inclusionAI/SWE-CARE
SWE-CARE: A Comprehensiveness-aware Benchmark for Code Review Evaluation Dataset Description SWE-CARE (Software Engineering - Comprehensive Analysis and Review Evaluation) is a comprehensiveness-aware benchmark for evaluating Large Language Models (LLMs) on repository-level code review tasks. The dataset features real-world code review scenarios from popular open-source Python and Java repositories, with comprehensive metadata… See the full description on the dataset page: https://huggingface.co/datasets/inclusionAI/SWE-CARE.
| Author / organization | inclusionAI |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 355 (as reported by Hugging Face) |
| Likes | 8 |
| Created | 15 October 2025 |
| Last updated at source | 21 October 2025 |
Popularity, last 3 days
355 now (-22 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 16 Oct 2026 Description: SWE-CARE: A Comprehensiveness-aware Benchmark for Code Review Evaluation Dataset Description SWE-CARE (Software Engineering - Comprehensive Analysis and Review Evaluation) is a comprehensiveness-aware benchmark for evaluating Large Language → SWE-CARE: A Comprehensiveness-aware Benchmark for Code Review Evaluation Dataset Description SWE-CARE (Software Engineering - Comprehensive Analysis and Review Evaluation) is a comprehensiveness-aware benchmark for evaluating Large Language
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