Papers by Yubo Shan

1 papers
FactVerse: A Benchmark for Factual Consistency in Interleaved Image–Text Generation (2026.acl-long)

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Challenge: Existing benchmarks lack effective mechanisms to evaluate factual consistency in interleaved image-text generation.
Approach: They propose a benchmark dedicated to evaluating factual consistency in interleaved image-text generation.
Outcome: The proposed framework outperforms existing evaluation methods in evaluating factual consistency in interleaved image-text generation.

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