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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 Page: 1 2 Hits 1 – 20 of 21 1 Translation-based Supervision for Policy Generation in Simultaneous Neural Machine Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Alinejad, Ashkan; Sarkar, Anoop. - : Underline Science Inc., 2021 BASE Show details 2 Better Neural Machine Translation by Extracting Linguistic Information from BERT ... Shavarani, Hassan S.; Sarkar, Anoop. - : arXiv, 2021 BASE Show details 3 Pointer-based Fusion of Bilingual Lexicons into Neural Machine Translation ... Gū, Jetic; Shavarani, Hassan S.; Sarkar, Anoop. - : arXiv, 2019 BASE Show details 4 Top-down Tree Structured Decoding with Syntactic Connections for Neural Machine Translation and Parsing ... Gū, Jetic; Shavarani, Hassan S.; Sarkar, Anoop. - : arXiv, 2018 Abstract: The addition of syntax-aware decoding in Neural Machine Translation (NMT) systems requires an effective tree-structured neural network, a syntax-aware attention model and a language generation model that is sensitive to sentence structure. We exploit a top-down tree-structured model called DRNN (Doubly-Recurrent Neural Networks) first proposed by Alvarez-Melis and Jaakola (2017) to create an NMT model called Seq2DRNN that combines a sequential encoder with tree-structured decoding augmented with a syntax-aware attention model. Unlike previous approaches to syntax-based NMT which use dependency parsing models our method uses constituency parsing which we argue provides useful information for translation. In addition, we use the syntactic structure of the sentence to add new connections to the tree-structured decoder neural network (Seq2DRNN+SynC). We compare our NMT model with sequential and state of the art syntax-based NMT models and show that our model produces more fluent translations with better ... : Accepted as an EMNLP 2018 Long Paper ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1809.01854 https://arxiv.org/abs/1809.01854 BASE Hide details 5 An Easily Extensible HMM Word Aligner Gū Jetic; Bigvand Anahita Mansouri; Sarkar Anoop In: Prague Bulletin of Mathematical Linguistics , Vol 111, Iss 1, Pp 87-96 (2018) (2018) BASE Show details 6 A Python-based Interface for Wide Coverage Lexicalized Tree-adjoining Grammars Wang Ziqi; Zhang Haotian; Sarkar Anoop In: Prague Bulletin of Mathematical Linguistics , Vol 103, Iss 1, Pp 139-159 (2015) (2015) BASE Show details 7 Kriya - an end-to-end hierarchical phrase-based MT system Razmara, Majid; Sankaran, Baskaran; Sarkar, Anoop In: The Prague bulletin of mathematical linguistics. - Praha : Univ. (2012) 97, 83-98 BLLDB OLC Linguistik Show details 8 Analysis of Semi-Supervised Learning with the Yarowsky Algorithm ... Haffari, Gholam Reza; Sarkar, Anoop. - : arXiv, 2012 BASE Show details 9 Semi-supervised model adaptation for statistical machine translation Ueffing, Nicola; Sarkar, Anoop; Haffari, Gholamreza In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 21 (2007) 2, 77-94 BLLDB OLC Linguistik Show details 10 A clustering approach for the nearly unsupervised recognition of nonliteral language Birke, Julia; Sarkar, Anoop In: Association for Computational Linguistics / European Chapter. Conference of the European Chapter of the Association for Computational Linguistics. - Menlo Park, Calif. : ACL 11 (2006), 329-336 BLLDB Show details 11 D-LTAG System: Discourse Parsing with a Lexicalized Tree-Adjoining Grammar Forbes, Katherine; Miltsakaki, Eleni; Prasad, Rashmi... In: Journal of logic, language and information. - Dordrecht [u.a.] : Kluwer 12 (2003) 3, 261-280 OLC Linguistik Show details 12 Discourse and information structure Kruijff-Korbayová, Ivana (Hrsg.); Steedman, Mark (Hrsg.); Forbes-Riley, Katherine (Mitarb.)... In: Journal of logic, language and information. - Dordrecht [u.a.] : Kluwer 12 (2003) 3, 249-374 BLLDB Show details 13 Tree adjoining grammars and their application to statistical parsing Joshi, Aravind K.; Sarkar, Anoop In: Data-oriented parsing. - Stanford, Calif. : CSLI Publ. (2003), 253-281 BLLDB Show details 14 A Note on Typing Feature Structures Wintner, Shuly; Sarkar, Anoop In: Computational linguistics. - Cambridge, Mass. : MIT Press 28 (2002) 3, 389 OLC Linguistik Show details 15 A note on typing feature structures Wintner, Shuly; Sarkar, Anoop In: Computational linguistics. - Cambridge, Mass. : MIT Press 28 (2002) 3, 389-397 BLLDB Show details 16 Combining labeled and unlabeled data in statistical natural language parsing Sarkar, Anoop In: Dissertations available from ProQuest (2002) BASE Show details 17 Tree adjoining grammars : formalisms, linguistic analysis and processing Issac, Fabrice (Mitarb.); Sarkar, Anoop (Mitarb.); Joshi, Aravind K. (Mitarb.). - Stanford, Calif. : CSLI Publ., 2000 BLLDB UB Frankfurt Linguistik Show details 18 The conflict between future tense and modality : the case of "will" in English Sarkar, Anoop In: University of Pennsylvania. University of Pennsylvania working papers in linguistics. - Philadelphia, Pa. : Univ. 5 (1998) 2, 91-117 BLLDB Show details 19 Separating Dependency from Constituency in a Tree Rewriting System ... Sarkar, Anoop. - : arXiv, 1998 BASE Show details 20 The Conflict Between Future Tense and Modality: The Case of Will in English Sarkar, Anoop In: University of Pennsylvania Working Papers in Linguistics (1998) BASE Show details Page: 1 2

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