9 citations · 16 across the 9 of their papers we have counts for
11 papers
Remembering What Matters for Long-Horizon Robotic World Models
Hao Wu, Tianyu Shao, Shengju Qian +10
Autoregressive robot video world models based on discrete visual tokens remain unreliable over long rollout horizons. Retaining the entire generated history does not necessarily im…
FutureWorlds: Learning Robotic World Models from Alternative Futures
Hao Wu, Shengju Qian, Weiyan Wang +5
Robotic world models predict action-conditioned future scenes, providing a foundation for understanding action outcomes. However, turning alternative predictions into useful learni…
RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models
Hao Wu, Yuqi Li, Yuan Gao +10
Existing robot video world models are typically trained with low-level objectives such as reconstruction and perceptual similarity, which are poorly aligned with the capabilities t…
PDA-LSTM: Knowledge-driven page data arrangement based on LSTM for LCM supression in QLC 3D NAND flash memories
Qianhui Li, Weiya Wang, Qianqi Zhao +7
Quarter level cell (QLC) 3D NAND flash memory is emerging as the predominant storage solution in the era of artificial intelligence. QLC 3D NAND flash stores 4 bit per cell to expa…
Spatiotemporal Forecasting as Planning: A Model-Based Reinforcement Learning Approach with Generative World Models
Hao Wu, Yuan Gao, Xingjian Shi +9
To address the dual challenges of inherent stochasticity and non-differentiable metrics in physical spatiotemporal forecasting, we propose Spatiotemporal Forecasting as Planning (S…
BeamVQ: Beam Search with Vector Quantization to Mitigate Data Scarcity in Physical Spatiotemporal Forecasting
Weiyan Wang, Xingjian Shi, Ruiqi Shu +10
In practice, physical spatiotemporal forecasting can suffer from data scarcity, because collecting large-scale data is non-trivial, especially for extreme events. Hence, we propose…
HunyuanVideo: A Systematic Framework For Large Video Generative Models
Weijie Kong, Qi Tian, Zijian Zhang +49
Recent advancements in video generation have significantly impacted daily life for both individuals and industries. However, the leading video generation models remain closed-sourc…
BeamVQ: Aligning Space-Time Forecasting Model via Self-training on Physics-aware Metrics
Hao Wu, Xingjian Shi, Ziyue Huang +6
Data-driven deep learning has emerged as the new paradigm to model complex physical space-time systems. These data-driven methods learn patterns by optimizing statistical metrics a…
Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
Zhimin Li, Jianwei Zhang, Qin Lin +42
We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transfo…
Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling
Shuaipeng Li, Penghao Zhao, Hailin Zhang +10
In current deep learning tasks, Adam style optimizers such as Adam, Adagrad, RMSProp, Adafactor, and Lion have been widely used as alternatives to SGD style optimizers. These optim…
Spatio-Temporal Fluid Dynamics Modeling via Physical-Awareness and Parameter Diffusion Guidance
Hao Wu, Fan Xu, Yifan Duan +6
This paper proposes a two-stage framework named ST-PAD for spatio-temporal fluid dynamics modeling in the field of earth sciences, aiming to achieve high-precision simulation and p…