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speech-question-answering

topic1 events
papersTODAY 04:00 UTC

arXiv Paper Proposes Machine Unlearning for Speech Question Answering Models

A new arXiv preprint examines how large audio-language models can be made to forget sensitive information they may have memorized during training. The work focuses on the speech question-answering setting, where such models have shown strong performance but also carry privacy risks. The authors frame machine unlearning as a way to reduce unintended retention of private data in these systems.

privacy/unlearning/audio-language-models/research