Learning-Time Encoding Shapes Unlearning in LLMs
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Ruihan, Garov, Konstantin, Chaudhuri, Kamalika |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Closer Look at the Learnability of Out-of-Distribution (OOD) Detection
by: Garov, Konstantin, et al.
Published: (2025)
by: Garov, Konstantin, et al.
Published: (2025)
Can We Infer Confidential Properties of Training Data from LLMs?
by: Huang, Pengrun, et al.
Published: (2025)
by: Huang, Pengrun, et al.
Published: (2025)
Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
by: Wei, Rongzhe, et al.
Published: (2025)
by: Wei, Rongzhe, et al.
Published: (2025)
Evaluating Deep Unlearning in Large Language Models
by: Wu, Ruihan, et al.
Published: (2024)
by: Wu, Ruihan, et al.
Published: (2024)
Data Redaction from Conditional Generative Models
by: Kong, Zhifeng, et al.
Published: (2023)
by: Kong, Zhifeng, et al.
Published: (2023)
Better Membership Inference Privacy Measurement through Discrepancy
by: Wu, Ruihan, et al.
Published: (2024)
by: Wu, Ruihan, et al.
Published: (2024)
Influence-based Attributions can be Manipulated
by: Yadav, Chhavi, et al.
Published: (2024)
by: Yadav, Chhavi, et al.
Published: (2024)
How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective
by: Qiu, Xinchi, et al.
Published: (2024)
by: Qiu, Xinchi, et al.
Published: (2024)
Learn and Unlearn: Addressing Misinformation in Multilingual LLMs
by: Lu, Taiming, et al.
Published: (2024)
by: Lu, Taiming, et al.
Published: (2024)
Leverage Unlearning to Sanitize LLMs
by: Boutet, Antoine, et al.
Published: (2025)
by: Boutet, Antoine, et al.
Published: (2025)
Multilingual Amnesia: On the Transferability of Unlearning in Multilingual LLMs
by: Farashah, Alireza Dehghanpour, et al.
Published: (2026)
by: Farashah, Alireza Dehghanpour, et al.
Published: (2026)
TOFU: A Task of Fictitious Unlearning for LLMs
by: Maini, Pratyush, et al.
Published: (2024)
by: Maini, Pratyush, et al.
Published: (2024)
Privacy-Preserving Retrieval-Augmented Generation with Differential Privacy
by: Koga, Tatsuki, et al.
Published: (2024)
by: Koga, Tatsuki, et al.
Published: (2024)
Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs
by: Cha, Sungmin, et al.
Published: (2024)
by: Cha, Sungmin, et al.
Published: (2024)
GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping
by: Dahal, Chahana, et al.
Published: (2026)
by: Dahal, Chahana, et al.
Published: (2026)
GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs
by: Wang, Yue, et al.
Published: (2025)
by: Wang, Yue, et al.
Published: (2025)
Tool Unlearning for Tool-Augmented LLMs
by: Cheng, Jiali, et al.
Published: (2025)
by: Cheng, Jiali, et al.
Published: (2025)
Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs
by: Kadhe, Swanand Ravindra, et al.
Published: (2024)
by: Kadhe, Swanand Ravindra, et al.
Published: (2024)
Distribution Learning with Valid Outputs Beyond the Worst-Case
by: Rittler, Nick, et al.
Published: (2024)
by: Rittler, Nick, et al.
Published: (2024)
UCD: Unlearning in LLMs via Contrastive Decoding
by: Suriyakumar, Vinith M., et al.
Published: (2025)
by: Suriyakumar, Vinith M., et al.
Published: (2025)
Align-then-Unlearn: Embedding Alignment for LLM Unlearning
by: Spohn, Philipp, et al.
Published: (2025)
by: Spohn, Philipp, et al.
Published: (2025)
Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods
by: Doshi, Jai, et al.
Published: (2024)
by: Doshi, Jai, et al.
Published: (2024)
Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs
by: Xu, Xiaoyu, et al.
Published: (2025)
by: Xu, Xiaoyu, et al.
Published: (2025)
Extracting Unlearned Information from LLMs with Activation Steering
by: Seyitoğlu, Atakan, et al.
Published: (2024)
by: Seyitoğlu, Atakan, et al.
Published: (2024)
CURaTE: Continual Unlearning in Real Time with Ensured Preservation of LLM Knowledge
by: Bae, Seyun, et al.
Published: (2026)
by: Bae, Seyun, et al.
Published: (2026)
e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs
by: Setlur, Amrith, et al.
Published: (2025)
by: Setlur, Amrith, et al.
Published: (2025)
SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs?
by: Zhuang, Haomin, et al.
Published: (2024)
by: Zhuang, Haomin, et al.
Published: (2024)
Mechanistic Unlearning: Robust Knowledge Unlearning and Editing via Mechanistic Localization
by: Guo, Phillip, et al.
Published: (2024)
by: Guo, Phillip, et al.
Published: (2024)
Learn while Unlearn: An Iterative Unlearning Framework for Generative Language Models
by: Tang, Haoyu, et al.
Published: (2024)
by: Tang, Haoyu, et al.
Published: (2024)
Dataset Watermarking for Closed LLMs with Provable Detection
by: Huang, Pengrun, et al.
Published: (2026)
by: Huang, Pengrun, et al.
Published: (2026)
UnStar: Unlearning with Self-Taught Anti-Sample Reasoning for LLMs
by: Sinha, Yash, et al.
Published: (2024)
by: Sinha, Yash, et al.
Published: (2024)
Rotation Control Unlearning: Quantifying and Controlling Continuous Unlearning for LLM with The Cognitive Rotation Space
by: Zhang, Xiang, et al.
Published: (2025)
by: Zhang, Xiang, et al.
Published: (2025)
Can Small Language Models Learn, Unlearn, and Retain Noise Patterns?
by: Scaria, Nicy, et al.
Published: (2024)
by: Scaria, Nicy, et al.
Published: (2024)
Towards Robust Evaluation of Unlearning in LLMs via Data Transformations
by: Joshi, Abhinav, et al.
Published: (2024)
by: Joshi, Abhinav, et al.
Published: (2024)
Do LLMs Encode Functional Importance of Reasoning Tokens?
by: Singh, Janvijay, et al.
Published: (2026)
by: Singh, Janvijay, et al.
Published: (2026)
LLM Unlearning with LLM Beliefs
by: Li, Kemou, et al.
Published: (2025)
by: Li, Kemou, et al.
Published: (2025)
Déjà Vu Memorization in Vision-Language Models
by: Jayaraman, Bargav, et al.
Published: (2024)
by: Jayaraman, Bargav, et al.
Published: (2024)
Online Cascade Learning for Efficient Inference over Streams
by: Nie, Lunyiu, et al.
Published: (2024)
by: Nie, Lunyiu, et al.
Published: (2024)
SAEs $\textit{Can}$ Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs
by: Muhamed, Aashiq, et al.
Published: (2025)
by: Muhamed, Aashiq, et al.
Published: (2025)
DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy
by: Wang, Erchi, et al.
Published: (2026)
by: Wang, Erchi, et al.
Published: (2026)
Similar Items
-
A Closer Look at the Learnability of Out-of-Distribution (OOD) Detection
by: Garov, Konstantin, et al.
Published: (2025) -
Can We Infer Confidential Properties of Training Data from LLMs?
by: Huang, Pengrun, et al.
Published: (2025) -
Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
by: Wei, Rongzhe, et al.
Published: (2025) -
Evaluating Deep Unlearning in Large Language Models
by: Wu, Ruihan, et al.
Published: (2024) -
Data Redaction from Conditional Generative Models
by: Kong, Zhifeng, et al.
Published: (2023)