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Adapting BigScience Multilingual Model to Unseen Languages ...
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On Efficiently Acquiring Annotations for Multilingual Models ...
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Team ÚFAL at CMCL 2022 Shared Task: Figuring out the correct recipe for predicting Eye-Tracking features using Pretrained Language Models ...
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Does Corpus Quality Really Matter for Low-Resource Languages? ...
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Abstract:
The vast majority of non-English corpora are derived from automatically filtered versions of CommonCrawl. While prior work has identified major issues on the quality of these datasets (Kreutzer et al., 2021), it is not clear how this impacts downstream performance. Taking Basque as a case study, we explore tailored crawling (manually identifying and scraping websites with high-quality content) as an alternative to filtering CommonCrawl. Our new corpus, called EusCrawl, is similar in size to the Basque portion of popular multilingual corpora like CC100 and mC4, yet it has a much higher quality according to native annotators. For instance, 66% of documents are rated as high-quality for EusCrawl, in contrast with <33% for both mC4 and CC100. Nevertheless, we obtain similar results on downstream tasks regardless of the corpus used for pre-training. Our work suggests that NLU performance in low-resource languages is primarily constrained by the quantity rather than the quality of the data, prompting for ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://dx.doi.org/10.48550/arxiv.2203.08111 https://arxiv.org/abs/2203.08111
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IIITDWD-ShankarB@ Dravidian-CodeMixi-HASOC2021: mBERT based model for identification of offensive content in south Indian languages ...
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mSLAM: Massively multilingual joint pre-training for speech and text ...
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On the Representation Collapse of Sparse Mixture of Experts ...
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Politics and Virality in the Time of Twitter: A Large-Scale Cross-Party Sentiment Analysis in Greece, Spain and United Kingdom ...
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L3Cube-MahaHate: A Tweet-based Marathi Hate Speech Detection Dataset and BERT models ...
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Few-Shot Cross-lingual Transfer for Coarse-grained De-identification of Code-Mixed Clinical Texts ...
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A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model ...
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A New Generation of Perspective API: Efficient Multilingual Character-level Transformers ...
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Factual Consistency of Multilingual Pretrained Language Models ...
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Examining Scaling and Transfer of Language Model Architectures for Machine Translation ...
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MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset ...
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Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi ...
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From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction ...
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