# A Theme-Rewriting Approach for Generating Algebra Word Problems

arXiv: https://arxiv.org/abs/1610.06210 · HTML: https://mlsanity.com/paper/1610.06210/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Oct 2016.

## Built on by (most cited first, 10 of 10)

- [Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?](https://mlsanity.com/paper/2401.18070/) (2024)
- [Learning by Analogy: Diverse Questions Generation in Math Word Problem](https://mlsanity.com/paper/2306.09064/) (2023)
- [World Models for Math Story Problems](https://mlsanity.com/paper/2306.04347/) (2023)
- [MATHWELL: Generating Educational Math Word Problems Using Teacher Annotations](https://mlsanity.com/paper/2402.15861/) (2024)
- [Proactive and Reactive Engagement of Artificial Intelligence Methods for Education: A Review](https://mlsanity.com/paper/2301.10231/) (2023)
- [Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation](https://mlsanity.com/paper/2210.16557/) (2022)
- [THiNK: Can Large Language Models Think-aloud?](https://mlsanity.com/paper/2505.20184/) (2025)
- [COMPASS: a Creative Support System that Alerts Novelists to the Unnoticed Missing Contents](https://mlsanity.com/paper/2202.13151/) (2022)
- [EDUMATH: Generating Standards-aligned Educational Math Word Problems](https://mlsanity.com/paper/2510.06965/) (2025)
- [OLGA : An Ontology and LSTM-based approach for generating Arithmetic Word Problems (AWPs) of transfer type](https://mlsanity.com/paper/2211.12164/) (2022)

## Abstract (arXiv)

Texts present coherent stories that have a particular theme or overall setting, for example science fiction or western. In this paper, we present a text generation method called it rewriting that edits existing human-authored narratives to change their theme without changing the underlying story. We apply the approach to math word problems, where it might help students stay more engaged by quickly transforming all of their homework assignments to the theme of their favorite movie without changing the math concepts that are being taught. Our rewriting method uses a two-stage decoding process, which proposes new words from the target theme and scores the resulting stories according to a number of factors defining aspects of syntactic, semantic, and thematic coherence. Experiments demonstrate that the final stories typically represent the new theme well while still testing the original math concepts, outperforming a number of baselines. We also release a new dataset of human-authored rewrites of math word problems in several themes.