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Search Challenges in Natural Language Generation with Complex Optimization Objectives, , , , и . KI - Künstliche Intelligenz, (to appear)Enhancing the Expression of Contrast in the SPaRKy Restaurant Corpus., , и . ENLG, стр. 30-39. The Association for Computer Linguistics, (2013)Disentangling the Properties of Human Evaluation Methods: A Classification System to Support Comparability, Meta-Evaluation and Reproducibility Testing., , и . INLG, стр. 183-194. Association for Computational Linguistics, (2020)Inducing clause-combining operations for natural language generation, и . Proc. of the 1st International Workshop on Data-to-Text Generation, Edinburgh, Scotland, UK, (2015)Semantic Noise Matters for Neural Natural Language Generation., , и . INLG, стр. 421-426. Association for Computational Linguistics, (2019)LOWRECORP: the Low-Resource NLG Corpus Building Challenge., , , , , , , и . INLG (Generation Challenges), стр. 1-9. Association for Computational Linguistics, (2023)What happens if you treat ordinal ratings as interval data? Human evaluations in NLP are even more under-powered than you think., и . EMNLP (1), стр. 8932-8939. Association for Computational Linguistics, (2021)From OpenCCG to AI Planning: Detecting Infeasible Edges in Sentence Generation., , , , и . COLING, стр. 1524-1534. ACL, (2016)Inducing Clause-Combining Rules: A Case Study with the SPaRKy Restaurant Corpus., и . ENLG, стр. 28-37. The Association for Computer Linguistics, (2015)OTTers: One-turn Topic Transitions for Open-Domain Dialogue., , , и . ACL/IJCNLP (1), стр. 2492-2504. Association for Computational Linguistics, (2021)