mlsanityData to 14 Oct 2026

The Language of Looking: Motion Tokens Reveal Domain-Dependent Local Structure in Gaze Sequences

arXiv 2610.16565 ↗First posted 12 Oct 2026cs.LGcited by 0

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Abstract (arXiv)

Human gaze is the primary high-bandwidth interface through which we parse the semantics of our environment. While often modeled as a sequence, the degree to which gaze exhibits transferable local structure across domains remains underexplored. Using motion tokenization as a diagnostic lens across four diverse datasets, we investigate the transferability of local sequence structure. We demonstrate that while gaze can share a reusable motion-token vocabulary, identical motion tokens are organized into different local transition patterns depending on the dataset and task context. Our results show the limitations of naive data-pooling under low-semantic motion-token representations and provide a framework for evaluating behavioral sequences through information-theoretic diagnostics.

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References · 10

  1. 2019Gaze360: Physically Unconstrained Gaze Estimation in the Wildcited by 174
  2. 2019ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotationcited by 66
  3. 2023Gazeformer: Scalable, Effective and Fast Prediction of Goal-Directed Human Attentioncited by 38
  4. 2023Eyettention: An Attention-based Dual-Sequence Model for Predicting Human Scanpaths during Readingcited by 19
  5. 2023ScanDL: A Diffusion Model for Generating Synthetic Scanpaths on Textscited by 14
  6. 2024On the Proper Treatment of Tokenization in Psycholinguisticscited by 13
  7. 2024OAT: Object-Level Attention Transformer for Gaze Scanpath Predictioncited by 6
  8. 2024Decoding Reading Goals from Eye Movementscited by 6
  9. 2026Thinking with Gaze: Sequential Eye-Tracking as Visual Reasoning Supervision for Medical VLMscited by 2
  10. 2026Motion-Based Tokenization for Cross-Dataset Egocentric Gaze Modelingcited by 1

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