papers

Publications (8)

cs.CV2026

GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning

GigaBrain Team, Boyuan Wang, Bohan Li +23

Vision-language-action (VLA) models that directly predict multi-step action chunks from current observations face inherent limitations due to constrained scene understanding and we…

cs.CV2025

3D-MoRe: Unified Modal-Contextual Reasoning for Embodied Question Answering

Rongtao Xu, Han Gao, Mingming Yu +6

With the growing need for diverse and scalable data in indoor scene tasks, such as question answering and dense captioning, we propose 3D-MoRe, a novel paradigm designed to generat…

math.PR2014

Asymptotic distributions related to mildly-explosive second order autoregressive models

Hui Jiang, Mingming Yu, Guangyu Yang

In this paper, we consider the normalized least squares estimator of the parameter in a mildly-explosive first-order autoregressive model with dependent errors which are modeled as…

cs.RO2026

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

GigaWorld Team, Angen Ye, Angyuan Ma +26

The paper introduces GigaWorld-Policy-0.5, a robot control model that learns from future visual dynamics during training but generates actions only at inference, achieving faster (…

#robot control#world action models#action-conditioned world modeling#efficient inference
cs.RO2026

HMR-1: Hierarchical Massage Robot with Vision-Language-Model for Embodied Healthcare

Rongtao Xu, Mingming Yu, Xiaofeng Han +7

The rapid advancement of Embodied Intelligence has opened transformative opportunities in healthcare, particularly in physical therapy and rehabilitation. However, critical challen…

cs.RO2026

AtlasVLA: Persistent World-Ego State Modeling for Vision-Language-Action Models

Guiyu Zhao, Longteng Guo, Yanghong Mei +7

While Vision-Language-Action (VLA) models have advanced embodied AI, their fundamentally reactive paradigm severely limits performance in partially observable and long-horizon task…

math.PR2023

Moderate deviations for the mildly stationary autoregressive models with dependent errors

Hui Jiang, Guangyu Yang, Mingming Yu

In this paper, we consider the normalized least squares estimator of the parameter in a mildly stationary first-order autoregressive (AR(1)) model with dependent errors which are m…

cs.CV2023

Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning

Wenzhuo Liu, Xinjian Wu, Fei Zhu +3

Deep Neural Network (DNN) has achieved great success on datasets of closed class set. However, new classes, like new categories of social media topics, are continuously added to th…