{"total":119,"rows":[{"id":"2404.05868","title":"Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning","created":"2024-04-08","cited_by_count":504,"area":"alignment"},{"id":"2406.07933","title":"Large Language Model Unlearning via Embedding-Corrupted Prompts","created":"2024-06-12","cited_by_count":116,"area":"safety"},{"id":"2404.02936","title":"Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models","created":"2024-04-03","cited_by_count":103,"area":null},{"id":"2406.10890","title":"RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models","created":"2024-06-16","cited_by_count":78,"area":"safety"},{"id":"2410.11143","title":"LLM Unlearning via Loss Adjustment with Only Forget Data","created":"2024-10-14","cited_by_count":75,"area":"safety"},{"id":"2406.17975","title":"SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It)","created":"2024-06-25","cited_by_count":59,"area":"safety"},{"id":"2410.08109","title":"A Closer Look at Machine Unlearning for Large Language Models","created":"2024-10-10","cited_by_count":56,"area":"safety"},{"id":"2407.20516","title":"Machine Unlearning in Generative AI: A Survey","created":"2024-07-30","cited_by_count":49,"area":"safety"},{"id":"2405.12523","title":"Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models","created":"2024-05-21","cited_by_count":46,"area":"mllm"},{"id":"2505.16831","title":"Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs","created":"2025-05-22","cited_by_count":42,"area":"safety"},{"id":"2410.12777","title":"Meta-Unlearning on Diffusion Models: Preventing Relearning Unlearned Concepts","created":"2024-10-16","cited_by_count":40,"area":"diffusion"},{"id":"2502.18943","title":"Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models","created":"2025-02-26","cited_by_count":37,"area":"safety"},{"id":"2404.11045","title":"Offset Unlearning for Large Language Models","created":"2024-04-17","cited_by_count":36,"area":"safety"},{"id":"2408.06621","title":"Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs","created":"2024-08-13","cited_by_count":36,"area":"lr"},{"id":"2405.07406","title":"Machine Unlearning: A Comprehensive Survey","created":"2024-05-13","cited_by_count":35,"area":"safety"},{"id":"2503.01854","title":"A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models","created":"2025-02-22","cited_by_count":34,"area":"safety"},{"id":"2411.03554","title":"Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset","created":"2024-11-05","cited_by_count":30,"area":"mllm"},{"id":"2406.02958","title":"PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs","created":"2024-06-05","cited_by_count":29,"area":null},{"id":"2410.17509","title":"WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models","created":"2024-10-23","cited_by_count":26,"area":"safety"},{"id":"2410.15267","title":"When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?","created":"2024-10-20","cited_by_count":24,"area":"rag"},{"id":"2506.01339","title":"Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning","created":"2025-06-02","cited_by_count":21,"area":"safety"},{"id":"2502.01083","title":"Tool Unlearning for Tool-Augmented LLMs","created":"2025-02-03","cited_by_count":17,"area":"agents"},{"id":"2505.13312","title":"GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection","created":"2025-05-19","cited_by_count":17,"area":"safety"},{"id":"2604.20358","title":"ConeSep: Cone-based Robust Noise-Unlearning Compositional Network for Composed Image Retrieval","created":"2026-04-22","cited_by_count":17,"area":"safety"},{"id":"2403.03536","title":"Towards Efficient and Effective Unlearning of Large Language Models for Recommendation","created":"2024-03-06","cited_by_count":16,"area":"safety"},{"id":"2405.16720","title":"Large Scale Knowledge Washing","created":"2024-05-26","cited_by_count":16,"area":"safety"},{"id":"2410.15153","title":"Evaluating Deep Unlearning in Large Language Models","created":"2024-10-19","cited_by_count":14,"area":"safety"},{"id":"2506.05735","title":"Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness","created":"2025-06-06","cited_by_count":14,"area":"safety"},{"id":"2503.14530","title":"SAUCE: Selective Concept Unlearning in Vision-Language Models with Sparse Autoencoders","created":"2025-03-16","cited_by_count":13,"area":"mllm"},{"id":"2410.02159","title":"Mitigating Memorization In Language Models","created":"2024-10-03","cited_by_count":12,"area":"safety"},{"id":"2506.06278","title":"Distillation Robustifies Unlearning","created":"2025-06-06","cited_by_count":11,"area":"safety"},{"id":"2506.09227","title":"SoK: Machine Unlearning for Large Language Models","created":"2025-06-10","cited_by_count":11,"area":"safety"},{"id":"2502.17591","title":"Proactive Privacy Amnesia for Large Language Models: Safeguarding PII with Negligible Impact on Model Utility","created":"2025-02-24","cited_by_count":10,"area":null},{"id":"2507.05578","title":"The Landscape of Memorization in LLMs: Mechanisms, Measurement, and Mitigation","created":"2025-07-08","cited_by_count":10,"area":"safety"},{"id":"2412.08559","title":"Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning","created":"2024-12-11","cited_by_count":9,"area":"safety"},{"id":"2505.15214","title":"R-TOFU: Unlearning in Large Reasoning Models","created":"2025-05-21","cited_by_count":9,"area":"lr"},{"id":"2510.22535","title":"OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Models","created":"2025-10-26","cited_by_count":8,"area":"mllm"},{"id":"2512.07375","title":"LUNE: Efficient LLM Unlearning via LoRA Fine-Tuning with Negative Examples","created":"2025-12-08","cited_by_count":8,"area":"safety"},{"id":"2602.17692","title":"Agentic Unlearning: When LLM Agent Meets Machine Unlearning","created":"2026-02-06","cited_by_count":8,"area":"agents"},{"id":"2404.12530","title":"TrajDeleter: Enabling Trajectory Forgetting in Offline Reinforcement Learning Agents","created":"2024-04-18","cited_by_count":7,"area":"offlinerl"},{"id":"2502.12430","title":"Position: Bridge the Gaps between Machine Unlearning and AI Regulation","created":"2025-02-18","cited_by_count":7,"area":"safety"},{"id":"2509.13755","title":"Scrub It Out! Erasing Sensitive Memorization in Code Language Models via Machine Unlearning","created":"2025-09-17","cited_by_count":7,"area":"safety"},{"id":"2603.01285","title":"Attention Smoothing Is All You Need For Unlearning","created":"2026-03-01","cited_by_count":7,"area":"safety"},{"id":"2605.09530","title":"MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud Agents","created":"2026-05-10","cited_by_count":7,"area":"agents"},{"id":"2503.12545","title":"PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models","created":"2025-03-16","cited_by_count":6,"area":"mllm"},{"id":"2506.17279","title":"Step-by-Step Reasoning Attack: Revealing 'Erased' Knowledge in Large Language Models","created":"2025-06-14","cited_by_count":6,"area":"lr"},{"id":"2507.01271","title":"PULSE: Practical Evaluation Scenarios for Large Multimodal Model Unlearning","created":"2025-07-02","cited_by_count":6,"area":"mllm"},{"id":"2602.06441","title":"Is Gradient Ascent Really Necessary? Memorize to Forget for Machine Unlearning","created":"2026-02-06","cited_by_count":6,"area":"safety"},{"id":"2502.19982","title":"Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language Models","created":"2025-02-27","cited_by_count":5,"area":"safety"},{"id":"2509.22263","title":"Erase or Hide? Suppressing Spurious Unlearning Neurons for Robust Unlearning","created":"2025-09-26","cited_by_count":5,"area":"safety"},{"id":"2407.06483","title":"Composable Interventions for Language Models","created":"2024-07-09","cited_by_count":4,"area":"safety"},{"id":"2503.01224","title":"CE-U: Cross Entropy Unlearning","created":"2025-03-03","cited_by_count":4,"area":"safety"},{"id":"2507.11128","title":"What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests","created":"2025-07-15","cited_by_count":4,"area":"safety"},{"id":"2507.19894","title":"Generative Model Unlearning: A Survey through Target Events, Unlearning Operators, and Evaluation Protocols","created":"2025-07-26","cited_by_count":4,"area":"safety"},{"id":"2508.04329","title":"Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning","created":"2025-08-06","cited_by_count":4,"area":null},{"id":"2510.25117","title":"A Survey on Unlearning in Large Language Models","created":"2025-10-29","cited_by_count":4,"area":"safety"},{"id":"2511.17100","title":"Geometric-disentangelment Unlearning","created":"2025-11-21","cited_by_count":4,"area":"safety"},{"id":"2601.20568","title":"Reinforcement Unlearning via Group Relative Policy Optimization","created":"2026-01-28","cited_by_count":4,"area":"safety"},{"id":"2601.22359","title":"The Unseen Threat: Residual Knowledge in Machine Unlearning under Perturbed Samples","created":"2026-01-29","cited_by_count":4,"area":"safety"},{"id":"2602.10568","title":"Gauss-Newton Unlearning for the LLM Era","created":"2026-02-11","cited_by_count":4,"area":"safety"},{"id":"2504.12681","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","created":"2025-04-17","cited_by_count":3,"area":"safety"},{"id":"2506.07795","title":"LLM Unlearning Should Be Form-Independent","created":"2025-06-09","cited_by_count":3,"area":"safety"},{"id":"2508.17233","title":"Module-Aware Parameter-Efficient Machine Unlearning on Transformers","created":"2025-08-24","cited_by_count":3,"area":"safety"},{"id":"2510.02392","title":"KnowledgeSmith: Uncovering Knowledge Updating in LLMs with Model Editing and Unlearning","created":"2025-10-01","cited_by_count":3,"area":"safety"},{"id":"2510.04773","title":"Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning","created":"2025-10-06","cited_by_count":3,"area":"alignment"},{"id":"2605.08031","title":"Object Hallucination-Free Reinforcement Unlearning for Vision-Language Models","created":"2026-05-08","cited_by_count":3,"area":"mllm"},{"id":"2405.08134","title":"Many-Shot Regurgitation (MSR) Prompting","created":"2024-05-13","cited_by_count":2,"area":"safety"},{"id":"2410.03772","title":"Precision Knowledge Editing: Enhancing Safety in Large Language Models","created":"2024-10-02","cited_by_count":2,"area":"safety"},{"id":"2503.07806","title":"Towards Large Language Models that Benefit for All: Benchmarking Group Fairness in Reward Models","created":"2025-03-10","cited_by_count":2,"area":"alignment"},{"id":"2504.13774","title":"DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs","created":"2025-04-18","cited_by_count":2,"area":"safety"},{"id":"2506.10946","title":"GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models","created":"2025-06-12","cited_by_count":2,"area":"safety"},{"id":"2509.25973","title":"Scalable and Robust LLM Unlearning by Correcting Responses with Retrieved Exclusions","created":"2025-09-30","cited_by_count":2,"area":"safety"},{"id":"2510.00125","title":"Direct Token Optimization: A Self-contained Approach to Large Language Model Unlearning","created":"2025-09-30","cited_by_count":2,"area":"safety"},{"id":"2602.08901","title":"Mitigating Memorization Where It Happens","created":"2026-02-09","cited_by_count":2,"area":null},{"id":"2604.16591","title":"Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning","created":"2026-04-17","cited_by_count":2,"area":"safety"},{"id":"2412.00881","title":"Learn to Unlearn: Meta-Learning-Based Knowledge Graph Embedding Unlearning","created":"2024-12-01","cited_by_count":1,"area":"safety"},{"id":"2506.15076","title":"Learning-Time Encoding Shapes Unlearning in LLMs","created":"2025-06-18","cited_by_count":1,"area":"safety"},{"id":"2508.12220","title":"Unlearning at Scale: State-Exact Trace-Preserving Deletion in Billion-Parameter Language Models","created":"2025-08-17","cited_by_count":1,"area":"safety"},{"id":"2508.20443","title":"Towards Mitigating Excessive Forgetting in LLM Unlearning via Entanglement-Guidance with Proxy Constraint","created":"2025-08-28","cited_by_count":1,"area":"safety"},{"id":"2509.14633","title":"CUFG: Curriculum Unlearning Guided by the Forgetting Gradient","created":"2025-09-18","cited_by_count":1,"area":"safety"},{"id":"2512.07374","title":"Recover-to-Forget: Gradient Reconstruction from LoRA for Efficient LLM Unlearning","created":"2025-12-08","cited_by_count":1,"area":"safety"},{"id":"2512.13837","title":"Explainable reinforcement learning from human feedback to improve alignment","created":"2025-12-15","cited_by_count":1,"area":"alignment"},{"id":"2604.00430","title":"Secure Forgetting: A Framework for Privacy-Driven Unlearning in Large Language Model (LLM)-Based Agents","created":"2026-04-01","cited_by_count":1,"area":"lr"},{"id":"2606.12809","title":"MLUBench: A Benchmark for Lifelong Unlearning Evaluation in MLLMs","created":"2026-06-11","cited_by_count":1,"area":"mllm"},{"id":"2606.26036","title":"Detect, Unlearn, Restore: Defending Text Summarization Models Against Data Poisoning","created":"2026-06-24","cited_by_count":1,"area":"safety"},{"id":"2607.19442","title":"Unlearning as Distribution Restoration: A Controlled Counterfactual Study, a Validated Selective Screen, and the Limits of Oracle-Free Certification","created":"2026-07-21","cited_by_count":1,"area":"safety"},{"id":"2505.05064","title":"WaterDrum: Watermarking for Data-centric Unlearning Metric","created":"2025-05-08","cited_by_count":0,"area":null},{"id":"2506.04712","title":"UNO: Unlearning via Orthogonalization in Generative models","created":"2025-06-05","cited_by_count":0,"area":"safety"},{"id":"2506.11253","title":"Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models","created":"2025-06-12","cited_by_count":0,"area":"safety"},{"id":"2510.21184","title":"Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference","created":"2025-10-24","cited_by_count":0,"area":null},{"id":"2511.05605","title":"FiCABU: A Fisher-Based, Context-Adaptive Machine Unlearning Processor for Edge AI","created":"2025-11-06","cited_by_count":0,"area":"safety"},{"id":"2512.04457","title":"RapidUn: Influence-Driven Parameter Reweighting for Efficient Large Language Model Unlearning","created":"2025-12-04","cited_by_count":0,"area":"safety"},{"id":"2512.12469","title":"Sparse Concept Anchoring for Interpretable and Controllable Neural Representations","created":"2025-12-13","cited_by_count":0,"area":null},{"id":"2601.04275","title":"Shadow Unlearning: A Neuro-Semantic Approach to Fidelity-Preserving Faceless Forgetting in LLMs","created":"2026-01-07","cited_by_count":0,"area":"safety"},{"id":"2601.20282","title":"Memory Retrieval in Transformers: Insights from The Encoding Specificity Principle","created":"2026-01-28","cited_by_count":0,"area":"safety"},{"id":"2601.21682","title":"FIT to Forget: Robust Continual Unlearning for Large Language Models","created":"2026-01-29","cited_by_count":0,"area":"safety"},{"id":"2602.14938","title":"Variance-Reduced $(\\varepsilon,\\delta)-$Unlearning using Forget Set Gradients","created":"2026-02-16","cited_by_count":0,"area":"safety"},{"id":"2604.04800","title":"Forgetting to Witness: Efficient Federated Unlearning and Its Visible Evaluation","created":"2026-04-06","cited_by_count":0,"area":"safety"},{"id":"2604.05716","title":"Can Large Language Models Reinvent Foundational Algorithms?","created":"2026-04-07","cited_by_count":0,"area":"safety"},{"id":"2604.06154","title":"Exclusive Unlearning","created":"2026-04-07","cited_by_count":0,"area":"safety"}],"next_cursor":"100"}