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Symbolic planning unlocks significant gains in RTL synthesis and summarization, boosting LLM performance by 20% without fine-tuning.
A multi-agent system that mimics rubber-duck debugging slashes critical path delay by 25% and power consumption by 22% in RTL code, outperforming LLM-based baselines.
