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title: "Workshop on Insights from Negative Results in NLP 2020"
description: "Workshop on Insights from Negative Results in NLP 2020 — accepted papers: 1 paper in the Elamur Research library (Online), with our…"
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# Workshop on Insights from Negative Results in NLP 2020 — accepted papers

Workshop on Insights from Negative Results in NLP 2020 is the 2020 edition of the Workshop on Insights from Negative Results in NLP, held in Online, November 2020 (publisher: Association for Computational Linguistics). The ACL Anthology lists 18 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

[**18** papers in the proceedings](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/insights/2020/#works) · [**50** citations of these works](https://md.research.elamur.ai/free/en/venues/insights/2020/#works)**Online** where it was held**November 2020** when

## Most cited papers

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

1. **[Domain adaptation challenges of BERT in tokenization and sub-word representations of Out-of-Vocabulary words](https://aclanthology.org/2020.insights-1.1/)**Anmol Nayak, Hariprasad Timmapathini, Karthikeyan Ponnalagu et al.*43 citations*
2. **[Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data](https://md.research.elamur.ai/free/en/papers/huang-2020-counterfactually-augmented-snli-training-data/)**William Huang, Haokun Liu, Samuel R. Bowman*32 citations · our summary*
3. **[HINT3: Raising the bar for Intent Detection in the Wild](https://aclanthology.org/2020.insights-1.16/)**Gaurav Arora, Chirag Jain, Manas Chaturvedi et al.*18 citations*
4. **[Label Propagation-Based Semi-Supervised Learning for Hate Speech Classification](https://aclanthology.org/2020.insights-1.8/)**Ashwin Geet D'Sa, Irina Illina, Dominique Fohr et al.*17 citations*
5. **[How Effectively Can Machines Defend Against Machine-Generated Fake News? An Empirical Study](https://aclanthology.org/2020.insights-1.7/)**Meghana Moorthy Bhat, Srinivasan Parthasarathy*15 citations*
6. **[Which Matters Most? Comparing the Impact of Concept and Document Relationships in Topic Models](https://aclanthology.org/2020.insights-1.5/)**Silvia Terragni, Debora Nozza, Elisabetta Fersini et al.*12 citations*
7. **[If You Build Your Own NER Scorer, Non-replicable Results Will Come](https://aclanthology.org/2020.insights-1.15/)**Constantine Lignos, Marjan Kamyab*8 citations*
8. **[Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks](https://aclanthology.org/2020.insights-1.4/)**Ansel MacLaughlin, Jwala Dhamala, Anoop Kumar et al.*7 citations*
9. **[The Extraordinary Failure of Complement Coercion Crowdsourcing](https://aclanthology.org/2020.insights-1.17/)**Yanai Elazar, Victoria Basmov, Shauli Ravfogel et al.*4 citations*
10. **[An Analysis of Capsule Networks for Part of Speech Tagging in High- and Low-resource Scenarios](https://aclanthology.org/2020.insights-1.10/)**Andrew Zupon, Faiz Rafique, Mihai Surdeanu*3 citations*

## All accepted papers (18)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. **[Domain adaptation challenges of BERT in tokenization and sub-word representations of Out-of-Vocabulary words](https://aclanthology.org/2020.insights-1.1/)**Anmol Nayak, Hariprasad Timmapathini, Karthikeyan Ponnalagu et al.*43 citations*
2. **[Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data](https://md.research.elamur.ai/free/en/papers/huang-2020-counterfactually-augmented-snli-training-data/)**William Huang, Haokun Liu, Samuel R. Bowman*32 citations · our summary*
3. **[HINT3: Raising the bar for Intent Detection in the Wild](https://aclanthology.org/2020.insights-1.16/)**Gaurav Arora, Chirag Jain, Manas Chaturvedi et al.*18 citations*
4. **[Label Propagation-Based Semi-Supervised Learning for Hate Speech Classification](https://aclanthology.org/2020.insights-1.8/)**Ashwin Geet D'Sa, Irina Illina, Dominique Fohr et al.*17 citations*
5. **[How Effectively Can Machines Defend Against Machine-Generated Fake News? An Empirical Study](https://aclanthology.org/2020.insights-1.7/)**Meghana Moorthy Bhat, Srinivasan Parthasarathy*15 citations*
6. **[Which Matters Most? Comparing the Impact of Concept and Document Relationships in Topic Models](https://aclanthology.org/2020.insights-1.5/)**Silvia Terragni, Debora Nozza, Elisabetta Fersini et al.*12 citations*
7. **[If You Build Your Own NER Scorer, Non-replicable Results Will Come](https://aclanthology.org/2020.insights-1.15/)**Constantine Lignos, Marjan Kamyab*8 citations*
8. **[Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks](https://aclanthology.org/2020.insights-1.4/)**Ansel MacLaughlin, Jwala Dhamala, Anoop Kumar et al.*7 citations*
9. **[The Extraordinary Failure of Complement Coercion Crowdsourcing](https://aclanthology.org/2020.insights-1.17/)**Yanai Elazar, Victoria Basmov, Shauli Ravfogel et al.*4 citations*
10. **[An Analysis of Capsule Networks for Part of Speech Tagging in High- and Low-resource Scenarios](https://aclanthology.org/2020.insights-1.10/)**Andrew Zupon, Faiz Rafique, Mihai Surdeanu*3 citations*
11. **[Can Knowledge Graph Embeddings Tell Us What Fact-checked Claims Are About?](https://aclanthology.org/2020.insights-1.11/)**Valentina Beretta, Sébastien Harispe, Katarina Boland et al.*3 citations*
12. **[Layout-Aware Text Representations Harm Clustering Documents by Type](https://aclanthology.org/2020.insights-1.9/)**Catherine Finegan-Dollak, Ashish Verma*3 citations*
13. **[NMF Ensembles? Not for Text Summarization!](https://aclanthology.org/2020.insights-1.14/)**Alka Khurana, Vasudha Bhatnagar*3 citations*
14. **[Embedding Structured Dictionary Entries](https://aclanthology.org/2020.insights-1.18/)**Steven Wilson, Walid Magdy, Barbara McGillivray et al.*1 citation*
15. **[How Far Can We Go with Data Selection? A Case Study on Semantic Sequence Tagging Tasks](https://aclanthology.org/2020.insights-1.3/)**Samuel Louvan, Bernardo Magnini*1 citation*
16. **[Do Transformers Dream of Inference, or Can Pretrained Generative Models Learn Implicit Inferential Rules?](https://aclanthology.org/2020.insights-1.12/)**Zhengzhong Liang, Mihai Surdeanu
17. **[On Task-Level Dialogue Composition of Generative Transformer Model](https://aclanthology.org/2020.insights-1.6/)**Prasanna Parthasarathi, Sharan Narang, Arvind Neelakantan
18. **[Q. Can Knowledge Graphs be used to Answer Boolean Questions? A. It's complicated!](https://aclanthology.org/2020.insights-1.2/)**Daria Dzendzik, Carl Vogel, Jennifer Foster

## Papers with our summary in our library (1)

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

1. **[Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data](https://md.research.elamur.ai/free/en/papers/huang-2020-counterfactually-augmented-snli-training-data/) [Workshop on Insights from Negative Results in NLP](https://md.research.elamur.ai/free/en/venues/insights/)**William Huang, Haokun Liu, Samuel R. Bowman*2020 · 50 citations*

## Fields

[Arts and Humanities (1)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science (1)](https://md.research.elamur.ai/free/en/shelves/computer-science/)

## Top authors

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

[🧑‍🔬**Haokun Liu**1 work here · 50 citations](https://md.research.elamur.ai/free/en/authors/haokun-liu/) · [🧑‍🔬**Samuel R. Bowman**1 work here · 50 citations](https://md.research.elamur.ai/free/en/authors/samuel-r-bowman/)

## Top institutions

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

[🎓**New York University** New York · United States 1 work here](https://md.research.elamur.ai/free/en/universities/new-york-university/)

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

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