Papers by Mengsha Liu

1 papers
ChartThinker: A Contextual Chain-of-Thought Approach to Optimized Chart Summarization (2024.lrec-main)

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Challenge: Existing methods for chart summarization lack visual-language matching and reasoning ability.
Approach: They propose a method which synthesizes deep analysis based on chains of thought and strategies of context retrieval to improve the logical coherence and accuracy of the generated summaries.
Outcome: The proposed method outperforms 8 state-of-the-art models over 7 evaluation metrics and can significantly reduce time and cognitive resources required.

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