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arXiv AI By Amirhosein Javadi, Richa Dixit, Mehrdad Farajtabar, Minsik Cho, Devang Naik, Mohammad Samragh

Audio LLMs Know When They Can't Hear You

Read the original on arXiv AI →

The paper investigates whether audio large language models (Audio LLMs) can detect when their own transcriptions are unreliable. It finds that the models are poor at self-assessment and that existing methods offer limited detection. By leveraging audio-encoder representations, the authors develop a lightweight predictor that accurately flags unreliable transcriptions and can prompt user clarification without altering the underlying model.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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