--- title: "Papers of 2019 — page 5" description: "Papers of 2019: 480 papers of the Elamur Research library — what each work is about in our own words, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/papers/2019/page/5/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2019/page/5/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2019 # Papers of 2019 — page 5 480 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2019/page/4/) [1](https://md.research.elamur.ai/free/en/papers/2019/) … [4](https://md.research.elamur.ai/free/en/papers/2019/page/4/) **5** - [Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset](https://md.research.elamur.ai/free/en/papers/byrne-2019-taskmaster-1-realistic-diverse-dialog/) — Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar, et al. · Proceedings of the 2019 Conference on Empirical… - [Text Generation from Knowledge Graphs with Graph Transformers](https://md.research.elamur.ai/free/en/papers/kedziorski-2019-text-generation-knowledge-graphs-graph/) — Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, et al. · Proceedings of the 2019 Conference of the North… - [Text-Fabric: handling Biblical data with IKEA logistics](https://md.research.elamur.ai/free/en/papers/hbo-2019-roorda-text-fabric-handling-biblical-data/) — Dirk Roorda · Ancient Hebrew - [The Babylonian Talmud, the Jerusalem Talmud, and the “Quebec Talmud”: A response to the anti-Jewish attack in a “pious” Quebec newspaper”](https://md.research.elamur.ai/free/en/papers/hirschprung-2019-babylonian-talmud-jerusalem-talmud-quebec/) — Pinchas Hirschprung · Canadian Jewish Studies 27 - [The BEA-2019 Shared Task on Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/bryant-2019-bea-2019-shared-task-grammatical/) — Christopher Bryant, Mariano Felice, Øistein E. Andersen, et al. · Mova's core list - [The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives](https://md.research.elamur.ai/free/en/papers/voita-2019-bottom-up-evolution-representations-transformer/) — Elena Voita, Rico Sennrich, Ivan Titov · Proceedings of the 2019 Conference on Empirical… - [The CommitmentBank: Investigating projection in naturally occurring discourse](https://md.research.elamur.ai/free/en/papers/enprag-2019-marneffe-commitmentbank-investigating-projection-naturally/) — Marie-Catherine de Marneffe, Mandy Simons, Judith Tonhauser · English - [The discourse commitments of illocutionary reportatives](https://md.research.elamur.ai/free/en/papers/faller-2019-discourse-commitments-illocutionary-reportatives/) — Martina T Faller · English - [The DISRPT 2019 Shared Task on Elementary Discourse Unit Segmentation and Connective Detection](https://md.research.elamur.ai/free/en/papers/zeldes-2019-disrpt-2019-shared-task-elementary/) — Amir Zeldes, Debopam Das, Erick Galani Maziero, et al. · English - [The East Syriac Psalm Headings in Manuscript 18>8dt1: Manchester, John Rylands Library, Rylands Syriac Manuscript 4](https://md.research.elamur.ai/free/en/papers/rooy-2019-east-syriac-psalm-headings-manuscript/) — Herrie van Rooy · Old Testament Essays 32 - [The Effect of Translationese in Machine Translation Test Sets](https://md.research.elamur.ai/free/en/papers/zhang-2019-effect-translationese-machine-translation-test/) — Mike Zhang, Antonio Toral · Proceedings of the Fourth Conference on Machine… - [The emergence of number and syntax units in LSTM language models](https://md.research.elamur.ai/free/en/papers/lakretz-2019-emergence-number-syntax-units-lstm/) — Yair Lakretz, German Kruszewski, Theo Desbordes, et al. · Proceedings of the 2019 Conference of the North… - [The First Shared Task on Discourse Representation Structure Parsing](https://md.research.elamur.ai/free/en/papers/abzianidze-2019-first-shared-task-discourse-representation/) — Lasha Abzianidze, Rik van Noord, Hessel Haagsma, et al. · Machine translation - [The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English](https://md.research.elamur.ai/free/en/papers/guzman-2019-flores-evaluation-datasets-low-resource/) — Francisco Guzmán, Peng-Jen Chen, Myle Ott, et al. · Proceedings of the 2019 Conference on Empirical… - [The KnowRef Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/emami-2019-knowref-coreference-corpus-removing-gender/) — Ali Emami, Paul Trichelair, Adam Trischler, et al. · English - [The MADAR Shared Task on Arabic Fine-Grained Dialect Identification](https://md.research.elamur.ai/free/en/papers/bouamor-2019-madar-shared-task-arabic-fine/) — Houda Bouamor, Sabit Hassan, Nizar Habash · Proceedings of the Fourth Arabic Natural… - [The NiuTrans Machine Translation Systems for WMT19](https://md.research.elamur.ai/free/en/papers/li-2019-niutrans-machine-translation-systems-wmt19/) — Bei Li, Yinqiao Li, Chen Xu, et al. · Proceedings of the Fourth Conference on Machine… - [The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue](https://md.research.elamur.ai/free/en/papers/haber-2019-photobook-dataset-building-common-ground/) — Janosch Haber, Tim Baumgärtner, Ece Takmaz, et al. · Proceedings of the 57th Annual Meeting of the… - [The Referential Reader: A Recurrent Entity Network for Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/liu-2019-referential-reader-recurrent-entity-network/) — Fei Liu, Luke Zettlemoyer, Jacob Eisenstein · Proceedings of the 57th Annual Meeting of the… - [The Rhetorical Structure of Attribution](https://md.research.elamur.ai/free/en/papers/potter-2019-rhetorical-structure-attribution/) — Andrew Potter · Proceedings of the Workshop on Discourse… - [The Risk of Racial Bias in Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/sap-2019-risk-racial-bias-hate-speech/) — Maarten Sap, Dallas Card, Saadia Gabriel, et al. · Proceedings of the 57th Annual Meeting of the… - [The Role of Pragmatic and Discourse Context in Determining Argument Impact](https://md.research.elamur.ai/free/en/papers/durmus-2019-role-pragmatic-discourse-context-determining/) — Esin Durmus, Faisal Ladhak, Claire Cardie · Proceedings of the 2019 Conference on Empirical… - [The Second Conversational Intelligence Challenge (ConvAI2)](https://md.research.elamur.ai/free/en/papers/dinan-2019-second-conversational-intelligence-challenge-convai2/) — Emily Dinan, Varvara Logacheva, Valentin Malykh, et al. · arXiv:1902.00098 - [The syntax of comparison constructions in diachronic and dialectal perspective](https://md.research.elamur.ai/free/en/papers/jager-2019-syntax-comparison-constructions-diachronic-dialectal/) — Agnes Jäger · English - [The Unreasonable Effectiveness of Transformer Language Models in Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/alikaniotis-2019-unreasonable-effectiveness-transformer-language-models/) — Dimitris Alikaniotis, Vipul Raheja · Proceedings of the Fourteenth Workshop on… - [The Utility of Discourse Parsing Features for Predicting Argumentation Structure](https://md.research.elamur.ai/free/en/papers/hewett-2019-utility-discourse-parsing-features-predicting/) — Freya Hewett, Roshan Prakash Rane, Nina Harlacher, et al. · Proceedings of the 6th Workshop on Argument… - [The Woman Worked as a Babysitter: On Biases in Language Generation](https://md.research.elamur.ai/free/en/papers/sheng-2019-woman-worked-as-babysitter-biases/) — Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, et al. · Proceedings of the 2019 Conference on Empirical… - [Topic Tensor Network for Implicit Discourse Relation Recognition in Chinese](https://md.research.elamur.ai/free/en/papers/xu-2019-topic-tensor-network-implicit-discourse/) — Sheng Xu, Peifeng Li, Fang Kong, et al. · Proceedings of the 57th Annual Meeting of the… - [Towards a Common Aim and Framework for Tools and Research in Support of Bible Translation and Biblical Language Online Learning](https://md.research.elamur.ai/free/en/papers/hbo-2019-o-rear-towards-common-aim-framework-tools/) — Paul A. O'Rear · Ancient Hebrew - [Towards an adequate account of parataxis in Universal Dependencies](https://md.research.elamur.ai/free/en/papers/ud-2019-ahrenberg-adequate-account-parataxis-universal-dependencies/) — Lars Ahrenberg · English - [Towards Debiasing Fact Verification Models](https://md.research.elamur.ai/free/en/papers/schuster-2019-debiasing-fact-verification-models/) — Tal Schuster, Darsh Shah, Yun Jie Serene Yeo, et al. · Proceedings of the 2019 Conference on Empirical… - [Towards Handling Verb Phrase Ellipsis in English-Hindi Machine Translation](https://md.research.elamur.ai/free/en/papers/bafna-2019-handling-verb-phrase-ellipsis-english/) — Niyati Bafna, Dipti Sharma · Proceedings of the 16th International… - [Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)](https://md.research.elamur.ai/free/en/papers/castro-2019-towards-multimodal-sarcasm-detection-obviously/) — Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al. · arXiv:1906.01815 - [Towards Universal Dialogue Act Tagging for Task-Oriented Dialogues](https://md.research.elamur.ai/free/en/papers/paul-2019-towards-universal-dialogue-act-tagging/) — Shachi Paul, Rahul Goel, Dilek Hakkani-Tur · English - [Training Neural Machine Translation to Apply Terminology Constraints](https://md.research.elamur.ai/free/en/papers/dinu-2019-training-neural-machine-translation-apply/) — Georgiana Dinu, Prashant Mathur, Marcello Federico, et al. · Proceedings of the 57th Annual Meeting of the… - [Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets](https://md.research.elamur.ai/free/en/papers/peng-2019-transfer-learning-biomedical-natural-language/) — Yifan Peng, Shankai Yan, Zhiyong Lu · Proceedings of the 18th BioNLP Workshop and… - [Transfer Learning in Natural Language Processing](https://md.research.elamur.ai/free/en/papers/ruder-2019-transfer-learning-natural-language-processing/) — Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, et al. · Proceedings of the 2019 Conference of the North… - [Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/) — Philippe Tillet, H. T. Kung, David Cox · MAPL 2019 - [TuckER: Tensor Factorization for Knowledge Graph Completion](https://md.research.elamur.ai/free/en/papers/balazevic-2019-tucker-tensor-factorization-knowledge-graph/) — Ivana Balažević, Carl Allen, Timothy M. Hospedales · arXiv:1901.09590 - [Tuning Multilingual Transformers for Language-Specific Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/arkhipov-2019-tuning-multilingual-transformers-language-specific/) — Mikhail Arkhipov, Maria Trofimova, Yuri Kuratov, et al. · Proceedings of the 7th Workshop on Balto-Slavic… - [Tweet Stance Detection Using an Attention based Neural Ensemble Model](https://md.research.elamur.ai/free/en/papers/siddiqua-2019-tweet-stance-detection-attention-based/) — Umme Aymun Siddiqua, Abu Nowshed Chy, Masaki Aono · Proceedings of the 2019 Conference of the North… - [Tyndale STEPBible Data development for machine analysis and computational linguistics](https://md.research.elamur.ai/free/en/papers/hbo-2019-instone-brewer-tyndale-stepbible-data-development-machine/) — David Instone-Brewer · Ancient Hebrew - [Un corpus arboré pour le français : le French Treebank A parsed corpus for French: the French treebank](https://md.research.elamur.ai/free/en/papers/abeille-2019-un-corpus-arbore-pour-le/) — Anne Abeillé, Lionel Clément, Loïc Liégeois · Research library - [Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks](https://md.research.elamur.ai/free/en/papers/huang-2019-unicoder-universal-language-encoder-pre/) — Haoyang Huang, Yaobo Liang, Nan Duan, et al. · Proceedings of the 2019 Conference on Empirical… - [Unified Language Model Pre-training for Natural Language Understanding and Generation](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/) — Li Dong, Nan Yang, Wenhui Wang, et al. · arXiv:1905.03197 - [UNITER: UNiversal Image-TExt Representation Learning](https://md.research.elamur.ai/free/en/papers/chen-2019-uniter-universal-image-text-representation/) — Yen-Chun Chen, Linjie Li, Licheng Yu, et al. · arXiv:1909.11740 - [Universal dependencies for Scottish Gaelic: syntax](https://md.research.elamur.ai/free/en/papers/batchelor-2019-universal-dependencies-scottish-gaelic-syntax/) — Colin Batchelor · Proceedings of the Celtic Language Technology… - [Universal Dependencies in a galaxy far, far away... What makes Yoda's English truly alien](https://md.research.elamur.ai/free/en/papers/ud-2019-levshina-universal-dependencies-galaxy-far-far/) — Natalia Levshina · English - [Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual](https://md.research.elamur.ai/free/en/papers/he-2019-unlearn-dataset-bias-natural-language/) — He He, Sheng Zha, Haohan Wang · Proceedings of the 2nd Workshop on Deep… - [Unrestricted Original Language Resources](https://md.research.elamur.ai/free/en/papers/hbo-2019-griffin-unrestricted-original-language-resources/) — Jesse A. Griffin, Todd L. Price · Ancient Hebrew - [Unsupervised Data Augmentation for Consistency Training](https://md.research.elamur.ai/free/en/papers/xie-2019-unsupervised-data-augmentation-consistency-training/) — Qizhe Xie, Zihang Dai, Eduard Hovy, et al. · arXiv:1904.12848 - [Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling](https://md.research.elamur.ai/free/en/papers/han-2019-unsupervised-domain-adaptation-contextualized-embeddings/) — Xiaochuang Han, Jacob Eisenstein · Proceedings of the 2019 Conference on Empirical… - [Usage patterns in the development of Hebrew grammatical subjects](https://md.research.elamur.ai/free/en/papers/lingbulk-2019-dattner-usage-patterns-development-hebrew-grammatical/) — Elitzur Dattner, Liron Kertes, Racehli Zwilling, et al. · Modern Hebrew - [Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection](https://md.research.elamur.ai/free/en/papers/moosavi-2019-automatically-extracted-minimum-spans-disentangle/) — Nafise Sadat Moosavi, Leo Born, Massimo Poesio, et al. · English - [Using Syntax to Resolve NPE in English](https://md.research.elamur.ai/free/en/papers/aclbulk-2019-khullar-syntax-resolve-npe-english/) — Payal Khullar, Allen Antony, Manish Shrivastava · English - [Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence](https://md.research.elamur.ai/free/en/papers/sun-2019-utilizing-bert-aspect-based-sentiment/) — Chi Sun, Luyao Huang, Xipeng Qiu · Proceedings of the 2019 Conference of the North… - [Vecalign: Improved Sentence Alignment in Linear Time and Space](https://md.research.elamur.ai/free/en/papers/thompson-2019-vecalign-improved-sentence-alignment-linear/) — Brian Thompson, Philipp Koehn · Proceedings of the 2019 Conference on Empirical… - [VerbAtlas: a Novel Large-Scale Verbal Semantic Resource and Its Application to Semantic Role Labeling](https://md.research.elamur.ai/free/en/papers/fabio-2019-verbatlas-novel-large-scale-verbal/) — Andrea Di Fabio, Simone Conia, Roberto Navigli · English - [VerbNet Representations: Subevent Semantics for Transfer Verbs](https://md.research.elamur.ai/free/en/papers/brown-2019-verbnet-representations-subevent-semantics-transfer/) — Susan Windisch Brown, Julia Bonn, James Gung, et al. · English - [VideoBERT: A Joint Model for Video and Language Representation Learning](https://md.research.elamur.ai/free/en/papers/sun-2019-videobert-joint-model-video-language/) — Chen Sun, Austin Myers, Carl Vondrick, et al. · arXiv:1904.01766 - [ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks](https://md.research.elamur.ai/free/en/papers/lu-2019-vilbert-pretraining-task-agnostic-visiolinguistic/) — Jiasen Lu, Dhruv Batra, Devi Parikh, et al. · arXiv:1908.02265 - [VisualBERT: A Simple and Performant Baseline for Vision and Language](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/) — Liunian Harold Li, Mark Yatskar, Da Yin, et al. · arXiv:1908.03557 - [Visualizing and Measuring the Geometry of BERT](https://md.research.elamur.ai/free/en/papers/coenen-2019-visualizing-measuring-geometry-bert/) — Andy Coenen, Emily Reif, Ann Yuan, et al. · arXiv:1906.02715 - [VL-BERT: Pre-training of Generic Visual-Linguistic Representations](https://md.research.elamur.ai/free/en/papers/su-2019-vl-bert-pre-training-generic/) — Weijie Su, Xizhou Zhu, Yue Cao, et al. · arXiv:1908.08530 - [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://md.research.elamur.ai/free/en/papers/turc-2019-well-read-students-learn-better/) — Iulia Turc, Ming-Wei Chang, Kenton Lee, et al. · arXiv:1908.08962 - [What do you learn from context? Probing for sentence structure in contextualized word representations](https://md.research.elamur.ai/free/en/papers/tenney-2019-learn-context-probing-sentence-structure/) — Ian Tenney, Patrick Xia, Berlin Chen, et al. · arXiv:1905.06316 - [What Does BERT Learn about the Structure of Language?](https://md.research.elamur.ai/free/en/papers/jawahar-2019-what-does-bert-learn-about/) — Ganesh Jawahar, Benoît Sagot, Djamé Seddah · Proceedings of the 57th Annual Meeting of the… - [What makes a good conversation? How controllable attributes affect human judgments](https://md.research.elamur.ai/free/en/papers/see-2019-what-makes-good-conversation-how/) — Abigail See, Stephen Roller, Douwe Kiela, et al. · Proceedings of the 2019 Conference of the North… - [What You See is What You Get: Visual Pronoun Coreference Resolution in Dialogues](https://md.research.elamur.ai/free/en/papers/yu-2019-what-you-see-is-what/) — Xintong Yu, Hongming Zhang, Yangqiu Song, et al. · Proceedings of the 2019 Conference on Empirical… - [What's Wrong with Hebrew NLP? And How to Make it Right](https://md.research.elamur.ai/free/en/papers/aclbulk-2019-tsarfaty-what-s-wrong-hebrew-nlp/) — Reut Tsarfaty, Shoval Sadde, Stav Klein, et al. · Ancient Hebrew - [When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion](https://md.research.elamur.ai/free/en/papers/voita-2019-when-good-translation-is-wrong/) — Elena Voita, Rico Sennrich, Ivan Titov · Proceedings of the 57th Annual Meeting of the… - [WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations](https://md.research.elamur.ai/free/en/papers/pilehvar-2019-wic-word-context-dataset-evaluating/) — Mohammad Taher Pilehvar, Jose Camacho-Collados · Proceedings of the 2019 Conference of the North… - [WikiCREM: A Large Unsupervised Corpus for Coreference Resolution](https://md.research.elamur.ai/free/en/papers/kocijan-2019-wikicrem-large-unsupervised-corpus-coreference/) — Vid Kocijan, Oana-Maria Camburu, Ana-Maria Cretu, et al. · Proceedings of the 2019 Conference on Empirical… - [WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia](https://md.research.elamur.ai/free/en/papers/schwenk-2019-wikimatrix-mining-135m-parallel-sentences/) — Holger Schwenk, Vishrav Chaudhary, Shuo Sun, et al. · arXiv:1907.05791 - [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://md.research.elamur.ai/free/en/papers/yang-2019-xlnet-generalized-autoregressive-pretraining-language/) — Zhilin Yang, Zihang Dai, Yiming Yang, et al. · arXiv:1906.08237 - [YiSi - a Unified Semantic MT Quality Evaluation and Estimation Metric for Languages with Different Levels of Available Resources](https://md.research.elamur.ai/free/en/papers/lo-2019-yisi-unified-semantic-mt-quality/) — Chi-kiu Lo · Proceedings of the Fourth Conference on Machine… - [Zero-shot transfer for implicit discourse relation classification](https://md.research.elamur.ai/free/en/papers/kurfal-2019-zero-shot-transfer-implicit-discourse/) — Murathan Kurfalı, Robert Östling · Proceedings of the 20th Annual SIGdial Meeting… - [“Caption” as a Coherence Relation: Evidence and Implications](https://md.research.elamur.ai/free/en/papers/alikhani-2019-caption-as-coherence-relation-evidence/) — Malihe Alikhani, Matthew Stone · Proceedings of the Second Workshop on… - [“Transforming” Delete, Retrieve, Generate Approach for Controlled Text Style Transfer](https://md.research.elamur.ai/free/en/papers/sudhakar-2019-transforming-delete-retrieve-generate-approach/) — Akhilesh Sudhakar, Bhargav Upadhyay, Arjun Maheswaran · Proceedings of the 2019 Conference on Empirical… - [“When Numbers Matter!”: Detecting Sarcasm in Numerical Portions of Text](https://md.research.elamur.ai/free/en/papers/dubey-2019-when-numbers-matter-detecting-sarcasm/) — Abhijeet Dubey, Lakshya Kumar, Arpan Somani, et al. · Proceedings of the Tenth Workshop on… [← prev](https://md.research.elamur.ai/free/en/papers/2019/page/4/) [1](https://md.research.elamur.ai/free/en/papers/2019/) … [4](https://md.research.elamur.ai/free/en/papers/2019/page/4/) **5**