Word-Level Interpretation of Chatgpt Detector Based on Classification Contribution
Dekun Chen · Highlights in Science Engineering and Technology · 2023
The ChatGPT detector is considered a necessary task to standardize the use of ChatGPT. Difficulty interpreting the test process and results is a common problem with LLM. Most existing interpreters focus on attention visualization and rarely consider the classification process. This study presents a method to show the contribution of words to model predictions. Specifically, this study considers information from classification weight vectors, semantic vectors, and embedded input word vectors for a more complete interpretation of detector LLM. Three word-level attributes (word length, part of speech and word meaning) are compared with the conclusions of existing literatures to verify our method. Visual samples and analysis process can be found at https://github.com/salixc/WCC-DekunChen.