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20242026
most citedMachine Unlearning: A Comprehensive Survey

4 citations · 8 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.CR2026

Steering Beyond the Support: Adversarial Training on Unsupervised Jailbroken Activation Simulation

Luoyu Chen, Weiqi Wang, Zhiyi Tian +5

Jailbreak prompts can trigger harmful completions on aligned LLMs, In accordance, safety steering has been proposed: test-time activation interventions that steer jailbreak activat…

cs.CR2026

Ellipsoid Control: A White-list Jailbreak Defense via Benign Latent Modeling

Luoyu Chen, Weiqi Wang, Zhiyi Tian +3

Representation engineering (RepE) defenses have shown strong robustness against jailbreak attacks on large language models (LLMs). However, these methods fundamentally rely on blac…

cs.CR2026

BlindU: Blind Machine Unlearning without Revealing Erasing Data

Weiqi Wang, Zhiyi Tian, Chenhan Zhang +1

Machine unlearning enables data holders to remove the contribution of their specified samples from trained models to protect their privacy. However, it is paradoxical that most unl…

cs.CR2025

TAPE: Tailored Posterior Difference for Auditing of Machine Unlearning

Weiqi Wang, Zhiyi Tian, An Liu +1

With the increasing prevalence of Web-based platforms handling vast amounts of user data, machine unlearning has emerged as a crucial mechanism to uphold users' right to be forgott…

cs.CR2025

CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning

Weiqi Wang, Chenhan Zhang, Zhiyi Tian +2

Machine unlearning allows data owners to erase the impact of their specified data from trained models. Unfortunately, recent studies have shown that adversaries can recover the era…

cs.CR2025

SCU: An Efficient Machine Unlearning Scheme for Deep Learning Enabled Semantic Communications

Weiqi Wang, Zhiyi Tian, Chenhan Zhang +1

Deep learning (DL) enabled semantic communications leverage DL to train encoders and decoders (codecs) to extract and recover semantic information. However, most semantic training…