activity
20232025
most citedChatEDA: A Large Language Model Powered Autonomous Agent for EDA

143 citations · 151 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2025

On-Policy Optimization with Group Equivalent Preference for Multi-Programming Language Understanding

Haoyuan Wu, Rui Ming, Jilong Gao +6

Large language models (LLMs) achieve remarkable performance in code generation tasks. However, a significant performance disparity persists between popular programming languages (e…

cs.LG2025

Circuit Representation Learning with Masked Gate Modeling and Verilog-AIG Alignment

Haoyuan Wu, Haisheng Zheng, Yuan Pu +1

Understanding the structure and function of circuits is crucial for electronic design automation (EDA). Circuits can be formulated as And-Inverter graphs (AIGs), enabling efficient…

cs.CL2025

Efficient OpAmp Adaptation for Zoom Attention to Golden Contexts

Haoyuan Wu, Rui Ming, Haisheng Zheng +2

Large language models (LLMs) have shown significant promise in question-answering (QA) tasks, particularly in retrieval-augmented generation (RAG) scenarios and long-context applic…

cs.CL2025★ 1 cited

Divergent Thoughts toward One Goal: LLM-based Multi-Agent Collaboration System for Electronic Design Automation

Haoyuan Wu, Haisheng Zheng, Zhuolun He +1

Recently, with the development of tool-calling capabilities in large language models (LLMs), these models have demonstrated significant potential for automating electronic design a…

cs.LG2025

Architect of the Bits World: Masked Autoregressive Modeling for Circuit Generation Guided by Truth Table

Haoyuan Wu, Haisheng Zheng, Shoubo Hu +2

Logic synthesis, a critical stage in electronic design automation (EDA), optimizes gate-level circuits to minimize power consumption and area occupancy in integrated circuits (ICs)…

cs.AI2024

Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks

Haoyuan Wu, Haisheng Zheng, Zhuolun He +1

Large language models (LLMs) have demonstrated considerable proficiency in general natural language processing (NLP) tasks. Instruction tuning, a successful paradigm, enhances the…