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20242026
most citedE-morphic: Scalable Equality Saturation for Structural Exploration in Logic Synthesis

1 citations · 3 across the 11 of their papers we have counts for

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11 papers

cs.AI2026

VeriTrace: Human-Like Temporal Exploration Completes Agentic Action Space

Yu-Tung Liu, Cunxi Yu

Large language models have shown promise for automated Verilog RTL generation, yet state-of-the-art multi-agent systems plateau at ~95% accuracy on standard benchmarks. We trace th…

cs.AR2026

Autonomous Evolution of EDA Tools: Multi-Agent Self-Evolved ABC

Cunxi Yu, Haoxing Ren

This paper introduces the first \emph{self-evolving} logic synthesis framework, which leverages Large Language Model (LLM) agents to autonomously improve the source code of \textsc…

cs.LG2026

TOPCELL: Topology Optimization of Standard Cell via LLMs

Zhan Song, Yu-Tung Liu, Chen Chen +6

Transistor topology optimization is a critical step in standard cell design, directly dictating diffusion sharing efficiency and downstream routability. However, identifying optima…

cs.AR2026

FVRuleLearner: Operator-Level Reasoning Tree (Op-Tree)-Based Rules Learning for Formal Verification

Lily Jiaxin Wan, Chia-Tung Ho, Yunsheng Bai +4

The remarkable reasoning and code generation capabilities of large language models (LLMs) have recently motivated increasing interest in automating formal verification (FV), a proc…

cs.LO2025

ReVEAL: GNN-Guided Reverse Engineering for Formal Verification of Optimized Multipliers

Chen Chen, Daniela Kaufmann, Chenhui Deng +3

We present ReVEAL, a graph-learning-based method for reverse engineering of multiplier architectures to improve algebraic circuit verification techniques. Our framework leverages s…

cs.AI2025

e-boost: Boosted E-Graph Extraction with Adaptive Heuristics and Exact Solving

Jiaqi Yin, Zhan Song, Chen Chen +3

E-graphs have attracted growing interest in many fields, particularly in logic synthesis and formal verification. E-graph extraction is a challenging NP-hard combinatorial optimiza…

cs.AR2025

Revisit Choice Network for Synthesis and Technology Mapping

Chen Chen, Jiaqi Yin, Cunxi Yu

Choice network construction is a critical technique for alleviating structural bias issues in Boolean optimization, equivalence checking, and technology mapping. Previous works on…

cs.AR2025

HEC: Equivalence Verification Checking for Code Transformation via Equality Saturation

Jiaqi Yin, Zhan Song, Nicolas Bohm Agostini +2

In modern computing systems, compilation employs numerous optimization techniques to enhance code performance. Source-to-source code transformations, which include control flow and…

cs.AR2025★ 1 cited

E-morphic: Scalable Equality Saturation for Structural Exploration in Logic Synthesis

Chen Chen, Guangyu HU, Cunxi Yu +2

In technology mapping, the quality of the final implementation heavily relies on the circuit structure after technology-independent optimization. Recent studies have introduced equ…

cs.AR2025★ 1 cited

BoolE: Exact Symbolic Reasoning via Boolean Equality Saturation

Jiaqi Yin, Zhan Song, Chen Chen +2

Boolean symbolic reasoning for gate-level netlists is a critical step in verification, logic and datapath synthesis, and hardware security. Specifically, reasoning datapath and add…

cs.AR2024★ 1 cited

E-Syn: E-Graph Rewriting with Technology-Aware Cost Functions for Logic Synthesis

Chen Chen, Guangyu Hu, Dongsheng Zuo +3

Logic synthesis plays a crucial role in the digital design flow. It has a decisive influence on the final Quality of Results (QoR) of the circuit implementations. However, existing…