Wenjia Jiang, Jieke Shi, Zhensu Sun, Chengran Yang, Shidong Pan, Peixin Zhang, Yifan Jia, James Hoang · 2026 · arXiv
DOI: 10.48550/arXiv.2610.24824 · open-access PDF
로컬 코딩 에이전트는 더 강력한 클라우드 모델을 상담함으로써 범위를 확장할 수 있습니다.그러나 이러한 컨설팅은 종종 저장소의 개인 식별자, 파일 경로 및 소스 코드를 노출시킵니다.호스트 측의 마스크는 인식된 식별자를 숨기지만 주변 코드와 에이전트의 구문을 변경하지 않고, 덜 공개를 위한 훈련은 컨설팅을 억제하거나 대답하기에 너무 불확실한 질문을 생성할 위험이 있습니다.우리는 유틸리티 검증 abstraction (UVA)를 제안합니다.
Machine translation (Meta M2M100); the English original follows.
Local coding agents can extend their reach by consulting a stronger cloud model. Such consultations, however, often expose the repository's private identifiers, file paths, and source code. Host-side masking hides recognized identifiers but leaves the surrounding code and the agent's phrasing unchanged, while training for less disclosure risks suppressing consultation or producing questions too vague to answer. We propose utility-verified abstraction (UVA), which teaches the agent to describe private entities by their role and type while retaining the technical details an expert needs. From so
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