Faithful Chart Generation for Multimodal Deep Research: Frame-Evidence Co-Adaptation
Analytical charts in multimodal deep research encode quantitative claims, requiring every visualized value to be faithfully grounded in supporting evidence. Unlike retrieved images that mainly provide contextual information, charts require numerical fidelity: visualized values should not only match retrieved evidence quantitatively but also preserve its original meaning and scope. However, achieving such fidelity remains challenging because current systems usually construct visualization plans before knowing what quantitative evidence can actually be retrieved from the web. As a result, predefined plans may require entities, temporal ranges, or comparison dimensions that the retrieved evi...
| Authors | Yuxin Yue, Yingchen Zhang, Ruqing Zhang et al. |
|---|---|
| Primary category | cs.HC |
| Published | 30 September 2026 |
| Last updated at source | 30 September 2026 |
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