collaborators

5 papers

cs.AI2026

CubePart: An Open-Vocabulary Part-Controllable 3D Generator

Yiheng Zhu, Kangle Deng, Jean-Philippe Fauconnier +9

Interactive 3D assets used in games and simulation are typically decomposed into specific semantic parts to support animation, physics, and scripted behaviors, yet most generative…

cs.CV2026

WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild

Junzhe Huang, Xiaoxiao Sun, Yan Yang +6

Using multimodal foundation models to analyze table images is a high-value yet challenging application in consumer and enterprise scenarios. Despite its importance, current evaluat…

cs.CV2026

Incentivizing Generative Zero-Shot Learning via Outcome-Reward Reinforcement Learning with Visual Cues

Wenjin Hou, Xiaoxiao Sun, Hehe Fan

Recent advances in zero-shot learning (ZSL) have demonstrated the potential of generative models. Typically, generative ZSL synthesizes visual features conditioned on semantic prot…

cs.CV2025

Efficient Autoregressive Shape Generation via Octree-Based Adaptive Tokenization

Kangle Deng, Hsueh-Ti Derek Liu, Yiheng Zhu +7

Many 3D generative models rely on variational autoencoders (VAEs) to learn compact shape representations. However, existing methods encode all shapes into a fixed-size token, disre…

cs.CV2025

Cube: A Roblox View of 3D Intelligence

Foundation AI Team, Kiran Bhat, Nishchaie Khanna +44

Foundation models trained on vast amounts of data have demonstrated remarkable reasoning and generation capabilities in the domains of text, images, audio and video. Our goal at Ro…