Author

Yuandong Pu

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#artificial intelligence Apr 2025

Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision

It is demonstrated that separately encoding text and visual instructions, combined with co-training using shallow feature control, is essential to mitigate task ambiguity and enhance multi-task generalization and pave the way for more robust and generalizable low-level vision systems.

Yuandong Pu, Le Zhuo, Kaiwen Zhu et al. · arXiv.org · 19 citations

Preprint Aug 2026

Towards Physics-Faithful Generation of Scientific Diagrams

Princigram shows that explicit physics-structured supervision improves the physical faithfulness of generated scientific diagrams, and curate and structurally annotate 4.3 million physics images, carry expert-level annotation, and adapt a unified multimodal backbone.

Ming-Hui Zhang, Jinxin Shi, Yi-Fan Chang et al. · 0 citations

#artificial intelligence Preprint Aug 2026

PAWBench: How Far Are We from Probabilistically Aligned World Modeling?

This work formalizes probabilistic alignment as a distributional criterion for world models and introduces PAWBench, a benchmark for evaluating video generators as stochastic samplers of world dynamics, and introduces PAWEval, an outcome-level protocol that converts repeated video rollouts into empirical distributions...

Yuan-Dong Pu, Le Zhuo, Sayak Paul et al. · 0 citations