基本信息
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Bio
My research interest lies in retrieval-augmented text classification and its application in financial sentiment analysis.
Research
Retrieval-augmented natural language understanding.
Retrieval-augmented natural language understanding aims to fetch relevant examples from training sets or external knowledge bases to improve the performance of different NLU tasks. The main challenge of this task is to retrieve useful examples for downstream tasks.
Aspect-based Sentiment Analysis.
Aspect-based Sentiment Analysis (ABSA for short) is a burgeoning fine-grained sentiment analysis task, which aims to extract aspect terms, classify the related sentiment polarities, and find opinion terms as the cause of the sentiment.
Financial Event Extraction and Classification.
Financial Event extraction and Classification extract events form financial news and reports and obtain their classes. Such task could help users obtain competitors’ strategies, predict the stock market and make correct investment decisions.
Research
Retrieval-augmented natural language understanding.
Retrieval-augmented natural language understanding aims to fetch relevant examples from training sets or external knowledge bases to improve the performance of different NLU tasks. The main challenge of this task is to retrieve useful examples for downstream tasks.
Aspect-based Sentiment Analysis.
Aspect-based Sentiment Analysis (ABSA for short) is a burgeoning fine-grained sentiment analysis task, which aims to extract aspect terms, classify the related sentiment polarities, and find opinion terms as the cause of the sentiment.
Financial Event Extraction and Classification.
Financial Event extraction and Classification extract events form financial news and reports and obtain their classes. Such task could help users obtain competitors’ strategies, predict the stock market and make correct investment decisions.
Research Interests
Papers共 9 篇Author StatisticsCo-AuthorSimilar Experts
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CoRR (2024)
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EMNLP 2023 (2023): 6721-6735
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Journal of Beijing Institute of Technologyno. 5 (2022): 473-482
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