Key papers

• Towards a future space-based, highly scalable AI infrastructure system design (2025)
  Blaise Ag\"uera y Arcas et al.
  5.81
• Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows (2026)
  Jinyuan Deng et al.
  4.39
• LLM-Guided Neural Architecture Search for Robust Co-Design of Physical Neural Networks (2026)
  Tyler King et al.
  3.45
• SynCircuit: Automated Generation of New Synthetic RTL Circuits Can Enable Big Data in Circuits (2025)
  Shang Liu et al.
  3.04
• Toward Lifelong-Sustainable Electronic-Photonic AI Systems via Extreme Efficiency, Reconfigurability, and Robustness (2025)
  Ziang Yin et al.
  3.04
• EEsizer: LLM-Based AI Agent for Sizing of Analog and Mixed Signal Circuit (2025)
  Chang Liu and Danial Chitnis
  3.04
• LLM-based AI Agent for Sizing of Analog and Mixed Signal Circuit (2025)
  Chang Liu et al.
  2.76
• Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations (2026)
  Arthur Fyon et al.
  1.89
• Surrogate Neural Architecture Codesign Package (SNAC-Pack) (2026)
  Jason Weitz et al.
  1.89
• Harnessing Photonics for Machine Intelligence (2026)
  Hanqing Zhu et al.
  1.83
• Generative Design for Direct-to-Chip Liquid Cooling for Data Centers (2026)
  Zheng Liu
  1.83
• Accelerating Diffusion Models for Generative AI Applications with Silicon Photonics (2026)
  Tharini Suresh et al.
  1.78
• Investigating Quantum Circuit Designs Using Neuro-Evolution (2026)
  Devroop Kar et al.
  1.72
• Toward Large-Scale Photonics-Empowered AI Systems: From Physical Design Automation to System-Algorithm Co-Exploration (2026)
  Ziang Yin et al.
  1.67
• Democratizing Electronic-Photonic AI Systems: An Open-Source AI-Infused Cross-Layer Co-Design and Design Automation Toolflow (2026)
  Hongjian Zhou et al.
  1.67
• OSIRIS: Bridging Analog Circuit Design and Machine Learning with Scalable Dataset Generation (2026)
  Giuseppe Chiari et al.
  1.67
• RulePlanner: All-in-One Reinforcement Learner for Unifying Design Rules in 3D Floorplanning (2026)
  Ruizhe Zhong et al.
  1.67
• MaskOpt: A Large-Scale Mask Optimization Dataset to Advance AI in Integrated Circuit Manufacturing (2025)
  Yuting Hu et al.
  1.61
• AnaFlow: Agentic LLM-based Workflow for Reasoning-Driven Explainable and Sample-Efficient Analog Circuit Sizing (2025)
  Mohsen Ahmadzadeh et al.
  1.56
• ZeroSim: Zero-Shot Analog Circuit Evaluation with Unified Transformer Embeddings (2025)
  Xiaomeng Yang et al.
  1.56
• Hybrid unary-binary design for multiplier-less printed Machine Learning classifiers (2025)
  Giorgos Armeniakos et al.
  1.44
• RF-Informed Graph Neural Networks for Accurate and Data-Efficient Circuit Performance Prediction (2025)
  Anahita Asadi et al.
  1.39
• DALI-PD: Diffusion-based Synthetic Layout Heatmap Generation for ML in Physical Design (2025)
  Bing-Yue Wu and Vidya A. Chhabria
  1.33
• Graph Neural Network-Based Predictor for Optimal Quantum Hardware Selection (2025)
  Antonio Tudisco et al.
  1.33
• ORFS-agent: Tool-Using Agents for Chip Design Optimization (2025)
  Amur Ghose et al.
  1.28
• AI-Powered Agile Analog Circuit Design and Optimization (2025)
  Jinhai Hu et al.
  1.22
• What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips (2025)
  Renjie Li et al.
  1.22
• FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design (2025)
  Asal Mehradfar et al.
  1.22
• Data-Driven Antenna Miniaturization: A Knowledge-Based System Integrating Quantum PSO and Predictive Machine Learning Models (2025)
  Khan Masood Parvez et al.
  1.22
• A Survey of Circuit Foundation Model: Foundation AI Models for VLSI Circuit Design and EDA (2025)
  Wenji Fang et al.
  1.17
• Estimating Voltage Drop: Models, Features and Data Representation Towards a Neural Surrogate (2025)
  Yifei Jin et al.
  1.06
• DICE: Device-level Integrated Circuits Encoder with Graph Contrastive Pretraining (2025)
  Sungyoung Lee et al.
  1.06
• Supervised Learning for Analog and RF Circuit Design: Benchmarks and Comparative Insights (2025)
  Asal Mehradfar et al.
  1.00
• CktGen: Automated Analog Circuit Design with Generative Artificial Intelligence (2024)
  Yuxuan Hou et al.
  0.89
• Learning to Design Circuits (2018)
  Hanrui Wang and Jiacheng Yang and Hae-Seung Lee and Song Han
  —
• autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components (2019)
  Vojtech Mrazek and Muhammad Abdullah Hanif and Zdenek Vasicek and Lukas Sekanina and Muhammad Shafique
  —
• Machine learning thermal circuit network model for thermal design optimization of electronic circuit board layout with transient heating chips (2020)
  Daiki Otaki (1) et al.
  —
• OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis (2021)
  Animesh Basak Chowdhury and Benjamin Tan and Ramesh Karri and Siddharth Garg
  —
• Analog/Mixed-Signal Circuit Synthesis Enabled by the Advancements of Circuit Architectures and Machine Learning Algorithms (2021)
  Shiyu Su et al.
  —
• AI/ML Algorithms and Applications in VLSI Design and Technology (2022)
  Deepthi Amuru et al.
  —
• Cross-Layer Approximation For Printed Machine Learning Circuits (2022)
  Giorgos Armeniakos et al.
  —
• TensorCircuit: a Quantum Software Framework for the NISQ Era (2022)
  Shi-Xin Zhang et al.
  —
• Automated Circuit Sizing with Multi-objective Optimization based on Differential Evolution and Bayesian Inference (2022)
  Catalin Visan et al.
  —
• Intelligent Circuit Design and Implementation with Machine Learning (2022)
  Zhiyao Xie
  —
• A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms (2023)
  Shuvro Chowdhury et al.
  —
• OpenHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science (2023)
  Maksim Levental et al.
  —
• CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning (2023)
  Nihal Sanjay Singh et al.
  —
• Improving Quantum Circuit Synthesis with Machine Learning (2023)
  Mathias Weiden et al.
  —
• Energy Estimates Across Layers of Computing: From Devices to Large-Scale Applications in Machine Learning for Natural Language Processing, Scientific Computing, and Cryptocurrency Mining (2023)
  Sadasivan Shankar
  —
• Thermodynamic Computing System for AI Applications (2023)
  Denis Melanson et al.
  —
• \'Eliv\'agar: Efficient Quantum Circuit Search for Classification (2024)
  Sashwat Anagolum et al.
  —
• Silicon Photonic 2.5D Interposer Networks for Overcoming Communication Bottlenecks in Scale-out Machine Learning Hardware Accelerators (2024)
  Febin Sunny et al.
  —
• Architectural Implications of Neural Network Inference for High Data-Rate, Low-Latency Scientific Applications (2024)
  Olivia Weng et al.
  —
• SCATTER: Algorithm-Circuit Co-Sparse Photonic Accelerator with Thermal-Tolerant, Power-Efficient In-situ Light Redistribution (2024)
  Ziang Yin et al.
  —
• Machine Learning Assisted Design of mmWave Wireless Transceiver Circuits (2024)
  Xuzhe Zhao
  —
• Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms (2024)
  Zhihai Wang et al.
  —
• AICircuit: A Multi-Level Dataset and Benchmark for AI-Driven Analog Integrated Circuit Design (2024)
  Asal Mehradfar et al.
  —
• Quantifying artificial intelligence through algorithmic generalization (2024)
  Takuya Ito et al.
  —
• SimPhony: A Device-Circuit-Architecture Cross-Layer Modeling and Simulation Framework for Heterogeneous Electronic-Photonic AI System (2024)
  Ziang Yin et al.
  —
• Schemato -- An LLM for Netlist-to-Schematic Conversion (2024)
  Ryoga Matsuo et al.
  —