ScaleAI/SWE-Atlas-QnA
Update 03/30/2026: We released the dataset in harbor format in our official GitHub repo for SWE-Atlas. We recommend using the harbor scaffold with modal runtime sandboxes as the official way to run the benchmark. SWE-Atlas QnA Codebase QnA is the first benchmark in the SWE-Atlas suite. It evaluates AI agents on deep code comprehension — tracing execution paths, explaining architectural decisions, and answering deeply technical questions about production-grade software systems.… See the full description on the dataset page: https://huggingface.co/datasets/ScaleAI/SWE-Atlas-QnA.
| Author / organization | ScaleAI |
|---|---|
| Downloads | 661 (as reported by Hugging Face) |
| Likes | 22 |
| Created | 24 February 2026 |
| Last updated at source | 31 March 2026 |
Popularity, last 3 days
661 now (-21 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 16 Oct 2026 Description: Update 03/30/2026: We released the dataset in harbor format in our official GitHub repo for SWE-Atlas. We recommend using the harbor scaffold with modal runtime sandboxes as the official way to run the benchmark. SWE-Atlas QnA Codebase QnA → Update 03/30/2026: We released the dataset in harbor format in our official GitHub repo for SWE-Atlas. We recommend using the harbor scaffold with modal runtime sandboxes as the official way to run the benchmark. SWE-Atlas QnA Codebase QnA
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