10 papers
Embodied Operators and Benchmarking: Toward Reusable and Deployable Embodied Intelligence Systems
Junwu Xiong, Jiaxuan Gao, Wei Chai +10
Embodied intelligence systems require not only end-to-end policy models, but also reusable functional modules that transform multimodal observations, robot states, human demonstrat…
Building a Scalable, Reproducible, Evaluatable, and Closed-Loop Simulation Environment Foundation for Embodied Intelligence
Junwu Xiong, Yongjian Guo, Mingxi Luo +17
This paper presents a cloud-native simulation infrastructure framework for embodied intelligence that supports large-scale training, standardized evaluation, and simulation-based d…
AdaptiveLoad: Towards Efficient Video Diffusion Transformer Training
Yucheng Guo, Yongjian Guo, Zhong Guan +6
In video generation models, particularly world models, training large-scale video diffusion Transformers (such as DiT and MMDiT) poses significant computational challenges due to t…
D-VLA: A High-Concurrency Distributed Asynchronous Reinforcement Learning Framework for Vision-Language-Action Models
Yucheng Guo, Yongjian Guo, Zhong Guan +9
The rapid evolution of Embodied AI has enabled Vision-Language-Action (VLA) models to excel in multimodal perception and task execution. However, applying Reinforcement Learning (R…
NoiseGate: Learning Per-Latent Timestep Schedules as Information Gating in World Action Models
Wen Huang, Haoran Sun, Yongjian Guo +8
World Action Models (WAMs) are an emerging family of policies that tie robot action generation to future-observation modeling. In this work, we focus on the joint video--action mod…
Thousand-GPU Large-Scale Training and Optimization Recipe for AI-Native Cloud Embodied Intelligence Infrastructure
Yongjian Guo, Yunxuan Ma, Haoran Sun +22
Embodied intelligence is a key step towards Artificial General Intelligence (AGI), yet its development faces multiple challenges including data, frameworks, infrastructure, and eva…
MergeDNA: Context-aware Genome Modeling with Dynamic Tokenization through Token Merging
Siyuan Li, Kai Yu, Anna Wang +7
Modeling genomic sequences faces two unsolved challenges: the information density varies widely across different regions, while there is no clearly defined minimum vocabulary unit.…
EnTao-GPM: DNA Foundation Model for Predicting the Germline Pathogenic Mutations
Zekai Lin, Haoran Sun, Yucheng Guo +8
Distinguishing pathogenic mutations from benign polymorphisms remains a critical challenge in precision medicine. EnTao-GPM, developed by Fudan University and BioMap, addresses thi…
TrinityDNA: A Bio-Inspired Foundational Model for Efficient Long-Sequence DNA Modeling
Qirong Yang, Yucheng Guo, Zicheng Liu +7
The modeling of genomic sequences presents unique challenges due to their length and structural complexity. Traditional sequence models struggle to capture long-range dependencies…
Life-Code: Central Dogma Modeling with Multi-Omics Sequence Unification
Zicheng Liu, Siyuan Li, Zhiyuan Chen +6
The interactions between DNA, RNA, and proteins are fundamental to biological processes, as illustrated by the central dogma of molecular biology. Although modern biological pre-tr…