Freely available Longformer Content and Wording summary scoring models on HuggingFace¶
Product or Programme · All products and programmes
Evidence · 2 claims (2 for) · 1 study (1 design),q2· 1 of 1 report an effect size · 2 claims rest on one study
Description¶
Two Longformer checkpoints, longformer-content-global and longformer-wording-global, released by Morris et al. for automated content and wording scoring of learner summaries in educational platforms and intelligent textbooks.
Components¶
Claims¶
- Including the textbook source text in the model input improves automated summary scoring accuracy, with Longformer explaining 82% of Content and 70% of Wording score variance versus 67% and 41% for summary-only RoBERTa [+M]
- On professional OpenStax textbook summaries, matched summaries scored significantly higher than unmatched ones, with a larger effect for Content (d = 1.56) than Wording (d = 0.938) [+M]
Related Products and Programmes¶
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Key Sources¶
- Morris, W., Crossley, S., Holmes, L., Ou, C., Dascalu, M., & McNamara, D. (2025). Formative Feedback on Student-Authored Summaries in Intelligent Textbooks Using Large Language Models. International Journal of Artificial Intelligence in Education, 35, 1022–1043. https://doi.org/10.1007/s40593-024-00395-0
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
freely-available-longformer-content-and-wording-summary-scoring-models-on-huggingface |
title |
Freely available Longformer Content and Wording summary scoring models on HuggingFace |
description |
Two Longformer checkpoints, longformer-content-global and longformer-wording-global, released by Morris et al. |
status |
review |
product_kind |
software |
generated |
by process:settle-candidates on 2026-10-28 |
trust |
unverified — no one has confirmed this page's content |
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