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Zhejiang University
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FRAME achieves up to 13% better search accuracy by bridging the gap between UI code and graphical representations through innovative neuro-symbolic embeddings.
Quality-aware code search can significantly boost developer productivity by prioritizing high-quality code that meets specific resource optimization needs.
Integrating visual graphs with text interfaces allows LLM agents to reduce token consumption by 26% while enhancing their issue-resolution accuracy.
