📰 Workshop on Commonsense Inference in Natural Language Processing 2019 — accepted papers

Workshop on Commonsense Inference in Natural Language Processing 2019 is the 2019 edition of the Workshop on Commonsense Inference in Natural Language Processing, held in Hong Kong, China, November 2019 (publisher: Association for Computational Linguistics). The ACL Anthology lists 16 papers of it; our library holds 2 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 Hong Kong, China · 🗓 November 2019

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. Towards Generalizable Neuro-Symbolic Systems for Commonsense Question AnsweringKaixin Ma, Jonathan Francis, Quanyang Lu et al.65 citations · our summary
2. When Choosing Plausible Alternatives, Clever Hans can be Clever ↗Pride Kavumba, Naoya Inoue, Benjamin Heinzerling et al.40 citations
3. A Hybrid Neural Network Model for Commonsense Reasoning ↗Pengcheng He, Xiaodong Liu, Weizhu Chen et al.24 citations
4. Cracking the Contextual Commonsense Code: Understanding Commonsense Reasoning Aptitude of Deep Contextual Representations ↗Jeff Da, Jungo Kasai22 citations
5. Pingan Smart Health and SJTU at COIN - Shared Task: utilizing Pre-trained Language Models and Common-sense Knowledge in Machine Reading Tasks ↗Xiepeng Li, Zhexi Zhang, Wei Zhu et al.16 citations
6. Diversity-aware Event Prediction based on a Conditional Variational Autoencoder with Reconstruction ↗Hirokazu Kiyomaru, Kazumasa Omura, Yugo Murawaki et al.9 citations
7. Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Text ↗Ian Porada, Kaheer Suleman, Jackie Chi Kit Cheung8 citations
8. Commonsense Inference in Natural Language Processing (COIN) - Shared Task Report ↗Simon Ostermann, Sheng Zhang, Michael Roth et al.8 citations
9. How Pre-trained Word Representations Capture Commonsense Physical ComparisonsPranav Goel, Shi Feng, Jordan Boyd-Graber7 citations · our summary
10. Jeff Da at COIN - Shared Task: BIG MOOD: Relating Transformers to Explicit Commonsense Knowledge ↗Jeff Da6 citations

All accepted papers (16)

The most cited first; 2 with our summary link to their page here, the others to the original.

1. Towards Generalizable Neuro-Symbolic Systems for Commonsense Question AnsweringKaixin Ma, Jonathan Francis, Quanyang Lu et al.65 citations · our summary
2. When Choosing Plausible Alternatives, Clever Hans can be Clever ↗Pride Kavumba, Naoya Inoue, Benjamin Heinzerling et al.40 citations
3. A Hybrid Neural Network Model for Commonsense Reasoning ↗Pengcheng He, Xiaodong Liu, Weizhu Chen et al.24 citations
4. Cracking the Contextual Commonsense Code: Understanding Commonsense Reasoning Aptitude of Deep Contextual Representations ↗Jeff Da, Jungo Kasai22 citations
5. Pingan Smart Health and SJTU at COIN - Shared Task: utilizing Pre-trained Language Models and Common-sense Knowledge in Machine Reading Tasks ↗Xiepeng Li, Zhexi Zhang, Wei Zhu et al.16 citations
6. Diversity-aware Event Prediction based on a Conditional Variational Autoencoder with Reconstruction ↗Hirokazu Kiyomaru, Kazumasa Omura, Yugo Murawaki et al.9 citations
7. Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Text ↗Ian Porada, Kaheer Suleman, Jackie Chi Kit Cheung8 citations
8. Commonsense Inference in Natural Language Processing (COIN) - Shared Task Report ↗Simon Ostermann, Sheng Zhang, Michael Roth et al.8 citations
9. How Pre-trained Word Representations Capture Commonsense Physical ComparisonsPranav Goel, Shi Feng, Jordan Boyd-Graber7 citations · our summary
10. Jeff Da at COIN - Shared Task: BIG MOOD: Relating Transformers to Explicit Commonsense Knowledge ↗Jeff Da6 citations
11. KARNA at COIN Shared Task 1: Bidirectional Encoder Representations from Transformers with relational knowledge for machine comprehension with common sense ↗Yash Jain, Chinmay Singh4 citations
12. BLCU-NLP at COIN-Shared Task1: Stagewise Fine-tuning BERT for Commonsense Inference in Everyday Narrations ↗Chunhua Liu, Dong Yu3 citations
13. IIT-KGP at COIN 2019: Using pre-trained Language Models for modeling Machine Comprehension ↗Prakhar Sharma, Sumegh Roychowdhury3 citations
14. Commonsense about Human Senses: Labeled Data Collection Processes ↗Ndapa Nakashole1 citation
15. Commonsense inference in human-robot communication ↗Aliaksandr Huminski, Yan Bin Ng, Kenneth Kwok et al.1 citation
16. Extracting Common Inference Patterns from Semi-Structured Explanations ↗Sebastian Thiem, Peter Jansen1 citation

📄 Papers with our summary in our library (2)

The most cited first (OpenAlex citations plus our library's).

1. Towards Generalizable Neuro-Symbolic Systems for Commonsense Question AnsweringWorkshop on Commonsense Inference in Natural Language ProcessingKaixin Ma, Jonathan Francis, Quanyang Lu, et al.2019 · 105 citations
2. How Pre-trained Word Representations Capture Commonsense Physical ComparisonsWorkshop on Commonsense Inference in Natural Language ProcessingPranav Goel, Shi Feng, Jordan Boyd-Graber2019 · 12 citations

🧭 Top topics

Topics of its works in our library, with the number of works on each.

🧮Reasoning (2)❓Question answering (1)

📚 Fields

🎭Arts and Humanities (2)🖥️Computer Science (2)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🏢Robert Bosch (United States)Farmington Hills · United States1 work here🎓University of Maryland, College ParkCollege Park · United States1 work here🎓Carnegie Mellon UniversityPittsburgh · United States1 work here

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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