Fine-tuned BERTimbau-LoRA achieves 87.6% accuracy and 0.87 macro-F1 on LegalBench-BR, outperforming commercial LLMs by 22-28 points and eliminating their systematic bias toward civil law on Brazilian legal classification.
In International Conference on Computational Pro- cessing of the Portuguese Language , pages 406–412
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CL 2years
2026 2verdicts
CONDITIONAL 2representative citing papers
NorBERTo, a ModernBERT-style Portuguese encoder trained from scratch on the 331B-token Aurora-PT corpus, posts top scores on PLUE and ASSIN 2 entailment, but lower scores on semantic similarity.
citing papers explorer
-
LegalBench-BR: A Benchmark for Evaluating Large Language Models on Brazilian Legal Decision Classification
Fine-tuned BERTimbau-LoRA achieves 87.6% accuracy and 0.87 macro-F1 on LegalBench-BR, outperforming commercial LLMs by 22-28 points and eliminating their systematic bias toward civil law on Brazilian legal classification.
-
NorBERTo: A ModernBERT Model Trained for Portuguese with 331 Billion Tokens Corpus
NorBERTo, a ModernBERT-style Portuguese encoder trained from scratch on the 331B-token Aurora-PT corpus, posts top scores on PLUE and ASSIN 2 entailment, but lower scores on semantic similarity.