4 papers
DAGverse: Building Document-Grounded Semantic DAGs from Scientific Papers
Shu Wan, Saketh Vishnubhatla, Iskander Kushbay +4
Directed Acyclic Graphs (DAGs) are widely used to represent structured knowledge in scientific and technical domains. However, datasets for real-world DAGs remain scarce because co…
Causality Guided Representation Learning for Cross-Style Hate Speech Detection
Chengshuai Zhao, Shu Wan, Paras Sheth +3
The proliferation of online hate speech poses a significant threat to the harmony of the web. While explicit hate is easily recognized through overt slurs, implicit hate speech is…
CauSTream: Causal Spatio-Temporal Representation Learning for Streamflow Forecasting
Shu Wan, Reepal Shah, John Sabo +2
Streamflow forecasting is crucial for water resource management and risk mitigation. While deep learning models have achieved strong predictive performance, they often overlook und…
Spatio-temporal Causal Learning for Streamflow Forecasting
Shu Wan, Reepal Shah, Qi Deng +3
Streamflow plays an essential role in the sustainable planning and management of national water resources. Traditional hydrologic modeling approaches simulate streamflow by establi…