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Modeling Personalization in Continuous Space for Response Generation via Augmented Wasserstein Autoencoders.

, , , , , , and . EMNLP/IJCNLP (1), page 1931-1940. Association for Computational Linguistics, (2019)

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Adaptive Orthogonal Projection for Batch and Online Continual Learning., , , and . AAAI, page 6783-6791. AAAI Press, (2022)Predictive Adversarial Learning from Positive and Unlabeled Data., , , , , , and . AAAI, page 7806-7814. AAAI Press, (2021)Different Contexts Lead to Different Word Embeddings., , and . COLING, page 762-771. ACL, (2016)HRN: A Holistic Approach to One Class Learning., , , , and . NeurIPS, (2020)CMG: A Class-Mixed Generation Approach to Out-of-Distribution Detection., , , , and . ECML/PKDD (4), volume 13716 of Lecture Notes in Computer Science, page 502-518. Springer, (2022)Overcoming Catastrophic Forgetting for Continual Learning via Model Adaptation., , , , , , , and . ICLR (Poster), OpenReview.net, (2019)Transformation of Dense and Sparse Text Representations., , , , , and . COLING, page 3257-3267. International Committee on Computational Linguistics, (2020)Instruct Large Language Models to Generate Scientific Literature Survey Step by Step., , , , and . CoRR, (2024)Translation vs. Dialogue: A Comparative Analysis of Sequence-to-Sequence Modeling., , , , , and . COLING, page 4111-4122. International Committee on Computational Linguistics, (2020)BNS: Building Network Structures Dynamically for Continual Learning., , , , and . NeurIPS, page 20608-20620. (2021)