mlsanityData to 7 Oct 2026

Is ChatGPT a Good Causal Reasoner? A Comprehensive Evaluation

arXiv 2305.07375 ↗First posted 12 May 2023cs.CL cs.AIcited by 69

On the map: LLM reasoning → Causal reasoning in LLMs

Abstract (arXiv)

Causal reasoning ability is crucial for numerous NLP applications. Despite the impressive emerging ability of ChatGPT in various NLP tasks, it is unclear how well ChatGPT performs in causal reasoning. In this paper, we conduct the first comprehensive evaluation of the ChatGPT's causal reasoning capabilities. Experiments show that ChatGPT is not a good causal reasoner, but a good causal explainer. Besides, ChatGPT has a serious hallucination on causal reasoning, possibly due to the reporting biases between causal and non-causal relationships in natural language, as well as ChatGPT's upgrading processes, such as RLHF. The In-Context Learning (ICL) and Chain-of-Thought (CoT) techniques can further exacerbate such causal hallucination. Additionally, the causal reasoning ability of ChatGPT is sensitive to the words used to express the causal concept in prompts, and close-ended prompts perform better than open-ended prompts. For events in sentences, ChatGPT excels at capturing explicit causality rather than implicit causality, and performs better in sentences with lower event density and smaller lexical distance between events. The code is available on https://github.com/ArrogantL/ChatGPT4CausalReasoning .

Key facts. Cited by 69 papers in the map (data through 7 Oct 2026). Placed in Causal reasoning in LLMs, one of 17 directions in LLM reasoning. Builds on 25 of its 39 references that are in the map. First posted on arXiv 12 May 2023.

Builds on

25 of 39 references.

Closest ancestors · 3

Same direction, newest first

  1. 2023COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective9 May
  2. 2023Causal Reasoning and Large Language Models: Opening a New Frontier for Causality28 Apr
  3. 2022e-CARE: a New Dataset for Exploring Explainable Causal Reasoning12 May

Other references · 22

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  5. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  6. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  7. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  8. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  9. 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
  10. 2023Is ChatGPT a General-Purpose Natural Language Processing Task Solver?cited by 486
  11. 2023ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPTcited by 250
  12. 2022Ask Me Anything: A simple strategy for prompting language modelscited by 155
10 more
  1. 2023Exploring the Feasibility of ChatGPT for Event Extractioncited by 76
  2. 2022MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extractioncited by 65
  3. 2020How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Contextcited by 53
  4. 2022ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classificationcited by 45
  5. 2023ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relationscited by 39
  6. 2021Guided Generation of Cause and Effectcited by 33
  7. 2021Improving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statementcited by 21
  8. 2021LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identificationcited by 16
  9. 2021CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervisioncited by 12
  10. 2017A Sequential Model for Classifying Temporal Relations between Intra-Sentence Eventscited by 11

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 11; 2024: 29; 2025: 25; 2026: 4.

69 papers.

Sort:

By area:

  1. 2023Challenges and Applications of Large Language Modelscited by 251
  2. 2024Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMscited by 224
  3. 2023GPTEval: A Survey on Assessments of ChatGPT and GPT-4cited by 73
  4. 2024Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Datacited by 61
  5. 2025Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?cited by 36
  6. 2024Causal Inference with Large Language Model: A Surveycited by 31
  7. 2023Large Language Models are Complex Table Parserscited by 28
  8. 2023Primacy Effect of ChatGPTcited by 27
  9. 2024Large Language Models and Causal Inference in Collaboration: A Surveycited by 26
  10. 2024Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detectioncited by 26
  11. 2024Causality for Large Language Modelscited by 24
  12. 2024XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Modelscited by 23
38 more
  1. 2024From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalitiescited by 18
  2. 2024A Causal Explainable Guardrails for Large Language Modelscited by 18
  3. 2023Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuningcited by 14
  4. 2024A Critical Review of Causal Reasoning Benchmarks for Large Language Modelscited by 13
  5. 2023Through the Lens of Core Competency: Survey on Evaluation of Large Language Modelscited by 12
  6. 2024Document-level Causal Relation Extraction with Knowledge-guided Binary Question Answeringcited by 12
  7. 2024Failure Modes of LLMs for Causal Reasoning on Narrativescited by 12
  8. 2023Event Causality Is Key to Computational Story Understandingcited by 11
  9. 2024Causal Agent based on Large Language Modelcited by 10
  10. 2025Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safetycited by 10
  11. 2025ChartInsighter: An Approach for Mitigating Hallucination in Time-series Chart Summary Generation with A Benchmark Datasetcited by 9
  12. 2024How well can a large language model explain business processes as perceived by users?cited by 8
  13. 2023Enhance Multi-domain Sentiment Analysis of Review Texts through Prompting Strategiescited by 7
  14. 2024Towards a Benchmark for Causal Business Process Reasoning with LLMscited by 7
  15. 2024Are LLMs Good Annotators for Discourse-level Event Relation Extraction?cited by 7
  16. 2025LLM Cannot Discover Causality, and Should Be Restricted to Non-Decisional Support in Causal Discoverycited by 7
  17. 2024Identifying while Learning for Document Event Causality Identificationcited by 6
  18. 2024A Survey of Event Causality Identification: Taxonomy, Challenges, Assessment, and Prospectscited by 6
  19. 2025Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Actingcited by 6
  20. 2023An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Developmentcited by 5
  21. 2025MECD+: Unlocking Event-Level Causal Graph Discovery for Video Reasoningcited by 5
  22. 2025Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inferencecited by 5
  23. 2025Can LLMs Leverage Observational Data? Towards Data-Driven Causal Discovery with LLMscited by 4
  24. 2025CausalARC: Abstract Reasoning with Causal World Modelscited by 4
  25. 2023TILFA: A Unified Framework for Text, Image, and Layout Fusion in Argument Miningcited by 3
  26. 2024In-context Contrastive Learning for Event Causality Identificationcited by 3
  27. 2024Prompting or Fine-tuning? Exploring Large Language Models for Causal Graph Validationcited by 3
  28. 2024CausalChat: Interactive Causal Model Development and Refinement Using Large Language Modelscited by 3
  29. 2025ACCESS : A Benchmark for Abstract Causal Event Discovery and Reasoningcited by 3
  30. 2025ExpliCa: Evaluating Explicit Causal Reasoning in Large Language Modelscited by 3
  31. 2025Characterizing Mamba's Selective Memory using Auto-Encoderscited by 3
  32. 2024Is ChatGPT the Future of Causal Text Mining? A Comprehensive Evaluation and Analysiscited by 2
  33. 2024Do LLMs Have the Generalization Ability in Conducting Causal Inference?cited by 2
  34. 2025ExpeTrans: LLMs Are Experiential Transfer Learnerscited by 2
  35. 2025Paths to Causality: Finding Informative Subgraphs Within Knowledge Graphs for Knowledge-Based Causal Discoverycited by 2
  36. 2025"Amazing, They All Lean Left" -- Analyzing the Political Temperaments of Current LLMscited by 2
  37. 2025CausalPlan: Empowering Efficient LLM Multi-Agent Collaboration Through Causality-Driven Planningcited by 2
  38. 2023BOOST: Harnessing Black-Box Control to Boost Commonsense in LMs' Generationcited by 1

50 most cited of 69 All 69 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2023CLadder: Assessing Causal Reasoning in Language Models
  2. 2022Towards Fine-grained Causal Reasoning and QA
  3. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
  4. 2024Causal Interventions on Causal Paths: Mapping GPT-2's Reasoning From Syntax to Semantics
  5. 2025Causality for Natural Language Processing
  6. 2026NoisyCausal: A Benchmark for Evaluating Causal Reasoning Under Structured Noise
  7. 2026CausalFlip: A Benchmark for LLM Causal Judgment Beyond Semantic Matching
  8. 2024CausalBN-Bench: A Comprehensive Benchmark for Causal Learning Capability of LLMs