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DTSTAMP:20240626T180035Z
LOCATION:Level 2 Exhibit Hall
DTSTART;TZID=America/Los_Angeles:20240625T170000
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UID:dac_DAC 2024_sess233_ETPOST184@linklings.com
SUMMARY:Novel Preprocessing Technique for Data Embedding in Engineering Co
 de Generation Using Large Language Models
DESCRIPTION:Engineering Track Poster\n\nYu-Chen Lin (National Taiwan Unive
 rsity); Akhilesh Kumar, Norman Chang, Wen-liang Zhang, and Muhammad Zakir 
 (Ansys); and Jyh-Shing Jang (National Taiwan University)\n\nIn engineering
 , the use of Large Language Models (LLMs) for specific domain code generat
 ion presents a significant challenge and an important area of study. These
  models are crucial in assisting programming and development tasks, but th
 ey often require substantial computational resources and extensive dataset
 s. Our method focuses on improving data preprocessing and optimizing promp
 t engineering techniques. We propose using LLMs in the data preprocessing 
 phase to create data embeddings that more accurately reflect their context
 ual meanings within a semantic space. This will improve the relevance and 
 quality of the generated code.\n\nTopic: Back-End Design, Embedded Systems
 , Front-End Design, IP
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