Saved in:
| Main Authors: | Bushipaka, Praveen, Passaro, Lucia, Cucinotta, Tommaso |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.05316 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Embracing Diversity: A Multi-Perspective Approach with Soft Labels
by: Muscato, Benedetta, et al.
Published: (2025)
by: Muscato, Benedetta, et al.
Published: (2025)
Automatic Music Transcription using Convolutional Neural Networks and Constant-Q transform
by: Telila, Yohannis, et al.
Published: (2025)
by: Telila, Yohannis, et al.
Published: (2025)
Best of mini-N in-loop Sampling: A Contextual Quality Reward Model for Reliable and Efficient Best-of-N Sampling
by: Rho, Hyung Gyu, et al.
Published: (2025)
by: Rho, Hyung Gyu, et al.
Published: (2025)
Calibration vs Decision Making: Revisiting the Reliability Paradox in Unlearned Language Models
by: Shukla, Divyaksh, et al.
Published: (2026)
by: Shukla, Divyaksh, et al.
Published: (2026)
Towards Reliable Testing of Machine Unlearning
by: Mazhar, Anna, et al.
Published: (2026)
by: Mazhar, Anna, et al.
Published: (2026)
Unlearning vs. Obfuscation: Are We Truly Removing Knowledge?
by: Sun, Guangzhi, et al.
Published: (2025)
by: Sun, Guangzhi, et al.
Published: (2025)
Agentic Unlearning: When LLM Agent Meets Machine Unlearning
by: Wang, Bin, et al.
Published: (2026)
by: Wang, Bin, et al.
Published: (2026)
A Reliable Cryptographic Framework for Empirical Machine Unlearning Evaluation
by: Tu, Yiwen, et al.
Published: (2024)
by: Tu, Yiwen, et al.
Published: (2024)
A More Practical Approach to Machine Unlearning
by: Zagardo, David
Published: (2024)
by: Zagardo, David
Published: (2024)
Towards Best Practices for Open Datasets for LLM Training
by: Baack, Stefan, et al.
Published: (2025)
by: Baack, Stefan, et al.
Published: (2025)
Unlearning Clients, Features and Samples in Vertical Federated Learning
by: Varshney, Ayush K., et al.
Published: (2025)
by: Varshney, Ayush K., et al.
Published: (2025)
LLM Unlearning via Neural Activation Redirection
by: Shen, William F., et al.
Published: (2025)
by: Shen, William F., et al.
Published: (2025)
PULSE: Practical Evaluation Scenarios for Large Multimodal Model Unlearning
by: Kawakami, Tatsuki, et al.
Published: (2025)
by: Kawakami, Tatsuki, et al.
Published: (2025)
Modular Jets for Supervised Pipelines: Diagnosing Mirage vs Identifiability
by: Sanyal, Suman
Published: (2025)
by: Sanyal, Suman
Published: (2025)
Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness
by: Wang, Cheng-Long, et al.
Published: (2025)
by: Wang, Cheng-Long, et al.
Published: (2025)
Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
by: Yang, Puning, et al.
Published: (2025)
by: Yang, Puning, et al.
Published: (2025)
Robust LLM Unlearning with MUDMAN: Meta-Unlearning with Disruption Masking And Normalization
by: Sondej, Filip, et al.
Published: (2025)
by: Sondej, Filip, et al.
Published: (2025)
Mining Intrinsic Rewards from LLM Hidden States for Efficient Best-of-N Sampling
by: Guo, Jizhou, et al.
Published: (2025)
by: Guo, Jizhou, et al.
Published: (2025)
The Unseen Threat: Residual Knowledge in Machine Unlearning under Perturbed Samples
by: Hsu, Hsiang, et al.
Published: (2026)
by: Hsu, Hsiang, et al.
Published: (2026)
DUET: Distilled LLM Unlearning from an Efficiently Contextualized Teacher
by: Zhong, Yisheng, et al.
Published: (2026)
by: Zhong, Yisheng, et al.
Published: (2026)
Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning
by: Gu, Renjie, et al.
Published: (2026)
by: Gu, Renjie, et al.
Published: (2026)
Explainable LLM Unlearning Through Reasoning
by: Liao, Junfeng, et al.
Published: (2026)
by: Liao, Junfeng, et al.
Published: (2026)
Efficient Triple Modular Redundancy for Reliability Enhancement of DNNs Using Explainable AI
by: Soroush, Kimia, et al.
Published: (2025)
by: Soroush, Kimia, et al.
Published: (2025)
MASPO: Unifying Gradient Utilization, Probability Mass, and Signal Reliability for Robust and Sample-Efficient LLM Reasoning
by: Fu, Xiaoliang, et al.
Published: (2026)
by: Fu, Xiaoliang, et al.
Published: (2026)
Adaptive-lambda Subtracted Importance Sampled Scores in Machine Unlearning for DDPMs and VAEs
by: Dini, MohammadParsa, et al.
Published: (2025)
by: Dini, MohammadParsa, et al.
Published: (2025)
BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap
by: Hu, Shengyuan, et al.
Published: (2025)
by: Hu, Shengyuan, et al.
Published: (2025)
Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning
by: Qin, Kai, et al.
Published: (2025)
by: Qin, Kai, et al.
Published: (2025)
Best-of-$\infty$ -- Asymptotic Performance of Test-Time LLM Ensembling
by: Komiyama, Junpei, et al.
Published: (2025)
by: Komiyama, Junpei, et al.
Published: (2025)
A Neuro-inspired Interpretation of Unlearning in Large Language Models through Sample-level Unlearning Difficulty
by: Feng, Xiaohua, et al.
Published: (2025)
by: Feng, Xiaohua, et al.
Published: (2025)
LLM Unlearning Without an Expert Curated Dataset
by: Zhu, Xiaoyuan, et al.
Published: (2025)
by: Zhu, Xiaoyuan, et al.
Published: (2025)
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
by: Reuel, Anka, et al.
Published: (2024)
by: Reuel, Anka, et al.
Published: (2024)
Unlearned but Not Forgotten: Data Extraction after Exact Unlearning in LLM
by: Wu, Xiaoyu, et al.
Published: (2025)
by: Wu, Xiaoyu, et al.
Published: (2025)
Multi-LLM Adaptive Conformal Inference for Reliable LLM Responses
by: Noh, Kangjun, et al.
Published: (2026)
by: Noh, Kangjun, et al.
Published: (2026)
A Modular Dataset to Demonstrate LLM Abstraction Capability
by: Atanas, Adam, et al.
Published: (2025)
by: Atanas, Adam, et al.
Published: (2025)
Deep Unlearn: Benchmarking Machine Unlearning for Image Classification
by: Cadet, Xavier F., et al.
Published: (2024)
by: Cadet, Xavier F., et al.
Published: (2024)
Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning
by: Liu, Ziwen, et al.
Published: (2026)
by: Liu, Ziwen, et al.
Published: (2026)
MPRU: Modular Projection-Redistribution Unlearning as Output Filter for Classification Pipelines
by: Peng, Minyi, et al.
Published: (2025)
by: Peng, Minyi, et al.
Published: (2025)
Exploring LLM Agents for Cleaning Tabular Machine Learning Datasets
by: Bendinelli, Tommaso, et al.
Published: (2025)
by: Bendinelli, Tommaso, et al.
Published: (2025)
Performance of Small Language Model Pretraining on FABRIC: An Empirical Study
by: Rao, Praveen
Published: (2026)
by: Rao, Praveen
Published: (2026)
DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs
by: Mahmud, Tamim Al, et al.
Published: (2025)
by: Mahmud, Tamim Al, et al.
Published: (2025)
Similar Items
-
Embracing Diversity: A Multi-Perspective Approach with Soft Labels
by: Muscato, Benedetta, et al.
Published: (2025) -
Automatic Music Transcription using Convolutional Neural Networks and Constant-Q transform
by: Telila, Yohannis, et al.
Published: (2025) -
Best of mini-N in-loop Sampling: A Contextual Quality Reward Model for Reliable and Efficient Best-of-N Sampling
by: Rho, Hyung Gyu, et al.
Published: (2025) -
Calibration vs Decision Making: Revisiting the Reliability Paradox in Unlearned Language Models
by: Shukla, Divyaksh, et al.
Published: (2026) -
Towards Reliable Testing of Machine Unlearning
by: Mazhar, Anna, et al.
Published: (2026)