Abstract The growing power in computing and AI promises a near-term future of human-machine teamwork. In this talk, I will present my research group’s efforts in understanding the complex dynamics of human-machine interaction and designing[…]

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Abstract Embedding text sequences is a widespread requirement in modern language understanding. Existing approaches focus largely on constant-size representations. This is problematic, as the amount of information contained in text often varies with the length[…]

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Abstract The arms race to build increasingly larger, powerful language models (LMs) in the past year has been remarkable. Yet incorporating LMs effectively into practical applications that facilitate manual workflows remains challenging. I will discuss[…]

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Abstract Large language models (LLMs) have demonstrated incredible power, but they also possess vulnerabilities that can lead to misuse and potential attacks. In this presentation, we will address two fundamental questions regarding the responsible utilization[…]

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Abstract Automated analysis of student writing has the potential to provide alternatives to selected-response questions such as multiple choice, and to enable teachers and instructors to assess students’ reasoning skills based on their long-form writing.[…]

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