Summary of Ask-eda: a Design Assistant Empowered by Llm, Hybrid Rag and Abbreviation De-hallucination, By Luyao Shi et al.
Ask-EDA: A Design Assistant Empowered by LLM, Hybrid RAG and Abbreviation De-hallucination
by Luyao Shi, Michael Kazda, Bradley Sears, Nick Shropshire, Ruchir Puri
First submitted to arxiv on: 3 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Ask-EDA is a conversational agent designed to serve as a subject-matter expert for electronic design engineers, providing guidance 24/7. Leveraging large language models (LLMs), hybrid retrieval augmented generation (RAG) and abbreviation de-hallucination (ADH) techniques, Ask-EDA delivers more relevant and accurate responses. The paper presents three evaluation datasets (q2a-100, cmds-100, and abbr-100) tailored to assess different aspects of design question answering, command handling, and abbreviation resolution. Results show that hybrid RAG improves recall by over 40% on q2a-100 and 60% on cmds-100 compared to not using RAG, while ADH enhances recall by over 70% on abbr-100. The evaluation results demonstrate the effectiveness of Ask-EDA in responding to design-related inquiries. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper introduces a new tool called Ask-EDA that helps electronic design engineers get answers quickly. It’s like having a knowledgeable expert always available to give guidance and advice. Ask-EDA uses special computer models and techniques to provide better answers. The researchers tested this tool on three different tasks: answering questions, handling commands, and figuring out abbreviations. They found that the tool works really well, especially when it comes to understanding complex abbreviations. Overall, Ask-EDA is a helpful tool for design engineers who need quick answers. |
Keywords
» Artificial intelligence » Hallucination » Question answering » Rag » Recall » Retrieval augmented generation
