Papers by Winston Hsu

2 papers
OCID-Ref: A 3D Robotic Dataset With Embodied Language For Clutter Scene Grounding (2021.naacl-main)

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Challenge: Visual grounding (VG) is a crucial task in natural language processing, computer vision, and robotics.
Approach: They propose a visual grounding task with referring expressions of occluded objects in a OCID-Ref dataset with 2,300 scenes and a point cloud input.
Outcome: The proposed dataset shows that it can handle 2D and 3D signals but referring to occluded objects remains challenging for the modern visual grounding systems.
Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses (2024.findings-emnlp)

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Challenge: Large language models (LLMs) equipped with chain-of-thoughts (CoT) prompting have shown significant multi-step reasoning capabilities in factual content like mathematics, commonsense, and logic.
Approach: They introduce a trope-wise querying approach to assess the abstract reasoning abilities of large language models (LLMs) and uncover their low performance.
Outcome: The proposed approach boosts the F1 score by 11.8 points and also reduces the performance of the large language models (LLMs) it also shows that it can cause hallucinations in narrative content, reducing the performance.

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