Multimodal Generative AI for Story Point Estimation
This research explores Multimodal Generative AI for Agile story point estimation, integrating text, images, and categorical data with BERT, CNN, and XGBoost to enhance project planning. While effective for simpler estimates, challenges with complex cases due to data imbalance highlight the need for tailored strategies. Findings underscore multimodal AI's impact on Agile decision-making and suggest future improvements in data handling and model robustness.
Authors
- Peter Sandborn (ORCID: https://orcid.org/0000-0001-8335-2105)
- Mohammad Rubyet Islam (ORCID: https://orcid.org/0000-0002-8263-7560)
Institutions
- George Mason University (US)
- University of Maryland, College Park (US)
Publication Details
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1109/cai64502.2025.00120
- Citations
- 1
- Primary Topic
- Human Motion and Animation
- Type
- article
- Field-Weighted Citation Impact
- 1.21