Self-Supervised Scaling of Terminal Environments for Scientific Domains
Terminal agents are increasingly deployed beyond software engineering in science and other specialized domains. Constructing training environments requires executable reference behavior and a domain-specific verifier that distinguishes semantic correctness from superficially plausible artifacts. Authoring these components for each task requires repeated engineering and limits reuse. We introduce software-in-the-loop reconstruction, a self-supervised framework that obtains reference outputs and verification targets from existing software workflows, executable programs mapping structured inputs to outputs. For each workflow, we execute multiple input configurations and partition cases into ...
| Authors | Zhongzhi Li, Yucheng Shi, Zongxia Li et al. |
|---|---|
| Primary category | cs.SE |
| Published | 2 October 2026 |
| Last updated at source | 2 October 2026 |
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