5 citations · 11 across the 10 of their papers we have counts for
3 papers · 1 filter
Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models
Koki Takeshita, Kenji Uebayashi, Hikaru Tomonari +6
Recent studies have proposed reinforcement learning with verifiable rewards (RLVR) methods that enable LLMs to generate high-quality RTL circuits from natural-language specificatio…
Bridging the Sim-to-Real Gap in Semiconductor Visual Program Synthesis via Input Binarization
Yusuke Ohtsubo, Kota Dohi, Koichiro Yawata +2
Precise parametric control over circuit geometry is essential for semiconductor inspection, yet obtaining sufficient real training data remains costly. Although generative models s…
Hypergraph Neural Networks Accelerate MUS Enumeration
Hiroya Ijima, Koichiro Yawata
Enumerating Minimal Unsatisfiable Subsets (MUSes) is a fundamental task in constraint satisfaction problems (CSPs). Its major challenge is the exponential growth of the search spac…