--- title: "Papers of 2017 — page 4" description: "Papers of 2017: 331 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/2017/page/4/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2017/page/4/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2017 # Papers of 2017 — page 4 331 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2017/page/3/) [1](https://md.research.elamur.ai/free/en/papers/2017/) [2](https://md.research.elamur.ai/free/en/papers/2017/page/2/) [3](https://md.research.elamur.ai/free/en/papers/2017/page/3/) **4** - [TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension](https://md.research.elamur.ai/free/en/papers/joshi-2017-triviaqa-large-scale-distantly-supervised/) — Mandar Joshi, Eunsol Choi, Daniel Weld, et al. · Proceedings of the 55th Annual Meeting of the… - [Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking](https://md.research.elamur.ai/free/en/papers/rashkin-2017-truth-varying-shades-analyzing-language/) — Hannah Rashkin, Eunsol Choi, Jin Yea Jang, et al. · Proceedings of the 2017 Conference on Empirical… - [Udapi: Universal API for Universal Dependencies](https://md.research.elamur.ai/free/en/papers/popel-2017-udapi-universal-api-universal-dependencies/) — Martin Popel, Zdeněk Žabokrtský, Martin Vojtek · Mova's core list - [Understanding Abuse: A Typology of Abusive Language Detection Subtasks](https://md.research.elamur.ai/free/en/papers/waseem-2017-understanding-abuse-typology-abusive-language/) — Zeerak Waseem, Thomas Davidson, Dana Warmsley, et al. · Proceedings of the First Workshop on Abusive… - [Understanding Black-box Predictions via Influence Functions](https://md.research.elamur.ai/free/en/papers/koh-2017-understanding-black-box-predictions-influence/) — Pang Wei Koh, Percy Liang · arXiv:1703.04730 - [Unit Dependency Graph and its Application to Arithmetic Word Problem Solving](https://md.research.elamur.ai/free/en/papers/roy-2017-unit-dependency-graph-arithmetic/) — Subhro Roy, Dan Roth · Mova's core list - [Universal Dependencies for Arabic](https://md.research.elamur.ai/free/en/papers/ud-2017-taji-universal-dependencies-arabic/) — Dima Taji, Nizar Habash, Daniel Zeman · Semitic languages - [Universal Dependencies Parsing for Colloquial Singaporean English](https://md.research.elamur.ai/free/en/papers/ud-2017-wang-universal-dependencies-parsing-colloquial-singaporean/) — Hongmin Wang, Yue Zhang, GuangYong Leonard Chan, et al. · English - [Universal Joint Morph-Syntactic Processing: The Open University of Israel's Submission to The CoNLL 2017 Shared Task](https://md.research.elamur.ai/free/en/papers/ud-2017-more-universal-joint-morph-syntactic-processing/) — Amir More, Reut Tsarfaty · Modern Hebrew - [Unsupervised AMR-Dependency Parse Alignment](https://md.research.elamur.ai/free/en/papers/chen-2017-unsupervised-amr-dependency-parse-alignment/) — Wei-Te Chen, Martha Palmer · Machine translation - [Unsupervised Machine Translation Using Monolingual Corpora Only](https://md.research.elamur.ai/free/en/papers/lample-2017-unsupervised-machine-translation-using-monolingual/) — Guillaume Lample, Alexis Conneau, Ludovic Denoyer, et al. · arXiv:1711.00043 - [Unsupervised Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/artetxe-2017-unsupervised-neural-machine-translation/) — Mikel Artetxe, Gorka Labaka, Eneko Agirre, et al. · arXiv:1710.11041 - [Unsupervised Pretraining for Sequence to Sequence Learning](https://md.research.elamur.ai/free/en/papers/ramachandran-2017-unsupervised-pretraining-sequence-sequence-learning/) — Prajit Ramachandran, Peter Liu, Quoc Le · Proceedings of the 2017 Conference on Empirical… - [URIEL and lang2vec: Representing languages as typological, geographical, and phylogenetic vectors](https://md.research.elamur.ai/free/en/papers/littell-2017-uriel-lang2vec-representing-languages-as/) — Patrick Littell, David R. Mortensen, Ke Lin, et al. · Proceedings of the 15th Conference of the… - [Using Context Information for Dialog Act Classification in DNN Framework](https://md.research.elamur.ai/free/en/papers/liu-2017-context-information-dialog-act-classification/) — Yang Liu, Kun Han, Zhao Tan, et al. · Proceedings of the 2017 Conference on Empirical… - [Using Convolutional Neural Networks to Classify Hate-Speech](https://md.research.elamur.ai/free/en/papers/gamback-2017-convolutional-neural-networks-classify-hate/) — Björn Gambäck, Utpal Kumar Sikdar · Proceedings of the First Workshop on Abusive… - [Using Coreference Links to Improve Spanish-to-English Machine Translation](https://md.research.elamur.ai/free/en/papers/werlen-2017-coreference-links-improve-spanish-english/) — Lesly Miculicich Werlen, Andrei Popescu-Belis · Proceedings of the 2nd Workshop on Coreference… - [Using Electronic Dictionaries and NooJ to Generate Sentences Containing English Phrasal Verbs](https://md.research.elamur.ai/free/en/papers/machonis-2017-electronic-dictionaries-nooj-generate-sentences/) — Peter A. Machonis · English - [Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification](https://md.research.elamur.ai/free/en/papers/shi-2017-explicit-discourse-connectives-translation-implicit/) — Wei Shi, Frances Yung, Raphael Rubino, et al. · Proceedings of the Eighth International Joint… - [Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm](https://md.research.elamur.ai/free/en/papers/felbo-2017-millions-emoji-occurrences-learn-any/) — Bjarke Felbo, Alan Mislove, Anders Søgaard, et al. · Proceedings of the 2017 Conference on Empirical… - [Using the Output Embedding to Improve Language Models](https://md.research.elamur.ai/free/en/papers/press-2017-output-embedding-improve-language-models/) — Ofir Press, Lior Wolf · Proceedings of the 15th Conference of the… - [Validation of an Automatic Metric for the Accuracy of Pronoun Translation (APT)](https://md.research.elamur.ai/free/en/papers/werlen-2017-validation-automatic-metric-accuracy-pronoun/) — Lesly Miculicich Werlen, Andrei Popescu-Belis · Proceedings of the Third Workshop on Discourse… - [Very Deep Convolutional Networks for Text Classification](https://md.research.elamur.ai/free/en/papers/conneau-2017-very-deep-convolutional-networks-text/) — Alexis Conneau, Holger Schwenk, Loïc Barrault, et al. · Proceedings of the 15th Conference of the… - [Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://md.research.elamur.ai/free/en/papers/anderson-2017-vision-language-navigation-interpreting-visually/) — Peter Anderson, Qi Wu, Damien Teney, et al. · arXiv:1711.07280 - [WASSA-2017 Shared Task on Emotion Intensity](https://md.research.elamur.ai/free/en/papers/mohammad-2017-wassa-2017-shared-task-emotion/) — Saif Mohammad, Felipe Bravo-Marquez · Proceedings of the 8th Workshop on… - [What do Neural Machine Translation Models Learn about Morphology?](https://md.research.elamur.ai/free/en/papers/belinkov-2017-what-do-neural-machine-translation/) — Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, et al. · Proceedings of the 55th Annual Meeting of the… - [What is it? Disambiguating the different readings of the pronoun 'it'](https://md.research.elamur.ai/free/en/papers/loaiciga-2017-what-is-it-disambiguating-different/) — Sharid Loáiciga, Liane Guillou, Christian Hardmeier · English - [What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?](https://md.research.elamur.ai/free/en/papers/kendall-2017-uncertainties-need-bayesian-deep-learning/) — Alex Kendall, Yarin Gal · arXiv:1703.04977 - [Word Sense Disambiguation: A Unified Evaluation Framework and Empirical Comparison](https://md.research.elamur.ai/free/en/papers/onto-2017-raganato-word-sense-disambiguation-unified-evaluation/) — Alessandro Raganato, Jose Camacho-Collados, Roberto Navigli · English - [Ze lo kaχa ‘It’s Not Like That’: The Functions of the discourse-deictic kaχa ‘thus’ in spoken Israeli Hebrew](https://md.research.elamur.ai/free/en/papers/shor-2017-ze-lo-kaa-like-that/) — Leon Shor · Studia Orientalia Electronica 5 - [“Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection](https://md.research.elamur.ai/free/en/papers/wang-2017-liar-liar-pants-fire-new/) — William Yang Wang · Proceedings of the 55th Annual Meeting of the… [← prev](https://md.research.elamur.ai/free/en/papers/2017/page/3/) [1](https://md.research.elamur.ai/free/en/papers/2017/) [2](https://md.research.elamur.ai/free/en/papers/2017/page/2/) [3](https://md.research.elamur.ai/free/en/papers/2017/page/3/) **4**