Add model card and metadata

README.md

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----
-license: apache-2.0
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+---
+license: apache-2.0
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# CoCoReviewBench Model
+
+This repository contains a model checkpoint from the paper [CoCoReviewBench: A Completeness- and Correctness-Oriented Benchmark for AI Reviewers](https://huggingface.co/papers/2605.07905).
+
+## Introduction
+CoCoReviewBench is a benchmark designed for reliable and fine-grained evaluation of AI reviewers. It curates 3,900 papers from ICLR and NeurIPS, focusing on:
+- **Completeness**: Evaluating by category to avoid penalizing models for issues missing in human references.
+- **Correctness**: Filtering human reviews using reviewer-author-meta-reviewer discussions to ensure accuracy.
+
+## Links
+- **Paper**: [CoCoReviewBench: A Completeness- and Correctness-Oriented Benchmark for AI Reviewers](https://huggingface.co/papers/2605.07905)
+- **Code**: [Official GitHub Repository](https://github.com/hexuandeng/CoCoReviewBench)
+
+## Citation
+
+```bibtex
+@inproceedings{deng2026cocoreviewbench,
+  title     = {{CoCoReviewBench}: A Completeness- and Correctness-Oriented Benchmark for {AI} Reviewers},
+  author    = {Deng, Hexuan and Li, Yichen and Ke, Xiaopeng and Hu, Ruina and Wong, Derek F. and Wang, Yue and Liu, Xuebo and Huang, Dehao and Zhang, Min},
+  booktitle = {Proceedings of the 43rd International Conference on Machine Learning},
+  series    = {Proceedings of Machine Learning Research},
+  publisher = {PMLR},
+  year      = {2026},
+  note      = {To appear},
+  url       = {https://github.com/hexuandeng/CoCoReviewBench}
+}
+```