Papers by Yingshan Chang

2 papers
VISREAS: Complex Visual Reasoning with Unanswerable Questions (2024.findings-acl)

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Challenge: Logic2Vision is a visual question-answering dataset that validates question authenticity with the corresponding image and then reasoning over it.
Approach: They propose a compositional visual question-answering dataset, VisReas, that consists of answerable and unanswerable visual queries . they use visual genome scene graphs to generate the query and the reasoning steps to generate it.
Outcome: The proposed model outperforms generative models and the existing classification models and outperformed existing models.
Tools Fail: Detecting Silent Errors in Faulty Tools (2024.emnlp-main)

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Challenge: a failure in one tool can trigger a cascade of errors, leading to complete task failure.
Approach: They propose a framework for tools more broadly which explores a model’s ability to detect “silent” tool errors and reflect on how to plan.
Outcome: The proposed approach shows that the model can detect "silent" tool errors and plan.

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