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Investigating Data Variance in Evaluations of Automatic Machine Translation Metrics.

, , , , , , and . ACL (Findings), page 150-157. Association for Computational Linguistics, (2022)

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Learning to Stop: A Simple yet Effective Approach to Urban Vision-Language Navigation., , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 699-707. Association for Computational Linguistics, (2020)Pandora: Towards General World Model with Natural Language Actions and Video States., , , , , , , , , and 3 other author(s). CoRR, (2024)Visualizing the Relationship Between Encoded Linguistic Information and Task Performance., , , , , and . ACL (Findings), page 410-422. Association for Computational Linguistics, (2022)Investigating Data Variance in Evaluations of Automatic Machine Translation Metrics., , , , , , and . ACL (Findings), page 150-157. Association for Computational Linguistics, (2022)Not All Actions Are Equal: Learning to Stop in Language-Grounded Urban Navigation., , and . ViGIL@NeurIPS, (2019)ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models., , , , and . EMNLP (Findings), page 1886-1899. Association for Computational Linguistics, (2022)Assessing Dialogue Systems with Distribution Distances., , , , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 2192-2198. Association for Computational Linguistics, (2021)