--- title: "Papers of 2019 — page 3" 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/page/3/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2019/page/3/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2019 # Papers of 2019 — page 3 389 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [1](https://md.research.elamur.ai/free/en/papers/2019/) [2](https://md.research.elamur.ai/free/en/papers/2019/page/2/) **3** [4](https://md.research.elamur.ai/free/en/papers/2019/page/4/) - [LXMERT: Learning Cross-Modality Encoder Representations from Transformers](https://md.research.elamur.ai/free/en/papers/tan-2019-lxmert-learning-cross-modality-encoder/) — Hao Tan, Mohit Bansal · Proceedings of the 2019 Conference on Empirical… - [Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/artetxe-2019-margin-based-parallel-corpus-mining/) — Mikel Artetxe, Holger Schwenk · Proceedings of the 57th Annual Meeting of the… - [Mask-Predict: Parallel Decoding of Conditional Masked Language Models](https://md.research.elamur.ai/free/en/papers/ghazvininejad-2019-mask-predict-parallel-decoding-conditional/) — Marjan Ghazvininejad, Omer Levy, Yinhan Liu, et al. · Proceedings of the 2019 Conference on Empirical… - [MASS: Masked Sequence to Sequence Pre-training for Language Generation](https://md.research.elamur.ai/free/en/papers/song-2019-mass-masked-sequence-sequence-pre/) — Kaitao Song, Xu Tan, Tao Qin, et al. · arXiv:1905.02450 - [Massively Multilingual Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/aharoni-2019-massively-multilingual-neural-machine-translation/) — Roee Aharoni, Melvin Johnson, Orhan Firat · arXiv:1903.00089 - [Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/) — Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al. · arXiv:1907.05019 - [Massively Multilingual Transfer for NER](https://md.research.elamur.ai/free/en/papers/rahimi-2019-massively-multilingual-transfer-ner/) — Afshin Rahimi, Yuan Li, Trevor Cohn · Proceedings of the 57th Annual Meeting of the… - [MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms](https://md.research.elamur.ai/free/en/papers/amini-2019-mathqa-interpretable-math-word-problem/) — Aida Amini, Saadia Gabriel, Shanchuan Lin, et al. · Proceedings of the 2019 Conference of the North… - [Measuring Bias in Contextualized Word Representations](https://md.research.elamur.ai/free/en/papers/kurita-2019-measuring-bias-contextualized-word-representations/) — Keita Kurita, Nidhi Vyas, Ayush Pareek, et al. · Proceedings of the First Workshop on Gender… - [Microsoft Translator at WMT 2019: Towards Large-Scale Document-Level Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/dowmunt-2019-microsoft-translator-wmt-2019-large/) — Marcin Junczys-Dowmunt · Proceedings of the Fourth Conference on Machine… - [Mining Discourse Markers for Unsupervised Sentence Representation Learning](https://md.research.elamur.ai/free/en/papers/sileo-2019-mining-discourse-markers-unsupervised-sentence/) — Damien Sileo, Tim Van De Cruys, Camille Pradel, et al. · Proceedings of the 2019 Conference of the North… - [Mitigating Gender Bias in Natural Language Processing: Literature Review](https://md.research.elamur.ai/free/en/papers/sun-2019-mitigating-gender-bias-natural-language/) — Tony Sun, Andrew Gaut, Shirlyn Tang, et al. · Proceedings of the 57th Annual Meeting of the… - [MLQA: Evaluating Cross-lingual Extractive Question Answering](https://md.research.elamur.ai/free/en/papers/lewis-2019-mlqa-evaluating-cross-lingual-extractive/) — Patrick Lewis, Barlas Oğuz, Ruty Rinott, et al. · arXiv:1910.07475 - [Modeling Global Syntactic Variation in English Using Dialect Classification](https://md.research.elamur.ai/free/en/papers/dunn-2019-modeling-global-syntactic-variation-english/) — Jonathan Dunn · English - [Momentum Contrast for Unsupervised Visual Representation Learning](https://md.research.elamur.ai/free/en/papers/he-2019-momentum-contrast-unsupervised-visual-representation/) — Kaiming He, Haoqi Fan, Yuxin Wu, et al. · arXiv:1911.05722 - [Morphologically Annotated Corpora for Seven Arabic Dialects: Taizi, Sanaani, Najdi, Jordanian, Syrian, Iraqi and Moroccan](https://md.research.elamur.ai/free/en/papers/aclbulk-2019-alshargi-morphologically-annotated-corpora-seven-arabic/) — Faisal Alshargi, Shahd Dibas, Sakhar Alkhereyf, et al. · Semitic languages - [MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance](https://md.research.elamur.ai/free/en/papers/zhao-2019-moverscore-text-generation-evaluating-contextualized/) — Wei Zhao, Maxime Peyrard, Fei Liu, et al. · Proceedings of the 2019 Conference on Empirical… - [MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension](https://md.research.elamur.ai/free/en/papers/fisch-2019-mrqa-2019-shared-task-evaluating/) — Adam Fisch, Alon Talmor, Robin Jia, et al. · Proceedings of the 2nd Workshop on Machine… - [Multi-Modal Sarcasm Detection in Twitter with Hierarchical Fusion Model](https://md.research.elamur.ai/free/en/papers/cai-2019-multi-modal-sarcasm-detection-twitter/) — Yitao Cai, Huiyu Cai, Xiaojun Wan · Proceedings of the 57th Annual Meeting of the… - [Multi-News: A Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model](https://md.research.elamur.ai/free/en/papers/fabbri-2019-multi-news-large-scale-multi/) — Alexander Fabbri, Irene Li, Tianwei She, et al. · Proceedings of the 57th Annual Meeting of the… - [Multi-Relational Script Learning for Discourse Relations](https://md.research.elamur.ai/free/en/papers/lee-2019-multi-relational-script-learning-discourse/) — I-Ta Lee, Dan Goldwasser · Proceedings of the 57th Annual Meeting of the… - [Multi-Task Deep Neural Networks for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/liu-2019-multi-task-deep-neural-networks/) — Xiaodong Liu, Pengcheng He, Weizhu Chen, et al. · Proceedings of the 57th Annual Meeting of the… - [Multi-Task Stance Detection with Sentiment and Stance Lexicons](https://md.research.elamur.ai/free/en/papers/li-2019-multi-task-stance-detection-sentiment/) — Yingjie Li, Cornelia Caragea · Proceedings of the 2019 Conference on Empirical… - [MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims](https://md.research.elamur.ai/free/en/papers/augenstein-2019-multifc-real-world-multi-domain/) — Isabelle Augenstein, Christina Lioma, Dongsheng Wang, et al. · Proceedings of the 2019 Conference on Empirical… - [Multilingual and Multi-Aspect Hate Speech Analysis](https://md.research.elamur.ai/free/en/papers/ousidhoum-2019-multilingual-multi-aspect-hate-speech/) — Nedjma Ousidhoum, Zizheng Lin, Hongming Zhang, et al. · Proceedings of the 2019 Conference on Empirical… - [Multilingual Constituency Parsing with Self-Attention and Pre-Training](https://md.research.elamur.ai/free/en/papers/kitaev-2019-multilingual-constituency-parsing-self-attention/) — Nikita Kitaev, Steven Cao, Dan Klein · Proceedings of the 57th Annual Meeting of the… - [Multilingual is not enough: BERT for Finnish](https://md.research.elamur.ai/free/en/papers/virtanen-2019-multilingual-enough-bert-finnish/) — Antti Virtanen, Jenna Kanerva, Rami Ilo, et al. · arXiv:1912.07076 - [Multimodal Transformer for Unaligned Multimodal Language Sequences](https://md.research.elamur.ai/free/en/papers/tsai-2019-multimodal-transformer-unaligned-multimodal-language/) — Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, et al. · Proceedings of the 57th Annual Meeting of the… - [MuST-C: a Multilingual Speech Translation Corpus](https://md.research.elamur.ai/free/en/papers/gangi-2019-must-c-multilingual-speech-translation/) — Mattia A. Di Gangi, Roldano Cattoni, Luisa Bentivogli, et al. · Proceedings of the 2019 Conference of the North… - [Natural Questions: A Benchmark for Question Answering Research](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2019-natural-questions-benchmark-question-answering/) — Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, et al. · Research library - [Nested Coordination in Universal Dependencies](https://md.research.elamur.ai/free/en/papers/ud-2019-przepiorkowski-nested-coordination-universal-dependencies/) — Adam Przepiórkowski, Agnieszka Patejuk · English - [Neural Arabic Text Diacritization: State of the Art Results and a Novel Approach for Machine Translation](https://md.research.elamur.ai/free/en/papers/aclbulk-2019-fadel-neural-arabic-text-diacritization-state/) — Ali Fadel, Ibraheem Tuffaha, Bara' Al-Jawarneh, et al. · Semitic languages - [Neural Coreference Resolution with Limited Lexical Context and Explicit Mention Detection for Oral French](https://md.research.elamur.ai/free/en/papers/grobol-2019-neural-coreference-resolution-limited-lexical/) — Loïc Grobol · Proceedings of the Second Workshop on… - [Neural Decipherment via Minimum-Cost Flow: From Ugaritic to Linear B](https://md.research.elamur.ai/free/en/papers/acl-2019-luo-neural-decipherment-minimum-cost-flow/) — Jiaming Luo, Yuan Cao, Regina Barzilay · Ancient Hebrew - [Neural Generative Rhetorical Structure Parsing](https://md.research.elamur.ai/free/en/papers/mabona-2019-neural-generative-rhetorical-structure-parsing/) — Amandla Mabona, Laura Rimell, Stephen Clark, et al. · Proceedings of the 2019 Conference on Empirical… - [Neural language models as psycholinguistic subjects: Representations of syntactic state](https://md.research.elamur.ai/free/en/papers/futrell-2019-neural-language-models-as-psycholinguistic/) — Richard Futrell, Ethan Wilcox, Takashi Morita, et al. · Proceedings of the 2019 Conference of the North… - [Neural Legal Judgment Prediction in English](https://md.research.elamur.ai/free/en/papers/chalkidis-2019-neural-legal-judgment-prediction-english/) — Ilias Chalkidis, Ion Androutsopoulos, Nikolaos Aletras · Proceedings of the 57th Annual Meeting of the… - [Neural Lemmatization of Multiword Expressions](https://md.research.elamur.ai/free/en/papers/lingbulk-2019-schmitt-neural-lemmatization-multiword-expressions/) — Marine Schmitt, Mathieu Constant · English - [Neural Text Generation with Unlikelihood Training](https://md.research.elamur.ai/free/en/papers/welleck-2019-neural-text-generation-unlikelihood-training/) — Sean Welleck, Ilia Kulikov, Stephen Roller, et al. · arXiv:1908.04319 - [Neural Text Summarization: A Critical Evaluation](https://md.research.elamur.ai/free/en/papers/kryscinski-2019-neural-text-summarization-critical-evaluation/) — Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, et al. · Proceedings of the 2019 Conference on Empirical… - [Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains](https://md.research.elamur.ai/free/en/papers/shi-2019-next-sentence-prediction-helps-implicit/) — Wei Shi, Vera Demberg · Proceedings of the 2019 Conference on Empirical… - [oLMpics -- On what Language Model Pre-training Captures](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/) — Alon Talmor, Yanai Elazar, Yoav Goldberg, et al. · arXiv:1912.13283 - [On Measuring Social Biases in Sentence Encoders](https://md.research.elamur.ai/free/en/papers/may-2019-measuring-social-biases-sentence-encoders/) — Chandler May, Alex Wang, Shikha Bordia, et al. · Proceedings of the 2019 Conference of the North… - [On NMT Search Errors and Model Errors: Cat Got Your Tongue?](https://md.research.elamur.ai/free/en/papers/stahlberg-2019-nmt-search-errors-model-errors/) — Felix Stahlberg, Bill Byrne · Proceedings of the 2019 Conference on Empirical… - [One Model to Learn Both: Zero Pronoun Prediction and Translation](https://md.research.elamur.ai/free/en/papers/wang-2019-one-model-learn-both-zero/) — Longyue Wang, Zhaopeng Tu, Xing Wang, et al. · Proceedings of the 2019 Conference on Empirical… - [Open Sesame: Getting inside BERT's Linguistic Knowledge](https://md.research.elamur.ai/free/en/papers/lin-2019-open-sesame-getting-inside-bert/) — Yongjie Lin, Yi Chern Tan, Robert Frank · Proceedings of the 2019 ACL Workshop… - [OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/moon-2019-opendialkg-explainable-conversational-reasoning-attention/) — Seungwhan Moon, Pararth Shah, Anuj Kumar, et al. · Proceedings of the 57th Annual Meeting of the… - [OpenKiwi: An Open Source Framework for Quality Estimation](https://md.research.elamur.ai/free/en/papers/kepler-2019-openkiwi-open-source-framework-quality/) — Fabio Kepler, Jonay Trénous, Marcos Treviso, et al. · Proceedings of the 57th Annual Meeting of the… - [Optuna: A Next-generation Hyperparameter Optimization Framework](https://md.research.elamur.ai/free/en/papers/akiba-2019-optuna-next-generation-hyperparameter-optimization/) — Takuya Akiba, Shotaro Sano, Toshihiko Yanase, et al. · arXiv:1907.10902 - [Opuscula Ugaritico-Accadico-Hebraica: Relative particles, paʿam, and Amraphel](https://md.research.elamur.ai/free/en/papers/hbo-2019-wikander-opuscula-ugaritico-accadico-hebraica-relative/) — Ola Wikander · Ancient Hebrew - [ParaCrawl: Web-scale parallel corpora for the languages of the EU](https://md.research.elamur.ai/free/en/papers/espla-2019-paracrawl-web-scale-parallel-corpora/) — Miquel Esplà, Mikel Forcada, Gema Ramírez-Sánchez, et al. · Proceedings of Machine Translation Summit XVII… - [Passage Re-ranking with BERT](https://md.research.elamur.ai/free/en/papers/nogueira-2019-passage-re-ranking-bert/) — Rodrigo Nogueira, Kyunghyun Cho · arXiv:1901.04085 - [Patient Knowledge Distillation for BERT Model Compression](https://md.research.elamur.ai/free/en/papers/sun-2019-patient-knowledge-distillation-bert-model/) — Siqi Sun, Yu Cheng, Zhe Gan, et al. · arXiv:1908.09355 - [PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification](https://md.research.elamur.ai/free/en/papers/yang-2019-paws-x-cross-lingual-adversarial/) — Yinfei Yang, Yuan Zhang, Chris Tar, et al. · arXiv:1908.11828 - [PAWS: Paraphrase Adversaries from Word Scrambling](https://md.research.elamur.ai/free/en/papers/zhang-2019-paws-paraphrase-adversaries-word-scrambling/) — Yuan Zhang, Jason Baldridge, Luheng He · Proceedings of the 2019 Conference of the North… - [Pay Less Attention with Lightweight and Dynamic Convolutions](https://md.research.elamur.ai/free/en/papers/wu-2019-pay-less-attention-lightweight-dynamic/) — Felix Wu, Angela Fan, Alexei Baevski, et al. · arXiv:1901.10430 - [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/zhang-2019-pegasus-pre-training-extracted-gap/) — Jingqing Zhang, Yao Zhao, Mohammad Saleh, et al. · arXiv:1912.08777 - [Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good](https://md.research.elamur.ai/free/en/papers/wang-2019-persuasion-good-personalized-persuasive-dialogue/) — Xuewei Wang, Weiyan Shi, Richard Kim, et al. · Proceedings of the 57th Annual Meeting of the… - [PIQA: Reasoning about Physical Commonsense in Natural Language](https://md.research.elamur.ai/free/en/papers/bisk-2019-piqa-reasoning-about-physical-commonsense/) — Yonatan Bisk, Rowan Zellers, Ronan Le Bras, et al. · arXiv:1911.11641 - [Plug and Play Language Models: A Simple Approach to Controlled Text Generation](https://md.research.elamur.ai/free/en/papers/dathathri-2019-plug-play-language-models-simple/) — Sumanth Dathathri, Andrea Madotto, Janice Lan, et al. · arXiv:1912.02164 - [Pragmatically Informative Text Generation](https://md.research.elamur.ai/free/en/papers/shen-2019-pragmatically-informative-text-generation/) — Sheng Shen, Daniel Fried, Jacob Andreas, et al. · English - [Pre-Training with Whole Word Masking for Chinese BERT](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/) — Yiming Cui, Wanxiang Che, Ting Liu, et al. · arXiv:1906.08101 · IEEE/ACM Transactions on… - [Predicate Catenae: A Dependency Grammar Analysis of It-Clefts](https://md.research.elamur.ai/free/en/papers/osborne-2019-predicate-catenae-dependency-grammar-analysis/) — Timothy Osborne · English - [Predicting the Type and Target of Offensive Posts in Social Media](https://md.research.elamur.ai/free/en/papers/zampieri-2019-predicting-type-target-offensive-posts/) — Marcos Zampieri, Shervin Malmasi, Preslav Nakov, et al. · Proceedings of the 2019 Conference of the North… - [Prepositions and the Grammaticalization of Ancient Hebrew Bipartite Reciprocal Markers](https://md.research.elamur.ai/free/en/papers/hbo-2019-staps-prepositions-grammaticalization-ancient-hebrew-bipartite/) — Camil Staps · Ancient Hebrew - [Probing Natural Language Inference Models through Semantic Fragments](https://md.research.elamur.ai/free/en/papers/richardson-2019-probing-natural-language-inference-models/) — Kyle Richardson, Hai Hu, Lawrence S. Moss, et al. · arXiv:1909.07521 - [Probing What Different NLP Tasks Teach Machines about Function Word Comprehension](https://md.research.elamur.ai/free/en/papers/kim-2019-probing-what-different-nlp-tasks/) — Najoung Kim, Roma Patel, Adam Poliak, et al. · Proceedings of the Eighth Joint Conference on… - [Problem-oriented Corpus Annotation and the Hebrew Bible](https://md.research.elamur.ai/free/en/papers/hbo-2019-joode-problem-oriented-corpus-annotation-hebrew/) — Johan de Joode · Ancient Hebrew - [Proceedings of the Third Workshop on Universal Dependencies (UDW, SyntaxFest 2019)](https://md.research.elamur.ai/free/en/papers/anon-2019-proceedings-third-workshop-universal-dependencies/) — Research library - [Publicly Available Clinical BERT Embeddings](https://md.research.elamur.ai/free/en/papers/alsentzer-2019-publicly-available-clinical-bert-embeddings/) — Emily Alsentzer, John R. Murphy, Willie Boag, et al. · arXiv:1904.03323 - [PubMedQA: A Dataset for Biomedical Research Question Answering](https://md.research.elamur.ai/free/en/papers/jin-2019-pubmedqa-dataset-biomedical-research-question/) — Qiao Jin, Bhuwan Dhingra, Zhengping Liu, et al. · Proceedings of the 2019 Conference on Empirical… - [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://md.research.elamur.ai/free/en/papers/paszke-2019-pytorch-imperative-style-high-performance/) — Adam Paszke, Sam Gross, Francisco Massa, et al. · arXiv:1912.01703 - [Quantifying the Carbon Emissions of Machine Learning](https://md.research.elamur.ai/free/en/papers/lacoste-2019-quantifying-carbon-emissions-machine-learning/) — Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, et al. · arXiv:1910.09700 - [Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning](https://md.research.elamur.ai/free/en/papers/dasigi-2019-quoref-reading-comprehension-dataset-questions/) — Pradeep Dasigi, Nelson F. Liu, Ana Marasovic, et al. · English - [Racial Bias in Hate Speech and Abusive Language Detection Datasets](https://md.research.elamur.ai/free/en/papers/davidson-2019-racial-bias-hate-speech-abusive/) — Thomas Davidson, Debasmita Bhattacharya, Ingmar Weber · Proceedings of the Third Workshop on Abusive… - [Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/falke-2019-ranking-generated-summaries-correctness-interesting/) — Tobias Falke, Leonardo F. R. Ribeiro, Prasetya Ajie Utama, et al. · Proceedings of the 57th Annual Meeting of the… - [Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/) — Shane Storks, Qiaozi Gao, Joyce Y. Chai · arXiv:1904.01172 - [Recursive LSTM Tree Representation for Arc-Standard Transition-Based Dependency Parsing](https://md.research.elamur.ai/free/en/papers/ud-2019-elkaref-recursive-lstm-tree-representation-arc/) — Mohab Elkaref, Bernd Bohnet · English - [Reducing Transformer Depth on Demand with Structured Dropout](https://md.research.elamur.ai/free/en/papers/fan-2019-reducing-transformer-depth-demand-structured/) — Angela Fan, Edouard Grave, Armand Joulin · arXiv:1909.11556 - [Release Strategies and the Social Impacts of Language Models](https://md.research.elamur.ai/free/en/papers/solaiman-2019-release-strategies-social-impacts-language/) — Irene Solaiman, Miles Brundage, Jack Clark, et al. · arXiv:1908.09203 - [Representation Degeneration Problem in Training Natural Language Generation Models](https://md.research.elamur.ai/free/en/papers/gao-2019-representation-degeneration-problem-training-natural/) — Jun Gao, Di He, Xu Tan, et al. · arXiv:1907.12009 - [Restoring Arabic vowels through omission-tolerant dictionary lookup](https://md.research.elamur.ai/free/en/papers/langstream-2019-neme-restoring-arabic-vowels-through-omission/) — Alexis Amid Neme, Sebastien Paumier · Semitic languages - [Results of the WMT19 Metrics Shared Task: Segment-Level and Strong MT Systems Pose Big Challenges](https://md.research.elamur.ai/free/en/papers/ma-2019-results-wmt19-metrics-shared-task/) — Qingsong Ma, Johnny Wei, Ondřej Bojar, et al. · Proceedings of the Fourth Conference on Machine… - [Rethinking templates: A syntactic analysis of verbal morphology in Emirati Arabic](https://md.research.elamur.ai/free/en/papers/lingbulk-2019-kaabi-rethinking-templates-syntactic-analysis-verbal/) — Meera Al Kaabi, Dimitrios Ntelitheos · Semitic languages - [Revealing the Dark Secrets of BERT](https://md.research.elamur.ai/free/en/papers/kovaleva-2019-revealing-dark-secrets-bert/) — Olga Kovaleva, Alexey Romanov, Anna Rogers, et al. · arXiv:1908.08593 - [Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution](https://md.research.elamur.ai/free/en/papers/barhom-2019-revisiting-joint-modeling-cross-document/) — Shany Barhom, Vered Shwartz, Alon Eirew, et al. · Proceedings of the 57th Annual Meeting of the… - [Rewarding Coreference Resolvers for Being Consistent with World Knowledge](https://md.research.elamur.ai/free/en/papers/aralikatte-2019-rewarding-coreference-resolvers-being-consistent/) — Rahul Aralikatte, Heather Lent, Ana Valeria Gonzalez, et al. · Proceedings of the 2019 Conference on Empirical… - [Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/) — R. Thomas McCoy, Ellie Pavlick, Tal Linzen · English - [S2ORC: The Semantic Scholar Open Research Corpus](https://md.research.elamur.ai/free/en/papers/lo-2019-s2orc-semantic-scholar-open-research/) — Kyle Lo, Lucy Lu Wang, Mark Neumann, et al. · arXiv:1911.02782 - [SciBERT: A Pretrained Language Model for Scientific Text](https://md.research.elamur.ai/free/en/papers/beltagy-2019-scibert-pretrained-language-model-scientific/) — Iz Beltagy, Kyle Lo, Arman Cohan · Proceedings of the 2019 Conference on Empirical… - [SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python](https://md.research.elamur.ai/free/en/papers/virtanen-2019-scipy-1-0-fundamental-algorithms/) — Pauli Virtanen, Ralf Gommers, Travis E. 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