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Yu-Lun Liu

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#artificial intelligence Review Oct 2026

One Figure, Every Canvas: Editable Flowchart Relayout via Agentic Pipeline

Pipeline figures in ML papers must be repurposed across many canvases, including paper columns, 16:9 slides, portrait posters, 1:1 social teasers, 9:16 phone previews. Each format imposes a different aspect ratio on the same computational graph, where any silently broken connection misrepresents the method. We formulat...

Shih-Cheng Tseng, Chih-Hsuan Chen, Ryan Yang et al. · 0 citations
Preprint Oct 2026

PROWBench: Do Video Models Render What the Program Specifies?

Programmable world models separate executable dynamics from visual generation, offering a promising foundation for next-generation game engines. However, their visual adherence to explicit rules and interactions remains insufficiently evaluated. Existing benchmarks assess visual quality, controllability, and instructio...

Zheng-Hui Huang, Gui-Xu Lin, Yu-Ju Tsai et al. · 0 citations
Preprint Sep 2026

Programmable World Model

The Programmable World Model is introduced, a framework that decouples world-state evolution from visual observation generation and demonstrates the effectiveness of separating explicit state evolution from generative rendering for building persistent, programmable worlds.

Zheng-Hui Huang, Gui-Xu Lin, Jia-Cheng Lin et al. · 6 citations · ⚡1
Book Open access Jul 2026

LongE2V: Long-Horizon Event-based Video Reconstruction, Prediction, and Frame Interpolation with Video Diffusion Models

This work proposes LongE2V, a novel approach that leverages pre-trained video diffusion priors to jointly handle event-based video reconstruction, prediction, and frame interpolation, and introduces Autoregressive Unrolling and Adaptive Context Switching to mitigate temporal drift in extremely long sequences.

Cheng-De Fan, Chun-Wei Tuan Mu, Chen-Wei Chang et al. · 0 citations

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