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Why Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generation.

, , , and . ACL (Findings), page 700-710. Association for Computational Linguistics, (2022)

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Will my Spoken Dialogue System be a Slow Learner ?, and . SIGDIAL Conference, page 97-101. The Association for Computer Linguistics, (2013)Learning the Parameters of Reinforcement Learning from Data for Adaptive Spoken Dialogue Systems. (Apprentissage automatique des paramètres de l'apprentissage par renforcement pour les systèmes de dialogues adaptatifs).. University of Lorraine, Nancy, France, (2016)From FiLM to Video: Multi-turn Question Answering with Multi-modal Context., , , and . CoRR, (2018)Keep Drawing It: Iterative language-based image generation and editing., , , , , , , and . CoRR, (2018)A Sequence-to-Sequence Model for User Simulation in Spoken Dialogue Systems., , and . INTERSPEECH, page 1151-1155. ISCA, (2016)Diverse Keyphrase Generation with Neural Unlikelihood Training., and . COLING, page 5271-5287. International Committee on Computational Linguistics, (2020)SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks., , and . NeurIPS, page 22667-22681. (2021)Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction., , , , , , , and . ICCV, page 10303-10311. IEEE, (2019)Score-based Inverse Reinforcement Learning., , , , and . AAMAS, page 457-465. ACM, (2016)Towards Solving Text-based Games by Producing Adaptive Action Spaces., , , and . CoRR, (2018)