mlsanityData to 14 Oct 2026

A Survey on Using Gaze Behaviour for Natural Language Processing

arXiv 2112.15471 ↗First posted 21 Dec 2021cs.CLcited by 11

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Abstract (arXiv)

Gaze behaviour has been used as a way to gather cognitive information for a number of years. In this paper, we discuss the use of gaze behaviour in solving different tasks in natural language processing (NLP) without having to record it at test time. This is because the collection of gaze behaviour is a costly task, both in terms of time and money. Hence, in this paper, we focus on research done to alleviate the need for recording gaze behaviour at run time. We also mention different eye tracking corpora in multiple languages, which are currently available and can be used in natural language processing. We conclude our paper by discussing applications in a domain - education - and how learning gaze behaviour can help in solving the tasks of complex word identification and automatic essay grading.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 10 of its 82 references that are in the map. First posted on arXiv 21 Dec 2021.

Builds on

10 of 82 references.

References · 10

  1. 2016Automatic Text Scoring Using Neural Networkscited by 51
  2. 2018A Report on the Complex Word Identification Shared Task 2018cited by 30
  3. 2019Entity Recognition at First Sight: Improving NER with Eye Movement Informationcited by 26
  4. 2016Improving sentence compression by learning to predict gazecited by 24
  5. 2017SkipFlow: Incorporating Neural Coherence Features for End-to-End Automatic Text Scoringcited by 22
  6. 2017Leveraging Cognitive Features for Sentiment Analysiscited by 19
  7. 2019Co-Attention Based Neural Network for Source-Dependent Essay Scoringcited by 11
  8. 2017Predicting Native Language from Gazecited by 9
  9. 2018Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviourcited by 9
  10. 2017Harnessing Cognitive Features for Sarcasm Detectioncited by 8

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Cited by year (2026 to 14 Oct)

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

11 papers.

  1. 2023Synthesizing Human Gaze Feedback for Improved NLP Performancecited by 16
  2. 2024Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Modelscited by 12
  3. 2022The Copenhagen Corpus of Eye Tracking Recordings from Natural Reading of Danish Textscited by 7
  4. 2023WebQAmGaze: A Multilingual Webcam Eye-Tracking-While-Reading Datasetcited by 6
  5. 2023Longer Fixations, More Computation: Gaze-Guided Recurrent Neural Networkscited by 3
  6. 2025OASST-ETC Dataset: Alignment Signals from Eye-tracking Analysis of LLM Responsescited by 3
  7. 2022A Comparative Study on Textual Saliency of Styles from Eye Tracking, Annotations, and Language Modelscited by 2
  8. 2025Integrating Cognitive Processing Signals into Language Models: A Review of Advances, Applications and Future Directionscited by 2
  9. 2024Describing Images textitFast and Slow: Quantifying and Predicting the Variation in Human Signals during Visuo-Linguistic Processescited by 1
  10. 2023Revising with a Backward Glance: Regressions and Skips during Reading as Cognitive Signals for Revision Policies in Incremental Processingcited by 0
  11. 2026Your Mouse and Eyes Secretly Leak Your Preference: LLM Alignment using Implicit Feedback from Userscited by 0