Uni-Edit-148k is a dataset for tuning Unified Multimodal Models on an intelligent image editing task. It was created by the Uni-Edit project to address task conflicts in conventional multi-task training. The dataset was last updated on May 21, 2026.
Use Cases
- Fine-tuning multimodal models for image editing based on the described Uni-Edit task.
- Training models for improved image understanding as mentioned in the description.
- Benchmarking unified multimodal models against the Uni-Edit paradigm.
- Researching mutual reinforcement between tasks in multimodal learning.
Strengths
- Dataset is designed for the Uni-Edit task, which aims to achieve true mutual reinforcement between tasks.
- The project provides a paper, GitHub repository, and project page for context.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- Uni-Edit
- Freshness
- Last updated 2026-05-21 02:06:10; freshness should be verified.