MAGE builds a memory graph from a user anchor to generate its own supervision signals for corpus-free unlearning, matching the effectiveness of methods that use external reference data on TOFU and RWKU benchmarks.
lower Prob/ROUGE, higher TruthRatio
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
From Anchors to Supervision: Memory-Graph Guided Corpus-Free Unlearning for Large Language Models
MAGE builds a memory graph from a user anchor to generate its own supervision signals for corpus-free unlearning, matching the effectiveness of methods that use external reference data on TOFU and RWKU benchmarks.