--- title: "Papers of 2017 — page 1" 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/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2017/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2017 # Papers of 2017 — page 1 331 papers · [all years](https://md.research.elamur.ai/free/en/papers/) **1** [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](https://md.research.elamur.ai/free/en/papers/2017/page/4/) [next →](https://md.research.elamur.ai/free/en/papers/2017/page/2/) - ['IMS at the CoNLL 2017 UD Shared Task: CRFs and Perceptrons Meet Neural Networks'](https://md.research.elamur.ai/free/en/papers/ud-2017-bjorkelund-ims-conll-2017-ud-shared/) — Anders Björkelund, Agnieszka Falenska, Xiang Yu, et al. · English - ['The parse is darc and full of errors: Universal dependency parsing with transition-based and graph-based algorithms'](https://md.research.elamur.ai/free/en/papers/ud-2017-yu-parse-is-darc-full-errors/) — Kuan Yu, Pavel Sofroniev, Erik Schill, et al. · English - [A Challenge Set Approach to Evaluating Machine Translation](https://md.research.elamur.ai/free/en/papers/isabelle-2017-challenge-set-approach-evaluating-machine/) — Pierre Isabelle, Colin Cherry, George Foster · Machine translation - [A Continuously Growing Dataset of Sentential Paraphrases](https://md.research.elamur.ai/free/en/papers/lan-2017-continuously-growing-dataset-sentential-paraphrases/) — Wuwei Lan, Siyu Qiu, Hua He, et al. · Proceedings of the 2017 Conference on Empirical… - [A Convolutional Encoder Model for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gehring-2017-convolutional-encoder-model-neural-machine/) — Jonas Gehring, Michael Auli, David Grangier, et al. · Proceedings of the 55th Annual Meeting of the… - [A Dataset for Multi-Target Stance Detection](https://md.research.elamur.ai/free/en/papers/sobhani-2017-dataset-multi-target-stance-detection/) — Parinaz Sobhani, Diana Inkpen, Xiaodan Zhu · Proceedings of the 15th Conference of the… - [A Deep Generative Framework for Paraphrase Generation](https://md.research.elamur.ai/free/en/papers/gupta-2017-deep-generative-framework-paraphrase-generation/) — Ankush Gupta, Arvind Agarwal, Prawaan Singh, et al. · arXiv:1709.05074 - [A Deep Reinforced Model for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/paulus-2017-deep-reinforced-model-abstractive-summarization/) — Romain Paulus, Caiming Xiong, Richard Socher · arXiv:1705.04304 - [A Hierarchical Neural Model for Learning Sequences of Dialogue Acts](https://md.research.elamur.ai/free/en/papers/tran-2017-hierarchical-neural-model-learning-sequences/) — Quan Hung Tran, Ingrid Zukerman, Gholamreza Haffari · Proceedings of the 15th Conference of the… - [A Joint Sequential and Relational Model for Frame-Semantic Parsing](https://md.research.elamur.ai/free/en/papers/yang-2017-joint-sequential-relational-model-frame/) — Bishan Yang, Tom Mitchell · Proceedings of the 2017 Conference on Empirical… - [A Mention-Ranking Model for Abstract Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/marasovic-2017-mention-ranking-model-abstract-anaphora/) — Ana Marasović, Leo Born, Juri Opitz, et al. · English - [A Minimal Span-Based Neural Constituency Parser](https://md.research.elamur.ai/free/en/papers/stern-2017-minimal-span-based-neural-constituency/) — Mitchell Stern, Jacob Andreas, Dan Klein · Proceedings of the 55th Annual Meeting of the… - [A Neural Architecture for Dialectal Arabic Segmentation](https://md.research.elamur.ai/free/en/papers/aclbulk-2017-samih-neural-architecture-dialectal-arabic-segmentation/) — Younes Samih, Mohammed Attia, Mohamed Eldesouki, et al. · Semitic languages - [A non-projective greedy dependency parser with bidirectional LSTMs](https://md.research.elamur.ai/free/en/papers/ud-2017-vilares-non-projective-greedy-dependency-parser/) — David Vilares, Carlos Gómez-Rodríguez · English - [A Preliminary Study for Building an Arabic Corpus of Pair Questions-Texts from the Web: AQA-Webcorp](https://md.research.elamur.ai/free/en/papers/bakari-2017-preliminary-study-building-arabic-corpus/) — Wided Bakari, Patrice Bellot, Mahmoud Neji LSIS) · arXiv:1709.09404 · International Journal of… - [A Recurrent Neural Model with Attention for the Recognition of Chinese Implicit Discourse Relations](https://md.research.elamur.ai/free/en/papers/ronnqvist-2017-recurrent-neural-model-attention-recognition/) — Samuel Rönnqvist, Niko Schenk, Christian Chiarcos · Proceedings of the 55th Annual Meeting of the… - [A Rich Morphological Tagger for English: Exploring the Cross-Linguistic Tradeoff Between Morphology and Syntax](https://md.research.elamur.ai/free/en/papers/kirov-2017-rich-morphological-tagger-english-exploring/) — Christo Kirov, John Sylak-Glassman, Rebecca Knowles, et al. · English - [A semiautomatic lemmatisation procedure for treebanks. Old English strong and weak verbs](https://md.research.elamur.ai/free/en/papers/saenz-2017-semiautomatic-lemmatisation-procedure-treebanks-old/) — Marta Tío Sáenz, Darío Metola Rodríguez · English - [A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification](https://md.research.elamur.ai/free/en/papers/zhang-2017-sensitivity-analysis-practitioners-guide-convolutional/) — Ye Zhang, Byron Wallace · Proceedings of the Eighth International Joint… - [A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling](https://md.research.elamur.ai/free/en/papers/marcheggiani-2017-simple-accurate-syntax-agnostic-neural/) — Diego Marcheggiani, Anton Frolov, Ivan Titov · English - [A simple neural network module for relational reasoning](https://md.research.elamur.ai/free/en/papers/santoro-2017-simple-neural-network-module-relational/) — Adam Santoro, David Raposo, David G. T. Barrett, et al. · arXiv:1706.01427 - [A Structured Self-attentive Sentence Embedding](https://md.research.elamur.ai/free/en/papers/lin-2017-structured-self-attentive-sentence-embedding/) — Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, et al. · arXiv:1703.03130 - [A Survey on Hate Speech Detection using Natural Language Processing](https://md.research.elamur.ai/free/en/papers/schmidt-2017-survey-hate-speech-detection-natural/) — Anna Schmidt, Michael Wiegand · Proceedings of the Fifth International Workshop… - [A Syntactic Neural Model for General-Purpose Code Generation](https://md.research.elamur.ai/free/en/papers/yin-2017-syntactic-neural-model-general-purpose/) — Pengcheng Yin, Graham Neubig · Proceedings of the 55th Annual Meeting of the… - [A Systematic Study of Neural Discourse Models for Implicit Discourse Relation](https://md.research.elamur.ai/free/en/papers/rutherford-2017-systematic-study-neural-discourse-models/) — Attapol Rutherford, Vera Demberg, Nianwen Xue · Proceedings of the 15th Conference of the… - [A Text Normalisation System for Non-Standard English Words](https://md.research.elamur.ai/free/en/papers/flint-2017-text-normalisation-system-non-standard/) — Emma Flint, Elliot Ford, Olivia Thomas, et al. · English - [A Two-Stage Parsing Method for Text-Level Discourse Analysis](https://md.research.elamur.ai/free/en/papers/wang-2017-two-stage-parsing-method-text/) — Yizhong Wang, Sujian Li, Houfeng Wang · Proceedings of the 55th Annual Meeting of the… - [A Unified Approach to Interpreting Model Predictions](https://md.research.elamur.ai/free/en/papers/lundberg-2017-unified-approach-interpreting-model-predictions/) — Scott Lundberg, Su-In Lee · arXiv:1705.07874 - [Abstractive Document Summarization with a Graph-Based Attentional Neural Model](https://md.research.elamur.ai/free/en/papers/tan-2017-abstractive-document-summarization-graph-based/) — Jiwei Tan, Xiaojun Wan, Jianguo Xiao · Proceedings of the 55th Annual Meeting of the… - [Abusive Language Detection on Arabic Social Media](https://md.research.elamur.ai/free/en/papers/mubarak-2017-abusive-language-detection-arabic-social/) — Hamdy Mubarak, Kareem Darwish, Walid Magdy · Proceedings of the First Workshop on Abusive… - [Adposition and Case Supersenses v2.6: Guidelines for English](https://md.research.elamur.ai/free/en/papers/schneider-2017-adposition-case-supersenses-v2-6/) — Nathan Schneider, Jena D. Hwang, Vivek Srikumar, et al. · English - [Advances in Pre-Training Distributed Word Representations](https://md.research.elamur.ai/free/en/papers/mikolov-2017-advances-pre-training-distributed-word/) — Tomas Mikolov, Edouard Grave, Piotr Bojanowski, et al. · arXiv:1712.09405 - [Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification](https://md.research.elamur.ai/free/en/papers/qin-2017-adversarial-connective-exploiting-networks-implicit/) — Lianhui Qin, Zhisong Zhang, Hai Zhao, et al. · Proceedings of the 55th Annual Meeting of the… - [Adversarial Examples for Evaluating Reading Comprehension Systems](https://md.research.elamur.ai/free/en/papers/jia-2017-adversarial-examples-evaluating-reading-comprehension/) — Robin Jia, Percy Liang · English - [Adversarial Learning for Neural Dialogue Generation](https://md.research.elamur.ai/free/en/papers/li-2017-adversarial-learning-neural-dialogue-generation/) — Jiwei Li, Will Monroe, Tianlin Shi, et al. · Proceedings of the 2017 Conference on Empirical… - [Adversarial Multi-task Learning for Text Classification](https://md.research.elamur.ai/free/en/papers/liu-2017-adversarial-multi-task-learning-text/) — Pengfei Liu, Xipeng Qiu, Xuanjing Huang · Proceedings of the 55th Annual Meeting of the… - [Adversarial Training for Unsupervised Bilingual Lexicon Induction](https://md.research.elamur.ai/free/en/papers/zhang-2017-adversarial-training-unsupervised-bilingual-lexicon/) — Meng Zhang, Yang Liu, Huanbo Luan, et al. · Proceedings of the 55th Annual Meeting of the… - [Against Binarism, Simplicity, Neatness and Stasis: A Theoretical Prolegomenon to the Reality of Verbal Grams in Biblical Hebrew](https://md.research.elamur.ai/free/en/papers/hbo-2026-andrason-against-binarism-simplicity-neatness-stasis/) — Alexander Andrason · Ancient Hebrew - [Alto: Rapid Prototyping for Parsing and Translation](https://md.research.elamur.ai/free/en/papers/gontrum-2017-alto-rapid-prototyping-parsing-translation/) — Johannes Gontrum, Jonas Groschwitz, Alexander Koller, et al. · Machine translation - [AMR-to-text Generation with Synchronous Node Replacement Grammar](https://md.research.elamur.ai/free/en/papers/song-2017-amr-text-generation-synchronous-node/) — Linfeng Song, Xiaochang Peng, Yue Zhang, et al. · Machine translation - [An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chu-2017-empirical-comparison-domain-adaptation-methods/) — Chenhui Chu, Raj Dabre, Sadao Kurohashi · Proceedings of the 55th Annual Meeting of the… - [An Incremental Parser for Abstract Meaning Representation](https://md.research.elamur.ai/free/en/papers/damonte-2017-incremental-parser-abstract-meaning-representation/) — Marco Damonte, Shay B. Cohen, Giorgio Satta · Proceedings of the 15th Conference of the… - [An interpersonal sketch of the biblical Hebrew clause](https://md.research.elamur.ai/free/en/papers/hbo-2017-racher-interpersonal-sketch-biblical-hebrew-clause/) — Eric Todd Racher · Ancient Hebrew - [An Overview of Multi-Task Learning in Deep Neural Networks](https://md.research.elamur.ai/free/en/papers/ruder-2017-overview-multi-task-learning-deep/) — Sebastian Ruder · arXiv:1706.05098 - [Analyzing the Impact of Spelling Errors on POS-Tagging and Chunking in Learner English](https://md.research.elamur.ai/free/en/papers/mizumoto-2017-analyzing-impact-spelling-errors-pos/) — Tomoya Mizumoto, Ryo Nagata · English - [Annotating tense, mood and voice for English, French and German](https://md.research.elamur.ai/free/en/papers/ramm-2017-annotating-tense-mood-voice-english/) — Anita Ramm, Sharid Loáiciga, Annemarie Friedrich, et al. · English - [Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection Corpus](https://md.research.elamur.ai/free/en/papers/schuff-2017-annotation-modelling-analysis-fine-grained/) — Hendrik Schuff, Jeremy Barnes, Julian Mohme, et al. · Proceedings of the 8th Workshop on… - [Apports des analyses syntaxiques pour la détection automatique de mentions dans un corpus de français oral](https://md.research.elamur.ai/free/en/papers/grobol-2017-apports-analyses-syntaxiques-detection/) — Loïc Grobol, Isabelle Tellier, Éric Villemonte de La Clergerie, et al. · TALN 2017 - [Arabic Diacritization: Stats, Rules, and Hacks](https://md.research.elamur.ai/free/en/papers/aclbulk-2017-darwish-arabic-diacritization-stats-rules-hacks/) — Kareem Darwish, Hamdy Mubarak, Ahmed Abdelali · Semitic languages - [Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM](https://md.research.elamur.ai/free/en/papers/langstream-2017-eldesouki-arabic-multi-dialect-segmentation-bi/) — Mohamed Eldesouki, Younes Samih, Ahmed Abdelali, et al. · Semitic languages - [Arc-swift: A Novel Transition System for Dependency Parsing](https://md.research.elamur.ai/free/en/papers/ud-2017-qi-arc-swift-novel-transition-system/) — Peng Qi, Christopher D. Manning · English - [Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog](https://md.research.elamur.ai/free/en/papers/oraby-2017-are-you-serious-rhetorical-questions/) — Shereen Oraby, Vrindavan Harrison, Amita Misra, et al. · English - [Argumentation Mining in User-Generated Web Discourse](https://md.research.elamur.ai/free/en/papers/habernal-2017-argumentation-mining-user-generated-web/) — Ivan Habernal, Iryna Gurevych · Computational Linguistics - [Artificial Error Generation with Machine Translation and Syntactic Patterns](https://md.research.elamur.ai/free/en/papers/rei-2017-artificial-error-generation-machine-translation/) — Marek Rei, Mariano Felice, Zheng Yuan, et al. · arXiv:1707.05236 - [Assessing the Annotation Consistency of the Universal Dependencies Corpora](https://md.research.elamur.ai/free/en/papers/marneffe-2017-assessing-annotation-consistency-universal-dependencies/) — Marie-Catherine de Marneffe, Matias Grioni, Jenna Kanerva, et al. · Mova's core list - [At the interface of syntax and prosody: Differentiating left dislocated and tripartite verbless clauses in Biblical Hebrew](https://md.research.elamur.ai/free/en/papers/hbo-2018-naude-interface-syntax-prosody-differentiating-left/) — Jacobus A. Naudé, Cynthia L. Miller-Naudé · Ancient Hebrew - [Attention-based Recurrent Convolutional Neural Network for Automatic Essay Scoring](https://md.research.elamur.ai/free/en/papers/dong-2017-attention-based-recurrent-convolutional-neural/) — Fei Dong, Yue Zhang, Jie Yang · Proceedings of the 21st Conference on… - [Automated Hate Speech Detection and the Problem of Offensive Language](https://md.research.elamur.ai/free/en/papers/davidson-2017-automated-hate-speech-detection-problem/) — Thomas Davidson, Dana Warmsley, Michael Macy, et al. · arXiv:1703.04009 - [Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/bryant-2017-automatic-annotation-evaluation-error-types/) — Christopher Bryant, Mariano Felice, Ted Briscoe · Mova's core list - [Beam Search Strategies for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/freitag-2017-beam-search-strategies-neural-machine/) — Markus Freitag, Yaser Al-Onaizan · Proceedings of the First Workshop on Neural… - [Best-Worst Scaling More Reliable than Rating Scales: A Case Study on Sentiment Intensity Annotation](https://md.research.elamur.ai/free/en/papers/kiritchenko-2017-best-worst-scaling-more-reliable/) — Svetlana Kiritchenko, Saif Mohammad · Proceedings of the 55th Annual Meeting of the… - [Bias in polar questions: Evidence from English and German production experiments](https://md.research.elamur.ai/free/en/papers/domaneschi-2017-bias-polar-questions-evidence-english/) — Filippo Domaneschi, Maribel Romero, Bettina Braun · English - [Bilateral Multi-Perspective Matching for Natural Language Sentences](https://md.research.elamur.ai/free/en/papers/wang-2017-bilateral-multi-perspective-matching-natural/) — Zhiguo Wang, Wael Hamza, Radu Florian · arXiv:1702.03814 - [Billion-scale similarity search with GPUs](https://md.research.elamur.ai/free/en/papers/johnson-2017-billion-scale-similarity-search-gpus/) — Jeff Johnson, Matthijs Douze, Hervé Jégou · arXiv:1702.08734 - [Breaking NLP: Using Morphosyntax, Semantics, Pragmatics and World Knowledge to Fool Sentiment Analysis Systems](https://md.research.elamur.ai/free/en/papers/mahler-2017-breaking-nlp-morphosyntax-semantics-pragmatics/) — Taylor Mahler, Willy Cheung, Micha Elsner, et al. · Proceedings of the First Workshop on Building… - [Challenges in Data-to-Document Generation](https://md.research.elamur.ai/free/en/papers/wiseman-2017-challenges-data-document-generation/) — Sam Wiseman, Stuart M. Shieber, Alexander M. Rush · arXiv:1707.08052 - [Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging](https://md.research.elamur.ai/free/en/papers/aclbulk-2017-sajjad-challenging-language-dependent-segmentation-arabic/) — Hassan Sajjad, Fahim Dalvi, Nadir Durrani, et al. · Semitic languages - [Changes of Syntactic Patterns in the Textual Tradition of the Book of Isaiah: A Corpus-Linguistic Approach](https://md.research.elamur.ai/free/en/papers/hbo-2017-oosting-changes-syntactic-patterns-textual-tradition/) — Reinoud Oosting · Ancient Hebrew - [Chinese Zero Pronoun Resolution with Deep Memory Network](https://md.research.elamur.ai/free/en/papers/yin-2017-chinese-zero-pronoun-resolution-deep/) — Qingyu Yin, Yu Zhang, Weinan Zhang, et al. · Proceedings of the 2017 Conference on Empirical… - [chrF++: words helping character n-grams](https://md.research.elamur.ai/free/en/papers/popovic-2017-chrf-words-helping-character-n/) — Maja Popović · Machine translation - [Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding](https://md.research.elamur.ai/free/en/papers/monroe-2017-colors-context-pragmatic-neural-model/) — Will Monroe, Robert X.D. Hawkins, Noah D. Goodman, et al. · Research library - [Comparing Rule-based and SMT-based Spelling Normalisation for English Historical Texts](https://md.research.elamur.ai/free/en/papers/schneider-2017-comparing-rule-based-smt-based/) — Gerold Schneider, Eva Pettersson, Michael Percillier · English - [Computational Argumentation Quality Assessment in Natural Language](https://md.research.elamur.ai/free/en/papers/wachsmuth-2017-computational-argumentation-quality-assessment-natural/) — Henning Wachsmuth, Nona Naderi, Yufang Hou, et al. · Proceedings of the 15th Conference of the… - [Concept-Map-Based Multi-Document Summarization using Concept Coreference Resolution and Global Importance Optimization](https://md.research.elamur.ai/free/en/papers/falke-2017-concept-map-based-multi-document/) — Tobias Falke, Christian M. Meyer, Iryna Gurevych · Proceedings of the Eighth International Joint… - [CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies](https://md.research.elamur.ai/free/en/papers/ud-2017-zeman-conll-2017-shared-task-multilingual/) — Daniel Zeman, Martin Popel, Milan Straka, et al. · English - [Constraints in contact: Animacy in English and Afrikaans genitive variation – a cross-linguistic perspective](https://md.research.elamur.ai/free/en/papers/rosenbach-2017-constraints-contact-animacy-english-afrikaans/) — Anette Rosenbach · English - [Context-Dependent Sentiment Analysis in User-Generated Videos](https://md.research.elamur.ai/free/en/papers/poria-2017-context-dependent-sentiment-analysis-user/) — Soujanya Poria, Erik Cambria, Devamanyu Hazarika, et al. · Proceedings of the 55th Annual Meeting of the… - [Control vs. Raising in English. A Dependency Grammar Account](https://md.research.elamur.ai/free/en/papers/osborne-2017-control-vs-raising-english-dependency/) — Timothy Osborne, Matthew Reeve · English - [Controlling Linguistic Style Aspects in Neural Language Generation](https://md.research.elamur.ai/free/en/papers/ficler-2017-controlling-linguistic-style-aspects-neural/) — Jessica Ficler, Yoav Goldberg · Proceedings of the Workshop on Stylistic… - [Convolutional Sequence to Sequence Learning](https://md.research.elamur.ai/free/en/papers/gehring-2017-convolutional-sequence-sequence-learning/) — Jonas Gehring, Michael Auli, David Grangier, et al. · arXiv:1705.03122 - [Copied Monolingual Data Improves Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/currey-2017-copied-monolingual-data-improves-low/) — Anna Currey, Antonio Valerio Miceli Barone, Kenneth Heafield · Proceedings of the Second Conference on Machine… - [Corpus-Driven Visualization of Textual Worlds](https://md.research.elamur.ai/free/en/papers/hbo-2017-kofoed-corpus-driven-visualization-textual-worlds/) — Jens Bruun Kofoed · Ancient Hebrew - [Corpus-driven visualization, learning and linguistics](https://md.research.elamur.ai/free/en/papers/hbo-2017-winther-nielsen-corpus-driven-visualization-learning-linguistics/) — Nicolai Winther-Nielsen · Ancient Hebrew - [Creating Training Corpora for NLG Micro-Planners](https://md.research.elamur.ai/free/en/papers/gardent-2017-creating-training-corpora-nlg-micro/) — Claire Gardent, Anastasia Shimorina, Shashi Narayan, et al. · Proceedings of the 55th Annual Meeting of the… - [Cross-lingual Name Tagging and Linking for 282 Languages](https://md.research.elamur.ai/free/en/papers/pan-2017-cross-lingual-name-tagging-linking/) — Xiaoman Pan, Boliang Zhang, Jonathan May, et al. · Proceedings of the 55th Annual Meeting of the… - [Cross-Lingual Parser Selection for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/agic-2017-cross-lingual-parser-selection-low/) — Željko Agić · Proceedings of the NoDaLiDa 2017 Workshop on… - [Cross-lingual RST Discourse Parsing](https://md.research.elamur.ai/free/en/papers/braud-2017-cross-lingual-rst-discourse-parsing/) — Chloé Braud, Maximin Coavoux, Anders Søgaard · Proceedings of the 15th Conference of the… - [Cross-Sentence N-ary Relation Extraction with Graph LSTMs](https://md.research.elamur.ai/free/en/papers/peng-2017-cross-sentence-n-ary-relation/) — Nanyun Peng, Hoifung Poon, Chris Quirk, et al. · Transactions of the Association for… - [Crossroads between contrastive linguistics, translation studies and machine translation: TC3-II](https://md.research.elamur.ai/free/en/papers/czulo-2017-crossroads-between-contrastive-linguistics/) — Oliver Czulo, Silvia Hansen-schirra · Machine translation - [Crowdsourcing Multiple Choice Science Questions](https://md.research.elamur.ai/free/en/papers/welbl-2017-crowdsourcing-multiple-choice-science-questions/) — Johannes Welbl, Nelson F. Liu, Matt Gardner · Proceedings of the 3rd Workshop on Noisy… - [DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset](https://md.research.elamur.ai/free/en/papers/li-2017-dailydialog-manually-labelled-multi-turn/) — Yanran Li, Hui Su, Xiaoyu Shen, et al. · arXiv:1710.03957 - [Data Augmentation for Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/fadaee-2017-data-augmentation-low-resource-neural/) — Marzieh Fadaee, Arianna Bisazza, Christof Monz · Proceedings of the 55th Annual Meeting of the… - [Data Augmentation for Morphological Reinflection](https://md.research.elamur.ai/free/en/papers/silfverberg-2017-data-augmentation-morphological-reinflection/) — Miikka Silfverberg, Adam Wiemerslage, Ling Liu, et al. · Proceedings of the CoNLL SIGMORPHON 2017 Shared… - [DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/baziotis-2017-datastories-semeval-2017-task-4/) — Christos Baziotis, Nikos Pelekis, Christos Doulkeridis · Proceedings of the 11th International Workshop… - [Deal or No Deal? End-to-End Learning of Negotiation Dialogues](https://md.research.elamur.ai/free/en/papers/lewis-2017-deal-or-no-deal-end/) — Mike Lewis, Denis Yarats, Yann Dauphin, et al. · Proceedings of the 2017 Conference on Empirical… - [Dealing with Co-reference in Neural Semantic Parsing](https://md.research.elamur.ai/free/en/papers/noord-2017-dealing-co-reference-neural-semantic/) — Rik van Noord, Johan Bos · Proceedings of the 2nd Workshop on Semantic… - [Deep Keyphrase Generation](https://md.research.elamur.ai/free/en/papers/meng-2017-deep-keyphrase-generation/) — Rui Meng, Sanqiang Zhao, Shuguang Han, et al. · Proceedings of the 55th Annual Meeting of the… - [Deep Semantic Role Labeling with Self-Attention](https://md.research.elamur.ai/free/en/papers/tan-2017-deep-semantic-role-labeling-self/) — Zhixing Tan, Mingxuan Wang, Jun Xie, et al. · arXiv:1712.01586 - [Deep Semantic Role Labeling: What Works and What's Next](https://md.research.elamur.ai/free/en/papers/he-2017-deep-semantic-role-labeling-what/) — Luheng He, Kenton Lee, Mike Lewis, et al. · English - [Dependency Tree Transformation with Tree Transducers](https://md.research.elamur.ai/free/en/papers/hennig-2017-dependency-tree-transformation-tree-transducers/) — Felix Hennig, Arne Köhn · Machine translation **1** [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](https://md.research.elamur.ai/free/en/papers/2017/page/4/) [next →](https://md.research.elamur.ai/free/en/papers/2017/page/2/)