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HC3 Plus: A Semantic-Invariant Human ChatGPT Comparison Corpus
- Publication Year :
- 2023
-
Abstract
- ChatGPT has garnered significant interest due to its impressive performance; however, there is growing concern about its potential risks, particularly in the detection of AI-generated content (AIGC), which is often challenging for untrained individuals to identify. Current datasets used for detecting ChatGPT-generated text primarily focus on question-answering tasks, often overlooking tasks with semantic-invariant properties, such as summarization, translation, and paraphrasing. In this paper, we demonstrate that detecting model-generated text in semantic-invariant tasks is more challenging. To address this gap, we introduce a more extensive and comprehensive dataset that incorporates a wider range of tasks than previous work, including those with semantic-invariant properties.<br />Comment: This paper has been accepted by CIKM2023 workshop
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2309.02731
- Document Type :
- Working Paper