Update SOCO-LVLM release

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+.DS_Store
+**/.DS_Store
+.cache/

README.md

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 ---
 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}
+}
+```

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