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LACUNA: A Testbed for Evaluating Localization Precision for LLM Unlearning
Researchers introduce a new testbed called LACUNA that allows for the evaluation of unlearning methods at the parameter level, rather than just the output level. They find that current state-of-the-art (SOTA)…
LACUNA: A Testbed for Evaluating Localization Precision for LLM Unlearning
Researchers introduce LACUNA, a testbed that allows for direct evaluation of unlearning methods at the parameter level. LACUNA is used to assess current state-of-the-art unlearning methods and finds them to be…
LACUNA: A Testbed for Evaluating Localization Precision for LLM Unlearning
The researchers introduce a new testbed called LACUNA for evaluating the precision of post hoc removal methods (unlearning) for LLMs. The testbed focuses on injecting personal identifiable information into specific…
AI-Assisted Computational Reproducibility on the FABRIC Testbed
This paper discusses the use of an international research testbed, FABRIC, combined with a large language model (LLM) coding assistant called LoomAI, to simplify the reproduction of published experiments across various…
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