--- title: "Papers of 2019 — page 2" 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/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2019/page/2/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2019 # Papers of 2019 — page 2 480 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2019/) [1](https://md.research.elamur.ai/free/en/papers/2019/) **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/) [5](https://md.research.elamur.ai/free/en/papers/2019/page/5/) [next →](https://md.research.elamur.ai/free/en/papers/2019/page/3/) - [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 - [compare-mt: A Tool for Holistic Comparison of Language Generation Systems](https://md.research.elamur.ai/free/en/papers/neubig-2019-compare-mt-tool-holistic-comparison/) — Graham Neubig, Zi-Yi Dou, Junjie Hu, et al. · Proceedings of the 2019 Conference of the North… - [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 - [Compositional Questions Do Not Necessitate Multi-hop Reasoning](https://md.research.elamur.ai/free/en/papers/min-2019-compositional-questions-do-not-necessitate/) — Sewon Min, Eric Wallace, Sameer Singh, et al. · Proceedings of the 57th Annual Meeting of the… - [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 - [CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases](https://md.research.elamur.ai/free/en/papers/yu-2019-cosql-conversational-text-sql-challenge/) — Tao Yu, Rui Zhang, Heyang Er, et al. · Proceedings of the 2019 Conference on Empirical… - [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 Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing](https://md.research.elamur.ai/free/en/papers/schuster-2019-cross-lingual-alignment-contextual-word/) — Tal Schuster, Ori Ram, Regina Barzilay, et al. · Proceedings of the 2019 Conference of the North… - [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 - [DARTS: Dialectal Arabic Transcription System](https://md.research.elamur.ai/free/en/papers/khurana-2019-darts-dialectal-arabic-transcription-system/) — Sameer Khurana, Ahmed Ali, James Glass · arXiv:1909.12163 - [Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions](https://md.research.elamur.ai/free/en/papers/al-2019-bataineh-deep-contextualized-pairwise-semantic-similarity/) — Hesham Al-Bataineh, Wael Farhan, Ahmad Mustafa, et al. · arXiv:1909.09490 - [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 - [Discourse Relation Prediction: Revisiting Word Pairs with Convolutional Networks](https://md.research.elamur.ai/free/en/papers/varia-2019-discourse-relation-prediction-revisiting-word/) — Siddharth Varia, Christopher Hidey, Tuhin Chakrabarty · Proceedings of the 20th Annual SIGdial Meeting… - [Discourse-Aware Neural Extractive Text Summarization](https://md.research.elamur.ai/free/en/papers/xu-2019-discourse-aware-neural-extractive-text/) — Jiacheng Xu, Zhe Gan, Yu Cheng, et al. · arXiv:1910.14142 - [Disentangled Representation Learning for Non-Parallel Text Style Transfer](https://md.research.elamur.ai/free/en/papers/john-2019-disentangled-representation-learning-non-parallel/) — Vineet John, Lili Mou, Hareesh Bahuleyan, et al. · Proceedings of the 57th Annual Meeting of the… - [DisSent: Learning Sentence Representations from Explicit Discourse Relations](https://md.research.elamur.ai/free/en/papers/nie-2019-dissent-learning-sentence-representations-explicit/) — Allen Nie, Erin Bennett, Noah Goodman · Proceedings of the 57th Annual Meeting of the… - [DisSim: A Discourse-Aware Syntactic Text Simplification Framework for English and German](https://md.research.elamur.ai/free/en/papers/niklaus-2019-dissim-discourse-aware-syntactic-text/) — Christina Niklaus, Matthias Cetto, André Freitas, et al. · English - [Do NLP Models Know Numbers? Probing Numeracy in Embeddings](https://md.research.elamur.ai/free/en/papers/wallace-2019-do-nlp-models-know-numbers/) — Eric Wallace, Yizhong Wang, Sujian Li, et al. · Proceedings of the 2019 Conference on Empirical… - [Document Expansion by Query Prediction](https://md.research.elamur.ai/free/en/papers/nogueira-2019-document-expansion-query-prediction/) — Rodrigo Nogueira, Wei Yang, Jimmy Lin, et al. · arXiv:1904.08375 - [Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/belinkov-2019-don-t-take-premise-granted/) — Yonatan Belinkov, Adam Poliak, Stuart Shieber, et al. · Proceedings of the 57th Annual Meeting of the… - [DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sun-2019-dream-challenge-data-set-models/) — Kai Sun, Dian Yu, Jianshu Chen, et al. · Transactions of the Association for… - [DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs](https://md.research.elamur.ai/free/en/papers/dua-2019-drop-reading-comprehension-benchmark-requiring/) — Dheeru Dua, Yizhong Wang, Pradeep Dasigi, et al. · English - [EASSE: Easier Automatic Sentence Simplification Evaluation](https://md.research.elamur.ai/free/en/papers/manchego-2019-easse-easier-automatic-sentence-simplification/) — Fernando Alva-Manchego, Louis Martin, Carolina Scarton, et al. · Proceedings of the 2019 Conference on Empirical… - [EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks](https://md.research.elamur.ai/free/en/papers/wei-2019-eda-easy-data-augmentation-techniques/) — Jason Wei, Kai Zou · arXiv:1901.11196 - [EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing](https://md.research.elamur.ai/free/en/papers/dong-2019-editnts-neural-programmer-interpreter-model/) — Yue Dong, Zichao Li, Mehdi Rezagholizadeh, et al. · Proceedings of the 57th Annual Meeting of the… - [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/tan-2019-efficientnet-rethinking-model-scaling-convolutional/) — Mingxing Tan, Quoc V. Le · arXiv:1905.11946 · International Conference on… - [ELI5: Long Form Question Answering](https://md.research.elamur.ai/free/en/papers/fan-2019-eli5-long-form-question-answering/) — Angela Fan, Yacine Jernite, Ethan Perez, et al. · Proceedings of the 57th Annual Meeting of the… - [Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings](https://md.research.elamur.ai/free/en/papers/nguyen-2019-employing-correspondence-relations-connectives-identify/) — Linh The Nguyen, Linh Van Ngo, Khoat Than, et al. · Proceedings of the 57th Annual Meeting of the… - [Encode, Tag, Realize: High-Precision Text Editing](https://md.research.elamur.ai/free/en/papers/malmi-2019-encode-tag-realize-high-precision/) — Eric Malmi, Sebastian Krause, Sascha Rothe, et al. · arXiv:1909.01187 - [End-to-end Deep Reinforcement Learning Based Coreference Resolution](https://md.research.elamur.ai/free/en/papers/fei-2019-end-end-deep-reinforcement-learning/) — Hongliang Fei, Xu Li, Dingcheng Li, et al. · Proceedings of the 57th Annual Meeting of the… - [End-to-End Open-Domain Question Answering with BERTserini](https://md.research.elamur.ai/free/en/papers/yang-2019-end-end-open-domain-question/) — Wei Yang, Yuqing Xie, Aileen Lin, et al. · Proceedings of the 2019 Conference of the North… - [Energy and Policy Considerations for Deep Learning in NLP](https://md.research.elamur.ai/free/en/papers/strubell-2019-energy-policy-considerations-deep-learning/) — Emma Strubell, Ananya Ganesh, Andrew McCallum · Proceedings of the 57th Annual Meeting of the… - [English WordNet 2019 – An Open-Source WordNet for English](https://md.research.elamur.ai/free/en/papers/lex-2019-mccrae-english-wordnet/) — John P. McCrae, Alexandre Rademaker, Francis Bond · English - [Entity, Relation, and Event Extraction with Contextualized Span Representations](https://md.research.elamur.ai/free/en/papers/wadden-2019-entity-relation-event-extraction-contextualized/) — David Wadden, Ulme Wennberg, Yi Luan, et al. · Proceedings of the 2019 Conference on Empirical… - [Entity-Relation Extraction as Multi-Turn Question Answering](https://md.research.elamur.ai/free/en/papers/li-2019-entity-relation-extraction-as-multi/) — Xiaoya Li, Fan Yin, Zijun Sun, et al. · Proceedings of the 57th Annual Meeting of the… - [EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/ravichander-2019-equate-benchmark-evaluation-framework-quantitative/) — Abhilasha Ravichander, Aakanksha Naik, Carolyn Rose, et al. · English - [ERNIE 2.0: A Continual Pre-training Framework for Language Understanding](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-2-0-continual/) — Yu Sun, Shuohuan Wang, Yukun Li, et al. · arXiv:1907.12412 - [ERNIE: Enhanced Representation through Knowledge Integration](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-enhanced-representation-through-knowledge/) — Yu Sun, Shuohuan Wang, Yukun Li, et al. · arXiv:1904.09223 - [EusDisParser: improving an under-resourced discourse parser with cross-lingual data](https://md.research.elamur.ai/free/en/papers/iruskieta-2019-eusdisparser-improving-under-resourced-discourse/) — Mikel Iruskieta, Chloé Braud · Proceedings of the Workshop on Discourse… - [Evaluating Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/stanovsky-2019-evaluating-gender-bias-machine-translation/) — Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer · Proceedings of the 57th Annual Meeting of the… - [Evaluating Style Transfer for Text](https://md.research.elamur.ai/free/en/papers/mir-2019-evaluating-style-transfer-text/) — Remi Mir, Bjarke Felbo, Nick Obradovich, et al. · Proceedings of the 2019 Conference of the North… - [Evaluating the Underlying Gender Bias in Contextualized Word Embeddings](https://md.research.elamur.ai/free/en/papers/basta-2019-evaluating-underlying-gender-bias-contextualized/) — Christine Basta, Marta R. Costa-jussà, Noe Casas · Proceedings of the First Workshop on Gender… - [Evaluation of named entity coreference](https://md.research.elamur.ai/free/en/papers/agarwal-2019-evaluation-named-entity-coreference/) — Oshin Agarwal, Sanjay Subramanian, Ani Nenkova, et al. · Proceedings of the Second Workshop on… - [Explain Yourself! Leveraging Language Models for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/rajani-2019-explain-yourself-leveraging-language-models/) — Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, et al. · Proceedings of the 57th Annual Meeting of the… - [Exploring Author Context for Detecting Intended vs Perceived Sarcasm](https://md.research.elamur.ai/free/en/papers/oprea-2019-exploring-author-context-detecting-intended/) — Silviu Oprea, Walid Magdy · Proceedings of the 57th Annual Meeting of the… - [Exploring Pre-trained Language Models for Event Extraction and Generation](https://md.research.elamur.ai/free/en/papers/yang-2019-exploring-pre-trained-language-models/) — Sen Yang, Dawei Feng, Linbo Qiao, et al. · Proceedings of the 57th Annual Meeting of the… - [Facebook FAIR's WMT19 News Translation Task Submission](https://md.research.elamur.ai/free/en/papers/ng-2019-facebook-fair-s-wmt19-news/) — Nathan Ng, Kyra Yee, Alexei Baevski, et al. · Proceedings of the Fourth Conference on Machine… - [Factorising AMR generation through syntax](https://md.research.elamur.ai/free/en/papers/cao-2019-factorising-amr-generation-through-syntax/) — Kris Cao, Stephen Clark · Machine translation - [fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://md.research.elamur.ai/free/en/papers/ott-2019-fairseq-fast-extensible-toolkit-sequence/) — Myle Ott, Sergey Edunov, Alexei Baevski, et al. · Proceedings of the 2019 Conference of the North… - [Fast Graph Representation Learning with PyTorch Geometric](https://md.research.elamur.ai/free/en/papers/fey-2019-fast-graph-representation-learning-pytorch/) — Matthias Fey, Jan Eric Lenssen · arXiv:1903.02428 - [Few-Shot and Zero-Shot Learning for Historical Text Normalization](https://md.research.elamur.ai/free/en/papers/aclbulk-2019-bollmann-few-shot-zero-shot-learning/) — Marcel Bollmann, Natalia Korchagina, Anders Søgaard · English - [Findings of the 2019 Conference on Machine Translation (WMT19)](https://md.research.elamur.ai/free/en/papers/barrault-2019-findings-2019-conference-machine-translation/) — Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, et al. · Proceedings of the Fourth Conference on Machine… - [Findings of the WMT 2019 Biomedical Translation Shared Task: Evaluation for MEDLINE Abstracts and Biomedical Terminologies](https://md.research.elamur.ai/free/en/papers/bawden-2019-findings-wmt-2019-biomedical-translation/) — Rachel Bawden, Kevin Bretonnel Cohen, Cristian Grozea, et al. · Proceedings of the Fourth Conference on Machine… - [Findings of the WMT 2019 Shared Task on Automatic Post-Editing](https://md.research.elamur.ai/free/en/papers/chatterjee-2019-findings-wmt-2019-shared-task/) — Rajen Chatterjee, Christian Federmann, Matteo Negri, et al. · Proceedings of the Fourth Conference on Machine… - [Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions](https://md.research.elamur.ai/free/en/papers/koehn-2019-findings-wmt-2019-shared-task/) — Philipp Koehn, Francisco Guzmán, Vishrav Chaudhary, et al. · Proceedings of the Fourth Conference on Machine… - [Findings of the WMT 2019 Shared Tasks on Quality Estimation](https://md.research.elamur.ai/free/en/papers/fonseca-2019-findings-wmt-2019-shared-tasks/) — Erick Fonseca, Lisa Yankovskaya, André F. T. Martins, et al. · Proceedings of the Fourth Conference on Machine… - [Fine-Grained Analysis of Propaganda in News Articles](https://md.research.elamur.ai/free/en/papers/martino-2019-fine-grained-analysis-propaganda-news/) — Giovanni Da San Martino, Seunghak Yu, Alberto Barrón-Cedeño, et al. · Proceedings of the 2019 Conference on Empirical… - [FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP](https://md.research.elamur.ai/free/en/papers/akbik-2019-flair-easy-use-framework-state/) — Alan Akbik, Tanja Bergmann, Duncan Blythe, et al. · Proceedings of the 2019 Conference of the North… - [FlauBERT: Unsupervised Language Model Pre-training for French](https://md.research.elamur.ai/free/en/papers/le-2019-flaubert-unsupervised-language-model-pre/) — Hang Le, Loïc Vial, Jibril Frej, et al. · arXiv:1912.05372 - [FreeLB: Enhanced Adversarial Training for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/zhu-2019-freelb-enhanced-adversarial-training-natural/) — Chen Zhu, Yu Cheng, Zhe Gan, et al. · arXiv:1909.11764 - [GBI Treebanks as a Resource for New Applications](https://md.research.elamur.ai/free/en/papers/hbo-2019-wu-gbi-treebanks-resource-new-applications/) — Andi Wu · Ancient Hebrew - [GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification](https://md.research.elamur.ai/free/en/papers/zhou-2019-gear-graph-based-evidence-aggregating/) — Jie Zhou, Xu Han, Cheng Yang, et al. · Proceedings of the 57th Annual Meeting of the… - [GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialogue](https://md.research.elamur.ai/free/en/papers/quan-2019-gecor-end-end-generative-ellipsis/) — Jun Quan, Deyi Xiong, Bonnie Webber, et al. · Proceedings of the 2019 Conference on Empirical… - [Gemination and degemination in English affixation](https://md.research.elamur.ai/free/en/papers/hedia-2019-gemination-degemination-english-affixation/) — Sonia Ben Hedia · English - [Gender Bias in Contextualized Word Embeddings](https://md.research.elamur.ai/free/en/papers/zhao-2019-gender-bias-contextualized-word-embeddings/) — Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al. · Proceedings of the 2019 Conference of the North… - [Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency](https://md.research.elamur.ai/free/en/papers/ren-2019-generating-natural-language-adversarial-examples/) — Shuhuai Ren, Yihe Deng, Kun He, et al. · Proceedings of the 57th Annual Meeting of the… - [Generative Modeling by Estimating Gradients of the Data Distribution](https://md.research.elamur.ai/free/en/papers/song-2019-generative-modeling-estimating-gradients-data/) — Yang Song, Stefano Ermon · arXiv:1907.05600 - [GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge](https://md.research.elamur.ai/free/en/papers/huang-2019-glossbert-bert-word-sense-disambiguation/) — Luyao Huang, Chi Sun, Xipeng Qiu, et al. · Proceedings of the 2019 Conference on Empirical… - [GLTR: Statistical Detection and Visualization of Generated Text](https://md.research.elamur.ai/free/en/papers/gehrmann-2019-gltr-statistical-detection-visualization-generated/) — Sebastian Gehrmann, Hendrik Strobelt, Alexander M. Rush · arXiv:1906.04043 - [GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering](https://md.research.elamur.ai/free/en/papers/hudson-2019-gqa-new-dataset-real-world/) — Drew A. Hudson, Christopher D. 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