arXiv Machine Learning By Smriti Jha, Matteo Paltenghi, Chandra Maddila, Vijayaraghavan Murali, Shubham Ugare, Satish Chandra

REAP: Automatic Curation of Coding Agent Benchmarks from Interactive Production Usage

Read the original on arXiv Machine Learning →

arXiv:2604. 01527v4 Announce Type: replace-cross Abstract: Production deployment of AI coding agents requires fast, reproducible evaluation signals.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jun 30

SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?

arXiv:2511. 06090v3 Announce Type: replace-cross Abstract: Optimizing the performance of large-scale software repositories demands expertise in code reasoning and software engineering (SWE) to reduce runtime while preserving program correctness.

By Jeffrey Jian Ma, Milad Hashemi, Amir Yazdanbakhsh, Kevin Swersky, Ofir Press, Enhui Li, Vijay Janapa Reddi, Parthasarathy Ranganathan