| 研究課題/領域番号 |
22K12091
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| 研究機関 | 大阪大学 |
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研究代表者 |
GARCIA・DOCAMPO NOA 大阪大学, データビリティフロンティア機構, 特任助教(常勤) (80870005)
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| 研究期間 (年度) |
2022-04-01 – 2026-03-31
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| キーワード | computer vision / machine learning / vision and language / societal bias / fairness / artificial intelligence / benchmarking |
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| 研究実績の概要 |
In 2023, we have made substantial advancements on identifying societal biases in artificial intelligence models. Firstly, we have collected and annotated a dataset for studying societal biases in image and language models. Secondly, we proposed a bias mitigation method for image captioning. Lastly, we investigated misinformation in large language models (LLM) like ChatGPT, which largely affects topics related to women and healthcare.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
According to the plan, the project has accomplished the goal of collecting a dataset for studying social bias in vision and language models. We have also proposed mitigation techniques.
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| 今後の研究の推進方策 |
The next steps in the project are to study how bias is transferred from the pretraining datasets to the downstream tasks. We also plan to investigate bias in large generative models like Stable Diffusion.
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| 次年度使用額が生じた理由 |
Due to being on maternity leave, I did not use the full amount of the conceded grant. I am planning to use during the next fiscal year to attend conferences to present our work, publication expenses, and collection of datasets.
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| 備考 |
We have released the source code of our models and experiments on the above urls.
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