Author:
Shimada Hinari,Kimura Masaomi
Publisher
Engineering and Technology Publishing
Reference25 articles.
1. [1] S. Lin, J. Hilton, and O. Evans, "TruthfulQA: Measuring how models mimic human falsehoods," in Proc. the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Dublin, Ireland, 2022, pp. 3214-3252.
2. [2] S. Gehrmann, H. Strobelt, and A. Rush, "GLTR: Statistical detection and visualization of generated text," in Proc. the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, Italy, 2019, pp. 111-116.
3. [3] D. Ippolito, D. Duckworth, C. Callison-Burch, and D. Eck, "Automatic detection of generated text is easiest when humans are fooled," in Proc. the 58th Annual Meeting of the Association for Computational Linguistics, Online, 2020, pp. 1808-1822.
4. [4] E. Mitchell, Y. Lee, A. Khazatsky, C. D. Manning, and C. Finn, "DetectGPT: Zero-shot machine-generated text detection using probability curvature," in Proc. the 40th International Conference on Machine Learning, USA, 2023, pp. 24950-24962.
5. [5] J. Su, T. Zhuo, D. Wang, and P. Nakov, "DetectLLM: Leveraging log rank information for zero-shot detection of machine-generated text," in Proc. the Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore, 2023, pp. 12395-12412.