The dataset is constructed based on the training set of MMEB-V2. We employ the pure-thinking model GLM-4.1V-Thinking to generate chain-of-thought (CoT) rationales for both the query and the target in each pair.
To ensure data quality, we filter out samples that meet any of the following criteria:
Contain extensive contiguous token repetition.
Include excessively long reasoning traces.
Produce responses that do… See the full description on the dataset page:
https://huggingface.co/datasets/zhibinlan/UME-sft-train.
