A Neighborhood Framework for Resource-Lean Content Flagging

A Neighborhood Framework for Resource-Lean Content Flagging

<p dir="ltr">We propose a novel framework for cross- lingual content flagging with limited target- language data, which significantly outperforms prior work in terms of predictive performance. The framework is based on a nearest-neighbor architecture. It is a modern instantiation of...

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Bibliographic Details
Main Author: Sheikh Muhammad Sarwar (19517701) (author)
Other Authors: Dimitrina Zlatkova (19517704) (author), Momchil Hardalov (18618397) (author), Yoan Dinkov (19517707) (author), Isabelle Augenstein (14013962) (author), Preslav Nakov (17760905) (author)
Published: 2022
Subjects:
Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Language, communication and culture
Language studies
Linguistics
Cross-Lingual Content Flagging
Limited Target-Language Data
Encoding Schemes
Abusive Language Detection
Jigsaw Multilingual Dataset
Model Adaptation
Neighborhood-Based Approaches
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