# GisPy: A Tool for Measuring Gist Inference Score in Text

arXiv: https://arxiv.org/abs/2205.12484 · HTML: https://mlsanity.com/paper/2205.12484/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 23 references that are in the map.
- First posted on arXiv 25 May 2022.

## Builds on (most cited first, 6 of 6)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [Can Transformer Models Measure Coherence In Text? Re-Thinking the Shuffle Test](https://mlsanity.com/paper/2107.03448/) (2021)
- [Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddings](https://mlsanity.com/paper/1807.02903/) (2018)
- [Evaluating Text Coherence at Sentence and Paragraph Levels](https://mlsanity.com/paper/2006.03221/) (2020)

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

- [SciGisPy: a Novel Metric for Biomedical Text Simplification via Gist Inference Score](https://mlsanity.com/paper/2410.09632/) (2024)
- [IntrEx: A Dataset for Modeling Engagement in Educational Conversations](https://mlsanity.com/paper/2509.06652/) (2025)

## Abstract (arXiv)

Decision making theories such as Fuzzy-Trace Theory (FTT) suggest that individuals tend to rely on gist, or bottom-line meaning, in the text when making decisions. In this work, we delineate the process of developing GisPy, an open-source tool in Python for measuring the Gist Inference Score (GIS) in text. Evaluation of GisPy on documents in three benchmarks from the news and scientific text domains demonstrates that scores generated by our tool significantly distinguish low vs. high gist documents. Our tool is publicly available to use at: https://github.com/phosseini/GisPy.