Table of Contents

• Frontmatter [doi]
• Generating Diverse Descriptions from Semantic GraphsJiuzhou Han, Daniel Beck, Trevor Cohn. 1-11 [doi]
• Neural Methodius Revisited: Do Discourse Relations Help with Pre-Trained Models Too?Aleksandre Maskharashvili, Symon Jory Stevens-Guille, Xintong Li, Michael White. 12-23 [doi]
• Exploring Input Representation Granularity for Generating Questions Satisfying Question-Answer CongruenceMadeeswaran Kannan, Haemanth Santhi Ponnusamy, Kordula De Kuthy, Lukas Stein, Detmar Meurers. 24-34 [doi]
• Towards Zero-Shot Multilingual Synthetic Question and Answer Generation for Cross-Lingual Reading ComprehensionSiamak Shakeri, Noah Constant, Mihir Kale, Linting Xue. 35-45 [doi]
• Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue SystemsCarl Strathearn, Dimitra Gkatzia. 46-47 [doi]
• Predicting Antonyms in Context using BERTAyana Niwa, Keisuke Nishiguchi, Naoaki Okazaki. 48-54 [doi]
• Examining Covert Gender Bias: A Case Study in Turkish and English Machine Translation ModelsChloe Ciora, Nur Iren, Malihe Alikhani. 55-63 [doi]
• WeaSuL: Weakly Supervised Dialogue Policy Learning: Reward Estimation for Multi-turn DialogueAnant Khandelwal. 64-75 [doi]
• Multi-Sentence Knowledge Selection in Open-Domain DialogueMihail Eric, Nicole Chartier, Behnam Hedayatnia, Karthik Gopalakrishnan, Pankaj Rajan, Yang Liu, Dilek Hakkani-Tur. 76-86 [doi]
• Self-Training for Compositional Neural NLG in Task-Oriented DialogueXintong Li, Symon Stevens-Guille, Aleksandre Maskharashvili, Michael White. 87-102 [doi]
• Generating Racing Game Commentary from Vision, Language, and Structured DataTatsuya Ishigaki, Goran Topic, Yumi Hamazono, Hiroshi Noji, Ichiro Kobayashi, Yusuke Miyao, Hiroya Takamura. 103-113 [doi]
• Explaining Decision-Tree Predictions by Addressing Potential Conflicts between Predictions and Plausible ExpectationsSameen Maruf, Ingrid Zukerman, Ehud Reiter, Gholamreza Haffari. 114-127 [doi]
• Formulating Neural Sentence Ordering as the Asymmetric Traveling Salesman ProblemVishal Keswani, Harsh Jhamtani. 128-139 [doi]
• Underreporting of errors in NLG output, and what to do about itEmiel van Miltenburg, Miruna-Adriana Clinciu, Ondrej Dusek, Dimitra Gkatzia, Stephanie Inglis, Leo Leppänen, Saad Mahamood, Emma Manning, Stephanie Schoch, Craig Thomson, Luou Wen. 140-153 [doi]
• What can Neural Referential Form Selectors Learn?Guanyi Chen, Fahime Same, Kees van Deemter. 154-166 [doi]
• HI-CMLM: Improve CMLM with Hybrid Decoder InputMinghan Wang, Jiaxin Guo, Yuxia Wang, Yimeng Chen, Chang Su, Daimeng Wei, Min Zhang, Shimin Tao, Hao Yang. 167-171 [doi]
• Using BERT for choosing classifiers in MandarinJani Järnfors, Guanyi Chen, Kees van Deemter, Rint Sybesma. 172-176 [doi]
• Enriching the E2E datasetThiago Castro Ferreira, Helena Vaz, Brian Davis, Adriana Pagano. 177-183 [doi]
• Goal-Oriented Script ConstructionQing Lyu, Li Zhang, Chris Callison-Burch. 184-200 [doi]
• Single Example Can Improve Zero-Shot Data GenerationPavel Burnyshev, Valentin Malykh, Andrey Bout, Ekaterina Artemova, Irina Piontkovskaya. 201-211 [doi]
• SAPPHIRE: Approaches for Enhanced Concept-to-Text GenerationSteven Y. Feng, Jessica Huynh, Chaitanya Prasad Narisetty, Eduard H. Hovy, Varun Gangal. 212-225 [doi]
• Contextualizing Variation in Text Style Transfer DatasetsStephanie Schoch, Wanyu Du, Yangfeng Ji. 226-239 [doi]
• Generation Challenges: Results of the Accuracy Evaluation Shared TaskCraig Thomson, Ehud Reiter. 240-248 [doi]
• The ReproGen Shared Task on Reproducibility of Human Evaluations in NLG: Overview and ResultsAnya Belz, Anastasia Shimorina, Shubham Agarwal, Ehud Reiter. 249-258 [doi]
• Text-in-Context: Token-Level Error Detection for Table-to-Text GenerationZdenek Kasner, Simon Mille, Ondrej Dusek. 259-265 [doi]
• Shared Task in Evaluating Accuracy: Leveraging Pre-Annotations in the Validation ProcessNicolas Garneau, Luc Lamontagne. 266-270 [doi]
• Automatic Verification of Data SummariesRayhane Rezgui, Mohammed Saeed 0002, Paolo Papotti. 271-275 [doi]
• Grounding NBA Matchup SummariesTadashi Nomoto. 276-281 [doi]
• Reproducing a Comparison of Hedged and Non-hedged NLG TextsSaad Mahamood. 282-285 [doi]
• Another PASS: A Reproduction Study of the Human Evaluation of a Football Report Generation SystemSimon Mille, Thiago Castro Ferreira, Anya Belz, Brian Davis. 286-292 [doi]
• A Reproduction Study of an Annotation-based Human Evaluation of MT OutputsMaja Popovic, Anya Belz. 293-300 [doi]
• TUDA-Reproducibility @ ReproGen: Replicability of Human Evaluation of Text-to-Text and Concept-to-Text GenerationChristian Richter, Yanran Chen, Steffen Eger. 301-307 [doi]
• DialogSum Challenge: Summarizing Real-Life Scenario DialoguesYulong Chen, Yang Liu, Yue Zhang. 308-313 [doi]
• Quality Evaluation of the Low-Resource Synthetically Generated Code-Mixed Hinglish TextVivek Srivastava, Mayank Singh 0001. 314-319 [doi]
• Shared Task on Feedback Comment Generation for Language LearnersRyo Nagata, Masato Hagiwara, Kazuaki Hanawa, Masato Mita, Artem Chernodub, Olena Nahorna. 320-324 [doi]
• The SelectGen Challenge: Finding the Best Training Samples for Few-Shot Neural Text GenerationErnie Chang, Xiaoyu Shen 0001, Alex Marin, Vera Demberg. 325-330 [doi]
• Affective Decoding for Empathetic Response GenerationChengkun Zheng, Guanyi Chen, Chenghua Lin, Ruizhe Li, Zhi Chen. 331-340 [doi]
• Controllable Sentence Simplification with a Unified Text-to-Text Transfer TransformerKim Cheng Sheang, Horacio Saggion. 341-352 [doi]
• SEPRG: Sentiment aware Emotion controlled Personalized Response GenerationMauajama Firdaus, Umang Jain, Asif Ekbal, Pushpak Bhattacharyya. 353-363 [doi]
• Biomedical Data-to-Text Generation via Fine-Tuning TransformersRuslan Yermakov, Nicholas Drago, Angelo Ziletti. 364-370 [doi]
• Decoding, Fast and Slow: A Case Study on Balancing Trade-Offs in Incremental, Character-level Pragmatic ReasoningSina Zarrieß, Hendrik Buschmeier, Ting Han, Simeon Schüz. 371-376 [doi]
• GraphPlan: Story Generation by Planning with Event GraphHong Chen, Raphael Shu, Hiroya Takamura, Hideki Nakayama. 377-386 [doi]
• BERT-based distractor generation for Swedish reading comprehension questions using a small-scale datasetDmytro Kalpakchi, Johan Boye. 387-403 [doi]
• Exploring Structural Encoding for Data-to-Text GenerationJoy Mahapatra, Utpal Garain. 404-415 [doi]
• Attention Is Indeed All You Need: Semantically Attention-Guided Decoding for Data-to-Text NLGJuraj Juraska, Marilyn A. Walker. 416-431 [doi]