LLM Unlearning with LLM Beliefs
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Kemou, Wang, Qizhou, Wang, Yue, Li, Fengpeng, Liu, Jun, Han, Bo, Zhou, Jiantao |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models
by: Li, Fengpeng, et al.
Published: (2026)
by: Li, Fengpeng, et al.
Published: (2026)
DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain
by: Li, Fengpeng, et al.
Published: (2024)
by: Li, Fengpeng, et al.
Published: (2024)
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)
Explainable LLM Unlearning Through Reasoning
by: Liao, Junfeng, et al.
Published: (2026)
by: Liao, Junfeng, et al.
Published: (2026)
$k$NNProxy: Efficient Training-Free Proxy Alignment for Black-Box Zero-Shot LLM-Generated Text Detection
by: Wong, Kahim, et al.
Published: (2026)
by: Wong, Kahim, et al.
Published: (2026)
A General Framework to Enhance Fine-tuning-based LLM Unlearning
by: Ren, Jie, et al.
Published: (2025)
by: Ren, Jie, et al.
Published: (2025)
From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium
by: Yi, Xie, et al.
Published: (2025)
by: Yi, Xie, 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)
CLUE: Conflict-guided Localization for LLM Unlearning Framework
by: Chen, Hang, et al.
Published: (2025)
by: Chen, Hang, et al.
Published: (2025)
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)
Label Smoothing Improves Gradient Ascent in LLM Unlearning
by: Pang, Zirui, et al.
Published: (2025)
by: Pang, Zirui, et al.
Published: (2025)
$\textbf{AGT$^{AO}$}$: Robust and Stabilized LLM Unlearning via Adversarial Gating Training with Adaptive Orthogonality
by: Li, Pengyu, et al.
Published: (2026)
by: Li, Pengyu, et al.
Published: (2026)
Towards Effective Evaluations and Comparisons for LLM Unlearning Methods
by: Wang, Qizhou, et al.
Published: (2024)
by: Wang, Qizhou, et al.
Published: (2024)
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)
LLM Unlearning Under the Microscope: A Full-Stack View on Methods and Metrics
by: Fan, Chongyu, et al.
Published: (2025)
by: Fan, Chongyu, et al.
Published: (2025)
LUME: LLM Unlearning with Multitask Evaluations
by: Ramakrishna, Anil, et al.
Published: (2025)
by: Ramakrishna, Anil, et al.
Published: (2025)
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning
by: Jia, Jinghan, et al.
Published: (2024)
by: Jia, Jinghan, et al.
Published: (2024)
Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
by: Yang, Puning, et al.
Published: (2025)
by: Yang, Puning, et al.
Published: (2025)
Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond
by: Wang, Qizhou, et al.
Published: (2025)
by: Wang, Qizhou, et al.
Published: (2025)
LLM Unlearning via Loss Adjustment with Only Forget Data
by: Wang, Yaxuan, et al.
Published: (2024)
by: Wang, Yaxuan, et al.
Published: (2024)
DRAGON: Guard LLM Unlearning in Context via Negative Detection and Reasoning
by: Wang, Yaxuan, et al.
Published: (2025)
by: Wang, Yaxuan, et al.
Published: (2025)
Forgetting to Forget: Attention Sink as A Gateway for Backdooring LLM Unlearning
by: Shang, Bingqi, et al.
Published: (2025)
by: Shang, Bingqi, 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)
From Belief Entrenchment to Robust Reasoning in LLM Agents
by: Oh, Jihwan, et al.
Published: (2025)
by: Oh, Jihwan, et al.
Published: (2025)
Recover-to-Forget: Gradient Reconstruction from LoRA for Efficient LLM Unlearning
by: Liu, Yezi, et al.
Published: (2025)
by: Liu, Yezi, et al.
Published: (2025)
LLM Unlearning Should Be Form-Independent
by: Ye, Xiaotian, et al.
Published: (2025)
by: Ye, Xiaotian, et al.
Published: (2025)
Reveal and Release: Iterative LLM Unlearning with Self-generated Data
by: Xie, Linxi, et al.
Published: (2025)
by: Xie, Linxi, et al.
Published: (2025)
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)
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)
LLM Unlearning Reveals a Stronger-Than-Expected Coreset Effect in Current Benchmarks
by: Pal, Soumyadeep, et al.
Published: (2025)
by: Pal, Soumyadeep, et al.
Published: (2025)
LUNE: Efficient LLM Unlearning via LoRA Fine-Tuning with Negative Examples
by: Liu, Yezi, et al.
Published: (2025)
by: Liu, Yezi, et al.
Published: (2025)
EmbedLLM: Learning Compact Representations of Large Language Models
by: Zhuang, Richard, et al.
Published: (2024)
by: Zhuang, Richard, et al.
Published: (2024)
Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning
by: Fan, Chongyu, et al.
Published: (2024)
by: Fan, Chongyu, et al.
Published: (2024)
Harnessing Uncertainty: Entropy-Modulated Policy Gradients for Long-Horizon LLM Agents
by: Wang, Jiawei, et al.
Published: (2025)
by: Wang, Jiawei, et al.
Published: (2025)
Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond
by: Fan, Chongyu, et al.
Published: (2025)
by: Fan, Chongyu, et al.
Published: (2025)
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)
Faster MoE LLM Inference for Extremely Large Models
by: Yang, Haoqi, et al.
Published: (2025)
by: Yang, Haoqi, et al.
Published: (2025)
Measuring the Depth of LLM Unlearning via Activation Patching
by: Lee, Jaeung, et al.
Published: (2026)
by: Lee, Jaeung, et al.
Published: (2026)
DuoGuard: A Two-Player RL-Driven Framework for Multilingual LLM Guardrails
by: Deng, Yihe, et al.
Published: (2025)
by: Deng, Yihe, et al.
Published: (2025)
Enhancing LLM Tool Use with High-quality Instruction Data from Knowledge Graph
by: Wang, Jingwei, et al.
Published: (2025)
by: Wang, Jingwei, et al.
Published: (2025)
Similar Items
-
AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models
by: Li, Fengpeng, et al.
Published: (2026) -
DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain
by: Li, Fengpeng, et al.
Published: (2024) -
GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs
by: Wang, Yue, et al.
Published: (2025) -
Explainable LLM Unlearning Through Reasoning
by: Liao, Junfeng, et al.
Published: (2026) -
$k$NNProxy: Efficient Training-Free Proxy Alignment for Black-Box Zero-Shot LLM-Generated Text Detection
by: Wong, Kahim, et al.
Published: (2026)