2022
EMNLP
EMNLP 2022
Jetsons at the FinNLP-2022 ERAI Task: BERT-Chinese for mining high MPP posts
Abstract
AbstractIn this paper, we discuss the various approaches by the Jetsons team for the “Pairwise Comparison” sub-task of the ERAI shared task to compare financial opinions for profitability and loss. Our BERT-Chinese model considers a pair of opinions and predicts the one with a higher maximum potential profit (MPP) with 62.07% accuracy. We analyze the performance of our approaches on both the MPP and maximal loss (ML) problems and deeply dive into why BERT-Chinese outperforms other models.
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio