerns. However, achieving precise forgetting without compromising general uti…
cs.AI2026
AdapShot: Adaptive Many-Shot In-Context Learning with Semantic-Aware KV Cache Reuse
Jie Ou, Jinyu Guo, Shiyao Guo +5
Many-Shot In-Context Learning (ICL) has emerged as a promising paradigm, leveraging extensive examples to unlock the reasoning potential of Large Language Models (LLMs). However, e…
cs.LG2026
CAP: Controllable Alignment Prompting for Unlearning in LLMs
Zhaokun Wang, Jinyu Guo, Jingwen Pu +7
Large language models (LLMs) trained on unfiltered corpora inherently risk retaining sensitive information, necessitating selective knowledge unlearning for regulatory compliance a…