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While the fast-paced inception of novel tasks and new datasets helps foster active research in a community towards interesting directions, keeping track of the abundance of research activity in different areas on different datasets is likely to become increasingly difficult.
The PASCAL recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006 · 2006
Earlier work this paper cites.
The ACL anthology reference corpus: A reference dataset for bibliographic research in computational linguistics
Steven Bird, Robert Dale, Bonnie Dorr, Bryan Gibson, Mark Joseph, Min-Yen Kan, Dongwon Lee, Brett Powley, Dragomir Radev, and Yee Fan Tan. 2008 · 2008
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Improvements that don’t add up: Ad-hoc retrieval results since 1998
Timothy G. Armstrong, Alistair Moffat, William Webber, and Justin Zobel. 2009 · 2009
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GROBID: combining automatic bibliographic data recognition and term extraction for scholarship publications
Patrice Lopez. 2009 · 2009
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Analyzing the dynamics of research by extracting key aspects of scientific papers
Sonal Gupta and Christopher Manning. 2011 · 2011
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay. 2011 · 2011
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Context-enhanced citation sentiment detection
Awais Athar and Simone Teufel. 2012a · 2012
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He said, she said: Gender in the acl anthology
Adam Vogel and Dan Jurafsky. 2012 · 2012
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Concept-based analysis of scientific literature
Chen-Tse Tsai, Gourab Kundu, and Dan Roth. 2013 · 2013
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SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives
Aaron Defazio, Francis Bach, and Simon Lacoste-Julien. 2014 · 2014
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Semantic annotation of the ACL anthology corpus for the automatic analysis of scientific literature
Kata Gábor, Haifa Zargayouna, Davide Buscaldi, Isabelle Tellier, and Thierry Charnois. 2016 · 2016
Cited alongside, same era.
The AI2 system at SemEval-2017 Task 10 (ScienceIE): Semi-supervised end-to-end entity and relation extraction
Waleed Ammar, Matthew Peters, Chandra Bhagavatula, and Russell Power. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Vaswani Ashish, Shazeer Noam, Parmar Niki, Uszkoreit Jakob, Jones Llion, Gomez Aidan N., Kaiser Lukasz, and Polosukhin Illia. 2017 · 2017
Cited alongside, same era.
SemEval 2017 Task 10: ScienceIE - Extracting keyphrases and relations from scientific publications
Isabelle Augenstein, Mrinal Das, Sebastian Riedel, Lakshmi Vikraman, and Andrew McCallum. 2017 · 2017
Cited alongside, same era.
Introduction to the special issue on reproducibility in information retrieval: Evaluation campaigns, collections, and analyses
Nicola Ferro, Norbert Fuhr, and Andreas Rauber. 2018 · 2018
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Semeval-2018 task 7: Semantic relation extraction and classification in scientific papers
Kata Gábor, Davide Buscaldi, Anne-Kathrin Schumann, Behrang QasemiZadeh, Haïfa Zargayouna, and Thierry Charnois. 2018 · 2018
Later among the works it cites.
Measuring the evolution of a scientific field through citation frames
David Jurgens, Srijan Kumar, Raine Hoover, Dan McFarland, and Dan Jurafsky. 2018 · 2018
Later among the works it cites.
Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi. 2018 · 2018
Later among the works it cites.
Zero-shot relation classification as textual entailment
Abiola Obamuyide and Andreas Vlachos. 2018 · 2018
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Multi-task learning of keyphrase boundary classification
Isabelle Augenstein and Anders Søgaard. 2017 · 2017
Cited alongside, same era.
Generating pattern-based entailment graphs for relation extraction
Kathrin Eichler, Feiyu Xu, Hans Uszkoreit, and Sebastian Krause. 2017 · 2017
Cited alongside, same era.
Scientific information extraction with semi-supervised neural tagging
Yi Luan, Mari Ostendorf, and Hannaneh Hajishirzi. 2017 · 2017
Cited alongside, same era.
Inference is everything: Recasting semantic resources into a unified evaluation framework
Aaron Steven White, Pushpendre Rastogi, Kevin Duh, and Benjamin Van Durme. 2017 · 2017
Cited alongside, same era.
Construction of the literature graph in semantic scholar
Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier, Kyle Lo, Tyler Murray, Hsu-Han Ooi, Matthew Peters, Joanna Power, Sam Skjonsberg, Lucy Wang, Chris Willhelm, Zheng Yuan, Madeleine van Zuylen, and Oren Etzioni. 2018 · 2018
Cited alongside, same era.
Detection of implicit citations for sentiment detection
Awais Athar and Simone Teufel. 2012b
Cited in the paper.
Collecting diverse natural language inference problems for sentence representation evaluation
Adam Poliak, Aparajita Haldar, Rachel Rudinger, J. Edward Hu, Ellie Pavlick, Aaron Steven White, and Benjamin Van Durme. 2018 · 2018
Later among the works it cites.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Closest in time.
Semantic sentence matching with densely-connected recurrent and co-attentive information
Seonhoon Kim, Jin-Hyuk Hong, Inho Kang, and Nojun Kwak. 2019 · 2019
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Multi-task deep neural networks for natural language understanding
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao. 2019 · 2019
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