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Table-to-Text Generation via Row-Aware Hierarchical Encoder.

, , , and . CCL, volume 11856 of Lecture Notes in Computer Science, page 533-544. Springer, (2019)

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Controllable Text Generation via Probability Density Estimation in the Latent Space., , , , , and . CoRR, (2022)Enhancing Content Planning for Table-to-Text Generation with Data Understanding and Verification., , , , , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 2905-2914. Association for Computational Linguistics, (2020)STOA-VLP: Spatial-Temporal Modeling of Object and Action for Video-Language Pre-training., , , , , , and . AAAI, page 3715-3723. AAAI Press, (2023)Table-to-Text Generation with Effective Hierarchical Encoder on Three Dimensions (Row, Column and Time)., , , and . EMNLP/IJCNLP (1), page 3141-3150. Association for Computational Linguistics, (2019)Improving Controllable Text Generation with Position-Aware Weighted Decoding., , , , , and . ACL (Findings), page 3449-3467. Association for Computational Linguistics, (2022)TableGPT: Few-shot Table-to-Text Generation with Table Structure Reconstruction and Content Matching., , , , , , and . COLING, page 1978-1988. International Committee on Computational Linguistics, (2020)Table-to-Text Generation via Row-Aware Hierarchical Encoder., , , and . CCL, volume 11856 of Lecture Notes in Computer Science, page 533-544. Springer, (2019)Learning to Select Bi-Aspect Information for Document-Scale Text Content Manipulation., , , , , , , and . AAAI, page 7716-7723. AAAI Press, (2020)A Distributional Lens for Multi-Aspect Controllable Text Generation., , , , , and . EMNLP, page 1023-1043. Association for Computational Linguistics, (2022)D-Swoosh: A Family of Algorithms for Generic, Distributed Entity Resolution., , , , , , and . ICDCS, page 37. IEEE Computer Society, (2007)