Transactions of the Association for Computational Linguistics (TACL) 2017 — papers
The works of Transactions of the Association for Computational Linguistics (TACL) published in 2017 that our library holds (publisher: The MIT Press): 9 works, listed below with the most cited first; each has a page with our summary, its key points and its references.
All works of the year (37)
- A Generative Model of PhonotacticsRichard Futrell, Adam Albright, Peter Graff et al.
- A Polynomial-Time Dynamic Programming Algorithm for Phrase-Based Decoding with a Fixed Distortion LimitYin-Wen Chang, Michael Collins
- Anchored Correlation Explanation: Topic Modeling with Minimal Domain KnowledgeRyan J. Gallagher, Kyle Reing, David Kale et al.
- Aspect-augmented Adversarial Networks for Domain AdaptationYuan Zhang, Regina Barzilay, Tommi Jaakkola
- Automatically Tagging Constructions of Causation and Their Slot-FillersJesse Dunietz, Lori Levin, Jaime Carbonell
- Colors in Context: A Pragmatic Neural Model for Grounded Language UnderstandingWill Monroe, Robert X.D. Hawkins, Noah D. Goodman et al.our summary
- Context Gates for Neural Machine TranslationZhaopeng Tu, Yang Liu, Zhengdong Lu et al.our summary
- Cross-Lingual Syntactic Transfer with Limited ResourcesMohammad Sadegh Rasooli, Michael Collins
- Cross-Sentence N-ary Relation Extraction with Graph LSTMsNanyun Peng, Hoifung Poon, Chris Quirk et al.our summary
- Domain-Targeted, High Precision Knowledge ExtractionBhavana Dalvi Mishra, Niket Tandon, Peter Clark
- Enriching Word Vectors with Subword InformationPiotr Bojanowski, Edouard Grave, Armand Joulin et al.our summary
- Evaluating Low-Level Speech Features Against Human Perceptual DataCaitlin Richter, Naomi H. Feldman, Harini Salgado et al.
- Evaluating Visual Representations for Topic Understanding and Their Effects on Manually Generated Topic LabelsAlison Smith, Tak Yeon Lee, Forough Poursabzi-Sangdeh et al.
- Fine-Grained Prediction of Syntactic Typology: Discovering Latent Structure with Supervised LearningDingquan Wang, Jason Eisner
- Fully Character-Level Neural Machine Translation without Explicit SegmentationJason Lee, Kyunghyun Cho, Thomas Hofmannour summary
- Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot TranslationMelvin Johnson, Mike Schuster, Quoc V. Le et al.
- Head-Lexicalized Bidirectional Tree LSTMsZhiyang Teng, Yue Zhang
- In-Order Transition-based Constituent ParsingJiangming Liu, Yue Zhangour summary
- Joint Modeling of Topics, Citations, and Topical Authority in Academic CorporaJooyeon Kim, Dongwoo Kim, Alice Oh
- Joint Prediction of Word Alignment with Alignment TypesAnahita Mansouri Bigvand, Te Bu, Anoop Sarkar
- Learning Distributed Representations of Texts and Entities from Knowledge BaseIkuya Yamada, Hiroyuki Shindo, Hideaki Takeda et al.
- Learning to Prune: Exploring the Frontier of Fast and Accurate ParsingTim Vieira, Jason Eisner
- Modeling Semantic Expectation: Using Script Knowledge for Referent PredictionAshutosh Modi, Ivan Titov, Vera Demberg et al.
- Nonparametric Bayesian Semi-supervised Word SegmentationRyo Fujii, Ryo Domoto, Daichi Mochihashi
- Ordinal Common-sense InferenceSheng Zhang, Rachel Rudinger, Kevin Duh et al.our summary
Works with our summary in our library (9)
- Enriching Word Vectors with Subword InformationPiotr Bojanowski, Edouard Grave, Armand Joulin, et al.2017 · 11,848 citations
- Cross-Sentence N-ary Relation Extraction with Graph LSTMsNanyun Peng, Hoifung Poon, Chris Quirk, et al.2017 · 554 citations
- Fully Character-Level Neural Machine Translation without Explicit SegmentationJason Lee, Kyunghyun Cho, Thomas Hofmann2017 · 551 citations
- Generating Sentences by Editing PrototypesKelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, et al.2017 · 407 citations
- Semantic Specialization of Distributional Word Vector Spaces using Monolingual and Cross-Lingual ConstraintsNikola Mrkšić, Ivan Vulić, Diarmuid Ó Séaghdha, et al.2017 · 236 citations
- Ordinal Common-sense InferenceSheng Zhang, Rachel Rudinger, Kevin Duh, et al.2017 · 192 citations
- Colors in Context: A Pragmatic Neural Model for Grounded Language UnderstandingWill Monroe, Robert X.D. Hawkins, Noah D. Goodman, et al.2017 · 155 citations
- Context Gates for Neural Machine TranslationZhaopeng Tu, Yang Liu, Zhengdong Lu, et al.2017 · 153 citations
- In-Order Transition-based Constituent ParsingJiangming Liu, Yue Zhang2017 · 99 citations
Top topics
Machine translation (2)Information extraction (1)Multilingual & cross-lingual NLP (1)Reasoning (1)Syntax & grammar formalisms (1)Tokenization & segmentation (1)
Fields
Computer Science (9)Arts and Humanities (8)Biochemistry, Genetics and Molecular Biology (1)Psychology (1)
Top authors
🧑🔬Armand Joulin1 work here · 11,848 citations🧑🔬Edouard Grave1 work here · 11,848 citations🧑🔬Piotr Bojanowski1 work here · 11,848 citations🧑🔬Tomas Mikolov1 work here · 11,848 citations🧑🔬Chris Quirk1 work here · 554 citations🧑🔬Hoifung Poon1 work here · 554 citations🧑🔬Kristina Toutanova1 work here · 554 citations🧑🔬Nanyun Peng1 work here · 554 citations🧑🔬Wen-tau Yih1 work here · 554 citations🧑🔬Jason Lee1 work here · 551 citations🧑🔬Kyunghyun Cho1 work here · 551 citations🧑🔬Thomas Hofmann1 work here · 551 citations
Top institutions
🎓Johns Hopkins UniversityBaltimore ·
United States2 works here🎓Stanford UniversityStanford ·
United States2 works here🏢MicrosoftRedmond ·
United States1 work here🏢GoogleMountain View ·
United States1 work here🎓Singapore University of Technology and DesignSingapore ·
Singapore1 work here🎓Technion – Israel Institute of TechnologyHaifa ·
Israel1 work here🏢Huawei TechnologiesShenzhen ·
China1 work here🎓University of CambridgeCambridge ·
United Kingdom1 work here🎓ETH ZurichZurich ·
Switzerland1 work here🏢MetaMenlo Park ·
United States1 work here🏢AppleCupertino ·
United States1 work here🎓New York UniversityNew York ·
United States1 work here
This page in Markdown → https://md.research.elamur.ai/free/en/venues/tacl/2017/