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His research focuses on building robust, context-aware dialogue systems with a focus on the machine learning theory behind these systems. He has designed theoretical ML frameworks for NLP tasks such as parsing, dialogue management, language generation, and bias mitigation. His contributions span broad topics in ML theory like Domain Generalization, PAC-Bayesian Domain Adaptation, & Multitask Learning.
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论文共 18 篇作者统计合作学者相似作者
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International Conference on Computational Linguisticspp.3538-3552, (2024)
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Conference of the European Chapter of the Association for Computational Linguisticspp.1127-1143, (2024)
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CoRR (2023)
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Conference of the Asia-Pacific Chapter of the Association for Computational Linguisticspp.30-53, (2022)
European Conference on Artificial Intelligencepp.1721-1727, (2022)
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