4 papers
SePO: Self-Evolving Prompt Agent for System Prompt Optimization
Wangcheng Tao, Han Wu, Weng-Fai Wong
System prompt optimization improves agent behavior without modifying the underlying model, yielding human-readable, model-agnostic instructions. Existing methods build a prompt age…
Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench
Qingyun Zou, Feng Yu, Hongshi Tan +2
We ask whether agentic AI systems built for software engineering transfer to realistic hardware engineering. Existing hardware LLM benchmarks isolate sub-tasks but none jointly req…
HLS-Seek: QoR-Aware Code Generation for High-Level Synthesis via Proxy Comparative Reward Reinforcement Learning
Qingyun Zou, Feng Yu, Hongshi Tan +3
High-Level Synthesis (HLS) compiles algorithmic C/C++ descriptions into hardware, with Quality of Results (QoR) -- latency and resource utilization -- critically governed by pragma…
Reward-Weighted On-Policy Distillation with an Open Property-Equivalence Verifier for NL-to-SVA Generation
Qingyun Zou, Yingze Li, Tianen Liu +2
LLM-based generation of SystemVerilog Assertions (SVA) is often reported as nearing saturation, with the strongest specialized model reaching accuracy on NL2SVA-Human.…