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An AI answer can look right and still fail an essential check.

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Did it produce the structure we asked for?

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Retrieve a relevant reference?

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Or actually use the video?

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Here are three different tests, from research I coauthored.

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StructEval studies structured generation and conversion, including JSON, HTML, and SVG.

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A page can contain valid HTML yet show the wrong layout.

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A format conversion can parse correctly yet lose content.

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Separate syntax, content preservation, and visual fidelity.

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ScholarCopilot jointly trains academic writing and citation retrieval.

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A retrieval token decides when to request references, and retrieved material informs the next text.

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But a real reference is not automatically support for a claim.

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Check existence, relevance, and evidence separately.

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Video questions can reveal clues in their wording or answer choices.

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Watch Before You Answer studies these shortcuts.

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VidGround selects questions intended to require visual evidence for post-training.

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Comparing video access with a text-only condition helps diagnose what a task measures.

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These are different tasks, so their benchmark scores should not be compared directly.

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Define the evidence your application needs, then choose an evaluation that can detect its absence.

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Use the original papers to understand the models, datasets, and limitations.

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Read the papers, code, and full author lists at yuxuan dot world slash publications.

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This is an author guide prepared with AI assistance and synthetic narration.

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It reports no new experiments, and the research contributions belong to all coauthors.