<ul><li>Developing algorithms to differentiate between machine-generated texts and human-written texts has garnered substantial attention in recent years.</li><li>In the online scenario, the ability to quickly and accurately determine if a source is an LLM (large language model) is crucial to prevent the spread of misinformation and misuse of LLMs.</li><li>To address the problem of online detection, an algorithm based on sequential hypothesis testing by betting has been developed.</li><li>Experiments were conducted to demonstrate the effectiveness of the proposed method.</li></ul>

Online Detecting LLM-Generated Texts via Sequential Hypothesis Testing by Betting

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