README.md

---
license: cc-by-4.0
pretty_name: SOCO-LVLM
viewer: false
task_categories:
- visual-question-answering
tags:
- computer-vision
- multimodal
- object-correspondence
- synthetic-data
---

# SOCO-LVLM

SOCO-LVLM provides multiple-choice semantic object correspondence evaluation data for
LVLMs. This is the SOCO-LVLM v1 release, derived from SOCOv1. The original SOCO
correspondence benchmark is available in
the [GenIntelLab/SOCO](https://huggingface.co/datasets/GenIntelLab/SOCO) dataset repository.

## Repository Layout

```text
GenIntelLab/SOCO-LVLM
  SOCO_LVLM/
    soco_lvlm_img.tsv
    soco_lvlm_imgtxt.tsv
    soco_lvlm_txt.tsv
  README.md
```

## Variants

- `soco_lvlm_img.tsv`: image-input evaluation variant (approximately 3.24 GB).
- `soco_lvlm_imgtxt.tsv`: image-and-text evaluation variant (approximately 3.24 GB).
- `soco_lvlm_txt.tsv`: text-input evaluation variant (approximately 1.63 GB).

Each TSV uses the columns `question`, `image`, `image_path`, `answer`, `index`, `g_index`,
`qid`, `category`, `A`, `B`, `C`, and `D`.

## Download

Install the Hub client:

```bash
pip install -U huggingface_hub
```

Download all three variants:

```bash
hf download GenIntelLab/SOCO-LVLM --repo-type dataset --local-dir SOCO-LVLM
```

Download only one variant in Python:

```python
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="GenIntelLab/SOCO-LVLM",
    repo_type="dataset",
    filename="SOCO_LVLM/soco_lvlm_img.tsv",
)
```

Replace the filename with `soco_lvlm_imgtxt.tsv` or `soco_lvlm_txt.tsv` to select a
different evaluation variant.

## Citation

```bibtex
@misc{duenkel2026soco,
  title         = {SOCO: Benchmarking Semantic Object Correspondence in Vision Foundation Models},
  author        = {D{\"u}nkel, Olaf and Sunagad, Basavaraj and Wang, Haoran and
                   Hoffmann, David T. and Theobalt, Christian and Kortylewski, Adam},
  year          = {2026},
  eprint        = {2605.31597},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CV},
  url           = {https://arxiv.org/abs/2605.31597}
}
```