--- title: "Papers of 2017 — page 2" 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/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2017/page/2/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2017 # Papers of 2017 — page 2 331 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2017/) [1](https://md.research.elamur.ai/free/en/papers/2017/) **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/3/) - [Depression and Self-Harm Risk Assessment in Online Forums](https://md.research.elamur.ai/free/en/papers/yates-2017-depression-self-harm-risk-assessment/) — Andrew Yates, Arman Cohan, Nazli Goharian · Proceedings of the 2017 Conference on Empirical… - [Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning](https://md.research.elamur.ai/free/en/papers/ma-2017-detect-rumors-microblog-posts-propagation/) — Jing Ma, Wei Gao, Kam-Fai Wong · Proceedings of the 55th Annual Meeting of the… - [Detecting Sarcasm Using Different Forms Of Incongruity](https://md.research.elamur.ai/free/en/papers/joshi-2017-detecting-sarcasm-different-forms-incongruity/) — Aditya Joshi · English - [Dialogue Act Sequence Labeling using Hierarchical encoder with CRF](https://md.research.elamur.ai/free/en/papers/kumar-2017-dialogue-act-sequence-labeling-using/) — Harshit Kumar, Arvind Agarwal, Riddhiman Dasgupta, et al. · arXiv:1709.04250 - [Discourse Markers in Speech: Distinctive Features and Corpus Annotation](https://md.research.elamur.ai/free/en/papers/crible-2017-discourse-markers-speech-distinctive-features/) — Ludivine Crible, Maria-Josep Cuenca · English - [Discourse Structure in Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/joty-2017-discourse-structure-machine-translation-evaluation/) — Shafiq Joty, Francisco Guzmán, Lluís Màrquez, et al. · Computational Linguistics - [Don't Throw Those Morphological Analyzers Away Just Yet: Neural Morphological Disambiguation for Arabic](https://md.research.elamur.ai/free/en/papers/aclbulk-2017-zalmout-don-t-throw-those-morphological/) — Nasser Zalmout, Nizar Habash · Semitic languages - [DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications](https://md.research.elamur.ai/free/en/papers/he-2017-dureader-chinese-machine-reading/) — Wei He, Kai Liu, Jing Liu, et al. · arXiv:1711.05073 - [DyNet: The Dynamic Neural Network Toolkit](https://md.research.elamur.ai/free/en/papers/neubig-2017-dynet-dynamic-neural-network-toolkit/) — Graham Neubig, Chris Dyer, Yoav Goldberg, et al. · arXiv:1701.03980 - [Effective Domain Mixing for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/britz-2017-effective-domain-mixing-neural-machine/) — Denny Britz, Quoc Le, Reid Pryzant · Proceedings of the Second Conference on Machine… - [EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/mageed-2017-emonet-fine-grained-emotion-detection/) — Muhammad Abdul-Mageed, Lyle Ungar · Proceedings of the 55th Annual Meeting of the… - [Emotion Intensities in Tweets](https://md.research.elamur.ai/free/en/papers/mohammad-2017-emotion-intensities-tweets/) — Saif Mohammad, Felipe Bravo-Marquez · Proceedings of the 6th Joint Conference on… - [Employing Language Typology for Teaching Biblical Hebrew: A Test Case in Cantonese-Chinese](https://md.research.elamur.ai/free/en/papers/chau-2017-employing-language-typology-teaching-biblical/) — Kevin Chau · Old Testament Essays 30 - [Empower Sequence Labeling with Task-Aware Neural Language Model](https://md.research.elamur.ai/free/en/papers/liu-2017-empower-sequence-labeling-task-aware/) — Liyuan Liu, Jingbo Shang, Frank F. Xu, et al. · arXiv:1709.04109 - [Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling](https://md.research.elamur.ai/free/en/papers/marcheggiani-2017-encoding-sentences-graph-convolutional-networks/) — Diego Marcheggiani, Ivan Titov · arXiv:1703.04826 - [End-to-end Neural Coreference Resolution](https://md.research.elamur.ai/free/en/papers/lee-2017-end-end-neural-coreference-resolution/) — Kenton Lee, Luheng He, Mike Lewis, et al. · English - [End-to-End Task-Completion Neural Dialogue Systems](https://md.research.elamur.ai/free/en/papers/li-2017-end-end-task-completion-neural/) — Xiujun Li, Yun-Nung Chen, Lihong Li, et al. · Proceedings of the Eighth International Joint… - [English Multiword Expression-aware Dependency Parsing Including Named Entities](https://md.research.elamur.ai/free/en/papers/aclbulk-2017-kato-english-multiword-expression-aware-dependency/) — Akihiko Kato, Hiroyuki Shindo, Yuji Matsumoto · English - [Enhanced UD Dependencies with Neutralized Diathesis Alternation](https://md.research.elamur.ai/free/en/papers/ud-2017-candito-enhanced-ud-dependencies-neutralized-diathesis/) — Marie Candito, Bruno Guillaume, Guy Perrier, et al. · English - [Ethical Research Protocols for Social Media Health Research](https://md.research.elamur.ai/free/en/papers/benton-2017-ethical-research-protocols-social-media/) — Adrian Benton, Glen Coppersmith, Mark Dredze · Proceedings of the First ACL Workshop on Ethics… - [Evaluating Discourse Phenomena in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/bawden-2017-evaluating-discourse-phenomena-neural-machine/) — Rachel Bawden, Rico Sennrich, Alexandra Birch, et al. · arXiv:1711.00513 - [Evaluating prose style transfer with the Bible](https://md.research.elamur.ai/free/en/papers/carlson-2017-evaluating-prose-style-transfer-bible/) — Keith Carlson, Allen Riddell, Daniel Rockmore · Machine translation - [Evaluation of Finite State Morphological Analyzers Based on Paradigm Extraction from Wiktionary](https://md.research.elamur.ai/free/en/papers/lex-2017-liu-fst-paradigm-extraction-wiktionary/) — Ling Liu, Mans Hulden · English - [Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events](https://md.research.elamur.ai/free/en/papers/choubey-2017-event-coreference-resolution-iteratively-unfolding/) — Prafulla Kumar Choubey, Ruihong Huang · Proceedings of the 2017 Conference on Empirical… - [Event Detection Using Frame-Semantic Parser](https://md.research.elamur.ai/free/en/papers/spiliopoulou-2017-event-detection-frame-semantic-parser/) — Evangelia Spiliopoulou, Eduard Hovy, Teruko Mitamura · Proceedings of the Events and Stories in the… - [Examples and Specifications that Prove a Point: Identifying Elaborative and Argumentative Discourse Relations](https://md.research.elamur.ai/free/en/papers/scholman-2017-examples-specifications-that-prove-point/) — Merel C.J. Scholman, Vera Demberg · Research library - [Explanation in Artificial Intelligence: Insights from the Social Sciences](https://md.research.elamur.ai/free/en/papers/miller-2017-explanation-artificial-intelligence-insights-social/) — Tim Miller · arXiv:1706.07269 - [Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms](https://md.research.elamur.ai/free/en/papers/liu-2017-exploiting-argument-information-improve-event/) — Shulin Liu, Yubo Chen, Kang Liu, et al. · Proceedings of the 55th Annual Meeting of the… - [Exploiting Cross-Sentence Context for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2017-exploiting-cross-sentence-context-neural/) — Longyue Wang, Zhaopeng Tu, Andy Way, et al. · Proceedings of the 2017 Conference on Empirical… - [Exploring Joint Neural Model for Sentence Level Discourse Parsing and Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/nejat-2017-exploring-joint-neural-model-sentence/) — Bita Nejat, Giuseppe Carenini, Raymond Ng · Proceedings of the 18th Annual SIGdial Meeting… - [Exploring Neural Text Simplification Models](https://md.research.elamur.ai/free/en/papers/nisioi-2017-exploring-neural-text-simplification-models/) — Sergiu Nisioi, Sanja Štajner, Simone Paolo Ponzetto, et al. · Proceedings of the 55th Annual Meeting of the… - [Exploring the Impact of Pragmatic Phenomena on Irony Detection in Tweets: A Multilingual Corpus Study](https://md.research.elamur.ai/free/en/papers/karoui-2017-exploring-impact-pragmatic-phenomena-irony/) — Jihen Karoui, Farah Benamara, Véronique Moriceau, et al. · Proceedings of the 15th Conference of the… - [Fast and Accurate Entity Recognition with Iterated Dilated Convolutions](https://md.research.elamur.ai/free/en/papers/strubell-2017-fast-accurate-entity-recognition-iterated/) — Emma Strubell, Patrick Verga, David Belanger, et al. · Proceedings of the 2017 Conference on Empirical… - [FiLM: Visual Reasoning with a General Conditioning Layer](https://md.research.elamur.ai/free/en/papers/perez-2017-film-visual-reasoning-general-conditioning/) — Ethan Perez, Florian Strub, Harm de Vries, et al. · arXiv:1709.07871 - [Findings of the 2017 Conference on Machine Translation (WMT17)](https://md.research.elamur.ai/free/en/papers/bojar-2017-findings-2017-conference-machine-translation/) — Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al. · Proceedings of the Second Conference on Machine… - [Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description](https://md.research.elamur.ai/free/en/papers/elliott-2017-findings-second-shared-task-multimodal/) — Desmond Elliott, Stella Frank, Loïc Barrault, et al. · Proceedings of the Second Conference on Machine… - [Findings of the VarDial Evaluation Campaign 2017](https://md.research.elamur.ai/free/en/papers/zampieri-2017-findings-vardial-evaluation-campaign/) — Marcos Zampieri, Shervin Malmasi, Nikola Ljubešić, et al. · VarDial 2017 - [Findings of the WMT 2017 Biomedical Translation Shared Task](https://md.research.elamur.ai/free/en/papers/yepes-2017-findings-wmt-2017-biomedical-translation/) — Antonio Jimeno Yepes, Aurélie Névéol, Mariana Neves, et al. · Proceedings of the Second Conference on Machine… - [Fixing the Infix: Unsupervised Discovery of Root-and-Pattern Morphology](https://md.research.elamur.ai/free/en/papers/langstream-2017-sakakini-fixing-infix-unsupervised-discovery-root/) — Tarek Sakakini, Suma Bhat, Pramod Viswanath · Semitic languages - [Focal Loss for Dense Object Detection](https://md.research.elamur.ai/free/en/papers/lin-2017-focal-loss-dense-object-detection/) — Tsung-Yi Lin, Priya Goyal, Ross Girshick, et al. · arXiv:1708.02002 - [Frame-Semantic Parsing with Softmax-Margin Segmental RNNs and a Syntactic Scaffold](https://md.research.elamur.ai/free/en/papers/swayamdipta-2017-frame-semantic-parsing-softmax-margin/) — Swabha Swayamdipta, Sam Thomson, Chris Dyer, et al. · arXiv:1706.09528 - [Frames: a corpus for adding memory to goal-oriented dialogue systems](https://md.research.elamur.ai/free/en/papers/asri-2017-frames-corpus-adding-memory-goal/) — Layla El Asri, Hannes Schulz, Shikhar Sharma, et al. · Proceedings of the 18th Annual SIGdial Meeting… - [From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood](https://md.research.elamur.ai/free/en/papers/guu-2017-language-programs-bridging-reinforcement-learning/) — Kelvin Guu, Panupong Pasupat, Evan Liu, et al. · Proceedings of the 55th Annual Meeting of the… - [From Shakespeare to Twitter: What are Language Styles all about?](https://md.research.elamur.ai/free/en/papers/xu-2017-shakespeare-twitter-what-are-language/) — Wei Xu · Machine translation - [Fronting and exhaustive exclusion in Biblical Hebrew](https://md.research.elamur.ai/free/en/papers/hbo-2018-merwe-fronting-exhaustive-exclusion-biblical-hebrew/) — Christo van der Merwe · Ancient Hebrew - [Fully Character-Level Neural Machine Translation without Explicit Segmentation](https://md.research.elamur.ai/free/en/papers/lee-2017-fully-character-level-neural-machine/) — Jason Lee, Kyunghyun Cho, Thomas Hofmann · Transactions of the Association for… - [Gapping Constructions in Universal Dependencies v2](https://md.research.elamur.ai/free/en/papers/ud-2017-schuster-gapping-constructions-universal-dependencies-v2/) — Sebastian Schuster, Matthew Lamm, Christopher D. Manning · English - [Gated Self-Matching Networks for Reading Comprehension and Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2017-gated-self-matching-networks-reading/) — Wenhui Wang, Nan Yang, Furu Wei, et al. · Proceedings of the 55th Annual Meeting of the… - [Gender and Dialect Bias in YouTube's Automatic Captions](https://md.research.elamur.ai/free/en/papers/tatman-2017-gender-dialect-bias-youtube-s/) — Rachael Tatman · Proceedings of the First ACL Workshop on Ethics… - [Gender exponence and apparent polarity in a class of Omani Mehri plurals](https://md.research.elamur.ai/free/en/papers/lingbulk-2017-fathi-gender-exponence-apparent-polarity-class/) — Radwa Fathi · Semitic languages - [Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution](https://md.research.elamur.ai/free/en/papers/liu-2017-generating-exploiting-large-scale-pseudo/) — Ting Liu, Yiming Cui, Qingyu Yin, et al. · Proceedings of the 55th Annual Meeting of the… - [Generating Sentences by Editing Prototypes](https://md.research.elamur.ai/free/en/papers/guu-2017-generating-sentences-editing-prototypes/) — Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, et al. · arXiv:1709.08878 - [Get that into your head: Tigre vowel harmonies as templatic](https://md.research.elamur.ai/free/en/papers/lingbulk-2017-faust-get-that-into-your-head/) — Noam Faust · Semitic languages - [Graph Attention Networks](https://md.research.elamur.ai/free/en/papers/veli-2017-vckovic-graph-attention-networks/) — Petar Veličkovic, Guillem Cucurull, Arantxa Casanova, et al. · arXiv:1710.10903 - [Graph Convolutional Encoders for Syntax-aware Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/bastings-2017-graph-convolutional-encoders-syntax-aware/) — Jasmijn Bastings, Ivan Titov, Wilker Aziz, et al. · Proceedings of the 2017 Conference on Empirical… - [Graph-based Neural Multi-Document Summarization](https://md.research.elamur.ai/free/en/papers/yasunaga-2017-graph-based-neural-multi-document/) — Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, et al. · Proceedings of the 21st Conference on… - [Guided Open Vocabulary Image Captioning with Constrained Beam Search](https://md.research.elamur.ai/free/en/papers/anderson-2017-guided-open-vocabulary-image-captioning/) — Peter Anderson, Basura Fernando, Mark Johnson, et al. · Proceedings of the 2017 Conference on Empirical… - [hdbscan: Hierarchical density based clustering](https://md.research.elamur.ai/free/en/papers/mcinnes-2017-hdbscan-hierarchical-density-clustering/) — Leland McInnes, John Healy, Steve Astels · Journal of Open Source Software 2(11) - [How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairs](https://md.research.elamur.ai/free/en/papers/sennrich-2017-how-grammatical-is-character-level/) — Rico Sennrich · Proceedings of the 15th Conference of the… - [How much progress have we made on RST discourse parsing? A replication study of recent results on the RST-DT](https://md.research.elamur.ai/free/en/papers/morey-2017-how-much-progress-have-we/) — Mathieu Morey, Philippe Muller, Nicholas Asher · English - [Identifying beneficial task relations for multi-task learning in deep neural networks](https://md.research.elamur.ai/free/en/papers/bingel-2017-identifying-beneficial-task-relations-multi/) — Joachim Bingel, Anders Søgaard · Proceedings of the 15th Conference of the… - [Improved Neural Machine Translation with a Syntax-Aware Encoder and Decoder](https://md.research.elamur.ai/free/en/papers/chen-2017-improved-neural-machine-translation-syntax/) — Huadong Chen, Shujian Huang, David Chiang, et al. · Proceedings of the 55th Annual Meeting of the… - [Improving a Strong Neural Parser with Conjunction-Specific Features](https://md.research.elamur.ai/free/en/papers/aclbulk-2017-ficler-improving-strong-neural-parser-conjunction/) — Jessica Ficler, Yoav Goldberg · English - [Improving Implicit Discourse Relation Recognition with Discourse-specific Word Embeddings](https://md.research.elamur.ai/free/en/papers/wu-2017-improving-implicit-discourse-relation-recognition/) — Changxing Wu, Xiaodong Shi, Yidong Chen, et al. · Proceedings of the 55th Annual Meeting of the… - [Improving Word Sense Disambiguation in Neural Machine Translation with Sense Embeddings](https://md.research.elamur.ai/free/en/papers/gonzales-2017-improving-word-sense-disambiguation-neural/) — Annette Rios Gonzales, Laura Mascarell, Rico Sennrich · Proceedings of the Second Conference on Machine… - [Inductive Representation Learning on Large Graphs](https://md.research.elamur.ai/free/en/papers/hamilton-2017-inductive-representation-learning-large-graphs/) — William L. Hamilton, Rex Ying, Jure Leskovec · arXiv:1706.02216 - [Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework](https://md.research.elamur.ai/free/en/papers/white-2017-inference-is-everything-recasting-semantic/) — Aaron Steven White, Pushpendre Rastogi, Kevin Duh, et al. · English - [Initial Explorations of CCG Supertagging for Universal Dependency Parsing](https://md.research.elamur.ai/free/en/papers/akkus-2017-initial-explorations-ccg-supertagging-universal/) — Burak Kerim Akkus, Heval Azizoglu, Ruket Cakici · Proceedings of the CoNLL 2017 Shared Task… - [Integrating syntactic theory and variationist analysis: The structure of negative indefinites in regional dialects of British English](https://md.research.elamur.ai/free/en/papers/childs-2017-integrating-syntactic-theory-variationist-analysis/) — Claire Childs · English - [Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme](https://md.research.elamur.ai/free/en/papers/zheng-2017-joint-extraction-entities-relations-based/) — Suncong Zheng, Feng Wang, Hongyun Bao, et al. · Proceedings of the 55th Annual Meeting of the… - [Joint Prediction of Morphosyntactic Categories for Fine-Grained Arabic Part-of-Speech Tagging Exploiting Tag Dictionary Information](https://md.research.elamur.ai/free/en/papers/lingbulk-2017-inoue-joint-prediction-morphosyntactic-categories-fine/) — Go Inoue, Hiroyuki Shindo, Yuji Matsumoto · Semitic languages - [Joint Syntacto-Discourse Parsing and the Syntacto-Discourse Treebank](https://md.research.elamur.ai/free/en/papers/zhao-2017-joint-syntacto-discourse-parsing-syntacto/) — Kai Zhao, Liang Huang · English - [Language contact and the genesis of Mishnaic Hebrew](https://md.research.elamur.ai/free/en/papers/hbo-2017-cook-language-contact-genesis-mishnaic-hebrew/) — Edward M. Cook · Ancient Hebrew - [Learned in Translation: Contextualized Word Vectors](https://md.research.elamur.ai/free/en/papers/mccann-2017-learned-translation-contextualized-word-vectors/) — Bryan McCann, James Bradbury, Caiming Xiong, et al. · arXiv:1708.00107 - [Learning attention for historical text normalization by learning to pronounce](https://md.research.elamur.ai/free/en/papers/aclbulk-2017-bollmann-learning-attention-historical-text-normalization/) — Marcel Bollmann, Joachim Bingel, Anders Søgaard · English - [Learning bilingual word embeddings with (almost) no bilingual data](https://md.research.elamur.ai/free/en/papers/artetxe-2017-learning-bilingual-word-embeddings-almost/) — Mikel Artetxe, Gorka Labaka, Eneko Agirre · Proceedings of the 55th Annual Meeting of the… - [Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural Network](https://md.research.elamur.ai/free/en/papers/mishra-2017-learning-cognitive-features-gaze-data/) — Abhijit Mishra, Kuntal Dey, Pushpak Bhattacharyya · Proceedings of the 55th Annual Meeting of the… - [Learning Contextually Informed Representations for Linear-Time Discourse Parsing](https://md.research.elamur.ai/free/en/papers/liu-2017-learning-contextually-informed-representations-linear/) — Yang Liu, Mirella Lapata · Proceedings of the 2017 Conference on Empirical… - [Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders](https://md.research.elamur.ai/free/en/papers/zhao-2017-learning-discourse-level-diversity-neural/) — Tiancheng Zhao, Ran Zhao, Maxine Eskenazi · Proceedings of the 55th Annual Meeting of the… - [Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs](https://md.research.elamur.ai/free/en/papers/manchego-2017-learning-how-simplify-explicit-labeling/) — Fernando Alva-Manchego, Joachim Bingel, Gustavo Paetzold, et al. · Machine translation - [Learning Important Features Through Propagating Activation Differences](https://md.research.elamur.ai/free/en/papers/shrikumar-2017-learning-important-features-through-propagating/) — Avanti Shrikumar, Peyton Greenside, Anshul Kundaje · arXiv:1704.02685 · PMLR 70:3145-3153, 2017 - [Learning Joint Multilingual Sentence Representations with Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/schwenk-2017-learning-joint-multilingual-sentence-representations/) — Holger Schwenk, Matthijs Douze · Proceedings of the 2nd Workshop on… - [Learning multiple visual domains with residual adapters](https://md.research.elamur.ai/free/en/papers/rebuffi-2017-learning-multiple-visual-domains-residual/) — Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi · arXiv:1705.08045 - [Learning to Ask: Neural Question Generation for Reading Comprehension](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/) — Xinya Du, Junru Shao, Claire Cardie · arXiv:1705.00106 - [Learning to Generate Reviews and Discovering Sentiment](https://md.research.elamur.ai/free/en/papers/radford-2017-learning-generate-reviews-discovering-sentiment/) — Alec Radford, Rafal Jozefowicz, Ilya Sutskever · arXiv:1704.01444 - [Learning to Paraphrase for Question Answering](https://md.research.elamur.ai/free/en/papers/dong-2017-learning-paraphrase-question-answering/) — Li Dong, Jonathan Mallinson, Siva Reddy, et al. · Proceedings of the 2017 Conference on Empirical… - [Learning to Parse and Translate Improves Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/eriguchi-2017-learning-parse-translate-improves-neural/) — Akiko Eriguchi, Yoshimasa Tsuruoka, Kyunghyun Cho · Proceedings of the 55th Annual Meeting of the… - [Learning to Translate in Real-time with Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gu-2017-learning-translate-real-time-neural/) — Jiatao Gu, Graham Neubig, Kyunghyun Cho, et al. · Proceedings of the 15th Conference of the… - [Learning Transferable Architectures for Scalable Image Recognition](https://md.research.elamur.ai/free/en/papers/zoph-2017-learning-transferable-architectures-scalable-image/) — Barret Zoph, Vijay Vasudevan, Jonathon Shlens, et al. · arXiv:1707.07012 - [Learning with learner corpora: Using the TLE for native language identification](https://md.research.elamur.ai/free/en/papers/adams-2017-learning-learner-corpora-tle-native/) — Allison Adams, Sara Stymne · Proceedings of the joint workshop on NLP for… - [Lexical Features in Coreference Resolution: To be Used With Caution](https://md.research.elamur.ai/free/en/papers/moosavi-2017-lexical-features-coreference-resolution-be/) — Nafise Sadat Moosavi, Michael Strube · English - [Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search](https://md.research.elamur.ai/free/en/papers/hokamp-2017-lexically-constrained-decoding-sequence-generation/) — Chris Hokamp, Qun Liu · Proceedings of the 55th Annual Meeting of the… - [LIMSI@CoNLL'17: UD Shared Task](https://md.research.elamur.ai/free/en/papers/aufrant-2017-limsi-conll-17-ud-shared/) — Lauriane Aufrant, Guillaume Wisniewski, François Yvon · Proceedings of the CoNLL 2017 Shared Task… - [Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation](https://md.research.elamur.ai/free/en/papers/ferreira-2017-linguistic-realisation-as-machine-translation/) — Thiago Castro Ferreira, Iacer Calixto, Sander Wubben, et al. · Machine translation - [Magnets for Sarcasm: Making Sarcasm Detection Timely, Contextual and Very Personal](https://md.research.elamur.ai/free/en/papers/ghosh-2017-magnets-sarcasm-making-sarcasm-detection/) — Aniruddha Ghosh, Tony Veale · Proceedings of the 2017 Conference on Empirical… - [Massive Exploration of Neural Machine Translation Architectures](https://md.research.elamur.ai/free/en/papers/britz-2017-massive-exploration-neural-machine-translation/) — Denny Britz, Anna Goldie, Minh-Thang Luong, et al. · Proceedings of the 2017 Conference on Empirical… - [Mastering chess and shogi by self-play with a general reinforcement learning algorithm](https://md.research.elamur.ai/free/en/papers/al-2017-mastering-chess-shogi-self-play/) — Research library - [MEANT 2.0: Accurate semantic MT evaluation for any output language](https://md.research.elamur.ai/free/en/papers/lo-2017-meant-2-0-accurate-semantic/) — Chi-kiu Lo · Machine translation - [Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints](https://md.research.elamur.ai/free/en/papers/zhao-2017-men-also-like-shopping-reducing/) — Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al. · Proceedings of the 2017 Conference on Empirical… - [mixup: Beyond Empirical Risk Minimization](https://md.research.elamur.ai/free/en/papers/zhang-2017-mixup-empirical-risk-minimization/) — Hongyi Zhang, Moustapha Cisse, Yann N. 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