AI-PAVE-Br applies LLMs with prompt engineering to outperform NER baselines on Portuguese product attribute extraction and releases the Golden Set as a new benchmark dataset.
BERTimbau: Pretrained BERT Models for Brazilian Portuguese,
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CL 2years
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Trains a 125M-parameter Persian PLM on a curated 45GB corpus using vector semantic deduplication for domain balance, topping QA and NLI benchmarks while remaining competitive on NER and classification.
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AI-PAVE-Br: Leveraging Large Language Models for Enhanced Product Attribute Value Extraction through a Golden Set Approach
AI-PAVE-Br applies LLMs with prompt engineering to outperform NER baselines on Portuguese product attribute extraction and releases the Golden Set as a new benchmark dataset.
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IHUBERT: Vector-Based Semantic Deduplication and Domain-Balanced Pretraining for Persian Resources
Trains a 125M-parameter Persian PLM on a curated 45GB corpus using vector semantic deduplication for domain balance, topping QA and NLI benchmarks while remaining competitive on NER and classification.