arXiv Machine Learning June 5, 2026 By Zhen Sun, Yifan Liao, Zhicong Huang, Jiaheng Wei, Cheng Hong, Yutao Yue, Xinlei He

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer

Read the original on arXiv Machine Learning →

arXiv:2606. 05626v1 Announce Type: cross Abstract: Machine-generated text (MGT) attribution aims to identify the specific generator responsible for a given text, thereby providing fine-grained evidence for model accountability and misuse investigation.

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One email a morning, machine-written

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Beyond Representational Similarity: Source-Conditioned Description-Length Gain for Generative Plagiarism Detection and Candidate Source Reranking

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