Papers with domain-specific pretrained language models

1 papers
Exploring the Impact of Corpus Diversity on Financial Pretrained Language Models (2023.findings-emnlp)

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Challenge: Existing financial PLMs are not pretrained on sufficiently diverse financial data, leading to subpar generalization performance.
Approach: They propose to pretrain financial PLMs on financial corpus and train financial models on financial data.
Outcome: The proposed financial language models outperform existing financial PLMs on financial tasks even for unseen corpus groups.

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