Following much of the recent effort to use wikiHow as a learning resource for event understanding, commonsense reasoning, summarization, etc. we are constructing a paper list of research based on wikiHow.

1. STEPS: Semantic Typing of Event Processes with a Sequence-to-Sequence Approach.
   Sveva Pepe, Edoardo Barba, Rexhina Blloshmi, Roberto Navigli. (AAAI 2022) [paper]

2. Rethinking Why Intermediate-Task Fine-Tuning Works.
   Ting-Yun Chang, Chi-Jen Lu. (Findings of EMNLP 2021) [paper]

3. Effectiveness of Pre-training for Few-shot Intent Classification.
   Haode Zhang, Yuwei Zhang, Li-Ming Zhan, Jiaxin Chen, Guangyuan Shi, Xiao-Ming Wu, Albert Y.S. Lam. (Findings of EMNLP 2021) [paper]

4. Identify, Align, and Integrate: Matching Knowledge Graphs to Commonsense Reasoning Tasks.
   Lisa Bauer, Mohit Bansal. (EACL 2021) [paper]

5. ''What Are You Trying to Do?'' Semantic Typing of Event Processes.
   Muhao Chen, Hongming Zhang, Haoyu Wang, Dan Roth. (CoNLL 2020) [paper][repo]

6. Analogous Process Structure Induction for Sub-event Sequence Prediction.
   Hongming Zhang, Muhao Chen, Haoyu Wang, Yangqiu Song, Dan Roth. (EMNLP 2020) [paper][repo]

7. Reasoning about Goals, Steps, and Temporal Ordering with WikiHow.
   Qing Lyu, Li Zhang, Chris Callison-Burch. (EMNLP 2020) [paper]

8. Towards Modeling Revision Requirements in wikiHow Instructions.
   Irshad Ahmad Bhat, Talita Rani Anthonio and Michael Roth. (EMNLP 2020) [paper]

9. Intent Detection with WikiHow.
   Li Zhang, Qing Lyu, Chris Callison-Burch. (AACL-IJCNLP 2020) [paper]

10. HellaSwag: Can a Machine Really Finish Your Sentence?.
    Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, Yejin Choi. (ACL 2019) [paper]

1. Goal-Oriented Script Construction.
   Qing Lyu, Li Zhang, Chris Callison-Burch. (INLG 2021) [paper]

2. Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization.
   Yichen Jiang, Asli Celikyilmaz, Paul Smolensky, Paul Soulos, Sudha Rao, Hamid Palangi, Roland Fernandez, Caitlin Smith, Mohit Bansal, Jianfeng Gao. (NAACL 2021) [paper]

3. RefSum: Refactoring Neural Summarization.
   Yixin Liu, Zi-Yi Dou, Pengfei Liu. (NAACL 2021) [paper]

4. Meta-Transfer Learning for Low-Resource Abstractive Summarization.
   Yi-Syuan Chen, Hong-Han Shuai. (AAAI 2021) [paper]

5. Extractive Summarization as Text Matching.
   Ming Zhong, Pengfei Liu, Yiran Chen, Danqing Wang, Xipeng Qiu, Xuanjing Huang. (ACL 2020) [paper]

6. PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization.
   Jingqing Zhang, Yao Zhao, Mohammad Saleh, Peter J. Liu. (ICML 2020) [paper]

7. Multi-hop Inference for Question-driven Summarization.
   Yang Deng, Wenxuan Zhang, Wai Lam. (EMNLP 2020) [paper]

8. Compressive Summarization with Plausibility and Salience Modeling.
   Shrey Desai, Jiacheng Xu, Greg Durrett. (EMNLP 2020) [paper]

9. KLearn: Background Knowledge Inference from Summarization Data.
   Maxime Peyrard, Robert West. (Findings of EMNLP 2020) [paper]

1. Visual Goal-Step Inference using wikiHow
   Yue Yang, Artemis Panagopoulou, Qing Lyu, Li Zhang, Mark Yatskar, Chris Callison-Burch. (EMNLP 2021) [paper]

2. Does Vision-and-Language Pretraining Improve Lexical Grounding?
   Tian Yun, Chen Sun, Ellie Pavlick. (Findings of EMNLP 2021) [paper]

3. VLM: Task-agnostic Video-Language Model Pre-training for Video Understanding.
   Hu Xu, Gargi Ghosh, Po-Yao Huang, Prahal Arora, Masoumeh Aminzadeh, Christoph Feichtenhofer, Florian Metze, Luke Zettlemoyer. (Findings of ACL 2021) [paper]

4. Multimodal Pretraining for Dense Video Captioning
   Gabriel Huang1, Bo Pang, Zhenhai Zhu, Clara Rivera, Radu Soricut. (AACL-IJCNLP 2020) [paper]

5. Comprehensive Instructional Video Analysis: The COIN Dataset and Performance Evaluation
   Yansong Tang, Jiwen Lu, Jie Zhou. (TPAMI, 2020) [paper]

6. Learning to Segment Actions from Observation and Narration
   Daniel Fried, Jean-Baptiste Alayrac, Phil Blunsom, Chris Dyer, Stephen Clark, Aida Nematzadeh. (ACL 2020) [paper]

1. A Dataset for Tracking Entities in Open Domain Procedural Text
   Niket Tandon, Keisuke Sakaguchi, Bhavana Dalvi Mishra, Dheeraj Rajagopal, Peter Clark, Michal Guerquin, Kyle Richardson, Eduard Hovy. (EMNLP, 2020) [paper]

2. WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization.
   Faisal Ladhak, Esin Durmus, Claire Cardie, Kathleen McKeown. (Findings of EMNLP 2020) [paper]

3. wikiHowToImprove: A Resource and Analyses on Edits in Instructional Texts.
   Talita Anthonio, Irshad Bhat, Michael Roth. (LREC 2020) [paper]

4. HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips.
   Antoine Miech, Dimitri Zhukov, Jean-Baptiste Alayrac, Makarand Tapaswi, Ivan Laptev, Josef Sivic (ICCV 2019) [paper]

1. Event-Centric Natural Language Processing
   Muhao Chen, Hongming Zhang, Qiang Ning, Manling Li, Heng Ji, Kathleen McKeown, Dan Roth. (ACL, 2021) [website]

2. Event-Centric Natural Language Understanding
   Muhao Chen, Hongming Zhang, Qiang Ning, Manling Li, Heng Ji, Dan Roth. (AAAI, 2021) [website]