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Can Coding Agents Solve Repository-Level Issues with Rendered Code? An Exploratory Study of Visual Representations

arXiv cs.HC LLM Agents Weijie Liang, Yuanfeng Song, Xing Chen, Caleb Chen Cao, Sirui Han, Yike Guo 2026-08-10
Representative image for Can Coding Agents Solve Repository-Level Issues with Rendered Code? An Exploratory Study of Visual Representations

TL;DR - An exploratory study testing whether rendering source code as images (instead of text tokens) can serve as working context for repository-level coding agents on SWE-bench Verified. It matters because visual compression is a proposed way to cut prompt-token cost, and this work maps where that trade-off actually holds in agentic workflows.

  • Rendered code reliably lowers prompt-token cost, but savings scale sub-linearly with the nominal visual compression ratio.
  • End-to-end repair accuracy is largely preserved, yet rendering does not lift the ceiling set by the underlying model/agent architecture, and becomes unstable under aggressive compression.
  • Controlled agent settings separate unguided repository exploration from structured repair stages; visual code helps most when raw source reading is the dominant bottleneck.
  • Once localization is structured, remaining cost shifts to patch–test trial-and-error, where visual compression offers little leverage — positioning rendered code as a viable but conditional mechanism.

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