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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Error Correction in ASR using Sequence-to-Sequence Models ... Dutta, Samrat; Jain, Shreyansh; Maheshwari, Ayush. - : arXiv, 2022 BASE Show details 2 UDAAN -- Machine Learning based Post-Editing tool for Document Translation ... Maheshwari, Ayush; Ravindran, Ajay; Subramanian, Venkatapathy. - : arXiv, 2022 BASE Show details 3 Unsupervised Learning of Explainable Parse Trees for Improved Generalisation ... Sahay, Atul; Maheshwari, Ayush; Kumar, Ritesh. - : arXiv, 2021 BASE Show details 4 Semi-Supervised Data Programming with Subset Selection ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Maheshwari, Ayush. - : Underline Science Inc., 2021 BASE Show details 5 Rule Augmented Unsupervised Constituency Parsing ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Iyer, Rishabh; Maheshwari, Ayush. - : Underline Science Inc., 2021 BASE Show details 6 Rule Augmented Unsupervised Constituency Parsing ... Sahay, Atul; Nasery, Anshul; Maheshwari, Ayush; Ramakrishnan, Ganesh; Iyer, Rishabh. - : arXiv, 2021 Abstract: Recently, unsupervised parsing of syntactic trees has gained considerable attention. A prototypical approach to such unsupervised parsing employs reinforcement learning and auto-encoders. However, no mechanism ensures that the learnt model leverages the well-understood language grammar. We propose an approach that utilizes very generic linguistic knowledge of the language present in the form of syntactic rules, thus inducing better syntactic structures. We introduce a novel formulation that takes advantage of the syntactic grammar rules and is independent of the base system. We achieve new state-of-the-art results on two benchmarks datasets, MNLI and WSJ. The source code of the paper is available at https://github.com/anshuln/Diora_with_rules. ... : Accepted at Findings of ACL 2021. 10 Pages, 5 Tables, 2 Figures ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://arxiv.org/abs/2105.10193 https://dx.doi.org/10.48550/arxiv.2105.10193 BASE Hide details

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