Add dataset card and link to paper

README.md

@@ -1,3 +1,36 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+- zero-shot-image-classification
+---
+
+# N-COCO
+
+This dataset is associated with the paper [When Negation Is a Geometry Problem in Vision-Language Models](https://huggingface.co/papers/2603.20554).
+
+N-COCO is a dataset designed to evaluate and improve negation understanding in Vision-Language Models (VLMs) like CLIP. The work identifies that a "negation direction" exists in the CLIP embedding space and can be manipulated via representation engineering to improve performance without fine-tuning.
+
+- **Repository:** [https://github.com/fawazsammani/negation-steering](https://github.com/fawazsammani/negation-steering)
+- **Paper:** [When Negation Is a Geometry Problem in Vision-Language Models](https://huggingface.co/papers/2603.20554)
+
+## Dataset Description
+
+The dataset includes the following files used for training and evaluation:
+
+- `train_data.json`: Contains positive-negative sentence pairs used to train layerwise steering directions.
+- `simpleneg.json`: An evaluation benchmark for negation understanding.
+
+## Citation
+
+If you find this work or dataset useful, please consider citing:
+
+```bibtex
+@misc{sammani2026negationgeometry,
+  title={When Negation Is a Geometry Problem in Vision-Language Models},
+  author={Fawaz Sammani and Tzoulio Chamiti and Paul Gavrikov and Nikos Deligiannis},
+  year={2026},
+  eprint={2603.20554},
+  archivePrefix={arXiv},
+  primaryClass={cs.CV}
+}
+```