| license: apache-2.0 | |
| library_name: peft | |
| pipeline_tag: text-classification | |
| base_model: Qwen/Qwen2.5-7B-Instruct | |
| tags: | |
| - ai-detection | |
| - chinese | |
| - nlpcc | |
| # EnsemJudge (Qwen2.5-7B-Instruct LoRA) | |
| This repository contains a LoRA adapter for **EnsemJudge**, a robust framework for detecting Chinese LLM-generated text. This model is based on Qwen2.5-7B-Instruct and was developed as part of the system that achieved first place in the NLPCC 2025 Shared Task 1. | |
| ## Resources | |
| - **Paper:** [EnsemJudge: Enhancing Reliability in Chinese LLM-Generated Text Detection through Diverse Model Ensembles](https://huggingface.co/papers/2603.27949) | |
| - **Repository:** [https://github.com/johnsonwangzs/MGT-Mini](https://github.com/johnsonwangzs/MGT-Mini) | |
| ## Description | |
| EnsemJudge addresses the challenge of detecting AI-generated Chinese text, particularly in scenarios involving out-of-domain inputs or adversarial samples. The framework incorporates tailored strategies and ensemble voting mechanisms to demonstrate high effectiveness and reliability. | |
| ## Citation | |
| If you find this work useful, please cite: | |
| ```bibtex | |
| @article{ensemjudge2025, | |
| title={EnsemJudge: Enhancing Reliability in Chinese LLM-Generated Text Detection through Diverse Model Ensembles}, | |
| author={Guoyu Zhao and others}, | |
| journal={arXiv preprint arXiv:2603.27949}, | |
| year={2025} | |
| } | |
| ``` |