13 papers
EVIL-Detect for NLPCC 2026 Shared Task 6: LLM-Generated Text Detection
Hongrui Bao, Hangyu Rong, Zhuoshang Wang +2
The rapid development of large language models (LLMs) has increased the need for reliable detection of LLM-generated text, especially in realistic Chinese scenarios involving human…
Once a Response, Always a Response: Detecting LLM-generated Text via Latent Prompt Restoration
Hongrui Bao, Yubing Ren, Yanan Cao +3
Large language models (LLMs) can generate fluent and convincing text at scale, creating growing risks for misinformation dissemination, educational misuse, and platform governance.…
WorldCup Sampling for Multi-bit LLM Watermarking
Yidan Wang, Yubing Ren, Yanan Cao +1
As large language models (LLMs) generate increasingly human-like text, watermarking has emerged as a promising solution for reliable attribution beyond mere detection. While multi-…
DualGuard: Dual-stream Large Language Model Watermarking Defense against Paraphrase and Spoofing Attack
Hao Li, Yubing Ren, Yanan Cao +4
With the rapid development of cloud-based services, large language models have become increasingly accessible through various web platforms. However, this accessibility has also le…
Rethinking LLM Watermark Detection in Black-Box Settings: A Non-Intrusive Third-Party Framework
Zhuoshang Wang, Yubing Ren, Yanan Cao +3
While watermarking serves as a critical mechanism for LLM provenance, existing secret-key schemes tightly couple detection with injection, requiring access to keys or provider-side…
EnsemJudge: Enhancing Reliability in Chinese LLM-Generated Text Detection through Diverse Model Ensembles
Zhuoshang Wang, Yubing Ren, Guoyu Zhao +3
Large Language Models (LLMs) are widely applied across various domains due to their powerful text generation capabilities. While LLM-generated texts often resemble human-written on…