3 citations · 4 across the 8 of their papers we have counts for
9 papers
PR-OPD: Privileged Representation On-policy Self-Distillation for Agentic Reinforcement Learning
Muyang Li, Jie Yang, Zhengyu Fang +5
Language-model agents are usually trained by reinforcement learning from one reward per episode, and privileged self-distillation enriches it by letting the same policy, given a sk…
EarthSpatialBench: Benchmarking Spatial Reasoning Capabilities of Multimodal LLMs on Earth Imagery
Zelin Xu, Yupu Zhang, Saugat Adhikari +6
Benchmarking spatial reasoning in multimodal large language models (MLLMs) has attracted growing interest in computer vision due to its importance for embodied AI and other agentic…
VNU-Bench: A Benchmarking Dataset for Multi-Source Multimodal News Video Understanding
Zibo Liu, Muyang Li, Zhe Jiang +1
News videos are carefully edited multimodal narratives that combine narration, visuals, and external quotations into coherent storylines. In recent years, there have been significa…
Spatio-temporal Multivariate Time Series Forecast with Chosen Variables
Zibo Liu, Zhe Jiang, Zelin Xu +5
Spatio-Temporal Multivariate time series Forecast (STMF) uses the time series of spatially distributed variables in a period of recent past to forecast their values in a period…
Accelerate Coastal Ocean Circulation Model with AI Surrogate
Zelin Xu, Jie Ren, Yupu Zhang +8
Nearly 900 million people live in low-lying coastal zones around the world and bear the brunt of impacts from more frequent and severe hurricanes and storm surges. Oceanographers s…
Multi-View Neural Differential Equations for Continuous-Time Stream Data in Long-Term Traffic Forecasting
Zibo Liu, Zhe Jiang, Shigang Chen
Long-term traffic flow forecasting plays a crucial role in intelligent transportation as it allows traffic managers to adjust their decisions in advance. However, the problem is ch…
Spatio-Temporal Partial Sensing Forecast for Long-term Traffic
Zibo Liu, Zhe Jiang, Zelin Xu +5
Traffic forecasting uses recent measurements by sensors installed at chosen locations to forecast the future road traffic. Existing work either assumes all locations are equipped w…
XTSFormer: Cross-Temporal-Scale Transformer for Irregular-Time Event Prediction in Clinical Applications
Tingsong Xiao, Zelin Xu, Wenchong He +8
Adverse clinical events related to unsafe care are among the top ten causes of death in the U.S. Accurate modeling and prediction of clinical events from electronic health records…
A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space
Wenchong He, Zhe Jiang, Tingsong Xiao +5
Transformers are widely used deep learning architectures. Existing transformers are mostly designed for sequences (texts or time series), images or videos, and graphs. This paper p…