iScript: A Domain-Adapted Large Language Model and Benchmark for Physical Design Tcl Script Generation

• URL: http://arxiv.org/abs/2603.04476v1
• Date: Wed, 04 Mar 2026 15:20:35 GMT
• Title: iScript: A Domain-Adapted Large Language Model and Benchmark for Physical Design Tcl Script Generation
• Authors: Ning Xu, Zhaoyang Zhang, Senlin Shu, Lei Qi, Jiaqi Lv, Wensuo Wang, Tianhao Zhao, Chao Zhang, Zhaoliang Yang, Xiangyu Li, Zhaorui Su, Jingshan Li, Xin Geng,
• Abstract summary: iScript is a domain-adapted Qwen3-8B model for Innovus Tcl script generation.<n>iScript shows higher pass@k scores than currently state-of-the-art LLMs on average.
• Score: 48.502477318243386
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Modern EDA flows rely heavily on Tcl scripting, yet general LLMs perform poorly in this domain due to extreme data scarcity, domain-specific semantics, and the high reliability required in physical design. We present iScript, a domain-adapted Qwen3-8B model for Innovus Tcl script generation, and iScript-Bench, a comprehensive benchmark covering five task categories and three difficulty levels. To overcome the lack of training data, we introduce a multi-stage data synthesis pipeline that integrates command extraction, static linting, requirement back-inference, and Chain-of-Thought generation, producing a 10K-tuple (requirement, CoT, script) dataset. iScript is trained through a two-stage strategy combining domain-adaptive pretraining and supervised fine-tuning. To evaluate script correctness efficiently, we further propose a two-step verification framework consisting of static syntax verification and LLM-based functional evaluation. On our benchmark, iScript shows higher pass@k scores than currently state-of-the-art LLMs on average. These results demonstrate the effectiveness of domain adaptation and data synthesis for EDA scripting tasks.

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