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Eat: Enhanced ASR-TTS for Self-Supervised Speech Recognition., , , , and . ICASSP, page 6753-6757. IEEE, (2021)DocAMR: Multi-Sentence AMR Representation and Evaluation., , , , , , , , , and . NAACL-HLT, page 3496-3505. Association for Computational Linguistics, (2022)X-FACTOR: A Cross-metric Evaluation of Factual Correctness in Abstractive Summarization., , , , , , , , , and 1 other author(s). EMNLP, page 7100-7110. Association for Computational Linguistics, (2022)Ensembling Graph Predictions for AMR Parsing., , , , , , , and . NeurIPS, page 8495-8505. (2021)Laziness Is a Virtue When It Comes to Compositionality in Neural Semantic Parsing., , , , , , and . ACL (1), page 8434-8448. Association for Computational Linguistics, (2023)Ensemble-Instruct: Instruction Tuning Data Generation with a Heterogeneous Mixture of LMs., , , , , , , and . EMNLP (Findings), page 12561-12571. Association for Computational Linguistics, (2023)Self-supervised Sequence-to-sequence ASR using Unpaired Speech and Text., , , , , and . CoRR, (2019)Integration of beamforming and uncertainty-of-observation techniques for robust ASR in multi-source environments., , , , , , , and . Comput. Speech Lang., 27 (3): 837-850 (2013)Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing., , , and . IEEE Trans. Speech Audio Process., 21 (5): 983-997 (2013)Learning to Transpile AMR into SPARQL., , , , , , , and . CoRR, (2021)