Papers with M4 dataset

2 papers
Ranking Human and LLM Texts Using Locality Statistics (2026.findings-eacl)

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Challenge: The paper extends the Data Movement Distance (DMD) metric defined to measure the locality in computer memory to text by defining a new term designed to better characterize low-frequency tokens.
Approach: They propose to define a normalized version of the Data Movement Distance (nDMD) term is designed to better characterize low-frequency tokens.
Outcome: The proposed normalized version outperforms baselines and improves performance on the English subset of the M4 dataset and the GenAI detection shared task.
Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI (2026.acl-long)

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Challenge: Existing methods struggle with content-style entanglement, leading to poor generalization across domains.
Approach: They propose an explanation-by-design framework that explicitly disentangles style from content through architectural separation-by design.
Outcome: The proposed framework disentangles style from content through architectural separation-by-design.

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