Papers by Jaywon Koo

2 papers
Multimodal Multi-loss Fusion Network for Sentiment Analysis (2024.naacl-long)

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Challenge: This paper examines the optimal selection and fusion of feature encoders across multiple modalities and combines them in one neural network to improve sentiment detection.
Approach: They propose to combine feature encoders across multiple modalities into one neural network to improve sentiment detection.
Outcome: The proposed model achieves state-of-the-art performance for three datasets . it also shows that integrating context significantly improves model performance.
PropTest: Automatic Property Testing for Improved Visual Programming (2024.findings-emnlp)

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Challenge: Visual Programming is an alternative to end-to-end black-box visual reasoning models.
Approach: They propose a visual programming strategy that leverages Large Language Models to generate the logic of a program in the form of its source code.
Outcome: The proposed method improves ViperGPT on visual question answering and referring expression comprehension with an LLM.

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