Detecting LLM-Generated Tokens in Human--LLM Coauthored Text
The rise of human-AI collaborative writing has created a growing need for fine-grained detection methods that support localizing likely LLM-generated content in mixed-authorship documents. Existing methods for detecting LLM-generated text mainly focus on document-level classification and cannot identify which parts of the text are generated by LLMs. This paper introduces a new method to address this urgent need. Our method operates at the token level, the natural unit of modern language models, and builds on existing token-level detection scores. The key idea is to smooth adjacent token scores
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- LinkedLinked via arxiv author · 85%Yangjun Lu →
“Detecting LLM-Generated Tokens in Human--LLM Coauthored Text”
- LinkedLinked via arxiv author · 85%Hongyi Zhou →
“Detecting LLM-Generated Tokens in Human--LLM Coauthored Text”
- LinkedLinked via arxiv author · 85%Fabian Spill →
“Detecting LLM-Generated Tokens in Human--LLM Coauthored Text”
- LinkedLinked via arxiv author · 85%Kai Ye →
“Detecting LLM-Generated Tokens in Human--LLM Coauthored Text”
- LinkedLinked via arxiv author · 85%Chengchun Shi →
“Detecting LLM-Generated Tokens in Human--LLM Coauthored Text”