AI RESEARCH
CoRoVA: Compressed Representations for Vector-Augmented Code Completion
arXiv CS.CL
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ArXi:2510.19644v2 Announce Type: replace Retrieval-augmented generation has emerged as one of the most effective approaches for code completion enhancement, especially when repository-level context is important. However, adding this extra retrieved context significantly increases sequence length, raises prefill cost, and degrades time-to-first-token (TTFT), which slows down inference -- a critical limitation for interactive settings such as IDEs. In this work, we