On the NLPCC 2025 Chinese AI-text detection benchmark, LoRA-adapted Qwen2.5-7B reaches 95.94% test accuracy, beating BERT-large (79.3%), RoBERTa-large (76.3%), and FastText (83.5%).
Bert: Pre-training of deep bidirectional trans- formers for language understanding
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
LLM Encoder vs. Decoder: Robust Detection of Chinese AI-Generated Text with LoRA
On the NLPCC 2025 Chinese AI-text detection benchmark, LoRA-adapted Qwen2.5-7B reaches 95.94% test accuracy, beating BERT-large (79.3%), RoBERTa-large (76.3%), and FastText (83.5%).