4 papers
EmbodiedGen V2: An Agentic, Simulation-Ready 3D World Engine for Embodied AI
Xinjie Wang, Liu Liu, Taojun Ding +9
We present EmbodiedGen V2, a generative 3D world engine for building executable policy-ready environments for embodied intelligence. Sim-ready 3D asset generation has advanced rapi…
RankQ: Offline-to-Online Reinforcement Learning via Self-Supervised Action Ranking
Andrew Choi, Wei Xu
Offline-to-online reinforcement learning (RL) improves sample efficiency by leveraging pre-collected datasets prior to online interaction. A key challenge, however, is learning an…
Scaling Sim-to-Real Reinforcement Learning for Robot VLAs with Generative 3D Worlds
Andrew Choi, Xinjie Wang, Zhizhong Su +1
The strong performance of large vision-language models (VLMs) trained with reinforcement learning (RL) has motivated similar approaches for fine-tuning vision-language-action (VLA)…
LatentExplainer: Explaining Latent Representations in Deep Generative Models with Multimodal Large Language Models
Mengdan Zhu, Raasikh Kanjiani, Jiahui Lu +3
Deep generative models like VAEs and diffusion models have advanced various generation tasks by leveraging latent variables to learn data distributions and generate high-quality sa…