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TrafficSafetyGPT: Tuning a Pre-trained Large Language Model to a Domain-Specific Expert in Transportation Safety (2307.15311v1)

Published 28 Jul 2023 in cs.CL

Abstract: LLMs have shown remarkable effectiveness in various general-domain NLP tasks. However, their performance in transportation safety domain tasks has been suboptimal, primarily attributed to the requirement for specialized transportation safety expertise in generating accurate responses [1]. To address this challenge, we introduce TrafficSafetyGPT, a novel LLAMA-based model, which has undergone supervised fine-tuning using TrafficSafety-2K dataset which has human labels from government produced guiding books and ChatGPT-generated instruction-output pairs. Our proposed TrafficSafetyGPT model and TrafficSafety-2K train dataset are accessible at https://github.com/ozheng1993/TrafficSafetyGPT.

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Authors (5)
  1. Ou Zheng (15 papers)
  2. Mohamed Abdel-Aty (27 papers)
  3. Chenzhu Wang (1 paper)
  4. Shengxuan Ding (9 papers)
  5. DongDong Wang (28 papers)
Citations (16)

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