GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models
cs.LG, cs.AI, cs.CL
Submitted: 2025-06-12
Updated: 2026-10-13
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Matching-Theory-Based Multi-User Cooperative Computing Framework
- Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias
- A Topological Data Analysis of the CHIME/FRB Catalogues
- Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning
- Constraints on Sub-GeV Dark Matter--Electron Scattering from the CDEX-10 Experiment
- UNCOVERing the contribution of black holes to reionization in the JWST era
- WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
- Textbooks Are All You Need II: phi-1.5 technical report
- Counting Molecules: Python based scheme for automated enumeration and categorization of molecules in scanning tunneling microscopy images
- Distributionally Robust Receive Combining
- TOFU: A Task of Fictitious Unlearning for LLMs
- Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures
- DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform
- Training language models to follow instructions with human feedback
- Nonlinear electrodynamics for the vacuum of Dirac materials. Photon magnetic properties and radiation pressures
- A scalable estimate of the extra-sample prediction error via approximate leave-one-out
- MUSE: Machine Unlearning Six-Way Evaluation for Language Models
- Double-well Net for Image Segmentation
- LLaMA: Open and Efficient Foundation Language Models
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