Dataset Viewer
Auto-converted to Parquet
source
stringclasses
2 values
split
stringclasses
2 values
image_id
stringlengths
10
20
docci
test
test_00000
docci
test
test_00001
docci
test
test_00002
docci
test
test_00003
docci
test
test_00004
docci
test
test_00005
docci
test
test_00006
docci
test
test_00007
docci
test
test_00008
docci
test
test_00009
docci
test
test_00010
docci
test
test_00011
docci
test
test_00012
docci
test
test_00013
docci
test
test_00014
docci
test
test_00015
docci
test
test_00016
docci
test
test_00017
docci
test
test_00018
docci
test
test_00019
docci
test
test_00020
docci
test
test_00021
docci
test
test_00022
docci
test
test_00023
docci
test
test_00024
docci
test
test_00025
docci
test
test_00026
docci
test
test_00027
docci
test
test_00028
docci
test
test_00029
docci
test
test_00030
docci
test
test_00031
docci
test
test_00032
docci
test
test_00033
docci
test
test_00034
docci
test
test_00035
docci
test
test_00036
docci
test
test_00037
docci
test
test_00038
docci
test
test_00039
docci
test
test_00040
docci
test
test_00041
docci
test
test_00042
docci
test
test_00043
docci
test
test_00044
docci
test
test_00045
docci
test
test_00046
docci
test
test_00047
docci
test
test_00048
docci
test
test_00049
docci
test
test_00050
docci
test
test_00051
docci
test
test_00052
docci
test
test_00053
docci
test
test_00054
docci
test
test_00055
docci
test
test_00056
docci
test
test_00057
docci
test
test_00058
docci
test
test_00059
docci
test
test_00060
docci
test
test_00061
docci
test
test_00062
docci
test
test_00063
docci
test
test_00064
docci
test
test_00065
docci
test
test_00066
docci
test
test_00067
docci
test
test_00068
docci
test
test_00069
docci
test
test_00070
docci
test
test_00071
docci
test
test_00072
docci
test
test_00073
docci
test
test_00074
docci
test
test_00075
docci
test
test_00076
docci
test
test_00077
docci
test
test_00078
docci
test
test_00079
docci
test
test_00080
docci
test
test_00081
docci
test
test_00082
docci
test
test_00083
docci
test
test_00084
docci
test
test_00085
docci
test
test_00086
docci
test
test_00087
docci
test
test_00088
docci
test
test_00089
docci
test
test_00090
docci
test
test_00091
docci
test
test_00092
docci
test
test_00093
docci
test
test_00094
docci
test
test_00095
docci
test
test_00096
docci
test
test_00097
docci
test
test_00098
docci
test
test_00099
End of preview. Expand in Data Studio

ND400 Derivative Dataset

Description:
ND400 is a derivative evaluation dataset created to study semantic drift in Unified Models (UMs) across multiple image-text generations. It contains 400 samples:

  • 200 from DOCCI test set (test_00000test_00199)
  • 200 from NoCaps validation set (first 200 entries)

This dataset does not redistribute original images. It provides a CSV of image IDs, splits, and sources to enable users to fetch the images from the original datasets. A sample script to fetch the original dataset will be provided in the project GitHub repo.

CSV Columns:

source split image_id
docci test test_00000
nocaps validation 000123.jpg

Usage:

  1. Download the CSV (nd400.csv) from this dataset.
  2. Use the provided prepare_dataset.py to organize images and captions for evaluation:
<evaluation_data_root>/
├── text-first/
│ ├── gen-0.csv
├── image-first/
│ └── gen-0/ (images)

License

This dataset combines data from DOCCl (CC BY 4.0) and NoCaps (see original). Please respect the original licenses.

Citation:

@misc{mollah2025telephonegameevaluatingsemantic,
      title={The Telephone Game: Evaluating Semantic Drift in Unified Models}, 
      author={Sabbir Mollah and Rohit Gupta and Sirnam Swetha and Qingyang Liu and Ahnaf Munir and Mubarak Shah},
      year={2025},
      eprint={2509.04438},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2509.04438}, 
}
Downloads last month
58