8 papers
Photonic Quantum Computing on Spin Memory Architecture with Tree-Encoded Fusion
Xiangyu Ren, Yuexun Huang, Zhemin Zhang +4
Photonic quantum computing provides a promising route toward quantum computation by naturally supporting the measurement-based quantum computation (MBQC) model. In MBQC, programs a…
LongRTL: Graph-Similarity-Guided LLM-driven Long Context RTL Optimization
Yuyang Ye, Che-Kuan Shen, Xiangfei Hu +5
Large Language Models (LLMs) show great promise in RTL code generation and optimization. However, real-world RTL designs are typically long, entangled, and poorly modularized, posi…
CPPL: A Circuit Prompt Programming Language
Shuo Yin, Yihe Wang, Lancheng Zou +6
Large language models (LLMs) have shown promise in register-transfer level (RTL) design automation, but direct RTL generation remains difficult to validate, optimize, and integrate…
MappingEvolve: LLM-Driven Code Evolution for Technology Mapping
Rongliang Fu, Yi Liu, Qiang Xu +1
Technology mapping is a critical yet challenging stage in logic synthesis. While Large Language Models (LLMs) have been applied to generate optimization scripts, their potential fo…
PermLLM: Learnable Channel Permutation for N:M Sparse Large Language Models
Lancheng Zou, Shuo Yin, Zehua Pei +3
Channel permutation is a powerful technique for enhancing the accuracy of N:M sparse models by reordering the channels of weight matrices to prioritize the retention of important w…
Evaluating Text-to-Image Generative Models: An Empirical Study on Human Image Synthesis
Muxi Chen, Yi Liu, Jian Yi +5
In this paper, we present an empirical study introducing a nuanced evaluation framework for text-to-image (T2I) generative models, applied to human image synthesis. Our framework c…