GisPy: A Tool for Measuring Gist Inference Score in Text
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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.
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
6 of 23 references.
References · 6
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 723
- 2021Can Transformer Models Measure Coherence In Text? Re-Thinking the Shuffle Testcited by 17
- 2018Predicting Concreteness and Imageability of Words Within and Across Languages via Word Embeddingscited by 11
- 2020Evaluating Text Coherence at Sentence and Paragraph Levelscited by 7
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Citing papers per year: 2024: 1; 2025: 1.
2 papers.