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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.CL2026
ALTER: Asymmetric LoRA for Token-Entropy-Guided Unlearning of LLMs
Xunlei Chen, Jinyu Guo, Yuang Li +5
Large language models (LLMs) have advanced to encompass extensive knowledge across diverse domains. Yet controlling what a LLMs should not know is important for ensuring alignment…
cs.CL2025
RECALL: REpresentation-aligned Catastrophic-forgetting ALLeviation via Hierarchical Model Merging
Bowen Wang, Haiyuan Wan, Liwen Shi +10
We unveil that internal representations in large language models (LLMs) serve as reliable proxies of learned knowledge, and propose RECALL, a novel representation-aware model mergi…