Copertina

DUET: Distilled LLM Unlearning from an Efficiently Contextualized Teacher

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhong, Yisheng, Yang, Zhengbang, Zhu, Zhuangdi
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Hierarchical Federated Unlearning for Large Language Models
di: Zhong, Yisheng, et al.
Pubblicazione: (2025)

Harmonizing Multi-Objective LLM Unlearning via Unified Domain Representation and Bidirectional Logit Distillation
di: Zhong, Yisheng, et al.
Pubblicazione: (2026)

CATNIP: LLM Unlearning via Calibrated and Tokenized Negative Preference Alignment
di: Yang, Zhengbang, et al.
Pubblicazione: (2026)

Distillation Robustifies Unlearning
di: Lee, Bruce W., et al.
Pubblicazione: (2025)

QuickDrop: Efficient Federated Unlearning by Integrated Dataset Distillation
di: Dhasade, Akash, et al.
Pubblicazione: (2023)

DUET: Optimize Token-Budget Allocation for Reinforcement Learning with Verifiable Rewards
di: Hu, Haoyu, et al.
Pubblicazione: (2026)

DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks
di: Chen, Zhiliang, et al.
Pubblicazione: (2025)

Agentic Unlearning: When LLM Agent Meets Machine Unlearning
di: Wang, Bin, et al.
Pubblicazione: (2026)

Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors
di: Fang, Luyang, et al.
Pubblicazione: (2026)

Orthogonal Soft Pruning for Efficient Class Unlearning
di: Gong, Qinghui, et al.
Pubblicazione: (2025)

Efficient and Robust Knowledge Distillation from A Stronger Teacher Based on Correlation Matching
di: Niu, Wenqi, et al.
Pubblicazione: (2024)

DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs
di: Mahmud, Tamim Al, et al.
Pubblicazione: (2025)

User-LLM: Efficient LLM Contextualization with User Embeddings
di: Ning, Lin, et al.
Pubblicazione: (2024)

Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
di: Yang, Puning, et al.
Pubblicazione: (2025)

CLIP-Embed-KD: Computationally Efficient Knowledge Distillation Using Embeddings as Teachers
di: Nair, Lakshmi
Pubblicazione: (2024)

Robust LLM Unlearning with MUDMAN: Meta-Unlearning with Disruption Masking And Normalization
di: Sondej, Filip, et al.
Pubblicazione: (2025)

DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching
di: Li, Guanghe, et al.
Pubblicazione: (2024)

Graph Unlearning: Efficient Node Removal in Graph Neural Networks
di: Guan, Faqian, et al.
Pubblicazione: (2025)

Efficient Knowledge Graph Unlearning with Zeroth-order Information
di: Xiao, Yang, et al.
Pubblicazione: (2025)

Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
di: Ji, Guangda, et al.
Pubblicazione: (2020)

AdaProb: Efficient Machine Unlearning via Adaptive Probability
di: Zhao, Zihao, et al.
Pubblicazione: (2024)

LLM Unlearning via Neural Activation Redirection
di: Shen, William F., et al.
Pubblicazione: (2025)

Diffusion Models for Reinforcement Learning: A Survey
di: Zhu, Zhengbang, et al.
Pubblicazione: (2023)

Unified Parameter-Efficient Unlearning for LLMs
di: Ding, Chenlu, et al.
Pubblicazione: (2024)

LLM Unlearning Without an Expert Curated Dataset
di: Zhu, Xiaoyuan, et al.
Pubblicazione: (2025)

SHRED: Retain-Set-Free Unlearning via Self-Distillation with Logit Demotion
di: Hu, Zizhao, et al.
Pubblicazione: (2026)

Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
di: Zanger, Moritz A., et al.
Pubblicazione: (2025)

DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models
di: Zhang, Shenyu, et al.
Pubblicazione: (2025)

LLM Surgery: Efficient Knowledge Unlearning and Editing in Large Language Models
di: Veldanda, Akshaj Kumar, 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)

Efficient Machine Unlearning via Influence Approximation
di: Liu, Jiawei, et al.
Pubblicazione: (2025)

ChatWise: A Strategy-Guided Chatbot for Enhancing Cognitive Support in Older Adults
di: Yang, Zhengbang, et al.
Pubblicazione: (2025)

LLM-NEO: Parameter Efficient Knowledge Distillation for Large Language Models
di: Yang, Runming, et al.
Pubblicazione: (2024)

Linear Projections of Teacher Embeddings for Few-Class Distillation
di: Loo, Noel, et al.
Pubblicazione: (2024)

Model Merging via Multi-Teacher Knowledge Distillation
di: Dalili, Seyed Arshan, et al.
Pubblicazione: (2025)

Distill-then-Replace: Efficient Task-Specific Hybrid Attention Model Construction
di: Xia, Xiaojie, et al.
Pubblicazione: (2026)

Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning
di: Gu, Renjie, et al.
Pubblicazione: (2026)

Module-Aware Parameter-Efficient Machine Unlearning on Transformers
di: Bao, Wenjie, et al.
Pubblicazione: (2025)

Teaching the Teacher: The Role of Teacher-Student Smoothness Alignment in Genetic Programming-based Symbolic Distillation
di: Dhar, Soumyadeep, et al.
Pubblicazione: (2025)

Learning beyond Teacher: Generalized On-Policy Distillation with Reward Extrapolation
di: Yang, Wenkai, et al.
Pubblicazione: (2026)