Papers with hierarchical reward mechanism
ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning (2026.acl-long)
Copied to clipboard
Zhirong Chen, Kaiyan Chang, Zhuolin Li, Cangyuan Li, Xinyang He, Chujie Chen, Mengdi Wang, Haobo Xu, Yinhe Han, Huawei Li, Ying Wang
| Challenge: | Existing approaches to optimize Register-Transfer Level (RTL) code fail to simultaneously optimize functional correctness and hardware efficiency metrics such as Power, Performance, and Area (PPA). |
| Approach: | They propose a hierarchical reward based reinforcement learning framework that integrates direct feedback from EDA simulators and synthesis tools into a reward mechanism. |
| Outcome: | The proposed framework integrates direct feedback from EDA simulators and synthesis tools into a hierarchical reward based reinforcement learning framework. |
VIDA: A Visual Intent-driven Design Assistant for Proactive Multimodal Clarification (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing vision-language models fail to provide accurate and complete answers to user requests . a new strategy-aware design assistant is developed to help designers create proactive, visually grounded, and strategically prioritized clarification questions. |
| Approach: | They propose a visual intent-driven design assistant to generate proactive, visually grounded, and strategically prioritized clarification questions. |
| Outcome: | The proposed assistant improves the strategic alignment score by 20.59% over baselines and restores visual grounding capabilities lost during fine-tuning. |