mlsanityData to 14 Oct 2026

Transformer-Based Temporal Information Extraction and Application: A Review

arXiv 2504.07470 ↗First posted 10 Apr 2025cs.CLcited by 1

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Abstract (arXiv)

Temporal information extraction (IE) aims to extract structured temporal information from unstructured text, thereby uncovering the implicit timelines within. This technique is applied across domains such as healthcare, newswire, and intelligence analysis, aiding models in these areas to perform temporal reasoning and enabling human users to grasp the temporal structure of text. Transformer-based pre-trained language models have produced revolutionary advancements in natural language processing, demonstrating exceptional performance across a multitude of tasks. Despite the achievements garnered by Transformer-based approaches in temporal IE, there is a lack of comprehensive reviews on these endeavors. In this paper, we aim to bridge this gap by systematically summarizing and analyzing the body of work on temporal IE using Transformers while highlighting potential future research directions.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 41 of its 114 references that are in the map. First posted on arXiv 10 Apr 2025.

Builds on

41 of 114 references.

References · 41

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29 more
  1. 2022Generative Knowledge Graph Construction: A Reviewcited by 49
  2. 2020ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoningcited by 38
  3. 2019An Improved Neural Baseline for Temporal Relation Extractioncited by 32
  4. 2019Deep Structured Neural Network for Event Temporal Relation Extractioncited by 25
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  20. 2022Distilling Multi-Scale Knowledge for Event Temporal Relation Extractioncited by 6
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  1. 2024Towards Effective Time-Aware Language Representation: Exploring Enhanced Temporal Understanding in Language Models
  2. 2025Temporal Relation Extraction in Clinical Texts: A Span-based Graph Transformer Approach
  3. 2025Fusing Large Language Models with Temporal Transformers for Time Series Forecasting
  4. 2025Linguistic Interpretability of Transformer-based Language Models: a systematic review
  5. 2025A Survey on Transformer Context Extension: Approaches and Evaluation
  6. 2025Event Extraction in Large Language Model
  7. 2024Event Temporal Relation Extraction based on Retrieval-Augmented on LLMs
  8. 2025It's High Time: A Survey of Temporal Question Answering