Papers by Frank Xing

2 papers
Financial Sentiment Analysis: An Investigation into Common Mistakes and Silver Bullets (2020.coling-main)

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Challenge: Recent dominance of machine learning-based natural language processing methods has overemphasized model accuracies rather than studying the reasons behind their errors.
Approach: They investigate the error patterns of some widely acknowledged sentiment analysis methods in the finance domain.
Outcome: The proposed models are based on the existing models and have important clues for improving them.
SenticNet 7: A Commonsense-based Neurosymbolic AI Framework for Explainable Sentiment Analysis (2022.lrec-1)

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Challenge: Despite recent advances, AI still struggles with complex tasks that require commonsense reasoning such as natural language understanding.
Approach: They propose a commonsense-based framework that aims to overcome these limitations in the context of sentiment analysis.
Outcome: The proposed framework overcomes these limitations in the context of sentiment analysis.

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