activity
20232026
most citedShow-1: Marrying Pixel and Latent Diffusion Models for Text-to-Video Generation

15 citations · 30 across the 19 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

physics.comp-ph2026

GeONet: Geometry-Encoded Operator Network for Predicting Flow in Heterogeneous Porous Media

Md Lal Mamud, Maruti K. Mudunuru, Yucheng Fu +13

Rapid prediction of pressure-driven flow in microfluidic porous media is important for experimental design, tracer-test interpretation, and digital-twin development for subsurface…

cs.CV2026

Physis-Lang: Self-Evolving Language as a Physical Representation for Video World Model

Liming Lu, Xianzheng Ma, Wenkun He +14

Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical principles. Existing approac…

cs.CV2026

SolarWM: Open Data and Scalable Training for Long-Horizon Video World Models

Junchao Huang, Guian Fang, Shengju Qian +15

We introduce SolarWM, a fully open foundation for building interactive video world models from data preparation through long-horizon inference. Training across heterogeneous data s…

cs.CV2026

MIND: Benchmarking Memory Consistency and Action Control in World Models

Yixuan Ye, Xuanyu Lu, Yuxin Jiang +7

World models aim to understand, remember, and predict dynamic visual environments, yet a unified benchmark for evaluating their fundamental abilities remains lacking. To address th…

cs.CV2026

Olaf-World: Orienting Latent Actions for Video World Modeling

Yuxin Jiang, Yuchao Gu, Ivor W. Tsang +1

Scaling action-controllable world models is limited by the scarcity of action labels. While latent action learning promises to extract control interfaces from unlabeled video, lear…