| TransDis系统，是一个基于Transformer语言模型的语义距离评分系统，用于自动评估中文（或其他语言）的多用途任务（AUT)中的独创性和灵活性（论文预印本见，https://arxiv.org/abs/2306.14790 ）。 | |
| 输入被试（id)+提示词+回答的数据，每行1个用途，用逗号隔开。您可以通过文本框直接输入数据，也可以上传用逗号隔开的CSV格式文件或xlsx文件作为输入，CSV输入优先级高于文本框输入。 | |
| 您可以选择用于评分的模型，请注意sentence-transformers_paraphrase-multilingual-mpnet-base-v2和sentence-transformers_paraphrase-multilingual-MiniLM-L12-v2可用于多语言，其他模型仅适用于英文或中文。 | |
| 我们提供Pooling方法的选择，对于bert-base-chinese建议使用mean pooling。 | |
| 如发生错误，请试着简化你的数据——用更少的行试试。如果不行，则可能是输入格式错误，请尝试重新保存为逗号分隔的CSV，然后再上传CSV文件。 | |
| 如需更多帮助或报告其他bug，请联系ydd409@163.com。 | |
| TranDis, a semantic distance scoring system based on transformer-based language models, can be a useful tool to automatically assess originality and flexibility for AUT in Chinese or other languages (for a pre-print, see https://arxiv.org/abs/2306.14790). | |
| Enter your participant ID + prompt + response data, one per line, with a COMMA between each variable. You can either input data directly into the text box or upload a comma-separated CSV file or a XLSX file as input. Please note that if both methods are used, the CSV input will take precedence over the text box input. | |
| You can choose the model to use for scoring. Please note that sentence-transformers_paraphrase-multilingual-mpnet-base-v2 and sentence-transformers_paraphrase-multilingual-MiniLM-L12-v2 are applicable to multiple languages; cyclone_simcse-chinese-roberta-wwm-ext is only applicable to Chinese; sentence-transformers/all-mpnet-base-v2 and sentence-transformers/all-MiniLM-L12-v2 are only applicable to English. | |
| If an error occurs, try simplifying your data - does it work with fewer rows? If not, the input format may be incorrect. | |
| For more assistance or to report potential issues with our system, please contact ydd409@163.com. |