Yifan Zhang

SAR2LiDAR: A deep learning-based cross-modal matching framework between SAR images and LiDAR point clouds

Yifan Zhang, J. Mallorquí, Wen Wang

Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning

Jian Hu, Huiying Li, Hao Zhang, Binfeng Xu, Yifan Zhang, Shaokun Zhang, et al.

Agentic reinforcement learning research is constant algorithm modification, new estimators, new pipeline stages, new rollout schemes, and in mainstream frameworks each change threads through layers of trainer, distributed backend, and rollout glue: the cost lands on the researche…Read more

DeepLoop: Depth Scaling for Looped Transformers

Shuzhen Li, Yifan Zhang, Jiacheng Guo, Quanquan Gu, Mengdi Wang

Looped Transformers scale sequential computation by applying a compact stack of physical blocks for multiple rounds, increasing unrolled depth without increasing stored parameters. This reuse changes the residual-scaling problem: in an untied Transformer, each residual branch rec…Read more

UASPL: Uncertainty-Aware Self-Paced Learning with Evidential Neural Networks

Yifan Zhang, Yuxin Hu, Zhuobin Hao, Xiaozhuan Gao, Lipeng Pan

Self-paced learning (SPL) is an effective learning paradigm that simulates the human learning process by progressing from easy to difficult samples based on the value of the loss function during the learning process. It has shown great potential in improving model performance and…Read more

SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation

Zhengbo Jiao, Yiming Cheng, Yilei Jiang, Kaituo Feng, Rui Huang, Tianyi Jiang, et al.

Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines construct training data, search environments, and reward signals independently, causing synthesized structural metadata to be discar…Read more

Extreme Adaptive Transformer for Time Series Forecasting

Sanjeev Shrestha, Hui Liu, Yifan Zhang

Time series forecasting remains challenging when the underlying data contain rare but critical extreme events. This issue is particularly important in hydrologic forecasting, where streamflow distributions are often highly skewed and extreme peaks can have substantial impacts on…Read more

HieDG: A Hierarchical Discrete Geometry-Guided Framework for Multi-Animal Tracking

Chenxun Deng, Zhongde Zhang, Ye Yuan, Chengyang Zhang, Yifan Zhang, Bohao Chen, et al.

Multi-animal tracking (MAT) is critical for wildlife monitoring and behavioral analysis, yet remains challenging due to uniform appearance, high density, and irregular motion. Existing methods typically follow heuristic- or query-based paradigms: the former relies on handcrafted…Read more