Text Source

Identifying the source of text, particularly whether it was generated by a large language model (LLM) or a human, is a burgeoning research area driven by concerns about misinformation and the responsible use of AI. Current approaches focus on developing methods to detect LLMs' "fingerprints" in generated text, employing techniques like originality scoring, watermarking, and analyzing token-level source information within the LLM's generation process. These methods utilize various deep learning architectures, including transformers and multi-layer perceptrons, aiming for high accuracy, robustness, and imperceptibility. The ability to reliably identify text sources has significant implications for combating misinformation, ensuring accountability in AI applications, and protecting intellectual property.