Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond

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Stress Test Evaluation for Natural Language InferencePreprint

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Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models

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Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress TestsPreprint

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Reducing Sentiment Bias in Language Models via Counterfactual EvaluationPreprint

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Bad Seeds: Evaluating Lexical Methods for Bias Measurement

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Semi-Supervised Learning and Domain Adaptation in Natural Language Processing

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Discovery of Treatments from Text Corpora

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Causal abstractions of neural networks

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Explaining The Efficacy of Counterfactually Augmented DataPreprint

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Tailor: Generating and Perturbing Text with Semantic Controls

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Fragile Masculinity

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Causal Effects of Linguistic Properties

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TextSETTR: Few-Shot Text Style Extraction and Tunable Targeted Restyling

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An Investigation of the (In)effectiveness of Counterfactually Augmented Data

Joshi, N., & He, H. (2022) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2022.acl-long.256 · Cited by 34 · see citing works

Self-training Avoids Using Spurious Features Under Domain ShiftPreprint

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An Introduction to Proximal Causal Inference

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Intrinsic bias metrics do not correlate with application bias

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Predicting Sales from the Language of Product Descriptions.

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Fairness and Robustness in Invariant Learning: A Case Study in Toxicity ClassificationPreprint

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Estimating Causal Effects of Tone in Online Debates

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DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation

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Quantifying the Causal Effects of Conversational Tendencies

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Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP

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Robust Text Classification under Confounding Shift

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Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference

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Polyjuice: Automated, General-purpose Counterfactual Generation.Preprint

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Does Data Augmentation Improve Generalization in NLP?Preprint

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The Dangers of Counterfactual Causal Thinking about Detecting Racial Discrimination

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Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions

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TextSETTR: Label-Free Text Style Extraction and Tunable Targeted RestylingPreprint

Riley, P., Constant, N., Guo, M., Kumar, G., Uthus, D., & Parekh, Z. (2021) · arXiv (Cornell University) · Cited by 8 · see citing works

Generating Synthetic Text Data to Evaluate Causal Inference MethodsPreprint

Wood-Doughty, Z., Shpitser, I., & Dredze, M. H. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.05638 · Cited by 7 · see citing works

TextSETTR: Few-Shot Text Style Extraction and Tunable Targeted RestylingPreprint

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Natural Language Processing for Smart Healthcare

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Reasoning with Language Model Prompting: A Survey

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Deep Learning for Intelligent Human–Computer Interaction

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Towards Faithful Model Explanation in NLP: A Survey

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Using natural language processing to analyse text data in behavioural science

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Causal Inference Meets Deep Learning: A Comprehensive Survey

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CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System

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From explainable to interpretable deep learning for natural language processing in healthcare: How far from reality?

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Local Interpretations for Explainable Natural Language Processing: A Survey

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Paralanguage Classifier (PARA): An Algorithm for Automatic Coding of Paralinguistic Nonverbal Parts of Speech in Text

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Learning consistent representations with temporal and causal enhancement for knowledge tracing

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Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective

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Large language models, social demography, and hegemony: comparing authorship in human and synthetic text

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Explainable depression symptom detection in social media

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DISCO: Distilling Counterfactuals with Large Language Models

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Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models

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Towards Effective Causal Partitioning by Edge Cutting of Adjoint Graph

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How Pre-trained Language Models Capture Factual Knowledge? A Causal-Inspired Analysis

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Debiasing NLU Models via Causal Intervention and Counterfactual Reasoning

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The language of opinion change on social media under the lens of communicative action

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Improving the quality evaluation process of machine learning algorithms applied to landslide time series analysis

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Natural language processing for social science research: A comprehensive review

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Counterfactual Learning on Graphs: A Survey

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DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation

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Modifying AI, Enhancing Essays: How Active Engagement with Generative AI Boosts Writing Quality

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Neural Architecture Search with Progressive Evaluation and Subpopulation Preservation

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Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang

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Causal Artificial Intelligence in Legal Language Processing: A Systematic Review

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The Sweet Danger of Sugar: Debunking Representation Learning for Encrypted Traffic Classification

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Can Prompt Probe Pretrained Language Models? Understanding the Invisible Risks from a Causal View

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CRAB: Assessing the Strength of Causal Relationships Between Real-world Events

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Counterfactually Augmented Data and Unintended Bias: The Case of Sexism and Hate Speech Detection

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Affection: Learning Affective Explanations for Real-World Visual Data

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Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP

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Interact with the Explanations: Causal Debiased Explainable Recommendation System

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FaiRR: Faithful and Robust Deductive Reasoning over Natural Language

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From text to model: Leveraging natural language processing for system dynamics model development

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Reconsidering Read and Spontaneous Speech: Causal Perspectives on the Generation of Training Data for Automatic Speech Recognition

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The Life Cycle of Knowledge in Big Language Models: A Survey

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The Life Cycle of Knowledge in Big Language Models: A Survey

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Informativeness and Invariance: Two Perspectives on Spurious Correlations in Natural Language

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Does Victim Gender Matter for Justice Delivery? Police and Judicial Responses to Women’s Cases in India

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A Causal View of Entity Bias in (Large) Language Models

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A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models

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NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation

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XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction

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DNA of learning behaviors: A novel approach of learning performance prediction by NLP

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Quantum causal inference with extremely light touch

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Prognosis of exploration on Chat GPT with artificial intelligence ethics

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Neural architecture search via similarity adaptive guidance

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Interpreting Low-Level Vision Models With Causal Effect Maps

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Unsupervised Editing for Counterfactual Stories

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An Empirical Study on Explanations in Out-of-Domain Settings

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COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective

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IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions

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A Primer on Deep Learning for Causal Inference

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Causality from bottom to top: a survey

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An exploration of mutual information based on emotion–cause pair extraction

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An empirical study of counterfactual visualization to support visual causal inference

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Using artificial intelligence to personalise curricula and increase motivation to learn, taking into account psychological aspects

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Seeded Topic Models in Digital Archives: Analyzing Interpretations of Immigration in Swedish Newspapers, 1945–2019

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Causality-aware Concept Extraction based on Knowledge-guided Prompting

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Human-machine interactions based on hand gesture recognition using deep learning methods

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Automatic Rule Induction for Efficient Semi-Supervised Learning

Pryzant, R., Yang, Z., Yi‐chong, X., Zhu, C., & Zeng, M. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.3 · Cited by 10 · see citing works

Using Sociolinguistic Variables to Reveal Changing Attitudes Towards Sexuality and Gender

CH-Wang, S., & Jurgens, D. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.782 · Cited by 9 · see citing works

Deconfounded Visual Question Generation with Causal Inference

Chen, J., Guo, Z., Xie, J., Cai, Y., & Li, Q. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612536 · Cited by 9 · see citing works

Label-aware debiased causal reasoning for Natural Language Inference

Zhang, K., Zhang, D., Wu, L., Hong, R., Zhao, Y., & Wang, M. (2024) · AI Open · doi:10.1016/j.aiopen.2024.02.001 · Cited by 9 · see citing works

Probabilistic Machine Learning: New Frontiers for Modeling Consumers and their Choices

Dew, R., Padilla, N., Luo, L., Oblander, S., Ansari, A., Boughanmi, K., Braun, M. I., Feinberg, F. M., Liu, J., Otter, T., et al. (2024) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2024.11.002 · Cited by 9 · see citing works

Disentangled Representation Learning for Causal Inference With Instruments

Cheng, D., Li, J., Liu, L., Xu, Z., Zhang, W., Liu, J., & Le, T. D. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3512790 · Cited by 9 · see citing works

Is anisotropy really the cause of BERT embeddings not being semantic?

Baggetto, A. F., & Fresno, V. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.314 · Cited by 9 · see citing works

Rating Sentiment Analysis Systems for Bias Through a Causal Lens

Lakkaraju, K., Srivastava, B., & Valtorta, M. (2024) · IEEE Transactions on Technology and Society · doi:10.1109/tts.2024.3375519 · Cited by 9 · see citing works

Mitigating Biases in Hate Speech Detection from A Causal Perspective

Zhang, Z., Chen, J., & Yang, D. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.440 · Cited by 8 · see citing works

A highly scalable deep learning language model for common risks prediction among psychiatric inpatients

Zhu, E., Wang, J., Zhou, G., Li, C., Chen, F., Ju, K., Chen, L., Yin, Y., Chen, Y., Zhang, Y., et al. (2025) · BMC Medicine · doi:10.1186/s12916-025-04150-7 · Cited by 8 · see citing works

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Volkova, S., Arendt, D., Saldanha, E., Glenski, M., Ayton, E., Cottam, J. A., Aksoy, S. G., Jefferson, B. A., & Shrivaram, K. (2021) · Computational and Mathematical Organization Theory · doi:10.1007/s10588-021-09351-y · Cited by 8 · see citing works

Is ChatGPT the Future of Causal Text Mining? A Comprehensive Evaluation and Analysis

Takayanagi, T., Suzuki, M., Kobayashi, R., Sakaji, H., & Izumi, K. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825555 · Cited by 8 · see citing works

Natural language processing

Németh, R., & Koltai, J. (2023) · Intersections · doi:10.17356/ieejsp.v9i1.871 · Cited by 8 · see citing works

Biomedical event causal relation extraction based on a knowledge-guided hierarchical graph network

Zhang, B., Li, L., Song, D., & Zhao, Y. S. (2023) · Soft Computing · doi:10.1007/s00500-023-08882-7 · Cited by 8 · see citing works

Using Computational Grounded Theory to Analyze Pre-service Chemistry Teachers’ Reflective Practice Regarding Technology Integration in Classrooms Within a Service-Learning–Oriented Seminar

Rost, M., Resch, K., & Lembens, A. (2025) · Journal of Science Education and Technology · doi:10.1007/s10956-025-10236-x · Cited by 7 · see citing works

CLICK: Integrating Causal Inference and Commonsense Knowledge Incorporation for Counterfactual Story Generation

Li, D., Guo, Z., Liu, Q., Jin, L., Zhang, Z., Wei, K., & Li, F. (2023) · Electronics · doi:10.3390/electronics12194173 · Cited by 7 · see citing works

Advances in automatically rating the trustworthiness of text processing services

Srivastava, B., Lakkaraju, K., Bernagozzi, M., & Valtorta, M. (2023) · AI and Ethics · doi:10.1007/s43681-023-00391-5 · Cited by 7 · see citing works

DDCI: Unsupervised Domain Adaptation for Remote Sensing Images Based on Diffusion Causal Distillation

Zhao, J., Li, Y., Zhou, Y. Z., Du, W.-L., Li, X., Yao, R., & Saddik, A. E. (2025) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2025.3553094 · Cited by 7 · see citing works

Conceptualizing Treatment Leakage in Text-based Causal Inference

Daoud, A., Jerzak, C., & Johansson, R. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.413 · Cited by 7 · see citing works

Improving long-tail relation extraction via adaptive adjustment and causal inference

Tang, J., Li, L., Lu, H., Zhang, B., & Wu, H. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126563 · Cited by 7 · see citing works

The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models

Hagström, L., Saynova, D., Norlund, T., Johansson, M., & Johansson, R. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2023.emnlp-main.332 · Cited by 6 · see citing works

Application of natural language processing to predict final recommendation of Brazilian health technology assessment reports

Cardoso, M. M. D. A., Rúgolo, J. R. M., Thabane, L., da Rocha, N. C., Barbosa, A. M. P., Komoda, D. S., de Almeida, J. T. C., Curado, D. D. S. P., Weber, S. A. T., & de Andrade, L. G. M. (2024) · International Journal of Technology Assessment in Health Care · doi:10.1017/s0266462324000163 · Cited by 6 · see citing works

Visual Comparison of Text Sequences Generated by Large Language Models

Sevastjanova, R., Vogelbacher, S., Spitz, A., Keim, D. A., & El‐Assady, M. (2023) · IEEE Visualization in Data Science (VDS) · doi:10.1109/vds60365.2023.00007 · Cited by 6 · see citing works

Causal Intervention for Mitigating Name Bias in Machine Reading Comprehension

Zhu, J., Wu, S., Zhang, X., Hou, Y., & Feng, Z. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.812 · Cited by 6 · see citing works

IDIAPers @ Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model

Fajčík, M., Singh, M., Zuluaga-gomez, J. P., Villatoro-Tello, E., Burdisso, S., Motlíček, P., & Smrž, P. (2022) · Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE) · doi:10.18653/v1/2022.case-1.10 · Cited by 6 · see citing works

Proceedings of the 2nd Workshop on Trustworthy Natural Language Processing (TrustNLP 2022)

(2022) · doi:10.18653/v1/2022.trustnlp-1 · Cited by 6 · see citing works

Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE)

(2022) · doi:10.18653/v1/2022.case-1 · Cited by 6 · see citing works

Future Directions for Quantitative Systems Pharmacology

Schoeberl, B., Musante, C. J., & Ramanujan, S. (2024) · Handbook of experimental pharmacology · doi:10.1007/164_2024_737 · Cited by 5 · see citing works

Causal Inferences from Digital Behavioral Data

Leitgöb, H., & Keusch, F. (2026) · KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie · doi:10.1007/s11577-026-01050-3 · Cited by 5 · see citing works

Causal Machine Learning: A Deductive–Inductive Framework for Sociological Research

Jeon, N., & Brand, J. E. (2026) · KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie · doi:10.1007/s11577-026-01053-0 · Cited by 5 · see citing works

Deconfounded Emotion Guidance Sticker Selection with Causal Inference

Chen, J., Cai, Y., Xu, R., Wang, J., Xie, J., & Li, Q. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681522 · Cited by 5 · see citing works

Evaluating Causal AI Techniques for Health Misinformation Detection

Clark, O., & Joshi, K. P. (2025) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomworkshops65533.2025.00040 · Cited by 5 · see citing works

Pseudo dense counterfactual augmentation for aspect-based sentiment analysis

Ouyang, J., Feng, S., Wang, B., & Yang, Z. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126869 · Cited by 5 · see citing works

Deciphering the Interplay of Parametric and Non-parametric Memory in Retrieval-augmented Language Models

Farahani, M., & Johansson, R. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2024.emnlp-main.943 · Cited by 5 · see citing works

Graphing the Truth: Harnessing Causal Insights for Advanced Multimodal Fake News Detection

Ma, Z., Luo, M., Zeng, Z., Wan, H., Li, Y., & Zhao, X. H. (2025) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2025.3637696 · Cited by 4 · see citing works

Conformal Counterfactual Inference under Hidden Confounding

Chen, Z., Guo, R., Ton, J.-F., & Liu, Y. (2024) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3637528.3671976 · Cited by 4 · see citing works

Darkness can not drive out darkness: Investigating Bias in Hate SpeechDetection Models

Elsafoury, F. (2022) · Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (ACL SRW) · doi:10.18653/v1/2022.acl-srw.4 · Cited by 4 · see citing works

Causal Inference and Natural Language Processing

Chen, W., & Chu, Z. (2023) · Springer eBooks · doi:10.1007/978-3-031-35051-1_9 · Cited by 1 · see citing works

CausalNLP Tutorial: An Introduction to Causality for Natural Language Processing

Jin, Z., Feder, A., & Zhang, K. (2022) · doi:10.18653/v1/2022.emnlp-tutorials.4 · Cited by 1 · see citing works

Causal Foundations for Language Data and Models

Lin, V. (2026) · KiltHub Repository · doi:10.1184/r1/33972265

Causal Inference in Natural Language Processing: Application Status and Future Outlook

Chu, Y. (2024) · Applied and Computational Engineering · doi:10.54254/2755-2721/103/20241128

A Survey on the Identification of Causal Relation in Texts

Han, M., & Wang, Y. (2021) · IEEE International Conference on Progress in Informatics and Computing · doi:10.1109/pic53636.2021.9687029 · Cited by 1 · see citing works