3 citations · 6 across the 14 of their papers we have counts for
15 papers
G0.5: One Autoregressive Stream for Robot Reasoning and Action
Yicheng Liu, Zibin Dong, Baijun Ye +24
The prevailing recipe for Vision-Language-Action (VLA) models couples a pretrained VLM with a separately trained flow-matching action expert. This makes the VLM a context encoder r…
Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models
Yifu Yuan, Yaoting Huang, Xianze Yao +20
We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied cognition, task planning, cor…
Fast-WAM: Do World Action Models Need Test-time Future Imagination?
Tianyuan Yuan, Zibin Dong, Yicheng Liu +1
World Action Models (WAMs) have emerged as a promising alternative to Vision-Language-Action (VLA) models for embodied control because they explicitly model how visual observations…
ActionCodec: What Makes for Good Action Tokenizers
Zibin Dong, Yicheng Liu, Shiduo Zhang +8
Vision-Language-Action (VLA) models leveraging the native autoregressive paradigm of Vision-Language Models (VLMs) have demonstrated superior instruction-following and training eff…
FASTer: Toward Efficient Autoregressive Vision Language Action Modeling via Neural Action Tokenization
Yicheng Liu, Shiduo Zhang, Zibin Dong +12
Autoregressive vision-language-action (VLA) models have recently demonstrated strong capabilities in robotic manipulation. However, their core process of action tokenization often…
Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation
Yifu Yuan, Haiqin Cui, Yaoting Huang +7
Generalization in embodied AI is hindered by the "seeing-to-doing gap," which stems from data scarcity and embodiment heterogeneity. To address this, we pioneer "pointing" as a uni…
Conditioning Matters: Training Diffusion Policies is Faster Than You Think
Zibin Dong, Yicheng Liu, Yinchuan Li +2
Diffusion policies have emerged as a mainstream paradigm for building vision-language-action (VLA) models. Although they demonstrate strong robot control capabilities, their traini…
EmbodiedMAE: A Unified 3D Multi-Modal Representation for Robot Manipulation
Zibin Dong, Fei Ni, Yifu Yuan +2
We present EmbodiedMAE, a unified 3D multi-modal representation for robot manipulation. Current approaches suffer from significant domain gaps between training datasets and robot m…
From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation
Yifu Yuan, Haiqin Cui, Yibin Chen +7
Achieving generalization in robotic manipulation remains a critical challenge, particularly for unseen scenarios and novel tasks. Current Vision-Language-Action (VLA) models, while…
MODULI: Unlocking Preference Generalization via Diffusion Models for Offline Multi-Objective Reinforcement Learning
Yifu Yuan, Zhenrui Zheng, Zibin Dong +1
Multi-objective Reinforcement Learning (MORL) seeks to develop policies that simultaneously optimize multiple conflicting objectives, but it requires extensive online interactions.…
CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making
Zibin Dong, Yifu Yuan, Jianye Hao +4
Leveraging the powerful generative capability of diffusion models (DMs) to build decision-making agents has achieved extensive success. However, there is still a demand for an easy…
A Method on Searching Better Activation Functions
Haoyuan Sun, Zihao Wu, Bo Xia +5
The success of artificial neural networks (ANNs) hinges greatly on the judicious selection of an activation function, introducing non-linearity into network and enabling them to mo…
Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
Yifu Yuan, Jianye Hao, Yi Ma +6
Reinforcement Learning with Human Feedback (RLHF) has received significant attention for performing tasks without the need for costly manual reward design by aligning human prefere…
DiffuserLite: Towards Real-time Diffusion Planning
Zibin Dong, Jianye Hao, Yifu Yuan +4
Diffusion planning has been recognized as an effective decision-making paradigm in various domains. The capability of generating high-quality long-horizon trajectories makes it a p…
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
Zibin Dong, Yifu Yuan, Jianye Hao +7
Aligning agent behaviors with diverse human preferences remains a challenging problem in reinforcement learning (RL), owing to the inherent abstractness and mutability of human pre…