--- title: "Papers of 2019 — page 1" description: "Papers of 2019: 389 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/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2019/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2019 # Papers of 2019 — page 1 389 papers · [all years](https://md.research.elamur.ai/free/en/papers/) **1** [2](https://md.research.elamur.ai/free/en/papers/2019/page/2/) [3](https://md.research.elamur.ai/free/en/papers/2019/page/3/) [4](https://md.research.elamur.ai/free/en/papers/2019/page/4/) - [75 Languages, 1 Model: Parsing Universal Dependencies Universally](https://md.research.elamur.ai/free/en/papers/ud-2019-kondratyuk-75-languages-1-model-parsing/) — Dan Kondratyuk, Milan Straka · English - [A Comprehensive Survey on Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/wu-2019-comprehensive-survey-graph-neural-networks/) — Zonghan Wu, Shirui Pan, Fengwen Chen, et al. · arXiv:1901.00596 - [A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)](https://md.research.elamur.ai/free/en/papers/suhr-2019-corpus-reasoning-natural-language-grounded/) — Alane Suhr, Stephanie Zhou, Ally Zhang, et al. · Mova's core list - [A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation](https://md.research.elamur.ai/free/en/papers/poesio-2019-crowdsourced-corpus-multiple-judgments-disagreement/) — Massimo Poesio, Jon Chamberlain, Silviu Paun, et al. · Proceedings of the 2019 Conference of the North… - [A deep-learning framework to detect sarcasm targets](https://md.research.elamur.ai/free/en/papers/patro-2019-deep-learning-framework-detect-sarcasm/) — Jasabanta Patro, Srijan Bansal, Animesh Mukherjee · Proceedings of the 2019 Conference on Empirical… - [A Discourse Signal Annotation System for RST Trees](https://md.research.elamur.ai/free/en/papers/gessler-2019-discourse-signal-annotation-system-rst/) — Luke Gessler, Yang Liu, Amir Zeldes · English - [A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer](https://md.research.elamur.ai/free/en/papers/luo-2019-dual-reinforcement-learning-framework-unsupervised/) — Fuli Luo, Peng Li, Jie Zhou, et al. · arXiv:1905.10060 - [A general framework for information extraction using dynamic span graphs](https://md.research.elamur.ai/free/en/papers/luan-2019-general-framework-information-extraction-dynamic/) — Yi Luan, Dave Wadden, Luheng He, et al. · Proceedings of the 2019 Conference of the North… - [A Large-Scale Comparison of Historical Text Normalization Systems](https://md.research.elamur.ai/free/en/papers/bollmann-2019-large-scale-comparison-historical-text/) — Marcel Bollmann · Machine translation - [A Linguistic Reappraisal of the Biblical Hebrew Accusative](https://md.research.elamur.ai/free/en/papers/hbo-2019-boulet-linguistic-reappraisal-biblical-hebrew-accusative/) — Jacques Boulet · Ancient Hebrew - [A Modular Architecture for Unsupervised Sarcasm Generation](https://md.research.elamur.ai/free/en/papers/mishra-2019-modular-architecture-unsupervised-sarcasm-generation/) — Abhijit Mishra, Tarun Tater, Karthik Sankaranarayanan · Proceedings of the 2019 Conference on Empirical… - [A Multiscale Visualization of Attention in the Transformer Model](https://md.research.elamur.ai/free/en/papers/vig-2019-multiscale-visualization-attention-transformer-model/) — Jesse Vig · arXiv:1906.05714 - [A Partially Rule-Based Approach to AMR Generation](https://md.research.elamur.ai/free/en/papers/manning-2019-partially-rule-based-approach-amr/) — Emma Manning · Machine translation - [A Probabilistic Approach to Syntactic Variation in Biblical Hebrew](https://md.research.elamur.ai/free/en/papers/hbo-2019-bijl-probabilistic-approach-syntactic-variation-biblical/) — Etienne P. van de Bijl, Cody Kingham, Wido van Peursen, et al. · Ancient Hebrew - [A Regularization Approach for Incorporating Event Knowledge and Coreference Relations into Neural Discourse Parsing](https://md.research.elamur.ai/free/en/papers/dai-2019-regularization-approach-incorporating-event-knowledge/) — Zeyu Dai, Ruihong Huang · Proceedings of the 2019 Conference on Empirical… - [A Simple Joint Model for Improved Contextual Neural Lemmatization](https://md.research.elamur.ai/free/en/papers/ud-2019-malaviya-simple-joint-model-improved-contextual/) — Chaitanya Malaviya, Shijie Wu, Ryan Cotterell · English - [A Structural Probe for Finding Syntax in Word Representations](https://md.research.elamur.ai/free/en/papers/hewitt-2019-structural-probe-finding-syntax-word/) — John Hewitt, Christopher D. Manning · Proceedings of the 2019 Conference of the North… - [A Survey on Bias and Fairness in Machine Learning](https://md.research.elamur.ai/free/en/papers/mehrabi-2019-survey-bias-fairness-machine-learning/) — Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, et al. · arXiv:1908.09635 - [A Transformer-based approach to Irony and Sarcasm detection](https://md.research.elamur.ai/free/en/papers/potamias-2019-transformer-based-approach-irony-sarcasm/) — Rolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis · arXiv:1911.10401 - [A Unified Linear-Time Framework for Sentence-Level Discourse Parsing](https://md.research.elamur.ai/free/en/papers/lin-2019-unified-linear-time-framework-sentence/) — Xiang Lin, Shafiq Joty, Prathyusha Jwalapuram, et al. · Proceedings of the 57th Annual Meeting of the… - [Abductive Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/bhagavatula-2019-abductive-commonsense-reasoning/) — Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, et al. · English - [Acquiring Annotated Data with Cross-lingual Explicitation for Implicit Discourse Relation Classification](https://md.research.elamur.ai/free/en/papers/shi-2019-acquiring-annotated-data-cross-lingual/) — Wei Shi, Frances Yung, Vera Demberg · Proceedings of the Workshop on Discourse… - [ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering](https://md.research.elamur.ai/free/en/papers/yu-2019-activitynet-qa-dataset-understanding-complex/) — Zhou Yu, Dejing Xu, Jun Yu, et al. · arXiv:1906.02467 - [Adapting Digital Biblical Resources for Translation and Teaching: Harvesting low-hanging fruit and growing next generation resources](https://md.research.elamur.ai/free/en/papers/hbo-2019-robie-adapting-digital-biblical-resources-translation/) — Jonathan Robie · Ancient Hebrew - [Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling](https://md.research.elamur.ai/free/en/papers/acl-2019-zalmout-adversarial-multitask-learning-joint-multi/) — Nasser Zalmout, Nizar Habash · Semitic languages - [ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks](https://md.research.elamur.ai/free/en/papers/shridhar-2019-alfred-benchmark-interpreting-grounded-instructions/) — Mohit Shridhar; Jesse Thomason; Daniel Gordon; Yonatan Bisk; Winson Han; Roozbeh Mottaghi; Luke Zettlemoyer;, Dieter Fox · arXiv:1912.01734 - [Ambiguity in Explicit Discourse Connectives](https://md.research.elamur.ai/free/en/papers/webber-2019-ambiguity-explicit-discourse-connectives/) — Bonnie Webber, Rashmi Prasad, Alan Lee · Proceedings of the 13th International… - [An Arabic Dependency Treebank in the Travel Domain](https://md.research.elamur.ai/free/en/papers/langstream-2019-taji-arabic-dependency-treebank-travel-domain/) — Dima Taji, Jamila El Gizuli, Nizar Habash · Semitic languages - [An Incremental Iterated Response Model of Pragmatics](https://md.research.elamur.ai/free/en/papers/gordon-2019-incremental-iterated-response-model-pragmatics/) — Reuben Cohn-Gordon, Noah Goodman, Christopher Potts · Proceedings of the Society for Computation in… - [Analysing Mathematical Reasoning Abilities of Neural Models](https://md.research.elamur.ai/free/en/papers/saxton-2019-analysing-mathematical-reasoning-abilities-neural/) — David Saxton, Edward Grefenstette, Felix Hill, et al. · arXiv:1904.01557 - [Analysis Methods in Neural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/) — Yonatan Belinkov, James Glass · Transactions of the Association for… - [Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/) — Elena Voita, David Talbot, Fedor Moiseev, et al. · arXiv:1905.09418 - [Analyzing the Structure of Attention in a Transformer Language Model](https://md.research.elamur.ai/free/en/papers/vig-2019-analyzing-structure-attention-transformer-language/) — Jesse Vig, Yonatan Belinkov · arXiv:1906.04284 - [APE at Scale and Its Implications on MT Evaluation Biases](https://md.research.elamur.ai/free/en/papers/freitag-2019-ape-scale-its-implications-mt/) — Markus Freitag, Isaac Caswell, Scott Roy · Proceedings of the Fourth Conference on Machine… - [Apertium-fin-eng–Rule-based Shallow Machine Translation for WMT 2019 Shared Task](https://md.research.elamur.ai/free/en/papers/pirinen-2019-apertium-fin-eng-rule-based/) — Tommi A Pirinen · Machine translation - [Are Sixteen Heads Really Better than One?](https://md.research.elamur.ai/free/en/papers/michel-2019-sixteen-heads-really-better-than/) — Paul Michel, Omer Levy, Graham Neubig · arXiv:1905.10650 - [Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection](https://md.research.elamur.ai/free/en/papers/corkery-2019-are-we-there-yet-encoder/) — Maria Corkery, Yevgen Matusevych, Sharon Goldwater · English - [Argument Mining: A Survey](https://md.research.elamur.ai/free/en/papers/lawrence-2019-argument-mining-survey/) — John Lawrence, Chris Reed · Computational Linguistics - [Assessing BERT's Syntactic Abilities](https://md.research.elamur.ai/free/en/papers/goldberg-2019-assessing-bert-s-syntactic-abilities/) — Yoav Goldberg · arXiv:1901.05287 - [Attention is not Explanation](https://md.research.elamur.ai/free/en/papers/jain-2019-attention-is-not-explanation/) — Sarthak Jain, Byron C. Wallace · Proceedings of the 2019 Conference of the North… - [Attention is not not Explanation](https://md.research.elamur.ai/free/en/papers/wiegreffe-2019-attention-is-not-not-explanation/) — Sarah Wiegreffe, Yuval Pinter · Proceedings of the 2019 Conference on Empirical… - [Automatic Detection of Generated Text is Easiest when Humans are Fooled](https://md.research.elamur.ai/free/en/papers/ippolito-2019-automatic-detection-generated-text-easiest/) — Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, et al. · arXiv:1911.00650 - [Automatic Language Identification in Texts: A Survey](https://md.research.elamur.ai/free/en/papers/jauhiainen-2019-automatic-language-identification-texts/) — Tommi Jauhiainen, Marco Lui, Marcos Zampieri, et al. · Journal of Artificial Intelligence Research 65 - [Automatic Propbank Generation for Turkish](https://md.research.elamur.ai/free/en/papers/ak-2019-automatic-propbank-generation-turkish/) — Koray AK, Olcay Taner Yıldız · Proceedings of the International Conference on… - [Automating Dictionary Production: a Tagalog-English-Korean Dictionary from Scratch](https://md.research.elamur.ai/free/en/papers/baisa-2019-automating-dictionary-production/) — Vít Baisa, Marek Blahuš, Michal Cukr, et al. · eLex 2019 (Sintra), pp. 805–818 - [Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach](https://md.research.elamur.ai/free/en/papers/yin-2019-benchmarking-zero-shot-text-classification/) — Wenpeng Yin, Jamaal Hay, Dan Roth · Proceedings of the 2019 Conference on Empirical… - [BERT for Coreference Resolution: Baselines and Analysis](https://md.research.elamur.ai/free/en/papers/joshi-2019-bert-coreference-resolution-baselines-analysis/) — Mandar Joshi, Omer Levy, Luke Zettlemoyer, et al. · Proceedings of the 2019 Conference on Empirical… - [BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model](https://md.research.elamur.ai/free/en/papers/wang-2019-bert-has-mouth-must-speak/) — Alex Wang, Kyunghyun Cho · arXiv:1902.04094 - [BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/xu-2019-bert-post-training-review-reading/) — Hu Xu, Bing Liu, Lei Shu, et al. · arXiv:1904.02232 - [BERT Rediscovers the Classical NLP Pipeline](https://md.research.elamur.ai/free/en/papers/tenney-2019-bert-rediscovers-classical-nlp-pipeline/) — Ian Tenney, Dipanjan Das, Ellie Pavlick · Proceedings of the 57th Annual Meeting of the… - [BERTje: A Dutch BERT Model](https://md.research.elamur.ai/free/en/papers/de-2019-vries-bertje-dutch-bert-model/) — Wietse de Vries, Andreas van Cranenburgh, Arianna Bisazza, et al. · arXiv:1912.09582 - [Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT](https://md.research.elamur.ai/free/en/papers/wu-2019-beto-bentz-becas-surprising-cross/) — Shijie Wu, Mark Dredze · arXiv:1904.09077 - [Beyond BLEU: Training Neural Machine Translation with Semantic Similarity](https://md.research.elamur.ai/free/en/papers/wieting-2019-beyond-bleu-training-neural-machine/) — John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, et al. · Proceedings of the 57th Annual Meeting of the… - [Beyond The Wall Street Journal: Anchoring and Comparing Discourse Signals across Genres](https://md.research.elamur.ai/free/en/papers/liu-2019-beyond-wall-street-journal-anchoring/) — Yang Liu · English - [BioBERT: a pre-trained biomedical language representation model for biomedical text mining](https://md.research.elamur.ai/free/en/papers/lee-2019-biobert-pre-trained-biomedical-language/) — Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, et al. · arXiv:1901.08746 - [BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions](https://md.research.elamur.ai/free/en/papers/clark-2019-boolq-exploring-surprising-difficulty-natural/) — Christopher Clark, Kenton Lee, Ming-Wei Chang, et al. · Proceedings of the 2019 Conference of the North… - [Bridging the Gap between Training and Inference for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2019-bridging-gap-between-training-inference/) — Wen Zhang, Yang Feng, Fandong Meng, et al. · Proceedings of the 57th Annual Meeting of the… - [Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack](https://md.research.elamur.ai/free/en/papers/dinan-2019-build-it-break-it-fix/) — Emily Dinan, Samuel Humeau, Bharath Chintagunta, et al. · Proceedings of the 2019 Conference on Empirical… - [CamemBERT: a Tasty French Language Model](https://md.research.elamur.ai/free/en/papers/martin-2019-camembert-tasty-french-language-model/) — Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, et al. · arXiv:1911.03894 · Proceedings of the 58th… - [CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB](https://md.research.elamur.ai/free/en/papers/schwenk-2019-ccmatrix-mining-billions-high-quality/) — Holger Schwenk, Guillaume Wenzek, Sergey Edunov, et al. · arXiv:1911.04944 - [Certified Robustness to Adversarial Word Substitutions](https://md.research.elamur.ai/free/en/papers/jia-2019-certified-robustness-adversarial-word-substitutions/) — Robin Jia, Aditi Raghunathan, Kerem Göksel, et al. · Proceedings of the 2019 Conference on Empirical… - [Choosing Transfer Languages for Cross-Lingual Learning](https://md.research.elamur.ai/free/en/papers/lin-2019-choosing-transfer-languages-cross-lingual/) — Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, et al. · Proceedings of the 57th Annual Meeting of the… - [CITE: A Corpus of Image-Text Discourse Relations](https://md.research.elamur.ai/free/en/papers/alikhani-2019-cite-corpus-image-text-discourse/) — Malihe Alikhani, Sreyasi Nag Chowdhury, Gerard de Melo, et al. · Proceedings of the 2019 Conference of the North… - [ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission](https://md.research.elamur.ai/free/en/papers/huang-2019-clinicalbert-modeling-clinical-notes-predicting/) — Kexin Huang, Jaan Altosaar, Rajesh Ranganath · arXiv:1904.05342 - [Combating Adversarial Misspellings with Robust Word Recognition](https://md.research.elamur.ai/free/en/papers/pruthi-2019-combating-adversarial-misspellings-robust-word/) — Danish Pruthi, Bhuwan Dhingra, Zachary C. Lipton · Proceedings of the 57th Annual Meeting of the… - [COMET: Commonsense Transformers for Automatic Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/bosselut-2019-comet-commonsense-transformers-automatic-knowledge/) — Antoine Bosselut, Hannah Rashkin, Maarten Sap, et al. · Proceedings of the 57th Annual Meeting of the… - [Common Voice: A Massively-Multilingual Speech Corpus](https://md.research.elamur.ai/free/en/papers/ardila-2019-common-voice-massively-multilingual-speech/) — Rosana Ardila, Megan Branson, Kelly Davis, et al. · arXiv:1912.06670 - [Comparing Sense Categorization Between English PropBank and English WordNet](https://md.research.elamur.ai/free/en/papers/bakay-2019-comparing-sense-categorization-between-english/) — Özge Bakay, Begüm Avar, Olcay Taner Yıldız · English - [Compressive Transformers for Long-Range Sequence Modelling](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/) — Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al. · arXiv:1911.05507 - [CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech](https://md.research.elamur.ai/free/en/papers/chung-2019-conan-counter-narratives-through-nichesourcing/) — Yi-Ling Chung, Elizaveta Kuzmenko, Serra Sinem Tekiroglu, et al. · Proceedings of the 57th Annual Meeting of the… - [Concord and agreement features in Modern Standard Arabic](https://md.research.elamur.ai/free/en/papers/lingbulk-2019-winchester-concord-agreement-features-modern-standard/) — Lindley Winchester · Semitic languages - [Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word Embeddings](https://md.research.elamur.ai/free/en/papers/aclbulk-2019-kishky-constrained-sequence-sequence-semitic-root/) — Ahmed El-Kishky, Xingyu Fu, Aseel Addawood, et al. · Ancient Hebrew - [Context-aware Neural Machine Translation with Coreference Information](https://md.research.elamur.ai/free/en/papers/ohtani-2019-context-aware-neural-machine-translation/) — Takumi Ohtani, Hidetaka Kamigaito, Masaaki Nagata, et al. · Proceedings of the Fourth Workshop on Discourse… - [Controllable Paraphrase Generation with a Syntactic Exemplar](https://md.research.elamur.ai/free/en/papers/chen-2019-controllable-paraphrase-generation-syntactic-exemplar/) — Mingda Chen, Qingming Tang, Sam Wiseman, et al. · Proceedings of the 57th Annual Meeting of the… - [Controlled Semi-automatic Annotation of Classical Ethiopic](https://md.research.elamur.ai/free/en/papers/aclbulk-2019-vertan-controlled-semi-automatic-annotation-classical/) — Cristina Vertan · Semitic languages - [Conversational implicatures in English dialogue: Annotated dataset](https://md.research.elamur.ai/free/en/papers/george-2019-conversational-implicatures-english-dialogue-annotated/) — Elizabeth Jasmi George, Radhika Mamidi · English - [CoQA: A Conversational Question Answering Challenge](https://md.research.elamur.ai/free/en/papers/reddy-2019-coqa-conversational-question-answering-challenge/) — Siva Reddy, Danqi Chen, Christopher D. Manning · Research library - [Coreference Resolution with Entity Equalization](https://md.research.elamur.ai/free/en/papers/kantor-2019-coreference-resolution-entity-equalization/) — Ben Kantor, Amir Globerson · Proceedings of the 57th Annual Meeting of the… - [Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/huang-2019-cosmos-qa-machine-reading-comprehension/) — Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, et al. · English - [Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology](https://md.research.elamur.ai/free/en/papers/zmigrod-2019-counterfactual-data-augmentation-mitigating-gender/) — Ran Zmigrod, Sabrina J. Mielke, Hanna Wallach, et al. · arXiv:1906.04571 - [Cross-document coreference: An approach to capturing coreference without context](https://md.research.elamur.ai/free/en/papers/bettner-2019-cross-document-coreference-approach-capturing/) — Kristin Wright-Bettner, Martha Palmer, Guergana Savova, et al. · Proceedings of the Tenth International Workshop… - [Cross-Domain Generalization of Neural Constituency Parsers](https://md.research.elamur.ai/free/en/papers/acl-2019-fried-cross-domain-generalization-neural-constituency/) — Daniel Fried, Nikita Kitaev, Dan Klein · English - [Cross-lingual Transfer Learning for Multilingual Task Oriented Dialog](https://md.research.elamur.ai/free/en/papers/schuster-2019-cross-lingual-transfer-learning-multilingual/) — Sebastian Schuster, Sonal Gupta, Rushin Shah, et al. · Proceedings of the 2019 Conference of the North… - [Crowdsourced Hedge Term Disambiguation](https://md.research.elamur.ai/free/en/papers/ulinski-2019-crowdsourced-hedge-term-disambiguation/) — Morgan Ulinski, Julia Hirschberg · English - [Crowdsourcing Discourse Relation Annotations by a Two-Step Connective Insertion Task](https://md.research.elamur.ai/free/en/papers/yung-2019-crowdsourcing-discourse-relation-annotations-two/) — Frances Yung, Vera Demberg, Merel Scholman · Proceedings of the 13th Linguistic Annotation… - [CTRL: A Conditional Transformer Language Model for Controllable Generation](https://md.research.elamur.ai/free/en/papers/keskar-2019-ctrl-conditional-transformer-language-model/) — Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al. · arXiv:1909.05858 - [Currents in the Historical Linguistics and Linguistic Dating of the Hebrew Bible: Report on the State of Research as Reflected in Recent Major Publications](https://md.research.elamur.ai/free/en/papers/hbo-2019-rezetko-currents-historical-linguistics-linguistic-dating/) — Robert Rezetko, Ian Young · Ancient Hebrew - [Deep Cross-Lingual Coreference Resolution for Less-Resourced Languages: The Case of Basque](https://md.research.elamur.ai/free/en/papers/urbizu-2019-deep-cross-lingual-coreference-resolution/) — Gorka Urbizu, Ander Soraluze, Olatz Arregi · Proceedings of the Second Workshop on… - [Defending Against Neural Fake News](https://md.research.elamur.ai/free/en/papers/zellers-2019-defending-against-neural-fake-news/) — Rowan Zellers, Ari Holtzman, Hannah Rashkin, et al. · arXiv:1905.12616 - [Dependency Parsing for Spoken Dialog Systems](https://md.research.elamur.ai/free/en/papers/ud-2019-davidson-dependency-parsing-spoken-dialog-systems/) — Sam Davidson, Dian Yu, Zhou Yu · English - [Designing a Symbolic Intermediate Representation for Neural Surface Realization](https://md.research.elamur.ai/free/en/papers/elder-2019-designing-symbolic-intermediate-representation-neural/) — Henry Elder, Jennifer Foster, James Barry, et al. · Machine translation - [Detecting Subevents using Discourse and Narrative Features](https://md.research.elamur.ai/free/en/papers/aldawsari-2019-detecting-subevents-discourse-narrative-features/) — Mohammed Aldawsari, Mark Finlayson · Proceedings of the 57th Annual Meeting of the… - [Detecting Syntactic Change Using a Neural Part-of-Speech Tagger](https://md.research.elamur.ai/free/en/papers/merrill-2019-detecting-syntactic-change-neural-part/) — William Merrill, Gigi Stark, Robert Frank · English - [Detection of Abusive Language: the Problem of Biased Datasets](https://md.research.elamur.ai/free/en/papers/wiegand-2019-detection-abusive-language-problem-biased/) — Michael Wiegand, Josef Ruppenhofer, Thomas Kleinbauer · Proceedings of the 2019 Conference of the North… - [Dialog State Tracking: A Neural Reading Comprehension Approach](https://md.research.elamur.ai/free/en/papers/gao-2019-dialog-state-tracking-neural-reading/) — Shuyang Gao, Abhishek Sethi, Sanchit Agarwal, et al. · Proceedings of the 20th Annual SIGdial Meeting… - [DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation](https://md.research.elamur.ai/free/en/papers/zhang-2019-dialogpt-large-scale-generative-pre/) — Yizhe Zhang, Siqi Sun, Michel Galley, et al. · arXiv:1911.00536 - [Dialogue Act Classification with Context-Aware Self-Attention](https://md.research.elamur.ai/free/en/papers/raheja-2019-dialogue-act-classification-context-aware/) — Vipul Raheja, Joel Tetreault · Proceedings of the 2019 Conference of the North… - [Dialogue Natural Language Inference](https://md.research.elamur.ai/free/en/papers/welleck-2019-dialogue-natural-language-inference/) — Sean Welleck, Jason Weston, Arthur Szlam, et al. · Proceedings of the 57th Annual Meeting of the… - [DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation](https://md.research.elamur.ai/free/en/papers/ghosal-2019-dialoguegcn-graph-convolutional-neural-network/) — Deepanway Ghosal, Navonil Majumder, Soujanya Poria, et al. · Proceedings of the 2019 Conference on Empirical… - [Differentiating dislocations, topicalisation, and extraposition in Biblical Hebrew: Evidence from negation](https://md.research.elamur.ai/free/en/papers/hbo-2019-miller-naude-differentiating-dislocations-topicalisation-extraposition-biblical/) — Cynthia L. Miller-Naudé, Jacobus A. Naudé · Ancient Hebrew **1** [2](https://md.research.elamur.ai/free/en/papers/2019/page/2/) [3](https://md.research.elamur.ai/free/en/papers/2019/page/3/) [4](https://md.research.elamur.ai/free/en/papers/2019/page/4/)