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Procedures are inherently hierarchical.
Bertscore: Evaluating text generation with bert
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Zero-shot entity linking with dense entity retrieval. corr abs/1911.03814 (2019)
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Automated knowledge acquisition for instructional text generation
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Open mind common sense: Knowledge acquisition from the general public
Push Singh, Thomas Lin, Erik T Mueller, Grace Lim, Travell Perkins, and Wan Li Zhu. 2002 · 2002
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Feature selection in categorizing procedural expressions
Mineki Takechi, Takenobu Tokunaga, Yuji Matsumoto, and Hozumi Tanaka. 2003 · 2003
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Dense passage retrieval for open-domain question answering
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Deberta: Decoding-enhanced bert with disentangled attention
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Dbpedia: A nucleus for a web of open data
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Investigating the structure of procedural texts for answering how-to questions
Estelle Delpech and Patrick Saint-Dizier. 2008 · 2008
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The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson and Hugo Zaragoza. 2009 · 2009
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Automatic construction of a large-scale situation ontology by mining how-to instructions from the web
Yuchul Jung, Jihee Ryu, Kyung-min Kim, and Sung-Hyon Myaeng. 2010 · 2010
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Learning script knowledge with web experiments
Michaela Regneri, Alexander Koller, and Manfred Pinkal. 2010 · 2010
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Analogous process structure induction for sub-event sequence prediction
Hongming Zhang, Muhao Chen, Haoyu Wang, Yangqiu Song, and Dan Roth. 2020a · 2010
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Crowdsourcing narrative intelligence
Boyang Li, Stephen Lee-Urban, Darren Scott Appling, and Mark O Riedl. 2012 · 2012
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Automatically extracting procedural knowledge from instructional texts using natural language processing
Ziqi Zhang, Philip Webster, Victoria Uren, Andrea Varga, and Fabio Ciravegna. 2012 · 2012
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Integrating know-how into the linked data cloud
Paolo Pareti, Benoit Testu, Ryutaro Ichise, Ewan Klein, and Adam Barker. 2014 · 2014
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Deep learning for content-based image retrieval: A comprehensive study
Ji Wan, Dayong Wang, Steven Chu Hong Hoi, Pengcheng Wu, Jianke Zhu, Yongdong Zhang, and Jintao Li. 2014 · 2014
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Activitynet: A large-scale video benchmark for human activity understanding
Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem, and Juan Carlos Niebles. 2015 · 2015
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Learning to predict script events from domain-specific text
Rachel Rudinger, Vera Demberg, Ashutosh Modi, Benjamin Van Durme, and Manfred Pinkal. 2015 · 2015
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Recent trends in natural language understanding for procedural knowledge
Dena Mujtaba and Nihar Mahapatra. 2019 · 2019
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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ATOMIC: an atlas of machine commonsense for if-then reasoning
Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, and Yejin Choi. 2019 · 2019
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WIQA: A dataset for “what if…” reasoning over procedural text
Niket Tandon, Bhavana Dalvi, Keisuke Sakaguchi, Peter Clark, and Antoine Bosselut. 2019 · 2019
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Coin: A large-scale dataset for comprehensive instructional video analysis
Yansong Tang, Dajun Ding, Yongming Rao, Yu Zheng, Danyang Zhang, Lili Zhao, Jiwen Lu, and Jie Zhou. 2019 · 2019
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Jean-Baptiste Alayrac, Piotr Bojanowski, Nishant Agrawal, Josef Sivic, Ivan Laptev, and Simon Lacoste-Julien. 2016 · 2016
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A crowdsourced database of event sequence descriptions for the acquisition of high-quality script knowledge
Lilian DA Wanzare, Alessandra Zarcone, Stefan Thater, and Manfred Pinkal. 2016 · 2016
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Distilling task knowledge from how-to communities
Cuong Xuan Chu, Niket Tandon, and Gerhard Weikum. 2017 · 2017
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Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2017 · 2017
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Enriching how-to guides with actionable phrases and linked data
Nikolaos Lagos, Matthias Gallé, Alexandr Chernov, and Ágnes Sándor. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
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John Wieting, Kevin Gimpel, Graham Neubig, and Taylor Berg-Kirkpatrick. 2019 · 2019
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HellaSwag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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Learning household task knowledge from WikiHow descriptions
Yilun Zhou, Julie Shah, and Steven Schockaert. 2019 · 2019
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spaCy: Industrial-strength Natural Language Processing in Python
Matthew Honnibal, Ines Montani, Sofie Van Landeghem, and Adriane Boyd. 2020 · 2020
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What-if I ask you to explain: Explaining the effects of perturbations in procedural text
Dheeraj Rajagopal, Niket Tandon, Peter Clark, Bhavana Dalvi, and Eduard Hovy. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Julien Chaumond, Lysandre Debut, Victor Sanh, Clement Delangue, Anthony Moi, Pierric Cistac, Morgan Funtowicz, Joe Davison, Sam Shleifer, et al. 2020 · 2020
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Analogous process structure induction for sub-event sequence prediction
Hongming Zhang, Muhao Chen, Haoyu Wang, Yangqiu Song, and Dan Roth. 2020b · 2020
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Reasoning about goals, steps, and temporal ordering with WikiHow
Li Zhang, Qing Lyu, and Chris Callison-Burch. 2020d · 2020
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CLIP4Clip: An empirical study of clip for end to end video clip retrieval
Huaishao Luo, Lei Ji, Ming Zhong, Yang Chen, Wen Lei, Nan Duan, and Tianrui Li. 2021 · 2021
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Goal-oriented script construction
Qing Lyu, Li Zhang, and Chris Callison-Burch. 2021 · 2021
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Paraphrastic representations at scale
John Wieting, Kevin Gimpel, Graham Neubig, and Taylor Berg-Kirkpatrick. 2021 · 2021
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Visual goal-step inference using wikihow
Yue Yang, Artemis Panagopoulou, Qing Lyu, Li Zhang, Mark Yatskar, and Chris Callison-Burch. 2021b · 2021
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Learning to decompose and organize complex tasks
Yi Zhang, Sujay Kumar Jauhar, Julia Kiseleva, Ryen White, and Dan Roth. 2021 · 2021
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