mlsanityData to 7 Oct 2026

Towards Fine-grained Causal Reasoning and QA

arXiv 2204.07408 ↗First posted 15 Apr 2022cs.CL cs.AI cs.LOcited by 13

On the map: LLM reasoning → Causal reasoning in LLMs

Abstract (arXiv)

Understanding causality is key to the success of NLP applications, especially in high-stakes domains. Causality comes in various perspectives such as enable and prevent that, despite their importance, have been largely ignored in the literature. This paper introduces a novel fine-grained causal reasoning dataset and presents a series of novel predictive tasks in NLP, such as causality detection, event causality extraction, and Causal QA. Our dataset contains human annotations of 25K cause-effect event pairs and 24K question-answering pairs within multi-sentence samples, where each can have multiple causal relationships. Through extensive experiments and analysis, we show that the complex relations in our dataset bring unique challenges to state-of-the-art methods across all three tasks and highlight potential research opportunities, especially in developing "causal-thinking" methods.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Placed in Causal reasoning in LLMs, one of 17 directions in LLM reasoning. Builds on 42 of its 66 references that are in the map. First posted on arXiv 15 Apr 2022.

Builds on

42 of 66 references.

References · 42

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  5. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  6. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  7. 2018HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answeringcited by 3,686
  8. 2020Big Bird: Transformers for Longer Sequencescited by 1,673
  9. 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,538
  10. 2019Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shiftcited by 1,274
  11. 2014Convolutional Neural Networks for Sentence Classificationcited by 1,124
  12. 2019DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphscited by 883
30 more
  1. 2017RACE: Large-scale ReAding Comprehension Dataset From Examinationscited by 851
  2. 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 832
  3. 2018Annotation Artifacts in Natural Language Inference Datacited by 656
  4. 2021FinQA: A Dataset of Numerical Reasoning over Financial Datacited by 552
  5. 2019Learning the Difference that Makes a Difference with Counterfactually-Augmented Datacited by 428
  6. 2020LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentioncited by 326
  7. 2019Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoningcited by 281
  8. 2020Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learningcited by 216
  9. 2021PAQ: 65 Million Probably-Asked Questions and What You Can Do With Themcited by 198
  10. 2021Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyondcited by 177
  11. 2019DREAM: A Challenge Dataset and Models for Dialogue-Based Reading Comprehensioncited by 156
  12. 2020Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasetscited by 137
  13. 2020MuTual: A Dataset for Multi-Turn Dialogue Reasoningcited by 114
  14. 2020Explaining The Efficacy of Counterfactually Augmented Datacited by 64
  15. 2020Robustness to Spurious Correlations via Human Annotationscited by 62
  16. 2021Can Generative Pre-trained Language Models Serve as Knowledge Bases for Closed-book QA?cited by 62
  17. 2018What Makes Reading Comprehension Questions Easier?cited by 59
  18. 2020Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimatescited by 59
  19. 2019Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasetscited by 46
  20. 2021Why Machine Reading Comprehension Models Learn Shortcuts?cited by 40
  21. 2021Learning Neural Causal Models with Active Interventionscited by 40
  22. 2020Question Directed Graph Attention Network for Numerical Reasoning over Textcited by 35
  23. 2018Constructing Narrative Event Evolutionary Graph for Script Event Predictioncited by 33
  24. 2021Guided Generation of Cause and Effectcited by 33
  25. 2020Financial Document Causality Detection Shared Task (FinCausal 2020)cited by 31
  26. 2021Challenges in Generalization in Open Domain Question Answeringcited by 30
  27. 2021DAGN: Discourse-Aware Graph Network for Logical Reasoningcited by 28
  28. 2021CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervisioncited by 12
  29. 2020Data Processing and Annotation Schemes for FinCausal Shared Taskcited by 3
  30. 2019Intra-Ensemble in Neural Networkscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 3; 2024: 4; 2025: 3; 2026: 1.

13 papers.

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  1. 2023Document Understanding Dataset and Evaluation (DUDE)cited by 132
  2. 2025Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?cited by 36
  3. 2024Cofca: A Step-Wise Counterfactual Multi-hop QA benchmarkcited by 26
  4. 2022WikiWhy: Answering and Explaining Cause-and-Effect Questionscited by 21
  5. 2024A Critical Review of Causal Reasoning Benchmarks for Large Language Modelscited by 13
  6. 2025HellaSwag-Pro: A Large-Scale Bilingual Benchmark for Evaluating the Robustness of LLMs in Commonsense Reasoningcited by 7
  7. 2023Learning to Generalize for Cross-domain QAcited by 6
  8. 2025Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Modelscited by 5
  9. 2024A Comprehensive Evaluation on Event Reasoning of Large Language Modelscited by 4
  10. 2024EVIT: Event-Oriented Instruction Tuning for Event Reasoningcited by 2
  11. 2022Trust in Language Grounding: a new AI challenge for human-robot teamscited by 1
  12. 2026Enhancing Structural Mapping with LLM-derived Abstractions for Analogical Reasoning in Narrativescited by 1
1 more
  1. 2023EDeR: A Dataset for Exploring Dependency Relations Between Eventscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025ACCESS : A Benchmark for Abstract Causal Event Discovery and Reasoning
  2. 2022e-CARE: a New Dataset for Exploring Explainable Causal Reasoning
  3. 2023CLadder: Assessing Causal Reasoning in Language Models
  4. 2025Causality for Natural Language Processing
  5. 2024Enhancing Event Causality Identification with Rationale and Structure-Aware Causal Question Answering
  6. 2025A Multi-Level Benchmark for Causal Language Understanding in Social Media Discourse
  7. 2026CausalFlip: A Benchmark for LLM Causal Judgment Beyond Semantic Matching
  8. 2024Causal Inference with Large Language Model: A Survey