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Towards Physics-Faithful Generation of Scientific Diagrams

arXiv cs.CV Multimodal & Generative Minghui Zhang, Jinxin Shi, Yifan Chang, Liangliang Zhao, Yuandong Pu, Qian Yu, Ming Hu, Hanxiao Zhang, Yun Gu, Yirong Chen, Yu Qiao, Bo Zhang, Xiangchao Yan, Bin Fu, Yihao Liu 2026-08-13
Representative image for Towards Physics-Faithful Generation of Scientific Diagrams

TL;DR - Princigram generates scientific diagrams using structured physics reasoning rather than visual plausibility alone. It aims to reduce physically incorrect forces, coordinate systems, states, and equations in educational and scientific graphics.

  • Structured Physical Chain-of-Thought applies fixed, discipline-specific reasoning schemas with explicit fidelity rules.
  • The training pipeline includes 4.3 million physics images, with 115,037 receiving expert-level structured annotations.
  • VeriphyT2IBench evaluates individual physical facts through diagram-specific binary questions instead of a single holistic score.
  • Evaluations on GenExam’s physics subset and VeriphyT2IBench indicate improved physical faithfulness from structured supervision.

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