Caption3o-XL-v4 is a large-scale, high-quality dataset derived from prithivMLmods/blip3o-caption-mini-arrow and other curated sources. It is designed for training and evaluating image-to-text models, with an emphasis on long-form captions covering a wide range of real-world and artistic scenes. The dataset is in Parquet format, contains English text, and was last updated on September 15, 2025.
Use Cases
- Training image-to-text models based on the described long-form caption data.
- Evaluating caption generation quality on diverse scenes based on the dataset's coverage of real-world and artistic imagery.
- Fine-tuning large language models for visual question answering based on the image-text modality.
- Benchmarking model performance on long-form caption generation tasks.
Strengths
- Dataset is explicitly designed for long-form captions, which suggests detailed textual descriptions.
- Covers a wide range of real-world and artistic scenes, indicating diversity in visual content.
- Released under the permissive Apache-2.0 license, facilitating commercial and research use.
- Last updated on 2025-09-15, suggesting recent maintenance.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count, file size, and sample data are unknown, which may limit suitability assessment.
- Data may reflect source bias inherent to the original curated sources from Hugging Face.
Provenance
- Source
- prithivMLmods on Hugging Face.
- Collection Method
- Derived from prithivMLmods/blip3o-caption-mini-arrow and additional curated sources.
- Time Range
- null
- Freshness
- Last updated 2025-09-15 10:31:53.
- Geography
- null