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IndicTriMix presents a new benchmark and models for token‑level language identification in tri‑language code‑mixed text involving Hindi, Gujarati, and Bengali. The authors reformulate the task as sequence labeling and fine‑tune transformer models MuRIL and XLM‑RoBERTa, evaluating them on manually annotated test sets. They also introduce two code‑mixing generation methods using parallel sentences and release the datasets and fine‑tuned models for public use.
arXiv:2610.15795v1 Announce Type: cross Abstract: Automated moderation systems are deployed at scale, yet they remain opaque to the users and moderators affected by their decisions, and their coverag...
arXiv:2606. 24825v1 Announce Type: cross Abstract: Part-of-Speech (POS) tagging is a foundational NLP task underpinning machine translation, information extraction, and syntactic parsing.
arXiv:2606.27314v2 Announce Type: replace Abstract: To avoid moderation and surveillance on social media, some users routinely invent indirect linguistic expressions (ILE) that camouflage sensitive m...
arXiv:2610.20370v1 Announce Type: new Abstract: Hate speech has become increasingly prevalent on social media, raising concerns about its detection, interpretation, and moderation. Persian, a relativ...
arXiv:2610.20279v1 Announce Type: new Abstract: Part-of-speech tagging is a fundamental sequence labeling task and an important component for many downstream natural language processing applications....