# Automatic learner summary assessment for reading comprehension

arXiv: https://arxiv.org/abs/1906.07555 · HTML: https://mlsanity.com/paper/1906.07555/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2019.

## Built on by (most cited first, 2 of 2)

- [Synthesizing Human Gaze Feedback for Improved NLP Performance](https://mlsanity.com/paper/2302.05721/) (2023)
- [Podcast Summary Assessment: A Resource for Evaluating Summary Assessment Methods](https://mlsanity.com/paper/2208.13265/) (2022)

## Abstract (arXiv)

Automating the assessment of learner summaries provides a useful tool for assessing learner reading comprehension. We present a summarization task for evaluating non-native reading comprehension and propose three novel approaches to automatically assess the learner summaries. We evaluate our models on two datasets we created and show that our models outperform traditional approaches that rely on exact word match on this task. Our best model produces quality assessments close to professional examiners.