L L M Unlearning
Table of Contents
NeurIPS
ICLR
KDD
AAAI
USENIX Security Symposium
COLING
CIKM
Expert Syst. Appl.
Neural Networks
IEEE Trans. Knowl. Data Eng.
Nat. Mac. Intell.
NeurIPS
Expand NeurIPS
2024
| Title | Venue | Year | Link |
|---|---|---|---|
| Large Language Model Unlearning via Embedding-Corrupted Prompts. | NeurIPS | 2024 | Link |
| Large Language Model Unlearning. | NeurIPS | 2024 | Link |
| RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models. | NeurIPS | 2024 | Link |
| Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference. | NeurIPS | 2024 | Link |
| Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models. | NeurIPS | 2024 | Link |
| Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space. | NeurIPS | 2024 | Link |
| WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. | NeurIPS | 2024 | Link |
ICML
Expand ICML
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| Adaptive Localization of Knowledge Negation for Continual LLM Unlearning. | ICML | 2025 | Link |
| Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning. | ICML | 2025 | Link |
| Fast Exact Unlearning for In-Context Learning Data for LLMs. | ICML | 2025 | Link |
| GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs. | ICML | 2025 | Link |
| Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning. | ICML | 2025 | Link |
| Tool Unlearning for Tool-Augmented LLMs. | ICML | 2025 | Link |
| Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond. | ICML | 2025 | Link |
| Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning. | ICML | 2025 | Link |
2024
| Title | Venue | Year | Link |
|---|---|---|---|
| In-Context Unlearning: Language Models as Few-Shot Unlearners. | ICML | 2024 | Link |
| To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models. | ICML | 2024 | Link |
ICLR
Expand ICLR
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| A Closer Look at Machine Unlearning for Large Language Models. | ICLR | 2025 | Link |
| A Probabilistic Perspective on Unlearning and Alignment for Large Language Models. | ICLR | 2025 | Link |
| Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset. | ICLR | 2025 | Link |
| Catastrophic Failure of LLM Unlearning via Quantization. | ICLR | 2025 | Link |
| LLM Unlearning via Loss Adjustment with Only Forget Data. | ICLR | 2025 | Link |
| MUSE: Machine Unlearning Six-Way Evaluation for Language Models. | ICLR | 2025 | Link |
| On Large Language Model Continual Unlearning. | ICLR | 2025 | Link |
| Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. | ICLR | 2025 | Link |
| Towards Effective Evaluations and Comparisons for LLM Unlearning Methods. | ICLR | 2025 | Link |
| Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs. | ICLR | 2025 | Link |
| Unified Parameter-Efficient Unlearning for LLMs. | ICLR | 2025 | Link |
| Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning. | ICLR | 2025 | Link |
KDD
Expand KDD
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| LLM-Eraser: Optimizing Large Language Model Unlearning through Selective Pruning. | KDD | 2025 | Link |
ACL
Expand ACL
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| A General Framework to Enhance Fine-tuning-based LLM Unlearning. | ACL | 2025 | Link |
| Answer When Needed, Forget When Not: Language Models Pretend to Forget via In-Context Knowledge Unlearning. | ACL | 2025 | Link |
| Beyond Single-Value Metrics: Evaluating and Enhancing LLM Unlearning with Cognitive Diagnosis. | ACL | 2025 | Link |
| Decoupling Memories, Muting Neurons: Towards Practical Machine Unlearning for Large Language Models. | ACL | 2025 | Link |
| Disentangling Biased Knowledge from Reasoning in Large Language Models via Machine Unlearning. | ACL | 2025 | Link |
| From Evasion to Concealment: Stealthy Knowledge Unlearning for LLMs. | ACL | 2025 | Link |
| MMUnlearner: Reformulating Multimodal Machine Unlearning in the Era of Multimodal Large Language Models. | ACL | 2025 | Link |
| Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models. | ACL | 2025 | Link |
| Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport. | ACL | 2025 | Link |
| REVS: Unlearning Sensitive Information in Language Models via Rank Editing in the Vocabulary Space. | ACL | 2025 | Link |
| ReLearn: Unlearning via Learning for Large Language Models. | ACL | 2025 | Link |
| Rectifying Belief Space via Unlearning to Harness LLMs' Reasoning. | ACL | 2025 | Link |
| SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? | ACL | 2025 | Link |
| SafeEraser: Enhancing Safety in Multimodal Large Language Models through Multimodal Machine Unlearning. | ACL | 2025 | Link |
| Tokens for Learning, Tokens for Unlearning: Mitigating Membership Inference Attacks in Large Language Models via Dual-Purpose Training. | ACL | 2025 | Link |
| Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation. | ACL | 2025 | Link |
| Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge Distillation. | ACL | 2025 | Link |
| Which Retain Set Matters for LLM Unlearning? A Case Study on Entity Unlearning. | ACL | 2025 | Link |
2024
| Title | Venue | Year | Link |
|---|---|---|---|
| Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning. | ACL | 2024 | Link |
| Machine Unlearning of Pre-trained Large Language Models. | ACL | 2024 | Link |
| Protecting Privacy Through Approximating Optimal Parameters for Sequence Unlearning in Language Models. | ACL | 2024 | Link |
| Towards Safer Large Language Models through Machine Unlearning. | ACL | 2024 | Link |
| Unlearning Traces the Influential Training Data of Language Models. | ACL | 2024 | Link |
2023
| Title | Venue | Year | Link |
|---|---|---|---|
| Knowledge Unlearning for Mitigating Privacy Risks in Language Models. | ACL | 2023 | Link |
| Unlearning Bias in Language Models by Partitioning Gradients. | ACL | 2023 | Link |
EMNLP
Expand EMNLP
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| A Fully Probabilistic Perspective on Large Language Model Unlearning: Evaluation and Optimization. | EMNLP | 2025 | Link |
| Does Localization Inform Unlearning? A Rigorous Examination of Local Parameter Attribution for Knowledge Unlearning in Language Models. | EMNLP | 2025 | Link |
| Mitigating Biases in Language Models via Bias Unlearning. | EMNLP | 2025 | Link |
| OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models. | EMNLP | 2025 | Link |
| REVIVING YOUR MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing. | EMNLP | 2025 | Link |
| SEPS: A Separability Measure for Robust Unlearning in LLMs. | EMNLP | 2025 | Link |
| SUA: Stealthy Multimodal Large Language Model Unlearning Attack. | EMNLP | 2025 | Link |
2024
| Title | Venue | Year | Link |
|---|---|---|---|
| Can Machine Unlearning Reduce Social Bias in Language Models? | EMNLP | 2024 | Link |
| Cross-Lingual Unlearning of Selective Knowledge in Multilingual Language Models. | EMNLP | 2024 | Link |
| Dissecting Fine-Tuning Unlearning in Large Language Models. | EMNLP | 2024 | Link |
| EFUF: Efficient Fine-Grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models. | EMNLP | 2024 | Link |
| Fine-grained Pluggable Gradient Ascent for Knowledge Unlearning in Language Models. | EMNLP | 2024 | Link |
| SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. | EMNLP | 2024 | Link |
| To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models. | EMNLP | 2024 | Link |
| Towards Robust Evaluation of Unlearning in LLMs via Data Transformations. | EMNLP | 2024 | Link |
| ULMR: Unlearning Large Language Models via Negative Response and Model Parameter Average. | EMNLP | 2024 | Link |
2023
| Title | Venue | Year | Link |
|---|---|---|---|
| Preserving Privacy Through Dememorization: An Unlearning Technique For Mitigating Memorization Risks In Language Models. | EMNLP | 2023 | Link |
| Unlearn What You Want to Forget: Efficient Unlearning for LLMs. | EMNLP | 2023 | Link |
AAAI
Expand AAAI
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| Backdoor Token Unlearning: Exposing and Defending Backdoors in Pretrained Language Models. | AAAI | 2025 | Link |
| Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage. | AAAI | 2025 | Link |
| On Effects of Steering Latent Representation for Large Language Model Unlearning. | AAAI | 2025 | Link |
| Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models. | AAAI | 2025 | Link |
| Towards Robust Knowledge Unlearning: An Adversarial Framework for Assessing and Improving Unlearning Robustness in Large Language Models. | AAAI | 2025 | Link |
USENIX Security Symposium
Expand USENIX Security Symposium
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| Refusal Is Not an Option: Unlearning Safety Alignment of Large Language Models. | USENIX Security Symposium | 2025 | Link |
COLING
Expand COLING
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| Alternate Preference Optimization for Unlearning Factual Knowledge in Large Language Models. | COLING | 2025 | Link |
| Unveiling Entity-Level Unlearning for Large Language Models: A Comprehensive Analysis. | COLING | 2025 | Link |
CIKM
Expand CIKM
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| Pseudo-Inverse Prefix Tuning for Effective Unlearning in LLMs. | CIKM | 2025 | Link |
Expert Syst. Appl.
Expand Expert Syst. Appl.
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| Law LLM unlearning via interfere prompt, review output and update parameter: new challenges, method and baseline. | Expert Syst. Appl. | 2025 | Link |
Neural Networks
Expand Neural Networks
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| DP2Unlearning: An efficient and guaranteed unlearning framework for LLMs. | Neural Networks | 2025 | Link |
IEEE Trans. Knowl. Data Eng.
Expand IEEE Trans. Knowl. Data Eng.
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| Exact and Efficient Unlearning for Large Language Model-Based Recommendation. | IEEE Trans. Knowl. Data Eng. | 2025 | Link |
Nat. Mac. Intell.
Expand Nat. Mac. Intell.
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| Rethinking machine unlearning for large language models. | Nat. Mac. Intell. | 2025 | Link |
arXiv
Expand arXiv
2026
| Title | Venue | Year | Link |
|---|---|---|---|
| $\textbf{AGT$^{AO}$}$: Robust and Stabilized LLM Unlearning via Adversarial Gating Training with Adaptive Orthogonality | arXiv | 2026 | Link |
| Auditing Language Model Unlearning via Information Decomposition | arXiv | 2026 | Link |
| BalDRO: A Distributionally Robust Optimization based Framework for Large Language Model Unlearning | arXiv | 2026 | Link |
| Beyond Forgetting: Machine Unlearning Elicits Controllable Side Behaviors and Capabilities | arXiv | 2026 | Link |
| CATNIP: LLM Unlearning via Calibrated and Tokenized Negative Preference Alignment | arXiv | 2026 | Link |
| DUET: Distilled LLM Unlearning from an Efficiently Contextualized Teacher | arXiv | 2026 | Link |
| FIT: Defying Catastrophic Forgetting in Continual LLM Unlearning | arXiv | 2026 | Link |
| From Domains to Instances: Dual-Granularity Data Synthesis for LLM Unlearning | arXiv | 2026 | Link |
| From Logits to Latents: Contrastive Representation Shaping for LLM Unlearning | arXiv | 2026 | Link |
| Gauss-Newton Unlearning for the LLM Era | arXiv | 2026 | Link |
| KUDA: Knowledge Unlearning by Deviating Representation for Large Language Models | arXiv | 2026 | Link |
| Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning | arXiv | 2026 | Link |
| Per-parameter Task Arithmetic for Unlearning in Large Language Models | arXiv | 2026 | Link |
| Quantization-Robust LLM Unlearning via Low-Rank Adaptation | arXiv | 2026 | Link |
| Reinforcement Unlearning via Group Relative Policy Optimization | arXiv | 2026 | Link |
| STaR: Sensitive Trajectory Regulation for Unlearning in Large Reasoning Models | arXiv | 2026 | Link |
| Visual-Guided Key-Token Regularization for Multimodal Large Language Model Unlearning | arXiv | 2026 | Link |
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models | arXiv | 2025 | Link |
| A General Framework to Enhance Fine-tuning-based LLM Unlearning | arXiv | 2025 | Link |
| A Neuro-inspired Interpretation of Unlearning in Large Language Models through Sample-level Unlearning Difficulty | arXiv | 2025 | Link |
| A Survey on Unlearning in Large Language Models | arXiv | 2025 | Link |
| A mean teacher algorithm for unlearning of language models | arXiv | 2025 | Link |
| Agents Are All You Need for LLM Unlearning | arXiv | 2025 | Link |
| Align-then-Unlearn: Embedding Alignment for LLM Unlearning | arXiv | 2025 | Link |
| BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap | arXiv | 2025 | Link |
| BLUR: A Bi-Level Optimization Approach for LLM Unlearning | arXiv | 2025 | Link |
| Beyond Sharp Minima: Robust LLM Unlearning via Feedback-Guided Multi-Point Optimization | arXiv | 2025 | Link |
| Beyond Single-Value Metrics: Evaluating and Enhancing LLM Unlearning with Cognitive Diagnosis | arXiv | 2025 | Link |
| Bridging the Gap Between Preference Alignment and Machine Unlearning | arXiv | 2025 | Link |
| CLUE: Conflict-guided Localization for LLM Unlearning Framework | arXiv | 2025 | Link |
| Collapse of Irrelevant Representations (CIR) Ensures Robust and Non-Disruptive LLM Unlearning | arXiv | 2025 | Link |
| Concept Unlearning in Large Language Models via Self-Constructed Knowledge Triplets | arXiv | 2025 | Link |
| Constrained Entropic Unlearning: A Primal-Dual Framework for Large Language Models | arXiv | 2025 | Link |
| Cyber for AI at SemEval-2025 Task 4: Forgotten but Not Lost: The Balancing Act of Selective Unlearning in Large Language Models | arXiv | 2025 | Link |
| DRAGON: Guard LLM Unlearning in Context via Negative Detection and Reasoning | arXiv | 2025 | Link |
| Direct Token Optimization: A Self-contained Approach to Large Language Model Unlearning | arXiv | 2025 | Link |
| Distillation Robustifies Unlearning | arXiv | 2025 | Link |
| Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning | arXiv | 2025 | Link |
| Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning | arXiv | 2025 | Link |
| Dual-Space Smoothness for Robust and Balanced LLM Unlearning | arXiv | 2025 | Link |
| Editing as Unlearning: Are Knowledge Editing Methods Strong Baselines for Large Language Model Unlearning? | arXiv | 2025 | Link |
| Existing Large Language Model Unlearning Evaluations Are Inconclusive | arXiv | 2025 | Link |
| Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning | arXiv | 2025 | Link |
| Forgetting to Forget: Attention Sink as A Gateway for Backdooring LLM Unlearning | arXiv | 2025 | Link |
| Forgetting-MarI: LLM Unlearning via Marginal Information Regularization | arXiv | 2025 | Link |
| From Learning to Unlearning: Biomedical Security Protection in Multimodal Large Language Models | arXiv | 2025 | Link |
| GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs | arXiv | 2025 | Link |
| GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection | arXiv | 2025 | Link |
| GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models | arXiv | 2025 | Link |
| Geometric-disentangelment Unlearning | arXiv | 2025 | Link |
| Holistic Audit Dataset Generation for LLM Unlearning via Knowledge Graph Traversal and Redundancy Removal | arXiv | 2025 | Link |
| Improving Fisher Information Estimation and Efficiency for LoRA-based LLM Unlearning | arXiv | 2025 | Link |
| Improving LLM Unlearning Robustness via Random Perturbations | arXiv | 2025 | Link |
| Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning | arXiv | 2025 | Link |
| Inverse IFEval: Can LLMs Unlearn Stubborn Training Conventions to Follow Real Instructions? | arXiv | 2025 | Link |
| Keeping an Eye on LLM Unlearning: The Hidden Risk and Remedy | arXiv | 2025 | Link |
| LLM Unlearning Reveals a Stronger-Than-Expected Coreset Effect in Current Benchmarks | arXiv | 2025 | Link |
| LLM Unlearning Should Be Form-Independent | arXiv | 2025 | Link |
| LLM Unlearning Under the Microscope: A Full-Stack View on Methods and Metrics | arXiv | 2025 | Link |
| LLM Unlearning Without an Expert Curated Dataset | arXiv | 2025 | Link |
| LLM Unlearning on Noisy Forget Sets: A Study of Incomplete, Rewritten, and Watermarked Data | arXiv | 2025 | Link |
| LLM Unlearning using Gradient Ratio-Based Influence Estimation and Noise Injection | arXiv | 2025 | Link |
| LLM Unlearning via Neural Activation Redirection | arXiv | 2025 | Link |
| LLM Unlearning with LLM Beliefs | arXiv | 2025 | Link |
| LUME: LLM Unlearning with Multitask Evaluations | arXiv | 2025 | Link |
| LUNE: Efficient LLM Unlearning via LoRA Fine-Tuning with Negative Examples | arXiv | 2025 | Link |
| Label Smoothing Improves Gradient Ascent in LLM Unlearning | arXiv | 2025 | Link |
| Large Language Model Unlearning for Source Code | arXiv | 2025 | Link |
| Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding | arXiv | 2025 | Link |
| Not All Data Are Unlearned Equally | arXiv | 2025 | Link |
| Not Every Token Needs Forgetting: Selective Unlearning to Limit Change in Utility in Large Language Model Unlearning | arXiv | 2025 | Link |
| Oblivionis: A Lightweight Learning and Unlearning Framework for Federated Large Language Models | arXiv | 2025 | Link |
| OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics | arXiv | 2025 | Link |
| RULE: Reinforcement UnLEarning Achieves Forget-Retain Pareto Optimality | arXiv | 2025 | Link |
| RapidUn: Influence-Driven Parameter Reweighting for Efficient Large Language Model Unlearning | arXiv | 2025 | Link |
| Recover-to-Forget: Gradient Reconstruction from LoRA for Efficient LLM Unlearning | arXiv | 2025 | Link |
| Reference-Specific Unlearning Metrics Can Hide the Truth: A Reality Check | arXiv | 2025 | Link |
| Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond | arXiv | 2025 | Link |
| Reveal and Release: Iterative LLM Unlearning with Self-generated Data | arXiv | 2025 | Link |
| Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing | arXiv | 2025 | Link |
| Robust LLM Unlearning with MUDMAN: Meta-Unlearning with Disruption Masking And Normalization | arXiv | 2025 | Link |
| SUA: Stealthy Multimodal Large Language Model Unlearning Attack | arXiv | 2025 | Link |
| Scalable and Robust LLM Unlearning by Correcting Responses with Retrieved Exclusions | arXiv | 2025 | Link |
| SemEval-2025 Task 4: Unlearning sensitive content from Large Language Models | arXiv | 2025 | Link |
| SoK: Machine Unlearning for Large Language Models | arXiv | 2025 | Link |
| Sparse-Autoencoder-Guided Internal Representation Unlearning for Large Language Models | arXiv | 2025 | Link |
| Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning | arXiv | 2025 | Link |
| Towards Benign Memory Forgetting for Selective Multimodal Large Language Model Unlearning | arXiv | 2025 | Link |
| Towards Evaluation for Real-World LLM Unlearning | arXiv | 2025 | Link |
| Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond | arXiv | 2025 | Link |
| Towards Mitigating Excessive Forgetting in LLM Unlearning via Entanglement-Guidance with Proxy Constraint | arXiv | 2025 | Link |
| UIPE: Enhancing LLM Unlearning by Removing Knowledge Related to Forgetting Targets | arXiv | 2025 | Link |
| UniErase: Towards Balanced and Precise Unlearning in Language Models | arXiv | 2025 | Link |
| Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs | arXiv | 2025 | Link |
| WaterDrum: Watermarking for Data-centric Unlearning Metric | arXiv | 2025 | Link |
| When Forgetting Builds Reliability: LLM Unlearning for Reliable Hardware Code Generation | arXiv | 2025 | Link |
| Which Retain Set Matters for LLM Unlearning? A Case Study on Entity Unlearning | arXiv | 2025 | Link |
| Wisdom is Knowing What not to Say: Hallucination-Free LLMs Unlearning via Attention Shifting | arXiv | 2025 | Link |
2024
| Title | Venue | Year | Link |
|---|---|---|---|
| A Closer Look at Machine Unlearning for Large Language Models | arXiv | 2024 | Link |
| Avoiding Copyright Infringement via Large Language Model Unlearning | arXiv | 2024 | Link |
| Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset | arXiv | 2024 | Link |
| Catastrophic Failure of LLM Unlearning via Quantization | arXiv | 2024 | Link |
| Classifier-free guidance in LLMs Safety | arXiv | 2024 | Link |
| Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods | arXiv | 2024 | Link |
| How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective | arXiv | 2024 | Link |
| Investigating the Feasibility of Mitigating Potential Copyright Infringement via Large Language Model Unlearning | arXiv | 2024 | Link |
| LLM Unlearning via Loss Adjustment with Only Forget Data | arXiv | 2024 | Link |
| Large Language Model Unlearning via Embedding-Corrupted Prompts | arXiv | 2024 | Link |
| MEOW: MEMOry Supervised LLM Unlearning Via Inverted Facts | arXiv | 2024 | Link |
| Methods to Assess the UK Government's Current Role as a Data Provider for AI | arXiv | 2024 | Link |
| Multi-Objective Large Language Model Unlearning | arXiv | 2024 | Link |
| Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning | arXiv | 2024 | Link |
| On Effects of Steering Latent Representation for Large Language Model Unlearning | arXiv | 2024 | Link |
| On Large Language Model Continual Unlearning | arXiv | 2024 | Link |
| Position: LLM Unlearning Benchmarks are Weak Measures of Progress | arXiv | 2024 | Link |
| Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench | arXiv | 2024 | Link |
| RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models | arXiv | 2024 | Link |
| Rethinking Machine Unlearning for Large Language Models | arXiv | 2024 | Link |
| Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference | arXiv | 2024 | Link |
| Revisiting Who's Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective | arXiv | 2024 | Link |
| SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? | arXiv | 2024 | Link |
| SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning | arXiv | 2024 | Link |
| Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning | arXiv | 2024 | Link |
| Towards Effective Evaluations and Comparisons for LLM Unlearning Methods | arXiv | 2024 | Link |
| Towards Robust Knowledge Unlearning: An Adversarial Framework for Assessing and Improving Unlearning Robustness in Large Language Models | arXiv | 2024 | Link |
| Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs | arXiv | 2024 | Link |
| Towards Transfer Unlearning: Empirical Evidence of Cross-Domain Bias Mitigation | arXiv | 2024 | Link |
| Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning | arXiv | 2024 | Link |
| Unveiling Entity-Level Unlearning for Large Language Models: A Comprehensive Analysis | arXiv | 2024 | Link |
| WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models | arXiv | 2024 | Link |
2023
| Title | Venue | Year | Link |
|---|---|---|---|
| Large Language Model Unlearning | arXiv | 2023 | Link |