Improve dataset card: add metadata, paper and GitHub links

Hi, I'm Niels from the Hugging Face community science team. I've opened this pull request to improve the dataset card by:
- Adding the `text-classification` task category to the metadata.
- Linking the dataset to the associated paper and GitHub repository.
- Adding a structured summary of the dataset based on the paper.
- Including the BibTeX citation for researchers.

README.md

@@ -1,6 +1,35 @@
-The arXiv data used in **_LLMs Know More About Numbers than They Can Say_**
-([arXiv:2602.07812](https://arxiv.org/abs/2602.07812),
-[code](https://github.com/VCY019/Numeracy-Probing)).
+---
+task_categories:
+- text-classification
+---
 
-The dataset is derived from
-[allenai/peS2o](https://huggingface.co/datasets/allenai/peS2o).
+# Numeracy Probing (arXiv Data)
+
+This repository contains the arXiv data used in the paper **[LLMs Know More About Numbers than They Can Say](https://huggingface.co/papers/2602.07812)**.
+
+The dataset is derived from [allenai/peS2o](https://huggingface.co/datasets/allenai/peS2o).
+
+## Links
+- **Paper:** [LLMs Know More About Numbers than They Can Say](https://huggingface.co/papers/2602.07812)
+- **GitHub Repository:** [VCY019/Numeracy-Probing](https://github.com/VCY019/Numeracy-Probing)
+
+## Dataset Summary
+This dataset contains a subset of approximately 100k samples from scientific papers (arXiv) used to evaluate how Large Language Models (LLMs) represent numerical magnitudes. The associated study probes the hidden states of LLMs to determine if they encode the log-magnitudes and rankings of numerals, even when the models fail to compare them correctly in verbalized text.
+
+The data was used specifically for training and evaluating linear probes (regression and classification) on scientific text as described in the EACL 2026 paper.
+
+## Citation
+```bibtex
+@inproceedings{yuchi-du-eisner-2026,
+  author =      {Fengting Yuchi and Li Du and Jason Eisner},
+  title =       {{LLM}s Know More About Numbers than They Can Say},
+  booktitle =   {Proceedings of the Conference of the European Chapter
+                 of the Association for Computational Linguistics: Human
+                 Language Technologies (EACL)},
+  year =        {2026},
+  month =       mar,
+  address =     {Rabat, Morocco},
+  note =        {Oral presentation.},
+  url =         {https://arxiv.org/abs/2602.07812}
+}
+```