Papers by Andrew D Wilson

2 papers
Out of Sight, Not Out of Context? Egocentric Spatial Reasoning in VLMs Across Disjoint Frames (2025.emnlp-main)

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Challenge: Disjoint-3DQA evaluates the spatial reasoning ability of embodied AI assistants based on egocentric video . it aims to catalyze future research at the intersection of vision, language, and embodie .
Approach: They propose a generative QA benchmark that evaluates the ability of embodied AI assistants to integrate spatial cues across time by asking object pairs that are not co-visible in the same frame.
Outcome: The proposed benchmark compares seven state-of-the-art VLMs and finds that they lag behind human performance by 28%, with steeper declines as the temporal gap widens.
Grounding Task Assistance with Multimodal Cues from a Single Demonstration (2025.findings-acl)

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Challenge: RGB video often fails to capture fine-grained contextual cues such as intent, safety-critical environmental factors, and subtle preferences embedded in human behavior.
Approach: They propose a framework that integrates eye gaze and speech cues to improve conversational agents for task assistance by integrating eye gaze with speech cuests.
Outcome: The proposed framework captures fine-grained intent and user-specific cues, enabling richer contextual grounding for visual question answering.

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