Papers with XLM-Roberta-large

1 papers
FewshotQA: A simple framework for few-shot learning of question answering tasks using pre-trained text-to-text models (2021.emnlp-main)

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Challenge: Existing pre-trained models need fine-tuning on tens of thousands of examples to achieve good results.
Approach: They propose a framework that leverages pre-trained text-to-text models and aligns them with their pre-training framework.
Outcome: The proposed framework outperforms the XLM-Roberta-large on multiple QA benchmarks and is applicable to multilingual situations.

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