AI RESEARCH
From Oracle to Noisy Context: Mitigating Contextual Exposure Bias in Speech-LLMs
arXiv CS.CL
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ArXi:2603.24034v1 Announce Type: new Contextual automatic speech recognition (ASR) with Speech-LLMs is typically trained with oracle conversation history, but relies on error-prone history at inference, causing a train-test mismatch in the context channel that we term contextual exposure bias. We propose a unified