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For monitoring crises, political events are extracted from the news.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2020 · 1910
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World event/interaction survey (WEIS) project, 1966-1978: Archival version
Charles McClelland. 1984 · 1978
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A conflict-cooperation scale for WEIS events data
Joshua Goldstein. 1992 · 1992
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A Natural Logic Inference System
Yaroslav Fyodorov, Yoad Winter, and Nissim Francez. 2000 · 2000
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Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence
Andrew Halterman, Katherine Keith, Sheikh Sarwar, and Brendan O’Connor. 2021 · 2002
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An automated information extraction tool for international conflict data with performance as good as human coders: A rare events evaluation design
Gary King and Will Lowe. 2003 · 2003
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Introducing the Global Terrorism Database
Gary LaFree and Laura Dugan. 2007 · 2007
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Introducing ACLED-Armed Conflict Location and Event Data
Clionadh Raleigh, Andrew Linke, Håvard Hegre, and Joakim Karlsen. 2010 · 2010
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CAMEO: Conflict and mediation event observations event and actor codebook
Philip Schrodt. 2012 · 2012
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SLUA: Towards Semantic Linking of Users with Actions in Crowdsourcing
Umair ul Hassan, Sean O’Riain, and Edward Curry. 2013 · 2013
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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ICEWS Coded Event Data
Elizabeth Boschee, Jennifer Lautenschlager, Sean O’Brien, Steve Shellman, James Starz, and Michael Ward. 2015 · 2015
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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
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Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language
Luheng He, Mike Lewis, and Luke Zettlemoyer. 2015 · 2015
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Nonviolent and violent campaigns and outcomes 3.0: Effects of tactical choices on strategic outcomes codebook
Orion A. Lewis, Erica Chenoweth, and Jonathan Pinckney. 2016 · 2016
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SQuAD: 100,000+ Questions for Machine Comprehension of Text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Tracing armed conflicts with diachronic word embedding models
Andrey Kutuzov, Erik Velldal, and Lilja Øvrelid. 2017 · 2017
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Petrarch2: Another event coding program
Clayton Norris, Philip Schrodt, and John Beieler. 2017 · 2017
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Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
SeismographAPI: Visualising temporal-spatial crisis data
Raphael Lepuschitz and Niklas Stoehr. 2021 · 2021
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Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2021 · 2021
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Team “DaDeFrNi” at CASE 2021 Task 1: Document and sentence classification for protest event detection
Francesco Re, Daniel Vegh, Dennis Atzenhofer, and Niklas Stoehr. 2021 · 2021
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Label verbalization and entailment for effective zero- and few-shot relation extraction
Oscar Sainz, Oier Lopez de Lacalle, Gorka Labaka, Ander Barrena, and Eneko Agirre. 2021 · 2021
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Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference
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Wenpeng Yin, Jamaal Hay, and Dan Roth. 2019 · 2019
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Text Categorization for Conflict Event Annotation
Fredrik Olsson, Magnus Sahlgren, Fehmi ben Abdesslem, Ariel Ekgren, and Kristine Eck. 2020 · 2020
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TF-IDF Character N-grams versus Word Embedding-based Models for Fine-grained Event Classification: A Preliminary Study
Jakub Piskorski and Guillaume Jacquet. 2020 · 2020
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Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification
Timo Schick, Helmut Schmid, and Hinrich Schütze. 2020 · 2020
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AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2020
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IBM MNLP IE at CASE 2021 Task 2: NLI Reranking for Zero-Shot Text Classification
Ken Barker, Parul Awasthy, Jian Ni, and Radu Florian. 2021 · 2021
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Making Pre-trained Language Models Better Few-shot Learners
Tianyu Gao, Adam Fisch, and Danqi Chen. 2021 · 2021
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Timo Schick and Hinrich Schütze. 2021 · 2021
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Constrained Language Models Yield Few-Shot Semantic Parsers
Richard Shin, Christopher Lin, Sam Thomson, Charles Chen, Subhro Roy, Emmanouil Antonios Platanios, Adam Pauls, Dan Klein, Jason Eisner, and Benjamin Van Durme. 2021 · 2021
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Classifying dyads for militarized conflict analysis
Niklas Stoehr, Lucas Torroba Hennigen, Samin Ahbab, Robert West, and Ryan Cotterell. 2021 · 2021
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Entailment as Few-Shot Learner
Sinong Wang, Han Fang, Madian Khabsa, Hanzi Mao, and Hao Ma. 2021 · 2021
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ConfliBERT: A pre-trained language model for political conflict and violence
Yibo Hu, MohammadSaleh Hosseini, Erick Skorupa Parolin, Javier Osorio, Latifur Khan, Patrick T. Brandt, and Vito J. D’Orazio. 2022 · 2022
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Multi-CoPED: A Multilingual Multi-Task Approach for Coding Political Event Data on Conflict and Mediation Domain
Erick Skorupa Parolin, MohammadSaleh Hosseini, Yibo Hu, Latifur Khan, Patrick T. Brandt, Javier Osorio, and Vito D’Orazio. 2022 · 2022
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An ordinal latent variable model of conflict intensity
Niklas Stoehr, Lucas Torroba Hennigen, Josef Valvoda, Robert West, Ryan Cotterell, and Aaron Schein. 2022 · 2022
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The Ordered Matrix Dirichlet for state-space models
Niklas Stoehr, Benjamin J. Radford, Ryan Cotterell, and Aaron Schein. 2023 · 2023
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Extracting victim counts from text
Mian Zhong, Shehzaad Dhuliawala, and Niklas Stoehr. 2023 · 2023
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