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cs.CV2026

Orca: The World is in Your Mind

Yihao Wang, Yuheng Ji, Mingyu Cao +54

We introduce Orca, an initial instantiation of a general world foundation model. Orca learns a unified world latent space from multimodal world signals and exposes it through multi…

cs.CV2026

LAST: Bridging Vision-Language and Action Manifolds via Gromov-Wasserstein Alignment

Huaihai Lyu, Chaofan Chen, Yuheng Ji +4

We take a Gromov-Wasserstein perspective on Vision-Language-Action (VLA) learning, where the goal is to make the relational geometry of action representations compatible with the s…

cs.CV2026

General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling

Huaihai Lyu, Chaofan Chen, Mingyu Cao +2

Achieving robust generalization from limited data is a central challenge in embodied intelligence. Prevailing methods fail by regressing absolute coordinates, which violates the pr…

cs.CV2025

OmniSAT: Compact Action Token, Faster Auto Regression

Huaihai Lyu, Chaofan Chen, Senwei Xie +4

Existing Vision-Language-Action (VLA) models can be broadly categorized into diffusion-based and auto-regressive (AR) approaches: diffusion models capture continuous action distrib…

cs.CV2025

MathSticks: A Benchmark for Visual Symbolic Compositional Reasoning with Matchstick Puzzles

Yuheng Ji, Huajie Tan, Cheng Chi +8

We introduce \textsc{MathSticks}, a benchmark for Visual Symbolic Compositional Reasoning (VSCR), which unifies visual perception, symbolic manipulation, and arithmetic consistency…

cs.CV2025

EgoPrompt: Prompt Learning for Egocentric Action Recognition

Huaihai Lyu, Chaofan Chen, Yuheng Ji +1

Driven by the increasing demand for applications in augmented and virtual reality, egocentric action recognition has emerged as a prominent research area. It is typically divided i…

cs.CV2025

VisualTrans: A Benchmark for Real-World Visual Transformation Reasoning

Yuheng Ji, Yipu Wang, Yuyang Liu +5

Visual transformation reasoning (VTR) is a vital cognitive capability that empowers intelligent agents to understand dynamic scenes, model causal relationships, and predict future…