mlsanityData to 7 Oct 2026

GLUCOSE: GeneraLized and COntextualized Story Explanations

arXiv 2009.07758 ↗First posted 16 Sep 2020cs.CL cs.AIcited by 85

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Abstract (arXiv)

When humans read or listen, they make implicit commonsense inferences that frame their understanding of what happened and why. As a step toward AI systems that can build similar mental models, we introduce GLUCOSE, a large-scale dataset of implicit commonsense causal knowledge, encoded as causal mini-theories about the world, each grounded in a narrative context. To construct GLUCOSE, we drew on cognitive psychology to identify ten dimensions of causal explanation, focusing on events, states, motivations, and emotions. Each GLUCOSE entry includes a story-specific causal statement paired with an inference rule generalized from the statement. This paper details two concrete contributions. First, we present our platform for effectively crowdsourcing GLUCOSE data at scale, which uses semi-structured templates to elicit causal explanations. Using this platform, we collected a total of ~670K specific statements and general rules that capture implicit commonsense knowledge about everyday situations. Second, we show that existing knowledge resources and pretrained language models do not include or readily predict GLUCOSE's rich inferential content. However, when state-of-the-art neural models are trained on this knowledge, they can start to make commonsense inferences on unseen stories that match humans' mental models.

Key facts. Cited by 85 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Sep 2020.

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Citing papers per year: 2021: 21; 2022: 23; 2023: 19; 2024: 12; 2025: 5; 2026: 5.

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  1. 2022Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMscited by 220
  2. 2021Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processingcited by 126
  3. 2023Boosting Language Models Reasoning with Chain-of-Knowledge Promptingcited by 77
  4. 2021ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoningcited by 58
  5. 2023ChatGPT Evaluation on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relationscited by 39
  6. 2023Analyzing Dataset Annotation Quality Management in the Wildcited by 39
  7. 2022CICERO: A Dataset for Contextualized Commonsense Inference in Dialoguescited by 38
  8. 2024SAPT: A Shared Attention Framework for Parameter-Efficient Continual Learning of Large Language Modelscited by 37
  9. 2025Neuro-Symbolic AI in 2024: A Systematic Reviewcited by 36
  10. 2021Dimensions of Commonsense Knowledgecited by 29
  11. 2021Automatic Story Generation: Challenges and Attemptscited by 28
  12. 2021ASER: Towards Large-scale Commonsense Knowledge Acquisition via Higher-order Selectional Preference over Eventualitiescited by 28
38 more
  1. 2021TellMeWhy: A Dataset for Answering Why-Questions in Narrativescited by 27
  2. 2021DISCOS: Bridging the Gap between Discourse Knowledge and Commonsense Knowledgecited by 26
  3. 2023COKE: A Cognitive Knowledge Graph for Machine Theory of Mindcited by 26
  4. 2023CAT: A Contextualized Conceptualization and Instantiation Framework for Commonsense Reasoningcited by 25
  5. 2022Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Modelscited by 24
  6. 2023COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspectivecited by 22
  7. 2021Improving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statementcited by 21
  8. 2022Open-world Story Generation with Structured Knowledge Enhancement: A Comprehensive Surveycited by 21
  9. 2021CIDER: Commonsense Inference for Dialogue Explanation and Reasoningcited by 20
  10. 2021Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense Language Understandingcited by 19
  11. 2022Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualizationcited by 17
  12. 2025BLEUBERI: BLEU is a surprisingly effective reward for instruction followingcited by 17
  13. 2022ROCK: Causal Inference Principles for Reasoning about Commonsense Causalitycited by 16
  14. 2021Benchmarking Commonsense Knowledge Base Population with an Effective Evaluation Datasetcited by 15
  15. 2023Modeling Empathic Similarity in Personal Narrativescited by 14
  16. 2021Probing Commonsense Explanation in Dialogue Response Generationcited by 13
  17. 2024CausalEval: Towards Better Causal Reasoning in Language Modelscited by 13
  18. 2021COINS: Dynamically Generating COntextualized Inference Rules for Narrative Story Completioncited by 12
  19. 2021A Survey on Deep Learning Event Extraction: Approaches and Applicationscited by 12
  20. 2023ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systemscited by 11
  21. 2023Event Causality Is Key to Computational Story Understandingcited by 11
  22. 2022Coalescing Global and Local Information for Procedural Text Understandingcited by 10
  23. 2023An Overview Of Temporal Commonsense Reasoning and Acquisitioncited by 10
  24. 2024mCSQA: Multilingual Commonsense Reasoning Dataset with Unified Creation Strategy by Language Models and Humanscited by 10
  25. 2021PaCo: Preconditions Attributed to Commonsense Knowledgecited by 9
  26. 2022Inferring Implicit Relations in Complex Questions with Language Modelscited by 9
  27. 2024EventGround: Narrative Reasoning by Grounding to Eventuality-centric Knowledge Graphscited by 9
  28. 2024Through the Theory of Mind's Eye: Reading Minds with Multimodal Video Large Language Modelscited by 9
  29. 2021Predicting Directionality in Causal Relations in Textcited by 8
  30. 2021Language Models as a Knowledge Source for Cognitive Agentscited by 7
  31. 2021Knowledge-Augmented Language Models for Cause-Effect Relation Classificationcited by 7
  32. 2022Are Hard Examples also Harder to Explain? A Study with Human and Model-Generated Explanationscited by 7
  33. 2022CoRRPUS: Code-based Structured Prompting for Neurosymbolic Story Understandingcited by 7
  34. 2021WhyAct: Identifying Action Reasons in Lifestyle Vlogscited by 6
  35. 2022Improving Language Model Prompting in Support of Semi-autonomous Task Learningcited by 6
  36. 2022Dense-ATOMIC: Towards Densely-connected ATOMIC with High Knowledge Coverage and Massive Multi-hop Pathscited by 6
  37. 2023Don't Take This Out of Context! On the Need for Contextual Models and Evaluations for Stylistic Rewritingcited by 6
  38. 2022PseudoReasoner: Leveraging Pseudo Labels for Commonsense Knowledge Base Populationcited by 5

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