New arXiv paper(s) on machine unlearning

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Corrective Machine Unlearning https://arxiv.org/abs/2402.14015 (This paper studies the interplay between adversarial attacks and machine unlearning).

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Decentralized Federated Unlearning on Blockchain https://arxiv.org/abs/2402.16294

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Dissecting Language Models: Machine Unlearning via Selective Pruning https://arxiv.org/abs/2403.01267

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Towards Efficient and Effective Unlearning of Large Language Models for Recommendation https://arxiv.org/abs/2403.03536 (Machine Unlearning + LLM + Recommender Systems)

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Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning https://arxiv.org/abs/2403.07362

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Towards Independence Criterion in Machine Unlearning of Features and Labels https://arxiv.org/abs/2403.08124

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∇τ : Gradient-based and Task-Agnostic machine Unlearning https://arxiv.org/abs/2403.14339

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Unlearning Backdoor Threats: Enhancing Backdoor Defense in Multimodal Contrastive Learning via Local Token Unlearning https://arxiv.org/abs/2403.16257

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Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective https://arxiv.org/abs/2403.16246

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CovarNav: Machine Unlearning via Model Inversion and Covariance Navigation https://arxiv.org/abs/2311.12999

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Making Users Indistinguishable: Attribute-wise Unlearning in Recommender Systems https://arxiv.org/abs/2310.05847

Post-Training Attribute Unlearning in Recommender Systems https://arxiv.org/abs/2403.06737

[adasken]

Papers added