Goal-Persistent Coding Agents as Scientific Performance Engineers: A Fixed-Radius Nearest-Neighbor Case Study
arXiv:2609.31980v1 Announce Type: new Abstract: Coding agents can pursue persistent objectives across many tool-use turns, but evidence that general-purpose agents can conduct rigorous scientific performance engineering remains limited. We present a repository-scale case study in which off-the-shel…
Read the full story at arXiv cs.AI ↗
Timeline · 1 report
- 2026-09-29 04:00 · arXiv cs.AI
Goal-Persistent Coding Agents as Scientific Performance Engineers: A Fixed-Radius Nearest-Neighbor Case Study