Papers by Kevin P. Yancey
FABRA: French Aggregator-Based Readability Assessment toolkit (2022.lrec-1)
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Rodrigo Wilkens, David Alfter, Xiaoou Wang, Alice Pintard, Anaïs Tack, Kevin P. Yancey, Thomas François
| Challenge: | a large number of readability predictor variables are used to predict reading difficulty of texts . the most important predictors for native texts are lexical diversity, dependency counts and text coherence . |
| Approach: | They propose a readability toolkit based on aggregation of readability predictor variables . they show which features are most predictive on two different corpora . |
| Outcome: | The proposed toolkit improves performance over standard feature-based readability prediction. |
Jump-Starting Item Parameters for Adaptive Language Tests (2021.emnlp-main)
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| Challenge: | Prior work has addressed ‘cold start’ estimation of item difficulties without piloting, but a multi-task generalized linear model with BERT features is needed to jump-start new items without pilot. |
| Approach: | They propose a multi-task generalized linear model with BERT features to jump-start new item difficulties without piloting them first. |
| Outcome: | The proposed model compares test-taker proficiency, item difficulty, and language proficiency frameworks like the Common European Framework of Reference (CEFR). |