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LAST at CMCL 2021 Shared Task: Predicting Gaze Data During Reading with a Gradient Boosting Decision Tree Approach

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A LightGBM model fed with target word lexical characteristics and features obtained from word frequency lists, psychometric data and bigram association measures has been optimized for the 2021 CMCL Shared Task on Eye-Tracking Data Prediction. It obtained the best performance of all teams on two of the five eye-tracking measures to predict, allowing it to rank first on the official challenge criterion and to outperform all deep-learning based systems participating in the challenge.

Yves Bestgen• 2021

Related benchmarks

TaskDatasetResultRank
Scanpath PredictionCELER English L1 (New Sentence Split)--
6
Scanpath PredictionCELER English L1 (New Reader Split)--
6
Scanpath PredictionCELER English L1 (New Sentence / New Reader Split)--
6
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