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Rethinking machine unlearning for large language models (99) 사진

Rethinking LLM Memorization – Machine Learning Blog | ML@CMU | Carnegie Mellon University

Large Language Models for Recommendation: Progresses and Future Direction

Rethinking LLM Training: The Promise of Inverse Reinforcement Learning Techniques - MarkTechPost

Scrub-and-Learn: Category-Aware Weight Modification for Machine Unlearning

ICML Poster Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond

Trustworthy LLM and an Unlearning Approach

LLM Unlearning on Noisy Forget Sets: A Study of Incomplete, Rewritten, and Watermarked Data

Learn to Forget: Machine Unlearning via Neuron Masking

Machine Unlearning

A CLOSER LOOK AT MACHINE UNLEARNING FOR LARGE LANGUAGE MODELS-CSDN博客

In December of 2024, Anthropic released a research paper about a new LLM phenomenon called Alignment Faking. Large Language Models (LLMs) trained with Reinforcement Learning from Human Feedback (RLHF) might fake alignment

Digital forgetting in large language models: a survey of unlearning methods | Artificial Intelligence Review | Springer Nature Link

Machine Unlearning

Learn to Forget: Machine Unlearning via Neuron Masking

A Survey on Unlearning in Large Language Models

Unlearn What You Want to Forget: Efficient Unlearning for LLMs

Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate

A General Framework to Enhance Fine-tuning-based LLM Unlearning

Knowledge-enhanced large language models for automatic lesson plan generation | Humanities and Social Sciences Communications

Digital forgetting in large language models: a survey of unlearning methods | Artificial Intelligence Review | Springer Nature Link

ICML Poster Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond

Paper page - CLEAR: Character Unlearning in Textual and Visual Modalities

Jinghan Jia

Literature Review] Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning

Literature Review] MUSE: Machine Unlearning Six-Way Evaluation for Language Models

Machine Unlearning in Large Language Models: A Comprehensive Survey with Empirical Insights from the Qwen 1.5 1.8B Model — LessWrong

Large Language Model Unlearning

Jogging the Memory of Unlearned LLMs Through Targeted Relearning Attacks

Rethinking Data Use in Large Language Models

Rethinking machine unlearning for large language models by Sijia Liu & Yuanshun Yao & Jinghan Jia & Stephen Casper & Nathalie Baracaldo & Peter Hase & Yuguang Yao & Chris Yuhao Liu

Scrub-and-Learn: Category-Aware Weight Modification for Machine Unlearning

A survey on large language models unlearning: taxonomy, evaluations, and future directions | Artificial Intelligence Review | Springer Nature Link

Industrial applications of large language models | Scientific Reports

PDF] RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models | Semantic Scholar

PDF) Rethinking Post-Unlearning Behavior of Large Vision-Language Models

Rethinking Data Use in Large Language Models

PDF] Machine Unlearning of Pre-trained Large Language Models | Semantic Scholar

Paper page - CLEAR: Character Unlearning in Textual and Visual Modalities

Scrub-and-Learn: Category-Aware Weight Modification for Machine Unlearning

Machine Unlearning in Large Language Models: A Comprehensive Survey with Empirical Insights from the Qwen 1.5 1.8B Model — LessWrong

ICML Poster Flexible, Efficient, and Stable Adversarial Attacks on Machine Unlearning

Rethinking Machine Unlearning for Large Language Models - 智源社区论文

Towards Efficient Machine Unlearning with Data Augmentation: Guided Loss-Increasing (GLI) to Prevent the Catastrophic Model Util

Decoupling Memories, Muting Neurons: Towards Practical Machine Unlearning for Large Language Models

SoK: Machine Unlearning for Large Language Models

Learning to Unlearn: Why Data Scientists and AI Practitioners Should Understand Machine Unlearning | by Raul Vizcarra Chirinos | TDS Archive | Medium

Trustworthy LLM and an Unlearning Approach

爱可可AI 前沿推介(2.16) - 知乎

Literature Review] OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models

Decoupling Memories, Muting Neurons: Towards Practical Machine Unlearning for Large Language Models

Can LLMs Unlearn? Part 4: The Technical Complexity of it All (continued)

LLM Unlearning via Neural Activation Redirection

Hierarchical Federated Unlearning for Large Language Models

Learning to Unlearn: Why Data Scientists and AI Practitioners Should Understand Machine Unlearning | by Raul Vizcarra Chirinos | TDS Archive | Medium

Beyond Aha Moments: Structuring Reasoning in Large Language Models - MarkTechPost

RETHINKING LLM UNLEARNING OBJECTIVES: A GRADIENT PERSPECTIVE AND GO BEYOND

Fine-tuning large language models for domain adaptation: exploration of training strategies, scaling, model merging and synergistic capabilities | npj Computational Materials

Learning to Unlearn: Why Data Scientists and AI Practitioners Should Understand Machine Unlearning | Towards Data Science

LLM Unlearning via Neural Activation Redirection

RETHINKING LLM UNLEARNING OBJECTIVES: A GRADIENT PERSPECTIVE AND GO BEYOND

Industrial applications of large language models | Scientific Reports

Decoupling Memories, Muting Neurons: Towards Practical Machine Unlearning for Large Language Models

LLM Unlearning with LLM Beliefs

PDF] RKLD: Reverse KL-Divergence-based Knowledge Distillation for Unlearning Personal Information in Large Language Models | Semantic Scholar

A survey of security and privacy issues of machine unlearning - Chen - 2025 - AI Magazine - Wiley Online Library

Harnessing large language models for data-scarce learning of polymer properties | Nature Computational Science

Vision-R1: Redefining Reinforcement Learning for Large Vision-Language Models - MarkTechPost

Literature Review] Offset Unlearning for Large Language Models

Rethinking LLM Memorization – Machine Learning Blog | ML@CMU | Carnegie Mellon University

Trustworthy LLM and an Unlearning Approach

A General Framework to Enhance Fine-tuning-based LLM Unlearning

PDF] RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models | Semantic Scholar

Large Language Models for Recommendation: Progresses and Future Direction

Major LLMs Have the Capability to Pursue Hidden Goals, Researchers Find - InfoQ

Machine Unlearning for Trustworthy AI: A Systematic Review of Techniques, Challenges, and Applications | Archives of Computational Methods in Engineering | Springer Nature Link

AI Blogs | AI Insights | AI Trends | AI Articles | AI News

PDF) SoK: Machine Unlearning for Large Language Models

Detecting Pretraining Data from Large Language Models

Machine Unlearning for Trustworthy AI: A Systematic Review of Techniques, Challenges, and Applications | Archives of Computational Methods in Engineering | Springer Nature Link

Machine Unlearning in Large Language Models: A Comprehensive Survey with Empirical Insights from the Qwen 1.5 1.8B Model — LessWrong

PDF) Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models

PDF] Rethinking machine unlearning for large language models | Semantic Scholar

MITIGATING MEMORIZATION IN LANGUAGE MODELS

Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling (Shanghai AI Laboratory, February 2025) Paper: [https://arxiv.org/abs/2502.06703](https://arxiv.org/abs/2502.06703) Abstract:

Rethinking Entity-level Unlearning for Large Language Models | AI Research Paper Details

🚨 Important + fun collaboration on this new position paper ➡️➡️

Learn to Forget: Machine Unlearning via Neuron Masking

Literature Review] Editing as Unlearning: Are Knowledge Editing Methods Strong Baselines for Large Language Model Unlearning?

PDF) The gains do not make up for the losses: a comprehensive evaluation for safety alignment of large language models via machine unlearning

Can LLMs Unlearn? Part 4: The Technical Complexity of it All (continued)

A Survey of Machine Unlearning Author Published Journal Title Version DOI Rights statement Downloaded from Funder(s) Grant ident

Efficient Knowledge Graph Unlearning with Zeroth-order Information | Proceedings of the 34th ACM International Conference on Information and Knowledge Management

Scrub-and-Learn: Category-Aware Weight Modification for Machine Unlearning

Jeena NLP Project | PDF | Cognitive Science

Innovative Approaches in Machine Unlearning: Insights and Breakthroughs from the first NeurIPS Unlearning Competition on Efficient Data Erasure - MarkTechPost

论文评述] Rethinking Machine Unlearning in Image Generation Models

A General Framework to Enhance Fine-tuning-based LLM Unlearning

论文评述] Machine Unlearning in Large Language Models

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