Papers by Sifan Wu

1 papers
Seeing Beyond Words: MatVQA for Challenging Visual-Scientific Reasoning in Materials Science (2026.findings-acl)

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Challenge: Multimodal Large Language Models (MLLMs) outperform existing benchmarks in both natural language and coding domains.
Approach: They propose a scalable benchmark that integrates vision and language modalities to address this gap by eliminating textual shortcuts.
Outcome: The new benchmark outperforms existing benchmarks in both natural language and coding domains.

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