The results of this study indicate that input reframing and the proposed pre-finetuning task is useful for RoBERTa.

May 2, 2023 · The results of this study indicate that input reframing and the proposed pre-finetuning task is useful for. RoBERTa. 1 Introduction. Numerals ...

The results of this study indicate that input reframing and the proposed pre-finetuning task is useful for RoBERTa, and whether changing notation and pre- ...

The design goal of pretraining tasks is to enhance the model's understanding of natural language through learning from a large amount of unlabeled data, thereby ...

"Improving Numeracy by Input Reframing and Quantitative Pre-Finetuning Task." Findings of the Association for Computational Linguistics: EACL 2023. 2023. [2] ...

In this work, we improve the numeracy in language models on the QNLI and QQA tasks which involve textual and computational quantitative reasoning. We do so by ...

"Improving Numeracy by Input Reframing and Quantitative Pre-Finetuning Task." Findings of the Association for Computational Linguistics: EACL 2023. 2023. [2] ...

In this work, we improve the numeracy in language models on the QNLI and QQA tasks which involve textual and com- putational quantitative reasoning. We do so by ...

[1] Chen, Chung-Chi, et al. "Improving Numeracy by Input Reframing and Quantitative Pre-Finetuning Task." Findings of the Association for Computational ...

This paper attempts to answer the question of whether neural network models can learn numeracy, which is the ability to predict the magnitude of a numeral ...