arXiv Machine Learning June 9, 2026 By Julia Kruk, Sanchita Porwal, Amitrajit Bhattacharjee, Mansi Phute

Community-Specific Slang and Entity Detection via Semantic Shift in Fine-Tuned Language Models

Read the original on arXiv Machine Learning →

arXiv:2606. 07522v1 Announce Type: cross Abstract: We propose an unsupervised method of resolving slang, unique entities, and folklore from online communities by isolating words in the lexicon that have the highest magnitude of semantic shift.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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slang.gr as a Large-Scale Crowdsourced Resource for Non-Standard Greek

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Polarization Detection: A Hybrid Approach with AfroXLMR-Social and DeBERTa for Low- and High-Resource Settings

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