Abstract Speech communications represents a core domain for education, team problem solving, social engagement, and business interactions. The ability for Speech Technology to extract layers of knowledge and assess engagement content represents the next generation[…]

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Abstract Understanding the implications underlying a text is critical to assessing its impact, in particular the social dynamics that may result from a reading of the text. This requires endowing artificial intelligence (AI) systems with[…]

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Abstract While GPT models have shown impressive performance on summarization and open-ended text generation, it’s important to assess their abilities on more constrained text generation tasks that require significant and diverse rewritings. In this talk,[…]

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Abstract Advanced neural language models have grown ever larger and more complex, pushing forward the limits of language understanding and generation, while diminishing interpretability. The black-box nature of deep neural networks blocks humans from understanding[…]

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Abstract Biases in datasets, or unintentionally introduced spurious cues, are a common source of misspecification in machine learning. Performant models trained on such data can gender stereotype or be brittle under distribution shift.  In this[…]

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Abstract While large language models have advanced the state-of-the-art in natural language processing, these models are trained on large-scale datasets, which may include harmful information. Studies have shown that as a result, the models exhibit[…]

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