mlsanityData to 7 Oct 2026

e-CARE: a New Dataset for Exploring Explainable Causal Reasoning

arXiv 2205.05849 ↗First posted 12 May 2022cs.AI cs.CLcited by 47

On the map: LLM reasoning → Causal reasoning in LLMs

Abstract (arXiv)

Understanding causality has vital importance for various Natural Language Processing (NLP) applications. Beyond the labeled instances, conceptual explanations of the causality can provide deep understanding of the causal facts to facilitate the causal reasoning process. However, such explanation information still remains absent in existing causal reasoning resources. In this paper, we fill this gap by presenting a human-annotated explainable CAusal REasoning dataset (e-CARE), which contains over 21K causal reasoning questions, together with natural language formed explanations of the causal questions. Experimental results show that generating valid explanations for causal facts still remains especially challenging for the state-of-the-art models, and the explanation information can be helpful for promoting the accuracy and stability of causal reasoning models.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). Placed in Causal reasoning in LLMs, one of 17 directions in LLM reasoning. Builds on 23 of its 59 references that are in the map. First posted on arXiv 12 May 2022.

Builds on

23 of 59 references.

References · 23

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  4. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,801
  5. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
  6. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
  7. 2018CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledgecited by 1,793
  8. 2019Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inferencecited by 864
  9. 2018Annotation Artifacts in Natural Language Inference Datacited by 656
  10. 2019ERASER: A Benchmark to Evaluate Rationalized NLP Modelscited by 523
  11. 2018e-SNLI: Natural Language Inference with Natural Language Explanationscited by 468
  12. 2019Explain Yourself! Leveraging Language Models for Commonsense Reasoningcited by 367
11 more
  1. 2019Abductive Commonsense Reasoningcited by 300
  2. 2016Adversarial Training Methods for Semi-Supervised Text Classificationcited by 280
  3. 2019Joint Reasoning for Temporal and Causal Relationscited by 60
  4. 2018Training Classifiers with Natural Language Explanationscited by 58
  5. 2020GenericsKB: A Knowledge Base of Generic Statementscited by 51
  6. 2020Learning to Explain: Datasets and Models for Identifying Valid Reasoning Chains in Multihop Question-Answeringcited by 49
  7. 2021Guided Generation of Cause and Effectcited by 33
  8. 2018Adversarial training for multi-context joint entity and relation extractioncited by 29
  9. 2019Finding Generalizable Evidence by Learning to Convince Q&A Modelscited by 25
  10. 2020Teaching Machine Comprehension with Compositional Explanationscited by 22
  11. 2017Robust Multilingual Part-of-Speech Tagging via Adversarial Trainingcited by 21

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 13; 2024: 13; 2025: 13; 2026: 5.

47 papers.

Sort:

By area:

  1. 2023FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Setscited by 198
  2. 2023Is ChatGPT a Good Causal Reasoner? A Comprehensive Evaluationcited by 69
  3. 2023Natural Language Reasoning, A Surveycited by 61
  4. 2025The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systemscited by 57
  5. 2023ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relationscited by 39
  6. 2024IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neuronscited by 36
  7. 2025Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?cited by 36
  8. 2023GPT-3.5, GPT-4, or BARD? Evaluating LLMs Reasoning Ability in Zero-Shot Setting and Performance Boosting Through Promptscited by 34
  9. 2024Causal Inference with Large Language Model: A Surveycited by 31
  10. 2025Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarkscited by 26
  11. 2023Intuitive or Dependent? Investigating LLMs' Behavior Style to Conflicting Promptscited by 23
  12. 2024Cause and Effect: Can Large Language Models Truly Understand Causality?cited by 23
35 more
  1. 2023Eliminating Reasoning via Inferring with Planning: A New Framework to Guide LLMs' Non-linear Thinkingcited by 19
  2. 2025Large language models for artificial general intelligence (AGI): A survey of foundational principles and approachescited by 18
  3. 2024Quantifying the Capabilities of LLMs across Scale and Precisioncited by 17
  4. 2025Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performancecited by 17
  5. 2024CausalEval: Towards Better Causal Reasoning in Language Modelscited by 13
  6. 2025Mitigating Hallucinations in Large Language Models via Causal Reasoningcited by 13
  7. 2023Through the Lens of Core Competency: Survey on Evaluation of Large Language Modelscited by 12
  8. 2023Emerging Synergies in Causality and Deep Generative Models: A Surveycited by 10
  9. 2023Reasoning before Responding: Integrating Commonsense-based Causality Explanation for Empathetic Response Generationcited by 9
  10. 2024Self-Evolving GPT: A Lifelong Autonomous Experiential Learnercited by 9
  11. 2024MMRA: A Benchmark for Evaluating Multi-Granularity and Multi-Image Relational Association Capabilities in Large Visual Language Modelscited by 9
  12. 2025Always Tell Me The Odds: Fine-grained Conditional Probability Estimationcited by 9
  13. 2024Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidancecited by 8
  14. 2025PROPHET: An Inferable Future Forecasting Benchmark with Causal Intervened Likelihood Estimationcited by 8
  15. 2024Causality extraction from medical text using Large Language Models (LLMs)cited by 7
  16. 2023A Survey of Methods, Challenges and Perspectives in Causalitycited by 6
  17. 2023EvEval: A Comprehensive Evaluation of Event Semantics for Large Language Modelscited by 6
  18. 2024Inference to the Best Explanation in Large Language Modelscited by 5
  19. 2026Diagnosing and Mitigating Sycophancy and Skepticism in LLM Causal Judgmentcited by 5
  20. 2026Wiring the 'Why': A Unified Taxonomy and Survey of Abductive Reasoning in LLMscited by 5
  21. 2024A Comprehensive Evaluation on Event Reasoning of Large Language Modelscited by 4
  22. 2022Harnessing Knowledge and Reasoning for Human-Like Natural Language Generation: A Brief Reviewcited by 3
  23. 2025ExpliCa: Evaluating Explicit Causal Reasoning in Large Language Modelscited by 3
  24. 2023How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors?cited by 2
  25. 2024EVIT: Event-Oriented Instruction Tuning for Event Reasoningcited by 2
  26. 2024Diagnosing and Remedying Knowledge Deficiencies in LLMs via Label-free Curricular Meaningful Learningcited by 2
  27. 2025Causal Graph based Event Reasoning using Semantic Relation Expertscited by 2
  28. 2025Causal MAS: A Survey of Large Language Model Architectures for Discovery and Effect Estimationcited by 2
  29. 2022Trust in Language Grounding: a new AI challenge for human-robot teamscited by 1
  30. 2022ReCo: Reliable Causal Chain Reasoning via Structural Causal Recurrent Neural Networkscited by 1
  31. 2025Beyond Benchmarks: LLM Evaluation with an Anthropomorphic and Lifecycle-oriented Roadmapcited by 1
  32. 2026CausalT5k: Diagnosing Refusal and Failure Modes in Trustworthy Causal Reasoning Across Causal Rungscited by 1
  33. 2025Causal Retrieval with Semantic Considerationcited by 0
  34. 2026KALE: Enhancing Knowledge Manipulation in Large Language Models via Knowledge-aware Learningcited by 0
  35. 2026Contextual Causality with Large Language Models: A Surveycited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2022Towards Fine-grained Causal Reasoning and QA
  2. 2023CLadder: Assessing Causal Reasoning in Language Models
  3. 2025A Multi-Level Benchmark for Causal Language Understanding in Social Media Discourse
  4. 2025ACCESS : A Benchmark for Abstract Causal Event Discovery and Reasoning
  5. 2025Causality for Natural Language Processing
  6. 2024A Critical Review of Causal Reasoning Benchmarks for Large Language Models
  7. 2023Causal Reasoning and Large Language Models: Opening a New Frontier for Causality
  8. 2024CausalGraph2LLM: Evaluating LLMs for Causal Queries