16 citations · 16 across the 25 of their papers we have counts for
16 papers · 1 filter
Dream4ACT: A Shared Visual Action Interface for Multi-Embodiment Video-Action Modeling
Xiangyu Zhu, Jin Xu, Yue Guo +6
Video generation models (VGMs) offer strong spatiotemporal priors for embodied observation--action modeling. However, joint-space action vectors lack explicit image-space structure…
Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence
Shilong Zou, Shilin Zhang, Yingji Zhang +8
In this technical report, we propose Pelican-Sim 1.0, a general world model simulator for embodied intelligence that predicts future observations from visual context and robot acti…
TrustRoboReward: Preference-Ordered Isotonic Score Editing for Multi-Paradigm Robot Reward Models
Yidong Wang, Yan Zhan, Ziteng Feng +16
Reward models are a bottleneck for reinforcement learning in embodied AI. Long-horizon robotic manipulation requires scalable vision feedback beyond handcrafted rewards or task-spe…
Group-of-Latents: Perceptual Video Compression at Extreme Bitrates via Masked Latent Generative Modeling
Shaokang Wang, Jinchang Xu, Peidong Jia +9
Most existing video compression algorithms follow a paradigm of transformation and quantization, optimizing the trade-off between distortion and bitrate. However, extremely low-bit…
IOI: Decoupling Kinematics and Physics for Interactive World Models
Chengyu Bai, Peidong Jia, Tiecheng Guo +11
Developing generalist embodied agents requires interactive environments providing visually realistic feedback and accurate action-conditioned dynamics. Interactive world models add…
MV-WAM: Manifold-Aware World Action Model with Value Augmentation
Jintao Chen, Peidong Jia, Qingpo Wuwu +13
Achieving robust and generalizable manipulation across diverse environments remains a fundamental challenge in embodied robotics. Recent world action models achieve strong in-domai…
Current World Models Lack a Persistent State Core
Jinpeng Lu, Dexu Zhu, Haoyuan Shi +8
World models are increasingly regarded as a decisive step toward artificial general intelligence, yet modeling the physical world demands more than rendering convincing frames on d…
SafeDojo: Safe Reinforcement Learning for VLA via Interactive World Model
Kai Tang, Peidong Jia, Zhong Chu +16
Safe control is a prerequisite for real-world embodied intelligence, for which safe reinforcement learning has emerged as a promising paradigm. However, existing safe reinforcement…
Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action
Yi Zhang, Yinda Chen, Che Liu +26
We present Pelican-Unify 1.0, the first embodied foundation model trained according to the principle of unification. Pelican-Unify 1.0 uses a single VLM as a unified understanding…
Robo-Cortex: A Self-Evolving Embodied Agent via Dual-Grain Cognitive Memory and Autonomous Knowledge Induction
Nga Teng Chan, Yi Zhang, Yechi Liu +9
The ability to navigate and interact with complex environments is central to real-world embodied agents, yet navigation in unseen environments remains challenging due to "experient…
EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models
Haozhe Shan, Xiancong Ren, Han Dong +10
While large vision-language models (VLMs) are increasingly adopted as the perceptual backbone for embodied agents, their fundamental vision-language grounding (VLG) capability in e…
VEGA: Visual Encoder Grounding Alignment for Spatially-Aware Vision-Language-Action Models
Hao Wang, Xiaobao Wei, Jingyang He +10
Precise spatial reasoning is fundamental to robotic manipulation, yet the visual backbones of current vision-language-action (VLA) models are predominantly pretrained on 2D image d…
VLA-Trace: Diagnosing Vision-Language-Action Models through Representation and Behavior Tracing
Haoyuan Shi, Xiancong Ren, Yingji Zhang +9
Understanding how Vision-Language-Action (VLA) models transform multimodal knowledge into embodied control remains an open challenge. We present VLA-Trace, a progressive diagnostic…
A2Eval: Agentic and Automated Evaluation for Embodied Brain
Shuai Zhang, Jiayu Hu, Zijie Chen +9
Current embodied VLM evaluation relies on static, expert-defined, manually annotated benchmarks that exhibit severe redundancy and coverage imbalance. This labor intensive paradigm…
TC-IDM: Grounding Video Generation for Executable Zero-shot Robot Motion
Weishi Mi, Yong Bao, Xiaowei Chi +7
The vision-language-action (VLA) paradigm has enabled powerful robotic control by leveraging vision-language models, but its reliance on large-scale, high-quality robot data limits…
Wow, wo, val! A Comprehensive Embodied World Model Evaluation Turing Test
Chun-Kai Fan, Xiaowei Chi, Xiaozhu Ju +18
As world models gain momentum in Embodied AI, an increasing number of works explore using video foundation models as predictive world models for downstream embodied tasks like 3D p…