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https://github.com/zhjohnchan/awesome-causality-in-nlp
A curated list of causality in NLP. :-)
https://github.com/zhjohnchan/awesome-causality-in-nlp
List: awesome-causality-in-nlp
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A curated list of causality in NLP. :-)
- Host: GitHub
- URL: https://github.com/zhjohnchan/awesome-causality-in-nlp
- Owner: zhjohnchan
- Created: 2021-10-30T09:59:53.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2021-11-07T09:04:01.000Z (almost 3 years ago)
- Last Synced: 2024-04-09T20:15:25.950Z (7 months ago)
- Homepage:
- Size: 24.4 KB
- Stars: 8
- Watchers: 2
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-interesting-topics-in-nlp - NLP
- ultimate-awesome - awesome-causality-in-nlp - A curated list of causality in NLP. :-). (Other Lists / PowerShell Lists)
README
# Awesome Causality in NLP[](https://awesome.re)
A curated list of causality in NLP. :-)
## Contributing
Please feel free to send me [pull requests](https://github.com/zhjohnchan/awesome-causality-in-nlp/pulls) or email ([email protected]) to add links.
## Table of Contents
- [Papers](#papers)
- [Survey](#survey)
- [Research Paper](#research-paper)
- [Researchers](#researchers)
- [Workshops](#workshops)
- [Related Repos](#related-repos)
## Papers
### Research Paper
| Year | Venue | Title |
|-------:|:---------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 2000 | ACL | [Extracting Causal Knowledge from a Medical Database Using Graphical Patterns](https://aclanthology.org/P00-1043.pdf) |
| 2000 | COLING | [KCAT: A Korean Corpus Annotating Tool Minimizing Human Intervention](https://aclanthology.org/C00-2165.pdf) |
| 2008 | ACL | [Learning Semantic Links from a Corpus of Parallel Temporal and Causal Relations](https://aclanthology.org/P08-2045.pdf) |
| 2011 | EMNLP | [Minimally Supervised Event Causality Identification](https://aclanthology.org/D11-1027.pdf) |
| 2012 | EMNLP | [Excitatory or Inhibitory: A New Semantic Orientation Extracts Contradiction and Causality from the Web](https://aclanthology.org/D12-1057.pdf) |
| 2012 | COLING | [Acquiring and Generalizing Causal Inference Rules from Deverbal Noun Constructions](https://aclanthology.org/C12-2118.pdf) |
| 2012 | CoNLL | [Excitatory or Inhibitory: A New Semantic Orientation Extracts Contradiction and Causality from the Web](https://aclanthology.org/D12-1057.pdf) |
| 2013 | ACL | [Why-Question Answering using Intra- and Inter-Sentential Causal Relations](https://aclanthology.org/P13-1170.pdf) |
| 2013 | ACL | [What causes a causal relation? Detecting Causal Triggers in Biomedical Scientific Discourse](https://aclanthology.org/P13-3006.pdf) |
| 2014 | ACL | [Toward Future Scenario Generation: Extracting Event Causality Exploiting Semantic Relation, Context, and Association Features](https://aclanthology.org/P14-1093.pdf) |
| 2014 | ACL | [Predicting Instructor’s Intervention in MOOC forums](https://aclanthology.org/P14-1141.pdf) |
| 2014 | ACL | [Extracting Temporal and Causal Relations between Events](https://aclanthology.org/P14-3002.pdf) |
| 2014 | COLING | [An Analysis of Causality between Events and its Relation to Temporal Information](https://aclanthology.org/C14-1198.pdf) |
| 2016 | ACL | [Identifying Causal Relations Using Parallel Wikipedia Articles](https://aclanthology.org/P16-1135.pdf) |
| 2016 | ACL | [Physical Causality of Action Verbs in Grounded Language Understanding](https://aclanthology.org/P16-1171.pdf) |
| 2016 | ACL | [Case and Cause in Icelandic: Reconstructing Causal Networks of Cascaded Language Changes](https://aclanthology.org/P16-1229.pdf) |
| 2016 | EMNLP | [Creating Causal Embeddings for Question Answering with Minimal Supervision](https://aclanthology.org/D16-1014.pdf) |
| 2016 | COLING | [CATENA: CAusal and TEmporal relation extraction from NAtural language texts](https://aclanthology.org/C16-1007.pdf) |
| 2016 | COLING | [Chinese Tense Labelling and Causal Analysis](https://aclanthology.org/C16-1210.pdf) |
| 2017 | ACL | [Recognizing Counterfactual Thinking in Social Media Texts](https://aclanthology.org/P17-2103.pdf) |
| 2017 | EMNLP | [A causal framework for explaining the predictions of black-box sequence-to-sequence models](https://aclanthology.org/D17-1042.pdf) |
| 2017 | EMNLP | [Counterfactual Learning from Bandit Feedback under Deterministic Logging : A Case Study in Statistical Machine Translation](https://aclanthology.org/D17-1272.pdf) |
| 2017 | CoNLL | [Feature Selection as Causal Inference: Experiments with Text Classification](https://aclanthology.org/K17-1018.pdf) |
| 2018 | ACL | [A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature](https://aclanthology.org/P18-1019.pdf) |
| 2018 | ACL | [Improving a Neural Semantic Parser by Counterfactual Learning from Human Bandit Feedback](https://aclanthology.org/P18-1169.pdf) |
| 2018 | ACL | [Joint Reasoning for Temporal and Causal Relations](https://aclanthology.org/P18-1212.pdf) |
| 2018 | ACL | [Causality Analysis of Twitter Sentiments and Stock Market Returns](https://aclanthology.org/W18-3102.pdf) |
| 2018 | ACL | [Countering Position Bias in Instructor Interventions in MOOC Discussion Forums](https://aclanthology.org/W18-3720.pdf) |
| 2018 | EMNLP | [Causal Explanation Analysis on Social Media](https://aclanthology.org/D18-1372.pdf) |
| 2018 | EMNLP | [Challenges of Using Text Classifiers for Causal Inference](https://aclanthology.org/D18-1488.pdf) |
| 2018 | NAACL | [An Encoder-decoder Approach to Predicting Causal Relations in Stories](https://aclanthology.org/W18-1506.pdf) |
| 2018 | COLING | [Crowdsourcing StoryLines: Harnessing the Crowd for Causal Relation Annotation](https://aclanthology.org/W18-4306.pdf) |
| 2018 | COLING | [Cyberbullying Intervention Based on Convolutional Neural Networks](https://aclanthology.org/W18-4405.pdf) |
| 2018 | CoNLL | [Vectorial Semantic Spaces Do Not Encode Human Judgments of Intervention Similarity](https://aclanthology.org/K18-1038.pdf) |
| 2019 | ACL | [Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology](https://aclanthology.org/P19-1161.pdf) |
| 2019 | ACL | [Conversational Response Re-ranking Based on Event Causality and Role Factored Tensor Event Embedding](https://aclanthology.org/W19-4106.pdf) |
| 2019 | ACL | [Transfer Learning for Causal Sentence Detection](https://aclanthology.org/W19-5031.pdf) |
| 2019 | EMNLP | [Identifying Predictive Causal Factors from News Streams](https://aclanthology.org/D19-1238.pdf) |
| 2019 | EMNLP | [Weakly Supervised Multilingual Causality Extraction from Wikipedia](https://aclanthology.org/D19-1296.pdf) |
| 2019 | EMNLP | [Detecting Causal Language Use in Science Findings](https://aclanthology.org/D19-1473.pdf) |
| 2019 | EMNLP | [Counterfactual Story Reasoning and Generation](https://aclanthology.org/D19-1509.pdf) |
| 2019 | EMNLP | [It’s All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution](https://aclanthology.org/D19-1530.pdf) |
| 2019 | EMNLP | [Event Causality Recognition Exploiting Multiple Annotators’ Judgments and Background Knowledge](https://aclanthology.org/D19-1590.pdf) |
| 2019 | EMNLP | [Towards Machine Reading for Interventions from Humanitarian-Assistance Program Literature](https://aclanthology.org/D19-1680.pdf) |
| 2019 | EMNLP | [Evaluating Research Novelty Detection: Counterfactual Approaches](https://aclanthology.org/D19-5315.pdf) |
| 2019 | NAACL | [Modeling Document-level Causal Structures for Event Causal Relation Identification](https://aclanthology.org/N19-1179.pdf) |
| 2019 | NAACL | [Enabling Search and Collaborative Assembly of Causal Interactions Extracted from Multilingual and Multi-domain Free Text](https://aclanthology.org/N19-4003.pdf) |
| 2019 | NAACL | [Eidos, INDRA, & Delphi: From Free Text to Executable Causal Models](https://aclanthology.org/N19-4008.pdf) |
| 2020 | ACL | [Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates](https://aclanthology.org/2020.acl-main.474.pdf) |
| 2020 | EMNLP | [De-Biased Court’s View Generation with Causality](https://aclanthology.org/2020.emnlp-main.56.pdf) |
| 2020 | EMNLP | [Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning](https://aclanthology.org/2020.emnlp-main.58.pdf) |
| 2020 | EMNLP | [Exploring Logically Dependent Multi-task Learning with Causal Inference](https://aclanthology.org/2020.emnlp-main.173.pdf) |
| 2020 | EMNLP | [XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning](https://aclanthology.org/2020.emnlp-main.185.pdf) |
| 2020 | EMNLP | [Conditional Causal Relationships between Emotions and Causes in Texts](https://aclanthology.org/2020.emnlp-main.252.pdf) |
| 2020 | EMNLP | [Learning to Contrast the Counterfactual Samples for Robust Visual Question Answering](https://aclanthology.org/2020.emnlp-main.265.pdf) |
| 2020 | EMNLP | [Counterfactual Off-Policy Training for Neural Dialogue Generation](https://aclanthology.org/2020.emnlp-main.276.pdf) |
| 2020 | EMNLP | [SSCR: Iterative Language-Based Image Editing via Self-Supervised Counterfactual Reasoning](https://aclanthology.org/2020.emnlp-main.357.pdf) |
| 2020 | EMNLP | [Less is More: Attention Supervision with Counterfactuals for Text Classification](https://aclanthology.org/2020.emnlp-main.543.pdf) |
| 2020 | EMNLP | [Counterfactual Generator: A Weakly-Supervised Method for Named Entity Recognition](https://aclanthology.org/2020.emnlp-main.590.pdf) |
| 2020 | EMNLP | [Causal Inference of Script Knowledge](https://aclanthology.org/2020.emnlp-main.612.pdf) |
| 2020 | EMNLP | [Reducing Sentiment Bias in Language Models via Counterfactual Evaluation](https://aclanthology.org/2020.findings-emnlp.7.pdf) |
| 2020 | EMNLP | [Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports](https://aclanthology.org/2020.findings-emnlp.274.pdf) |
| 2020 | EMNLP | [Neutralizing Gender Bias in Word Embeddings with Latent Disentanglement and Counterfactual Generation](https://aclanthology.org/2020.findings-emnlp.280.pdf) |
| 2020 | EMNLP | [Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented Data](https://aclanthology.org/2020.insights-1.13.pdf) |
| 2020 | EMNLP | [Twitter Data Augmentation for Monitoring Public Opinion on COVID-19 Intervention Measures](https://aclanthology.org/2020.nlpcovid19-2.19.pdf) |
| 2020 | COLING | [A Review of Dataset and Labeling Methods for Causality Extraction](https://aclanthology.org/2020.coling-main.133.pdf) |
| 2020 | COLING | [KnowDis: Knowledge Enhanced Data Augmentation for Event Causality Detection via Distant Supervision](https://aclanthology.org/2020.coling-main.135.pdf) |
| 2020 | COLING | [Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification](https://aclanthology.org/2020.coling-main.541.pdf) |
| 2020 | COLING | [A Sentiment-annotated Dataset of English Causal Connectives](https://aclanthology.org/2020.law-1.3.pdf) |
| 2020 | Findings | [Reducing Sentiment Bias in Language Models via Counterfactual Evaluation](https://aclanthology.org/2020.findings-emnlp.7.pdf) |
| 2020 | Findings | [Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports](https://aclanthology.org/2020.findings-emnlp.274.pdf) |
| 2020 | Findings | [Neutralizing Gender Bias in Word Embeddings with Latent Disentanglement and Counterfactual Generation](https://aclanthology.org/2020.findings-emnlp.280.pdf) |
| 2021 | ACL | [Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis](https://aclanthology.org/2021.acl-long.26.pdf) |
| 2021 | ACL | [COSY: COunterfactual SYntax for Cross-Lingual Understanding](https://aclanthology.org/2021.acl-long.48.pdf) |
| 2021 | ACL | [Learning Faithful Representations of Causal Graphs](https://aclanthology.org/2021.acl-long.69.pdf) |
| 2021 | ACL | [Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models](https://aclanthology.org/2021.acl-long.144.pdf) |
| 2021 | ACL | [ExCAR: Event Graph Knowledge Enhanced Explainable Causal Reasoning](https://aclanthology.org/2021.acl-long.183.pdf) |
| 2021 | ACL | [LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification](https://aclanthology.org/2021.acl-long.276.pdf) |
| 2021 | ACL | [Element Intervention for Open Relation Extraction](https://aclanthology.org/2021.acl-long.361.pdf) |
| 2021 | ACL | [De-biasing Distantly Supervised Named Entity Recognition via Causal Intervention](https://aclanthology.org/2021.acl-long.371.pdf) |
| 2021 | ACL | [Knowledge-Enriched Event Causality Identification via Latent Structure Induction Networks](https://aclanthology.org/2021.acl-long.376.pdf) |
| 2021 | ACL | [Counterfactual Inference for Text Classification Debiasing](https://aclanthology.org/2021.acl-long.422.pdf) |
| 2021 | ACL | [Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models](https://aclanthology.org/2021.acl-long.523.pdf) |
| 2021 | ACL | [Counterfactuals to Control Latent Disentangled Text Representations for Style Transfer](https://aclanthology.org/2021.acl-short.7.pdf) |
| 2021 | ACL | [Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions](https://aclanthology.org/2021.acl-short.10.pdf) |
| 2021 | ACL | [Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning Models](https://aclanthology.org/2021.acl-short.20.pdf) |
| 2021 | ACL | [Improving Counterfactual Generation for Fair Hate Speech Detection](https://aclanthology.org/2021.woah-1.10.pdf) |
| 2021 | NAACL | [Counterfactual Data Augmentation for Neural Machine Translation](https://aclanthology.org/2021.naacl-main.18.pdf) |
| 2021 | NAACL | [Everything Has a Cause: Leveraging Causal Inference in Legal Text Analysis](https://aclanthology.org/2021.naacl-main.155.pdf) |
| 2021 | NAACL | [Counterfactual Supporting Facts Extraction for Explainable Medical Record Based Diagnosis with Graph Network](https://aclanthology.org/2021.naacl-main.156.pdf) |
| 2021 | NAACL | [Graph Convolutional Networks for Event Causality Identification with Rich Document-level Structures](https://aclanthology.org/2021.naacl-main.273.pdf) |
| 2021 | NAACL | [Double Perturbation: On the Robustness of Robustness and Counterfactual Bias Evaluation](https://aclanthology.org/2021.naacl-main.305.pdf) |
| 2021 | NAACL | [Causal Effects of Linguistic Properties](https://aclanthology.org/2021.naacl-main.323.pdf) |
| 2021 | NAACL | [Error Causal inference for Multi-Fusion models](https://aclanthology.org/2021.alvr-1.2.pdf) |
| 2021 | NAACL | [Enhancing Multiple-Choice Question Answering with Causal Knowledge](https://aclanthology.org/2021.deelio-1.8.pdf) |
| 2021 | NAACL | [Statistically Evaluating Social Media Sentiment Trends towards COVID-19 Non-Pharmaceutical Interventions with Event Studies](https://aclanthology.org/2021.smm4h-1.1.pdf) |
| 2021 | EACL | [Interventions Recommendation: Professionals’ Observations Analysis in Special Needs Education](https://aclanthology.org/2021.bea-1.18.pdf) |
| 2021 | Findings | [Discovering Topics in Long-tailed Corpora with Causal Intervention](https://aclanthology.org/2021.findings-acl.15.pdf) |
| 2021 | Findings | [What if This Modified That? Syntactic Interventions with Counterfactual Embeddings](https://aclanthology.org/2021.findings-acl.76.pdf) |
| 2021 | Findings | [Improving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statement](https://aclanthology.org/2021.findings-acl.190.pdf) |
| 2021 | Findings | [Empowering Language Understanding with Counterfactual Reasoning](https://aclanthology.org/2021.findings-acl.196.pdf) |
| 2021 | Findings | [Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?](https://aclanthology.org/2021.findings-acl.364.pdf) |
| 2021 | Findings | [John praised Mary because _he_? Implicit Causality Bias and Its Interaction with Explicit Cues in LMs](https://aclanthology.org/2021.findings-acl.429.pdf) |
## Researchers
* [Susan Athey](https://athey.people.stanford.edu/)
* [David M. Blei](http://www.cs.columbia.edu/~blei/)
* [Cristian Danescu-Niculescu-Mizil](http://www.cs.cornell.edu/~cristian/)
* [Bernhard Schölkopf](https://www.is.mpg.de/~bs)
* [Aron Culotta](http://cs.tulane.edu/~aculotta/)
* [Amir Feder](https://amirfeder.github.io/)
* [Jacob Eisenstein](https://jacobeisenstein.github.io/)
* [Dhanya Sridhar](https://dsridhar91.github.io/)
* [Brandon Stewart](https://scholar.princeton.edu/bstewart/home)
* [Justine Zhang](https://tisjune.github.io/)
## Workshops
* [First Workshop on Causal Inference & NLP](https://causaltext.github.io/2021/)
## Related Repos
* [causaltext/causal-text-papers](https://github.com/causaltext/causal-text-papers)
* [fulifeng/Causal_Reading_Group](https://github.com/fulifeng/Causal_Reading_Group)
* [zhijing-jin/Causality4NLP_Papers](https://github.com/zhijing-jin/Causality4NLP_Papers)
* [wangzheng17/awesome-causal-vision](https://github.com/wangzheng17/awesome-causal-vision)
* [Awesome-Causality-in-CV](https://github.com/Wangt-CN/Awesome-Causality-in-CV)
* [napsternxg/awesome-causality](https://github.com/napsternxg/awesome-causality)
* [awesome-causality-algorithms](https://github.com/rguo12/awesome-causality-algorithms)
* [jvpoulos/causal-ml](https://github.com/jvpoulos/causal-ml)
* [RL-Causality](https://github.com/debmandal/RL-Causality)
* [awesome-causal-inference](https://github.com/imirzadeh/awesome-causal-inference)
## Licenses
[](http://creativecommons.org/publicdomain/zero/1.0/)
To the extent possible under law, [Zhihong Chen](https://github.com/zhjohnchan) has waived all copyright and related or neighboring rights to this work.