Do Multimodal Models Decide Consistently on Equivalent Optical Spectra?
How to prepare an accurate paper press kit? Illustrated guide
Ziyuan Wang, Genliang Zhu, Xiaobo Chen · arXiv: 2611.00428v1 · Summary page
Why cover this story this week?
The same spectrum, a different answer
Scientific evidence should not change when a wavelength table becomes a photon-energy plot. Yet a benchmark using measured optical spectra found that changing only the representation shifted a model’s accuracy by up to 41 percentage points. Researchers presented equivalent spectra in different table and plot formats, then removed selected data to test whether models would acknowledge missing evidence. Unadapted models rarely answered “undetermined” when the relevant extremum was absent. Fine-tuning helped, but initially taught a misleading shortcut: abstain whenever the input is truncated. Including truncated examples that remained answerable prevented that shortcut on held-out structures in the reported tests, although the training approaches performed similarly on gold spectra. For scientific AI, the implication is straightforward: average accuracy can conceal both sensitivity to presentation and failure to distinguish missing evidence from merely unfamiliar formatting.
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