Papers by Xiaosu Wang

3 papers
KeFVP: Knowledge-enhanced Financial Volatility Prediction (2023.findings-emnlp)

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Challenge: Current studies ignore the role of financial metrics knowledge in earnings calls and little consideration is given to integrating text and price information.
Approach: They propose to integrate financial metrics knowledge into text comprehension by knowledge-enhanced adaptive pre-training and effectively incorporating text and price information by introducing a conditional time series prediction module.
Outcome: The proposed method outperforms state-of-the-art methods on three real-world datasets and is effective and reliable.
Composition-based Heterogeneous Graph Multi-channel Attention Network for Multi-aspect Multi-sentiment Classification (2022.coling-1)

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Challenge: Existing methods for Aspect-based sentiment analysis (ABSA) focus on aspect terms with the same sentiment polarity . current methods focus on sentences with only one aspect term or multiple aspect terms .
Approach: They propose a novel method to model inter-aspect relationships and aspect-context relationships simultaneously using a heterogeneous graph.
Outcome: The proposed method can predict sentiments towards the given aspect term in a sentence . it can provide more detailed predictions compared with sentence-level sentiment analysis.
Adaptive Structure Induction for Aspect-based Sentiment Analysis with Spectral Perspective (2023.findings-emnlp)

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Challenge: incorporating structure information can enhance the performance of aspect-based sentiment analysis.
Approach: They propose to use pre-trained language models to induct latent structures from a spectrum perspective.
Outcome: The proposed model shortens Aspects-sentiment Distance and improves structure induction ability.

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