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This work proposes interactive tools and atomic rubrics for LLM agents to reliably assess accessibility and preliminary results on a subset of ACT test cases show substantially higher recall and precision than the strongest evaluated LLM-driven baseline.
This work systematically analyzes all 1,702 CHI 2026 full papers and identifies 125 that annotate videos, and derives a five-dimensional taxonomy spanning analytic purpose, viewpoint, phenomenon, reasoning requirement, and annotation authority to map the capabilities and limitations of a general-purpose VLM.
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