Fetching the paper…
Reading the bibliography…
Learning causal and temporal relationships between events is an important step towards deeper story and commonsense understanding.
Toward a model of children’s story comprehension
Eugene Charniak. 1972 · 1972
Earlier work this paper cites.
Understanding natural language
Terry Winograd. 1972 · 1972
Earlier work this paper cites.
Episodic logic meets little red riding hood: A comprehensive, natural representation for language understanding
Lenhart K Schubert and Chung Hee Hwang. 2000 · 2000
Earlier work this paper cites.
Temporal summaries of new topics
James Allan, Rahul Gupta, and Vikas Khandelwal. 2001 · 2001
Earlier work this paper cites.
Splitting complex temporal questions for question answering systems
Estela Saquete, Patricio Martinez-Barco, Rafael Munoz, and Jose-Luis Vicedo. 2004 · 2004
Earlier work this paper cites.
Inducing temporal graphs
P. Bramsen, P. Deshpande, Y. K. Lee, and R. Barzilay. 2006 · 2006
Earlier work this paper cites.
Machine learning of temporal relations
Inderjeet Mani, Marc Verhagen, Ben Wellner, Chong Min Lee, and James Pustejovsky. 2006 · 2006
Earlier work this paper cites.
Timelines from text: Identification of syntactic temporal relations
Steven Bethard, James H. Martin, and Sara Klingenstein. 2007 · 2007
Earlier work this paper cites.
Classifying temporal relations between events
Nathanael Chambers, Shan Wang, and Dan Jurafsky. 2007 · 2007
Earlier work this paper cites.
Semeval-2007 task 15: Tempeval temporal relation identification
Marc Verhagen, Robert Gaizauskas, Frank Schilder, Mark Hepple, Graham Katz, and James Pustejovsky. 2007 · 2007
Earlier work this paper cites.
Jointly combining implicit constraints improves temporal ordering
Nathanael Chambers and Dan Jurafsky. 2008 · 2008
Cited alongside, same era.
Temporal processing with the tarsqi toolkit
Marc Verhagen and James Pustejovsky. 2008 · 2008
Cited alongside, same era.
Semeval-2010 task 13: Tempeval-2
Marc Verhagen, Roser Saurí, Tommaso Caselli, and James Pustejovsky. 2010 · 2010
Cited alongside, same era.
Joint inference for event timeline construction
Quang Xuan Do, Wei Lu, and Dan Roth. 2012 · 2012
Cited alongside, same era.
Cleartk-timeml: A minimalist approach to tempeval 2013
Steven Bethard. 2013 · 2013
Cited alongside, same era.
Navytime: Event and time ordering from raw text
Nate Chambers. 2013 · 2013
Cited alongside, same era.
Dense event ordering with a multi-pass architecture
Nathanael Chambers, Taylor Cassidy, Bill McDowell, and Steven Bethard. 2014 · 2014
Later among the works it cites.
Richer event description: Integrating event coreference with temporal, causal and bridging annotation
Tim O’Gorman, Kristin Wright-Bettner, and Martha Palmer. 2016 · 2016
Later among the works it cites.
Classifying temporal relations by bidirectional lstm over dependency paths
Fei Cheng and Yusuke Miyao. 2017 · 2017
Later among the works it cites.
Temporal information extraction for question answering using syntactic dependencies in an lstm-based architecture
Yuanliang Meng, Anna Rumshisky, and Alexey Romanov. 2017 · 2017
Later among the works it cites.
Neural architecture for temporal relation extraction: a bi-lstm approach for detecting narrative containers
Julien Tourille, Olivier Ferret, Aurelie Neveol, and Xavier Tannier. 2017 · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Temporal summarization of event-related updates in wikipedia
Mihai Georgescu, Dang Duc Pham, Nattiya Kanhabua, Sergej Zerr, Stefan Siersdorfer, and Wolfgang Nejdl. 2013 · 2013
Cited alongside, same era.
Uttime: Temporal relation classification using deep syntactic features
Natsuda Laokulrat, Makoto Miwa, Yoshimasa Tsuruoka, and Takashi Chikayama. 2013 · 2013
Cited alongside, same era.
Semeval-2013 task 1: Tempeval-3: Evaluating time expressions, events, and temporal relations
Naushad UzZaman, Hector Llorens, Leon Derczynski, James Allen, Marc Verhagen, and James Pustejovsky. 2013 · 2013
Cited alongside, same era.
An annotation framework for dense event ordering
Taylor Cassidy, Bill McDowell, Nathanael Chambers, and Steven Bethard. 2014 · 2014
Cited alongside, same era.
A corpus and evaluation framework for deeper understanding of commonsense stories
Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, and James Allen. 2016a
Cited in the paper.
Caters: Causal and temporal relation scheme for semantic annotation of event structures
Nasrin Mostafazadeh, Alyson Grealish, Nathanael Chambers, James Allen, and Lucy Vanderwende. 2016b
Cited in the paper.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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. 2018 · 2018
Later among the works it cites.
Context-aware neural model for temporal information extraction
Yuanliang Meng and Anna Rumshisky. 2018 · 2018
Later among the works it cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 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.