【202406】REVS: Unlearning Sensitive Information in Language Models via Rank Editing in the Vocabulary Space [PDF]
【202405】Cross-Modal Safety Alignment: Is textual unlearning all you need? [PDF]
【202405】Large Scale Knowledge Washing [PDF]
【202405】Machine Unlearning in Large Language Models [PDF]
【202404】Offset Unlearning for Large Language Models [PDF]
【202404】Exact and Efficient Unlearning for Large Language Model-based Recommendation [PDF]
【202404】Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning [PDF]
【202404】Eraser: Jailbreaking Defense in Large Language Models via Unlearning Harmful Knowledge [PDF]
【202404】Digital Forgetting in Large Language Models: A Survey of Unlearning Methods [PDF]
【202403】The Frontier of Data Erasure: Machine Unlearning for Large Language Models [PDF]
【202403】Second-Order Information Matters: Revisiting Machine Unlearning for Large Language Models [PDF]
【202403】Guardrail Baselines for Unlearning in LLMs [PDF]
【202403】Towards Efficient and Effective Unlearning of Large Language Models for Recommendation [PDF]
【202403】The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning [PDF]
【202402】Eight Methods to Evaluate Robust Unlearning in LLMs [PDF]
【ACL2024】Machine Unlearning of Pre-trained Large Language Models [PDF]
【202402】EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models [PDF]
【202402】Unmemorization in Large Language Models via Self-Distillation and Deliberate Imagination [PDF]
【202402】Towards Safer Large Language Models through Machine Unlearning [PDF]
【202402】Rethinking Machine Unlearning for Large Language Models [PDF]
【202402】Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models [PDF]
【202401】Unlearning Reveals the Influential Training Data of Language Models [PDF]
【202401】TOFU: A Task of Fictitious Unlearning for LLMs [PDF]
【202312】Learning and Forgetting Unsafe Examples in Large Language Models [PDF]
【NeurIPS2023 Workshop】FAIRSISA: ENSEMBLE POST-PROCESSING TO IMPROVE FAIRNESS OF UNLEARNING IN LLMS [PDF]
【202311】Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges [PDF]
【202311】Forgetting before Learning: Utilizing Parametric Arithmetic for Knowledge Updating in Large Language Models [PDF]
【202311】Making Harmful Behaviors Unlearnable for Large Language Models [PDF]
【EMNLP2023】Unlearn What You Want to Forget: Efficient Unlearning for LLMs [PDF]
【202310】Large Language Model Unlearning
【202310】In-Context Unlearning: Language Models as Few Shot Unlearners
【202310】Who’s Harry Potter? Approximate Unlearning in LLMs
【202309】Neural Code Completion Tools Can Memorize Hard-coded Credentials
【202308】Separate the Wheat from the Chaff: Model Deficiency Unlearning via Parameter-Efficient Module Operatio
【202307】Make Text Unlearnable: Exploiting Effective Patterns to Protect Personal Data
【202307】What can we learn from Data Leakage and Unlearning for Law?
【202305】Right to be Forgotten in the Era of Large Language Models: Implications, Challenges, and Solutions
【202302】Knowledge Unlearning for Mitigating Privacy Risks in Language Models
【ACL2023】Unlearning Bias in Language Models by Partitioning Gradients
【202212】Privacy Adhering Machine Un-learning in NLP
【NeurIPS2022】Quark: Controllable Text Generation with Reinforced Unlearning
【ACL2022】Knowledge Neurons in Pretrained Transformers
【CCS2020】Analyzing Information Leakage of Updates to Natural Language Models