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Temporal Common Sense Acquisition with Minimal Supervision

arXiv 2005.04304 ↗First posted 8 May 2020cs.CLcited by 38

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Abstract (arXiv)

Temporal common sense (e.g., duration and frequency of events) is crucial for understanding natural language. However, its acquisition is challenging, partly because such information is often not expressed explicitly in text, and human annotation on such concepts is costly. This work proposes a novel sequence modeling approach that exploits explicit and implicit mentions of temporal common sense, extracted from a large corpus, to build TACOLM, a temporal common sense language model. Our method is shown to give quality predictions of various dimensions of temporal common sense (on UDST and a newly collected dataset from RealNews). It also produces representations of events for relevant tasks such as duration comparison, parent-child relations, event coreference and temporal QA (on TimeBank, HiEVE and MCTACO) that are better than using the standard BERT. Thus, it will be an important component of temporal NLP.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 May 2020.

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Citing papers per year: 2021: 12; 2022: 11; 2023: 9; 2024: 5; 2025: 1.

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  1. 2021Symbolic Knowledge Distillation: from General Language Models to Commonsense Modelscited by 270
  2. 2021SituatedQA: Incorporating Extra-Linguistic Contexts into QAcited by 145
  3. 2022Impact of Pretraining Term Frequencies on Few-Shot Reasoningcited by 142
  4. 2024Large Language Models Can Learn Temporal Reasoningcited by 110
  5. 2021Representing Numbers in NLP: a Survey and a Visioncited by 83
  6. 2021SpartQA: : A Textual Question Answering Benchmark for Spatial Reasoningcited by 75
  7. 2022MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extractioncited by 65
  8. 2021TIMEDIAL: Temporal Commonsense Reasoning in Dialogcited by 55
  9. 2023Test of Time: Instilling Video-Language Models with a Sense of Timecited by 51
  10. 2023Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoningcited by 44
  11. 2022Commonsense Knowledge Reasoning and Generation with Pre-trained Language Models: A Surveycited by 38
  12. 2021OntoED: Low-resource Event Detection with Ontology Embeddingcited by 23
26 more
  1. 2022There is a Time and Place for Reasoning Beyond the Imagecited by 22
  2. 2023Mitigating Temporal Misalignment by Discarding Outdated Factscited by 21
  3. 2021What do Large Language Models Learn about Scripts?cited by 19
  4. 2021What is Event Knowledge Graph: A Surveycited by 19
  5. 2022Learning to Decompose: Hypothetical Question Decomposition Based on Comparable Textscited by 18
  6. 2022Generic Temporal Reasoning with Differential Analysis and Explanationcited by 18
  7. 2024BIRD: A Trustworthy Bayesian Inference Framework for Large Language Modelscited by 18
  8. 2022ROCK: Causal Inference Principles for Reasoning about Commonsense Causalitycited by 16
  9. 2023Salient Span Masking for Temporal Understandingcited by 14
  10. 2021CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervisioncited by 12
  11. 2023Large Human Language Models: A Need and the Challengescited by 11
  12. 2023Traffic-Domain Video Question Answering with Automatic Captioningcited by 10
  13. 2023An Overview Of Temporal Commonsense Reasoning and Acquisitioncited by 10
  14. 2021Learning Constraints and Descriptive Segmentation for Subevent Detectioncited by 9
  15. 2022Zero-Shot On-the-Fly Event Schema Inductioncited by 9
  16. 2021Modality and Negation in Event Extractioncited by 6
  17. 2021Decomposing and Recomposing Event Structurecited by 5
  18. 2022Learning Action Conditions from Instructional Manuals for Instruction Understandingcited by 4
  19. 2022PInKS: Preconditioned Commonsense Inference with Minimal Supervisioncited by 4
  20. 2024Temporal Validity Change Predictioncited by 2
  21. 2024TacoERE: Cluster-aware Compression for Event Relation Extractioncited by 2
  22. 2022Cross-Lingual Speaker Identification Using Distant Supervisioncited by 0
  23. 2023QR-CLIP: Introducing Explicit Open-World Knowledge for Location and Time Reasoningcited by 0
  24. 2023Preconditioned Visual Language Inference with Weak Supervisioncited by 0
  25. 2024AcTED: Automatic Acquisition of Typical Event Duration for Semi-supervised Temporal Commonsense QAcited by 0
  26. 2025TComQA: Extracting Temporal Commonsense from Textcited by 0