InternData-A1: Pioneering High-Fidelity Synthetic Data for Pre-training Generalist Policy
Fuente:
arXiv
Guardado en:
| Autores principales: | Tian, Yang, Yang, Yuyin, Xie, Yiman, Cai, Zetao, Shi, Xu, Gao, Ning, Liu, Hangxu, Jiang, Xuekun, Qiu, Zherui, Yuan, Feng, Li, Yaping, Wang, Ping, Cai, Junhao, Zeng, Jia, Dong, Hao, Pang, Jiangmiao |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Gripper Keypose and Object Pointflow as Interfaces for Bimanual Robotic Manipulation
por: Yang, Yuyin, et al.
Publicado: (2025)
por: Yang, Yuyin, et al.
Publicado: (2025)
UltraDexGrasp: Learning Universal Dexterous Grasping for Bimanual Robots with Synthetic Data
por: Yang, Sizhe, et al.
Publicado: (2026)
por: Yang, Sizhe, et al.
Publicado: (2026)
InternVLA-A1: Unifying Understanding, Generation and Action for Robotic Manipulation
por: Cai, Junhao, et al.
Publicado: (2026)
por: Cai, Junhao, et al.
Publicado: (2026)
InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy
por: Chen, Xinyi, et al.
Publicado: (2025)
por: Chen, Xinyi, et al.
Publicado: (2025)
SIM1: Physics-Aligned Simulator as Zero-Shot Data Scaler in Deformable Worlds
por: Zhou, Yunsong, et al.
Publicado: (2026)
por: Zhou, Yunsong, et al.
Publicado: (2026)
Nimbus: A Unified Embodied Synthetic Data Generation Framework
por: He, Zeyu, et al.
Publicado: (2026)
por: He, Zeyu, et al.
Publicado: (2026)
LoGoPlanner: Localization Grounded Navigation Policy with Metric-aware Visual Geometry
por: Peng, Jiaqi, et al.
Publicado: (2025)
por: Peng, Jiaqi, et al.
Publicado: (2025)
A Data-Centric Revisit of Pre-Trained Vision Models for Robot Learning
por: Wen, Xin, et al.
Publicado: (2025)
por: Wen, Xin, et al.
Publicado: (2025)
InternScenes: A Large-scale Simulatable Indoor Scene Dataset with Realistic Layouts
por: Zhong, Weipeng, et al.
Publicado: (2025)
por: Zhong, Weipeng, et al.
Publicado: (2025)
Pre-training on Synthetic Driving Data for Trajectory Prediction
por: Li, Yiheng, et al.
Publicado: (2023)
por: Li, Yiheng, et al.
Publicado: (2023)
Embodiment-Aware Generalist Specialist Distillation for Unified Humanoid Whole-Body Control
por: Peng, Quanquan, et al.
Publicado: (2026)
por: Peng, Quanquan, et al.
Publicado: (2026)
What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights
por: Wen, Xin, et al.
Publicado: (2024)
por: Wen, Xin, et al.
Publicado: (2024)
SampleMix: A Sample-wise Pre-training Data Mixing Strategey by Coordinating Data Quality and Diversity
por: Xi, Xiangyu, et al.
Publicado: (2025)
por: Xi, Xiangyu, et al.
Publicado: (2025)
Pre-training with Synthetic Data Helps Offline Reinforcement Learning
por: Wang, Zecheng, et al.
Publicado: (2023)
por: Wang, Zecheng, et al.
Publicado: (2023)
Scaling Speech-Text Pre-training with Synthetic Interleaved Data
por: Zeng, Aohan, et al.
Publicado: (2024)
por: Zeng, Aohan, et al.
Publicado: (2024)
LSAP: Rethinking Inversion Fidelity, Perception and Editability in GAN Latent Space
por: Zhao, Xuekun, et al.
Publicado: (2022)
por: Zhao, Xuekun, et al.
Publicado: (2022)
Learn or Recall? Revisiting Incremental Learning with Pre-trained Language Models
por: Zheng, Junhao, et al.
Publicado: (2023)
por: Zheng, Junhao, et al.
Publicado: (2023)
Synthesize-on-Graph: Knowledgeable Synthetic Data Generation for Continue Pre-training of Large Language Models
por: Ma, Shengjie, et al.
Publicado: (2025)
por: Ma, Shengjie, et al.
Publicado: (2025)
Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation
por: Han, Xiaoshen, et al.
Publicado: (2025)
por: Han, Xiaoshen, et al.
Publicado: (2025)
Event Camera Data Dense Pre-training
por: Yang, Yan, et al.
Publicado: (2023)
por: Yang, Yan, et al.
Publicado: (2023)
RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
por: Yang, Xuning, et al.
Publicado: (2026)
por: Yang, Xuning, et al.
Publicado: (2026)
One Step to Efficient Synthetic Data
por: Awan, Jordan, et al.
Publicado: (2020)
por: Awan, Jordan, et al.
Publicado: (2020)
Optical parametric free-electron--photon quantum interaction
por: Xie, Zetao, et al.
Publicado: (2025)
por: Xie, Zetao, et al.
Publicado: (2025)
Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training
por: Luo, Gen, et al.
Publicado: (2024)
por: Luo, Gen, et al.
Publicado: (2024)
GraspVLA: a Grasping Foundation Model Pre-trained on Billion-scale Synthetic Action Data
por: Deng, Shengliang, et al.
Publicado: (2025)
por: Deng, Shengliang, et al.
Publicado: (2025)
PRIME-DP: Pre-trained Integrated Model for Earthquake Data Processing
por: Yu, Ziye, et al.
Publicado: (2024)
por: Yu, Ziye, et al.
Publicado: (2024)
Toward Scalable and Efficient Visual Data Transmission in 6G Networks
por: Cai, Junhao, et al.
Publicado: (2024)
por: Cai, Junhao, et al.
Publicado: (2024)
PhysEDA: Physics-Aware Learning Framework for Efficient EDA With Manhattan Distance Decay
por: Yang, Zetao
Publicado: (2026)
por: Yang, Zetao
Publicado: (2026)
Inside the Black Box: Detecting Data Leakage in Pre-trained Language Encoders
por: Xin, Yuan, et al.
Publicado: (2024)
por: Xin, Yuan, et al.
Publicado: (2024)
Synthetic Data Matters: Re-training with Geo-typical Synthetic Labels for Building Detection
por: Song, Shuang, et al.
Publicado: (2025)
por: Song, Shuang, et al.
Publicado: (2025)
BERTtime Stories: Investigating the Role of Synthetic Story Data in Language Pre-training
por: Theodoropoulos, Nikitas, et al.
Publicado: (2024)
por: Theodoropoulos, Nikitas, et al.
Publicado: (2024)
Can Medical Vision-Language Pre-training Succeed with Purely Synthetic Data?
por: Liu, Che, et al.
Publicado: (2024)
por: Liu, Che, et al.
Publicado: (2024)
Revisiting Data Analysis with Pre-trained Foundation Models
por: Liang, Chen, et al.
Publicado: (2025)
por: Liang, Chen, et al.
Publicado: (2025)
DataMan: Data Manager for Pre-training Large Language Models
por: Peng, Ru, et al.
Publicado: (2025)
por: Peng, Ru, et al.
Publicado: (2025)
NavDP: Learning Sim-to-Real Navigation Diffusion Policy with Privileged Information Guidance
por: Cai, Wenzhe, et al.
Publicado: (2025)
por: Cai, Wenzhe, et al.
Publicado: (2025)
Benchmarking the Fidelity and Utility of Synthetic Relational Data
por: Hudovernik, Valter, et al.
Publicado: (2024)
por: Hudovernik, Valter, et al.
Publicado: (2024)
Scaling Generalist Data-Analytic Agents
por: Qiao, Shuofei, et al.
Publicado: (2025)
por: Qiao, Shuofei, et al.
Publicado: (2025)
Bridging Synthetic and Real Worlds for Pre-training Scene Text Detectors
por: Guan, Tongkun, et al.
Publicado: (2023)
por: Guan, Tongkun, et al.
Publicado: (2023)
GLID: Pre-training a Generalist Encoder-Decoder Vision Model
por: Liu, Jihao, et al.
Publicado: (2024)
por: Liu, Jihao, et al.
Publicado: (2024)
How to Set the Learning Rate for Large-Scale Pre-training?
por: Zhou, Yunhua, et al.
Publicado: (2026)
por: Zhou, Yunhua, et al.
Publicado: (2026)
Ejemplares similares
-
Gripper Keypose and Object Pointflow as Interfaces for Bimanual Robotic Manipulation
por: Yang, Yuyin, et al.
Publicado: (2025) -
UltraDexGrasp: Learning Universal Dexterous Grasping for Bimanual Robots with Synthetic Data
por: Yang, Sizhe, et al.
Publicado: (2026) -
InternVLA-A1: Unifying Understanding, Generation and Action for Robotic Manipulation
por: Cai, Junhao, et al.
Publicado: (2026) -
InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy
por: Chen, Xinyi, et al.
Publicado: (2025) -
SIM1: Physics-Aligned Simulator as Zero-Shot Data Scaler in Deformable Worlds
por: Zhou, Yunsong, et al.
Publicado: (2026)