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This work systematically assess the opportunities and limits of pseudo-labeling to adapt foundation ASR models (Whisper and Qwen3-ASR) to noisy BPC domain corpora from Baltimore and Chicago and introduces a new cross-model pseudo-labeling paradigm where one model is finetuned with pseudo-labels from the other.
The need for more nuanced privacy-preserving interventions that offer rigorous privacy guarantees without compromising factual accuracy is underscored, as model properties driving this tradeoff are investigated.
Professional communication is increasingly mediated by LLMs - but do these models serve all users equally? We show that when prompts contain linguistic features more commonly used by women (hedges, tag questions, collective reference), they systematically elicit shorter, less sophisticated, and less formal responses ac...
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