Copertina

Beyond Superficial Forgetting: Thorough Unlearning through Knowledge Density Estimation and Block Re-insertion

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Guo, Feng, Wen, Yuntao, Gao, Shen, Zhang, Junshuo, Shang, Shuo
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning
di: Chen, Jinpeng, et al.
Pubblicazione: (2025)

Re-understanding Graph Unlearning through Memorization
di: Ding, Pengfei, et al.
Pubblicazione: (2026)

Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods
di: Jang, Yeonwoo, et al.
Pubblicazione: (2025)

Forget and Explain: Transparent Verification of GNN Unlearning
di: Ahsan, Imran, et al.
Pubblicazione: (2025)

Data Unlearning Beyond Uniform Forgetting via Diffusion Time and Frequency Selection
di: Park, Jinseong, et al.
Pubblicazione: (2025)

Beyond Superficial Unlearning: Sharpness-Aware Robust Erasure of Hallucinations in Multimodal LLMs
di: Fang, Xianya, et al.
Pubblicazione: (2026)

To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models
di: Tian, Bozhong, et al.
Pubblicazione: (2024)

Don't Forget It! Conditional Sparse Autoencoder Clamping Works for Unlearning
di: Khoriaty, Matthew, et al.
Pubblicazione: (2025)

Stable Forgetting: Bounded Parameter-Efficient Unlearning in Foundation Models
di: Garg, Arpit, et al.
Pubblicazione: (2025)

Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models
di: Ranjan, Ashutosh, et al.
Pubblicazione: (2026)

Synthetic Forgetting without Access: A Few-shot Zero-glance Framework for Machine Unlearning
di: Song, Qipeng, et al.
Pubblicazione: (2025)

BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap
di: Hu, Shengyuan, et al.
Pubblicazione: (2025)

OPC: One-Point-Contraction Unlearning Toward Deep Feature Forgetting
di: Jung, Jaeheun, et al.
Pubblicazione: (2025)

Machine Unlearning using Forgetting Neural Networks
di: Hatua, Amartya, et al.
Pubblicazione: (2024)

Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning
di: Fan, Chongyu, et al.
Pubblicazione: (2024)

Surgical Knowledge Rewrite in Compact LLMs: An 'Unlearn-then-Learn' Strategy with ($IA^3$) for Localized Factual Modulation and Catastrophic Forgetting Mitigation
di: Ngugi, Stanley
Pubblicazione: (2025)

Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills
di: Wang, Changsheng, et al.
Pubblicazione: (2025)

FaLW: A Forgetting-aware Loss Reweighting for Long-tailed Unlearning
di: Yu, Liheng, et al.
Pubblicazione: (2026)

LoReUn: Data Itself Implicitly Provides Cues to Improve Machine Unlearning
di: Li, Xiang, et al.
Pubblicazione: (2025)

ACU: Analytic Continual Unlearning for Efficient and Exact Forgetting with Privacy Preservation
di: Tang, Jianheng, et al.
Pubblicazione: (2025)

LLM Unlearning via Loss Adjustment with Only Forget Data
di: Wang, Yaxuan, et al.
Pubblicazione: (2024)

Distill, Forget, Repeat: A Framework for Continual Unlearning in Text-to-Image Diffusion Models
di: George, Naveen, et al.
Pubblicazione: (2025)

Towards Mitigating Excessive Forgetting in LLM Unlearning via Entanglement-Guidance with Proxy Constraint
di: Liu, Zhihao, et al.
Pubblicazione: (2025)

Thinking Before Running! Efficient Code Generation with Thorough Exploration and Optimal Refinement
di: Zhang, Xiaoqing, et al.
Pubblicazione: (2024)

On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
di: Peng, Ze, et al.
Pubblicazione: (2025)

Forget What Matters, Keep the Rest: Selective Unlearning of Informative Tokens
di: Koh, Seunghee, et al.
Pubblicazione: (2026)

Governing AI Forgetting: Auditing for Machine Unlearning Compliance
di: Lin, Qinqi, et al.
Pubblicazione: (2026)

A Thorough Assessment of the Non-IID Data Impact in Federated Learning
di: Jimenez-Gutierrez, Daniel M., et al.
Pubblicazione: (2025)

Probing Knowledge Holes in Unlearned LLMs
di: Ko, Myeongseob, et al.
Pubblicazione: (2025)

Forgetting Any Data at Any Time: A Theoretically Certified Unlearning Framework for Vertical Federated Learning
di: Wang, Linian, et al.
Pubblicazione: (2025)

Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage
di: Rashid, Md Rafi Ur, et al.
Pubblicazione: (2024)

A Neuro-inspired Interpretation of Unlearning in Large Language Models through Sample-level Unlearning Difficulty
di: Feng, Xiaohua, et al.
Pubblicazione: (2025)

FIT to Forget: Robust Continual Unlearning for Large Language Models
di: Xu, Xiaoyu, et al.
Pubblicazione: (2026)

Logical Structure as Knowledge: Enhancing LLM Reasoning via Structured Logical Knowledge Density Estimation
di: Bi, Zhen, et al.
Pubblicazione: (2025)

Revisiting Catastrophic Forgetting in Continual Knowledge Graph Embedding
di: Pons, Gerard, et al.
Pubblicazione: (2026)

Efficient Knowledge Deletion from Trained Models through Layer-wise Partial Machine Unlearning
di: Gogineni, Vinay Chakravarthi, et al.
Pubblicazione: (2024)

Null Space Constrained Contrastive Visual Forgetting for MLLM Unlearning
di: Wang, Yuhang, et al.
Pubblicazione: (2026)

Tackling Fake Forgetting through Uncertainty Quantification
di: Shi, Yingdan, et al.
Pubblicazione: (2025)

ROKA: Robust Knowledge Unlearning against Adversaries
di: Shin, Jinmyeong, et al.
Pubblicazione: (2026)

A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
di: Kolipaka, Varshita, et al.
Pubblicazione: (2024)