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arXiv · 2507.16844

TD-Interpreter: Enhancing the Understanding of Timing Diagrams with Visual-Language Learning

Jie He·Vincent Theo Willem Kenbeek·Zhantao Yang·Meixun Qu·Ezio Bartocci·Dejan Ničković·Radu Grosu
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Abstract

We introduce TD-Interpreter, a specialized ML tool that assists engineers in understanding complex timing diagrams (TDs), originating from a third party, during their design and verification process. TD-Interpreter is a visual question-answer environment which allows engineers to input a set of TDs and ask design and verification queries regarding these TDs. We implemented TD-Interpreter with multimodal learning by fine-tuning LLaVA, a lightweight 7B Multimodal Large Language Model (MLLM). To address limited training data availability, we developed a synthetic data generation workflow that aligns visual information with its textual interpretation. Our experimental evaluation demonstrates the usefulness of TD-Interpreter which outperformed untuned GPT-4o by a large margin on the evaluated benchmarks.

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Jie He, Vincent Theo Willem Kenbeek, Zhantao Yang, Meixun Qu, Ezio Bartocci, Dejan Ničković, Radu Grosu. 2025-07-20. TD-Interpreter: Enhancing the Understanding of Timing Diagrams with Visual-Language Learning. https://arxiv.org/abs/2507.16844

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