VETR: Execution-Grounded Self-Improving Agent for Symbolic Graphics Reasoning
Visual agents for symbolic graphics reasoning depend on executable world representations, yet continued improvement remains bottlenecked by ambiguous supervision from final renders. Recent agentic systems refine scenes through repeated interaction, but they lack mechanisms to recursively extract actionable evidence fro...
Ying-Bo Ma, Kuangshi Ai, Gordon Dai et al.
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