To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models

George-Octavian Barbulescu; Peter Triantafillou

2024 ICML ICML 2024

To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

🧭 Keyword Pioneer - unlearning

🐣 Hot Topic Early Bird - unlearning

Authors

George-Octavian Barbulescu, Peter Triantafillou

Topics

Machine Learning > Optimization & Theory > Optimization Natural Language Processing > Resources & Methods > Large Language Models Artificial Intelligence > Core AI > Large Language Models

Keywords

adversarial attack gradient ascent task arithmetic unlearning privacy memorized data

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