SeqFeed: Improving Agentic RTL Code Generation with Sequential Behavior Feedback
RTL code generation is a critical stage in hardware design, and the emergence of agentic systems offers new opportunities to automate this process. To generate correct RTL code, agents must understand sequential behavior, including how signals evolve and propagate over multiple clock cycles. However, effectively conveying such temporal information to agents remains a significant challenge. RTL code does not expose cycle-level signal behavior for a specific execution, whereas full simulation waveforms are too voluminous and noisy for effective LLM analysis. To address these limitations, we study how human engineers reason about sequential behavior and identify three requirements for effect...
| Authors | Yuxin Du, Juxin Niu, Tao Hu et al. |
|---|---|
| Primary category | cs.AR |
| Published | 9 August 2026 |
| Last updated at source | 19 August 2026 |
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