9 papers
RODE: A Radial-Orthogonal Decoupled Engine for Optimization
Guoxiang Xu, Bince Qu, Qi Sun +1
Modern neural network training increasingly uses matrix-aware optimizers, yet their conditioned matrix step is typically added directly to the weight, jointly changing its norm and…
Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows
Jinyuan Deng, Zhengrui Chen, Xufeng Wei +4
Large language model (LLM) agents are extending electronic design automation (EDA) beyond static RTL generation toward long-horizon, tool-interactive workflows. Yet it remains uncl…
LithoDreamer: A Physics-Informed World Model for Multi-Stage Computational Lithography
Yuqi Jiang, Yumeng Liu, Zimu Li +7
As semiconductor technology nodes scale, computational lithography is essential for ensuring yield and performance. However, lithography is a continuous physical process involving…
SafeSpec: Fast and Safe LLM via Dynamic Reflective Sampling
Haotian Xu, Zeyang Zhang, Linbao Li +3
Speculative inference accelerates large language model (LLM) decoding but provides no inherent safety guarantees. Existing safety defenses are largely incompatible with speculative…
ScoRe-Flow: Complete Distributional Control via Score-Based Reinforcement Learning for Flow Matching
Xiaotian Qiu, Lukai Chen, Jinhao Li +3
Flow Matching (FM) policies have emerged as an efficient backbone for robotic control, offering fast and expressive action generation that underpins recent large-scale embodied AI…
FluxEDA: A Unified Execution Infrastructure for Stateful Agentic EDA
Zhengrui Chen, Zixuan Song, Yu Li +2
Large language models and autonomous agents are increasingly explored for EDA automation, but many existing integrations still rely on script-level or request-level interactions, w…