Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding
Comments EMNLP Industry Track 2022
期刊&会议
Conference on Empirical Methods in Natural Language Processing · 会议 · Natural Language Processing
Comments EMNLP Industry Track 2022
Comments EMNLP 2022 Demo Track
Comments In publication at the First Workshop on Fact Extraction and Verification (FeVer) at EMNLP 2018
Comments EMNLP 2021 main conference
Comments Accepted by EMNLP 2021 main conference
Comments EMNLP 2018 camera ready
Comments Revision to EMNLP 2021 camera-ready; corrects simulatability terminology and clarifies computation of rationale quality metric (no results changed). For a detailed explanation of changes, see https://github.com/allenai/label_rationale_association
Comments This paper originally appeared in a NeurIPS Workshop in 2018: IRASL - Interpretability and Robustness in Audio, Speech, and Language. It builds on a shorter paper that appeared in the Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP). See acknowledgements for details
Comments Accepted at Findings of EMNLP 2021; Fixed an error in Table 3 (see footnote 4); Updated Q3 in Sec. 4.2
Comments Accepted at the First Workshop on Simple and Efficient Natural Language Processing (SustaiNLP) at EMNLP 2020
Comments Findings of the Association for Computational Linguistics: EMNLP 2020
Comments Accepted for publication in Findings of EMNLP 2021
Comments EMNLP 2021, 18 pages, 22 figures
Comments Accepted as Long Paper to EMNLP 2020
Comments In Findings of EMNLP 2020
Journal ref Findings of ACL: EMNLP (2020) 1324-1334
Comments Accepted at EMNLP 2020 Main Conference
Comments Findings of EMNLP 2021(10 pages)
Comments accepted at EMNLP 2021
Comments Findings of the Association for Computational Linguistics: EMNLP 2021
Comments published in EMNLP 2021
Comments Accepted at EMNLP 2020
Comments Findings of EMNLP 2021
Comments To appear at EMNLP 2021. 15 pages, 10 figures, 7 tables
Journal ref Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp 2023-2037
Comments Accepted to EMNLP 2021. The code and pre-trained models are available at https://github.com/princeton-nlp/simcse
Comments Accepted to EMNLP 2021
Comments Accepted to Findings of EMNLP 2021
Comments EMNLP 2021 Long Paper
Comments In Findings EMNLP 2021
Comments EMNLP 2021
Journal ref Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing