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Changing the Mind of Transformers for Topically-Controllable Language Generation.

, , , and . EACL, page 2601-2611. Association for Computational Linguistics, (2021)

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Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval., , and . ICDM, page 697-702. IEEE Computer Society, (2007)Interactive Information Extraction with Constrained Conditional Random Fields., , , and . AAAI, page 412-418. AAAI Press / The MIT Press, (2004)Group and Topic Discovery from Relations and Their Attributes., , and . NIPS, page 1449-1456. (2005)Alternating Projections for Learning with Expectation Constraints., , and . UAI, page 43-50. AUAI Press, (2009)Maximum Entropy Markov Models for Information Extraction and Segmentation., , and . ICML, page 591-598. Morgan Kaufmann, (2000)Toward Conditional Models of Identity Uncertainty with Application to Proper Noun Coreference., and . IIWeb, page 79-84. (2003)Rapid development of Hindi named entity recognition using conditional random fields and feature induction., and . ACM Trans. Asian Lang. Inf. Process., 2 (3): 290-294 (2003)Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data., , and . J. Mach. Learn. Res., (2007)Efficiently Inducing Features of Conditional Random Fields. CoRR, (2012)Automatically Extracting Action Graphs from Materials Science Synthesis Procedures., , , , , , , , and . CoRR, (2017)