--- title: "Papers of 2016 — page 3" description: "Papers of 2016: 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/2016/page/3/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/2016/page/3/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / 2016 # Papers of 2016 — page 3 331 papers · [all years](https://md.research.elamur.ai/free/en/papers/) [← prev](https://md.research.elamur.ai/free/en/papers/2016/page/2/) [1](https://md.research.elamur.ai/free/en/papers/2016/) [2](https://md.research.elamur.ai/free/en/papers/2016/page/2/) **3** [4](https://md.research.elamur.ai/free/en/papers/2016/page/4/) [next →](https://md.research.elamur.ai/free/en/papers/2016/page/4/) - [Merged bilingual trees based on Universal Dependencies in Machine Translation](https://md.research.elamur.ai/free/en/papers/marecek-2016-merged-bilingual-trees-based-universal/) — David Mareček · Machine translation - [Metaphor as a Medium for Emotion: An Empirical Study](https://md.research.elamur.ai/free/en/papers/mohammad-2016-metaphor-as-medium-emotion-empirical/) — Saif Mohammad, Ekaterina Shutova, Peter Turney · Proceedings of the Fifth Joint Conference on… - [MIMIC-III, a freely accessible critical care database](https://md.research.elamur.ai/free/en/papers/johnson-2016-mimic-iii-freely-accessible-critical/) — Alistair E. W. Johnson, Tom Pollard, Lu Shen, et al. · Scientific Data - [MITRE at SemEval-2016 Task 6: Transfer Learning for Stance Detection](https://md.research.elamur.ai/free/en/papers/zarrella-2016-mitre-semeval-2016-task-6/) — Guido Zarrella, Amy Marsh · Proceedings of the 10th International Workshop… - [Modeling Context in Referring Expressions](https://md.research.elamur.ai/free/en/papers/yu-2016-modeling-context-referring-expressions/) — Licheng Yu, Patrick Poirson, Shan Yang, et al. · arXiv:1608.00272 - [Modeling Coverage for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/tu-2016-modeling-coverage-neural-machine-translation/) — Zhaopeng Tu, Zhengdong Lu, Yang Liu, et al. · Proceedings of the 54th Annual Meeting of the… - [Modelling Context with User Embeddings for Sarcasm Detection in Social Media](https://md.research.elamur.ai/free/en/papers/amir-2016-modelling-context-user-embeddings-sarcasm/) — Silvio Amir, Byron C. Wallace, Hao Lyu, et al. · Proceedings of the 20th SIGNLL Conference on… - [Modelling the Usage of Discourse Connectives as Rational Speech Acts](https://md.research.elamur.ai/free/en/papers/yung-2016-modelling-usage-discourse-connectives-as/) — Frances Yung, Kevin Duh, Taku Komura, et al. · English - [Monday mornings are my fave :) #not Exploring the Automatic Recognition of Irony in English tweets](https://md.research.elamur.ai/free/en/papers/hee-2016-monday-mornings-are-my-fave/) — Cynthia Van Hee, Els Lefever, Véronique Hoste · English - [MS MARCO: A Human Generated MAchine Reading COmprehension Dataset](https://md.research.elamur.ai/free/en/papers/bajaj-2016-ms-marco-human-generated/) — Payal Bajaj, Daniel Campos, Nick Craswell, et al. · arXiv:1611.09268 - [Multi-level Gated Recurrent Neural Network for dialog act classification](https://md.research.elamur.ai/free/en/papers/li-2016-multi-level-gated-recurrent-neural/) — Wei Li, Yunfang Wu · Proceedings of COLING 2016, the 26th… - [Multi-Source Neural Translation](https://md.research.elamur.ai/free/en/papers/zoph-2016-multi-source-neural-translation/) — Barret Zoph, Kevin Knight · Proceedings of the 2016 Conference of the North… - [Multi-view and multi-task training of RST discourse parsers](https://md.research.elamur.ai/free/en/papers/braud-2016-multi-view-multi-task-training/) — Chloé Braud, Barbara Plank, Anders Søgaard · Proceedings of COLING 2016, the 26th… - [Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism](https://md.research.elamur.ai/free/en/papers/firat-2016-multi-way-multilingual-neural-machine/) — Orhan Firat, Kyunghyun Cho, Yoshua Bengio · Proceedings of the 2016 Conference of the North… - [Multi30K: Multilingual English-German Image Descriptions](https://md.research.elamur.ai/free/en/papers/elliott-2016-multi30k-multilingual-english-german-image/) — Desmond Elliott, Stella Frank, Khalil Sima'an, et al. · arXiv:1605.00459 - [Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss](https://md.research.elamur.ai/free/en/papers/plank-2016-multilingual-part-speech-tagging-bidirectional/) — Barbara Plank, Anders Søgaard, Yoav Goldberg · arXiv:1604.05529 - [Multilingual Projection for Parsing Truly Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/agic-2016-multilingual-projection-parsing-truly-low/) — Željko Agić, Anders Johannsen, Barbara Plank, et al. · Transactions of the Association for… - [Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding](https://md.research.elamur.ai/free/en/papers/fukui-2016-multimodal-compact-bilinear-pooling-visual/) — Akira Fukui, Dong Huk Park, Daylen Yang, et al. · Proceedings of the 2016 Conference on Empirical… - [MWEs in Treebanks: From Survey to Guidelines](https://md.research.elamur.ai/free/en/papers/bank-2016-rosen-mwes-treebanks-survey-guidelines/) — Victoria Rosén, Koenraad De Smedt, Gyri Smørdal Losnegaard, et al. · English - [Natural Language Inference by Tree-Based Convolution and Heuristic Matching](https://md.research.elamur.ai/free/en/papers/mou-2016-natural-language-inference-tree-based/) — Lili Mou, Rui Men, Ge Li, et al. · Proceedings of the 54th Annual Meeting of the… - [Neural Architecture Search with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zoph-2016-neural-architecture-search-reinforcement-learning/) — Barret Zoph, Quoc V. Le · arXiv:1611.01578 - [Neural Network Translation Models for Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/chollampatt-2016-neural-network-translation-models-grammatical/) — Shamil Chollampatt, Kaveh Taghipour, Hwee Tou Ng · arXiv:1606.00189 - [Neural Paraphrase Generation with Stacked Residual LSTM Networks](https://md.research.elamur.ai/free/en/papers/prakash-2016-neural-paraphrase-generation-stacked-residual/) — Aaditya Prakash, Sadid A. Hasan, Kathy Lee, et al. · Proceedings of COLING 2016, the 26th… - [Neural Semantic Role Labeling with Dependency Path Embeddings](https://md.research.elamur.ai/free/en/papers/roth-2016-neural-semantic-role-labeling-dependency/) — Michael Roth, Mirella Lapata · Proceedings of the 54th Annual Meeting of the… - [Neural Summarization by Extracting Sentences and Words](https://md.research.elamur.ai/free/en/papers/cheng-2016-neural-summarization-extracting-sentences-words/) — Jianpeng Cheng, Mirella Lapata · Proceedings of the 54th Annual Meeting of the… - [Neural Text Generation from Structured Data with Application to the Biography Domain](https://md.research.elamur.ai/free/en/papers/lebret-2016-neural-text-generation-structured-data/) — Remi Lebret, David Grangier, Michael Auli · arXiv:1603.07771 - [Neural versus Phrase-Based Machine Translation Quality: a Case Study](https://md.research.elamur.ai/free/en/papers/bentivogli-2016-neural-versus-phrase-based-machine/) — Luisa Bentivogli, Arianna Bisazza, Mauro Cettolo, et al. · Proceedings of the 2016 Conference on Empirical… - [OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles](https://md.research.elamur.ai/free/en/papers/lison-2016-opensubtitles2016-extracting-large-parallel-corpora/) — Pierre Lison, Jörg Tiedemann · Proceedings of the Tenth International… - [OPT: Oslo–Potsdam–Teesside. Pipelining Rules, Rankers, and Classifier Ensembles for Shallow Discourse Parsing](https://md.research.elamur.ai/free/en/papers/oepen-2016-opt-oslo-potsdam-teesside-pipelining/) — Stephan Oepen, Jonathon Read, Tatjana Scheffler, et al. · Proceedings of the CoNLL-16 shared task - [Optimizing Statistical Machine Translation for Text Simplification](https://md.research.elamur.ai/free/en/papers/xu-2016-optimizing-statistical-machine-translation-text/) — Wei Xu, Courtney Napoles, Ellie Pavlick, et al. · Machine translation - [Parallel Texts in the Hebrew Bible, New Methods and Visualizations](https://md.research.elamur.ai/free/en/papers/hbo-2016-naaijer-parallel-texts-hebrew-bible-new/) — Martijn Naaijer, Dirk Roorda · Ancient Hebrew - [Part-of-Speech Tagging for Historical English](https://md.research.elamur.ai/free/en/papers/aclbulk-2016-yang-part-speech-tagging-historical-english/) — Yi Yang, Jacob Eisenstein · English - [Participant-Reference Shifts in Zech. 1:1-6. An Assessment of Diachronic and Synchronic Approaches](https://md.research.elamur.ai/free/en/papers/hbo-2016-jensen-participant-reference-shifts-zech-1/) — Christian Højgaard Jensen · Ancient Hebrew - [Phrase Detectives Corpus 1.0 Crowdsourced Anaphoric Coreference.](https://md.research.elamur.ai/free/en/papers/chamberlain-2016-phrase-detectives-corpus-1-0/) — Jon Chamberlain, Massimo Poesio, Udo Kruschwitz · Proceedings of the Tenth International… - [pkudblab at SemEval-2016 Task 6 : A Specific Convolutional Neural Network System for Effective Stance Detection](https://md.research.elamur.ai/free/en/papers/wei-2016-pkudblab-semeval-2016-task-6/) — Wan Wei, Xiao Zhang, Xuqin Liu, et al. · Proceedings of the 10th International Workshop… - [Pointer Sentinel Mixture Models](https://md.research.elamur.ai/free/en/papers/merity-2016-pointer-sentinel-mixture-models/) — Stephen Merity, Caiming Xiong, James Bradbury, et al. · arXiv:1609.07843 - [Pointing the Unknown Words](https://md.research.elamur.ai/free/en/papers/gulcehre-2016-pointing-unknown-words/) — Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, et al. · Proceedings of the 54th Annual Meeting of the… - [Predicting and Using a Pragmatic Component of Lexical Aspect of Simple Past Verbal Tenses for Improving English-to-French Machine Translation](https://md.research.elamur.ai/free/en/papers/loaiciga-2016-predicting-pragmatic-component-lexical-aspect/) — Sharid Loáiciga, Cristina Grisot · English - [Probing for semantic evidence of composition by means of simple classification tasks](https://md.research.elamur.ai/free/en/papers/ettinger-2016-probing-semantic-evidence-composition-means/) — Allyson Ettinger, Ahmed Elgohary, Philip Resnik · Proceedings of the 1st Workshop on Evaluating… - [Problems With Evaluation of Word Embeddings Using Word Similarity Tasks](https://md.research.elamur.ai/free/en/papers/faruqui-2016-problems-evaluation-word-embeddings-word/) — Manaal Faruqui, Yulia Tsvetkov, Pushpendre Rastogi, et al. · Proceedings of the 1st Workshop on Evaluating… - [Putting Sarcasm Detection into Context: The Effects of Class Imbalance and Manual Labelling on Supervised Machine Classification of Twitter Conversations](https://md.research.elamur.ai/free/en/papers/abercrombie-2016-putting-sarcasm-detection-into-context/) — Gavin Abercrombie, Dirk Hovy · Proceedings of the ACL 2016 Student Research… - [Question Answering on Freebase via Relation Extraction and Textual Evidence](https://md.research.elamur.ai/free/en/papers/xu-2016-question-answering-freebase-relation-extraction/) — Kun Xu, Siva Reddy, Yansong Feng, et al. · Proceedings of the 54th Annual Meeting of the… - [Rationalizing Neural Predictions](https://md.research.elamur.ai/free/en/papers/lei-2016-rationalizing-neural-predictions/) — Tao Lei, Regina Barzilay, Tommi Jaakkola · Proceedings of the 2016 Conference on Empirical… - [Reasoning about Pragmatics with Neural Listeners and Speakers](https://md.research.elamur.ai/free/en/papers/andreas-2016-reasoning-about-pragmatics-neural-listeners/) — Jacob Andreas, Dan Klein · Proceedings of the 2016 Conference on Empirical… - [Recognizing Implicit Discourse Relations via Repeated Reading: Neural Networks with Multi-Level Attention](https://md.research.elamur.ai/free/en/papers/liu-2016-recognizing-implicit-discourse-relations-repeated/) — Yang Liu, Sujian Li · Proceedings of the 2016 Conference on Empirical… - [Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/wang-2016-recursive-neural-conditional-random-fields/) — Wenya Wang, Sinno Jialin Pan, Daniel Dahlmeier, et al. · Proceedings of the 2016 Conference on Empirical… - [Relation Classification via Multi-Level Attention CNNs](https://md.research.elamur.ai/free/en/papers/wang-2016-relation-classification-multi-level-attention/) — Linlin Wang, Zhu Cao, Gerard de Melo, et al. · Proceedings of the 54th Annual Meeting of the… - [Results of the WMT16 Metrics Shared Task](https://md.research.elamur.ai/free/en/papers/bojar-2016-results-wmt16-metrics-shared-task/) — Ondřej Bojar, Yvette Graham, Amir Kamran, et al. · Proceedings of the First Conference on Machine… - [Revisiting the Evaluation for Cross Document Event Coreference](https://md.research.elamur.ai/free/en/papers/upadhyay-2016-revisiting-evaluation-cross-document-event/) — Shyam Upadhyay, Nitish Gupta, Christos Christodoulopoulos, et al. · Proceedings of COLING 2016, the 26th… - [Richer Event Description: Integrating event coreference with temporal, causal and bridging annotation](https://md.research.elamur.ai/free/en/papers/gorman-2016-richer-event-description-integrating-event/) — Tim O'Gorman, Kristin Wright-Bettner, Martha Palmer · Proceedings of the 2nd Workshop on Computing… - [Robust Non-Explicit Neural Discourse Parser in English and Chinese](https://md.research.elamur.ai/free/en/papers/rutherford-2016-robust-non-explicit-neural-discourse/) — Attapol Rutherford, Nianwen Xue · Proceedings of the CoNLL-16 shared task - [rstWeb - A Browser-based Annotation Interface for Rhetorical Structure Theory and Discourse Relations](https://md.research.elamur.ai/free/en/papers/zeldes-2016-rstweb-browser-based-annotation-interface/) — Amir Zeldes · Proceedings of the 2016 Conference of the North… - [SciCorp: A Corpus of English Scientific Articles Annotated for Information Status Analysis](https://md.research.elamur.ai/free/en/papers/roesiger-2016-scicorp-corpus-english-scientific-articles/) — Ina Roesiger · English - [Search Space Pruning: A Simple Solution for Better Coreference Resolvers](https://md.research.elamur.ai/free/en/papers/moosavi-2016-search-space-pruning-simple-solution/) — Nafise Sadat Moosavi, Michael Strube · Proceedings of the 2016 Conference of the North… - [Self-critical Sequence Training for Image Captioning](https://md.research.elamur.ai/free/en/papers/rennie-2016-self-critical-sequence-training-image/) — Steven J. Rennie, Etienne Marcheret, Youssef Mroueh, et al. · arXiv:1612.00563 - [Semantically Motivated Hebrew Verb-Noun Multi-Word Expressions Identification](https://md.research.elamur.ai/free/en/papers/aclbulk-2016-liebeskind-semantically-motivated-hebrew-verb-noun/) — Chaya Liebeskind, Yaakov HaCohen-Kerner · Modern Hebrew - [SemEval 2016 Task 11: Complex Word Identification](https://md.research.elamur.ai/free/en/papers/paetzold-2016-semeval-2016-task-11-complex/) — Gustavo Paetzold, Lucia Specia · Proceedings of the 10th International Workshop… - [SemEval-2016 Task 10: Detecting Minimal Semantic Units and their Meanings (DiMSUM)](https://md.research.elamur.ai/free/en/papers/schneider-2016-semeval-2016-task-10-detecting/) — Nathan Schneider, Dirk Hovy, Anders Johannsen, et al. · Proceedings of the 10th International Workshop… - [SemEval-2016 Task 12: Clinical TempEval](https://md.research.elamur.ai/free/en/papers/bethard-2016-semeval-2016-task-12-clinical/) — Steven Bethard, Guergana Savova, Wei-Te Chen, et al. · Proceedings of the 10th International Workshop… - [SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation](https://md.research.elamur.ai/free/en/papers/agirre-2016-semeval-2016-task-1-semantic/) — Eneko Agirre, Carmen Banea, Daniel Cer, et al. · Proceedings of the 10th International Workshop… - [SemEval-2016 Task 3: Community Question Answering](https://md.research.elamur.ai/free/en/papers/nakov-2016-semeval-2016-task-3-community/) — Preslav Nakov, Lluís Màrquez, Alessandro Moschitti, et al. · Proceedings of the 10th International Workshop… - [SemEval-2016 Task 4: Sentiment Analysis in Twitter](https://md.research.elamur.ai/free/en/papers/nakov-2016-semeval-2016-task-4-sentiment/) — Preslav Nakov, Alan Ritter, Sara Rosenthal, et al. · Proceedings of the 10th International Workshop… - [SemEval-2016 Task 5: Aspect Based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/pontiki-2016-semeval-2016-task-5-aspect/) — Maria Pontiki, Dimitris Galanis, Haris Papageorgiou, et al. · Proceedings of the 10th International Workshop… - [SemEval-2016 Task 6: Detecting Stance in Tweets](https://md.research.elamur.ai/free/en/papers/mohammad-2016-semeval-2016-task-6-detecting/) — Saif Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, et al. · Proceedings of the 10th International Workshop… - [Semi-Supervised Classification with Graph Convolutional Networks](https://md.research.elamur.ai/free/en/papers/kipf-2016-semi-supervised-classification-graph-convolutional/) — Thomas N. Kipf, Max Welling · arXiv:1609.02907 - [Sense Anaphoric Pronouns: Am I One?](https://md.research.elamur.ai/free/en/papers/recasens-2016-sense-anaphoric-pronouns-am-i/) — Marta Recasens, Zhichao Hu, Olivia Rhinehart · Proceedings of the Workshop on Coreference… - [Sequence-Level Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/kim-2016-sequence-level-knowledge-distillation/) — Yoon Kim, Alexander M. Rush · Proceedings of the 2016 Conference on Empirical… - [Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/lee-2016-sequential-short-text-classification-recurrent/) — Ji Young Lee, Franck Dernoncourt · arXiv:1603.03827 - [Shallow Discourse Parsing Using Convolutional Neural Network](https://md.research.elamur.ai/free/en/papers/qin-2016-shallow-discourse-parsing-convolutional-neural/) — Lianhui Qin, Zhisong Zhang, Hai Zhao · Proceedings of the CoNLL-16 shared task - [Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations](https://md.research.elamur.ai/free/en/papers/narrative-2016-kiperwasser-simple-accurate-dependency-parsing-bidirectional/) — Eliyahu Kiperwasser, Yoav Goldberg · English - [SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity](https://md.research.elamur.ai/free/en/papers/gerz-2016-simverb-3500-large-scale-evaluation/) — Daniela Gerz, Ivan Vulić, Felix Hill, et al. · Proceedings of the 2016 Conference on Empirical… - [Speaking to One's Heart: דבר and its Semantic Extension](https://md.research.elamur.ai/free/en/papers/hbo-2016-mylonas-speaking-one-s-heart-semantic/) — Natalie Mylonas, Stephen Llewelyn, Gareth Wearne · Ancient Hebrew - [Speech Act Modeling of Written Asynchronous Conversations with Task-Specific Embeddings and Conditional Structured Models](https://md.research.elamur.ai/free/en/papers/joty-2016-speech-act-modeling-written-asynchronous/) — Shafiq Joty, Enamul Hoque · Proceedings of the 54th Annual Meeting of the… - [SPICE: Semantic Propositional Image Caption Evaluation](https://md.research.elamur.ai/free/en/papers/anderson-2016-spice-semantic-propositional-image-caption/) — Peter Anderson, Basura Fernando, Mark Johnson, et al. · arXiv:1607.08822 - [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://md.research.elamur.ai/free/en/papers/rajpurkar-2016-squad-100-000-questions-machine/) — Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, et al. · Proceedings of the 2016 Conference on Empirical… - [Squib: Expressive Power of Abstract Meaning Representations](https://md.research.elamur.ai/free/en/papers/bos-2016-squib-expressive-power-abstract-meaning/) — Johan Bos · Machine translation - [Stance Detection with Bidirectional Conditional Encoding](https://md.research.elamur.ai/free/en/papers/augenstein-2016-stance-detection-bidirectional-conditional-encoding/) — Isabelle Augenstein, Tim Rocktäschel, Andreas Vlachos, et al. · Proceedings of the 2016 Conference on Empirical… - [SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents](https://md.research.elamur.ai/free/en/papers/nallapati-2016-summarunner-recurrent-neural-network-based/) — Ramesh Nallapati, Feifei Zhai, Bowen Zhou · arXiv:1611.04230 - [Syntactic Variation in Masoretic Hebrew: The Object Clause Reconsidered](https://md.research.elamur.ai/free/en/papers/hbo-2017-naaijer-syntactic-variation-masoretic-hebrew-object/) — Martijn Naaijer, Dirk Roorda · Ancient Hebrew - [TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-large-scale-machine-learning/) — Martín Abadi, Ashish Agarwal, Paul Barham, et al. · arXiv:1603.04467 - [Text Readability Assessment for Second Language Learners](https://md.research.elamur.ai/free/en/papers/xia-2016-text-readability-assessment-second-language/) — Menglin Xia, Ekaterina Kochmar, Ted Briscoe · Proceedings of the 11th Workshop on Innovative… - [Text Understanding with the Attention Sum Reader Network](https://md.research.elamur.ai/free/en/papers/kadlec-2016-text-understanding-attention-sum-reader/) — Rudolf Kadlec, Martin Schmid, Ondrej Bajgar, et al. · Proceedings of the 54th Annual Meeting of the… - [The Biblical Hebrew wayyiqtol and the Evidence of the Amarna Letters from Canaan](https://md.research.elamur.ai/free/en/papers/hbo-2016-baranowski-biblical-hebrew-wayyiqtol-evidence-amarna/) — Krzysztof J. Baranowski · Ancient Hebrew - [The Complexity of Verbal Semantics — An Intricate Relationship Between Qatal and Wayyiqtol](https://md.research.elamur.ai/free/en/papers/hbo-2016-andrason-complexity-verbal-semanticsan-intricate-relationship/) — Alexander Andrason · Ancient Hebrew - [The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables](https://md.research.elamur.ai/free/en/papers/maddison-2016-concrete-distribution-continuous-relaxation-discrete/) — Chris J. Maddison, Andriy Mnih, Yee Whye Teh · arXiv:1611.00712 - [The contribution of Qumran to historical Hebrew linguistics: Evidence from the syntax of participial negation](https://md.research.elamur.ai/free/en/papers/hbo-2016-naude-contribution-qumran-historical-hebrew-linguistics/) — Jacobus A. Naudé, Cynthia L. Miller-Naudé · Ancient Hebrew - [The Creation and Analysis of a Website Privacy Policy Corpus](https://md.research.elamur.ai/free/en/papers/wilson-2016-creation-analysis-website-privacy-policy/) — Shomir Wilson, Florian Schaub, Aswarth Abhilash Dara, et al. · Proceedings of the 54th Annual Meeting of the… - [The Denoised Web Treebank: Evaluating Dependency Parsing under Noisy Input Conditions](https://md.research.elamur.ai/free/en/papers/lingbulk-2016-daiber-denoised-web-treebank-evaluating-dependency/) — Joachim Daiber, Rob van der Goot · English - [The Galactic Dependencies Treebanks: Getting More Data by Synthesizing New Languages](https://md.research.elamur.ai/free/en/papers/ud-2016-wang-galactic-dependencies-treebanks-getting-more/) — Dingquan Wang, Jason Eisner · English - [The Grammar of English Deverbal Compounds and their Meaning](https://md.research.elamur.ai/free/en/papers/chioaia-2016-grammar-english-deverbal-compounds-their/) — Gianina Iordăchioaia, Lonneke van der Plas, Glorianna Jagfeld · English - [The Hebrew FrameNet Project](https://md.research.elamur.ai/free/en/papers/frame-2016-hayoun-hebrew-framenet-project/) — Avi Hayoun, Michael Elhadad · Modern Hebrew - [The LAMBADA dataset: Word prediction requiring a broad discourse context](https://md.research.elamur.ai/free/en/papers/paperno-2016-lambada-dataset-word-prediction-requiring/) — Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, et al. · Proceedings of the 54th Annual Meeting of the… - [The material variance of the Dead Sea Scrolls: On texts and artefacts](https://md.research.elamur.ai/free/en/papers/tigchelaar-2016-material-variance-dead-sea-scrolls/) — Eibert Tigchelaar · HTS Teologiese Studies/Theological Studies 72 - [The MGB-2 Challenge: Arabic Multi-Dialect Broadcast Media Recognition](https://md.research.elamur.ai/free/en/papers/ali-2016-mgb-2-challenge-arabic-multi/) — Ahmed Ali, Peter Bell, James Glass, et al. · arXiv:1609.05625 - [The More Antecedents, the Merrier: Resolving Multi-Antecedent Anaphors](https://md.research.elamur.ai/free/en/papers/vala-2016-more-antecedents-merrier-resolving-multi/) — Hardik Vala, Andrew Piper, Derek Ruths · Proceedings of the 54th Annual Meeting of the… - [The morphosyntax of aspect stacking in Northeastern Neo-Aramaic](https://md.research.elamur.ai/free/en/papers/lingbulk-2016-kalin-morphosyntax-aspect-stacking-northeastern-neo/) — Laura Kalin · Aramaic - [The Role of Context Types and Dimensionality in Learning Word Embeddings](https://md.research.elamur.ai/free/en/papers/melamud-2016-role-context-types-dimensionality-learning/) — Oren Melamud, David McClosky, Siddharth Patwardhan, et al. · Proceedings of the 2016 Conference of the North… - [The Role of Modifier and Head Properties in Predicting the Compositionality of English and German Noun-Noun Compounds: A Vector-Space Perspective](https://md.research.elamur.ai/free/en/papers/walde-2016-role-modifier-head-properties-predicting/) — Sabine Schulte im Walde, Anna Hätty, Stefan Bott · English - [The Social Impact of Natural Language Processing](https://md.research.elamur.ai/free/en/papers/hovy-2016-social-impact-natural-language-processing/) — Dirk Hovy, Shannon L. 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