A new pre-training task that maps languages bidirectionally in embedding space improves machine translation by up to 11.9 BLEU, cross-lingual QA by 6.72 BERTScore points, and understanding accuracy by over 5% over strong baselines.
I nfo XLM : An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training
2 Pith papers cite this work, alongside 249 external citations. Polarity classification is still indexing.
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The paper surveys Indic NLP evolution and proposes 'Culture Sensing' to integrate indigenous oral knowledge into foundation models for cultural preservation.
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Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance
A new pre-training task that maps languages bidirectionally in embedding space improves machine translation by up to 11.9 BLEU, cross-lingual QA by 6.72 BERTScore points, and understanding accuracy by over 5% over strong baselines.
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Rethinking Indic AI from a Lens of Cultural Heritage Preservation
The paper surveys Indic NLP evolution and proposes 'Culture Sensing' to integrate indigenous oral knowledge into foundation models for cultural preservation.