5 citations · 12 across the 10 of their papers we have counts for
10 papers
From Causal Plausibility to Causal Reliability: Evaluating LLMs as Calibrated Direct Causal-Edge Classifiers
Amit Kumar, Elnur Adl Zarabi, Suranjana Trivedy +4
Large language models (LLMs) are increasingly used to provide prior causal knowledge for structural causal discovery, yet whether their direct-edge judgments and confidence can be…
MasterSet: A Large-Scale Benchmark for Must-Cite Citation Recommendation in the AI/ML Literature
Md Toyaha Rahman Ratul, Zhiqian Chen, Kaiqun Fu +2
The explosive growth of AI and machine learning literature -- with venues like NeurIPS and ICLR now accepting thousands of papers annually -- has made comprehensive citation covera…
Network Interdiction Goes Neural
Lei Zhang, Zhiqian Chen, Chang-Tien Lu +1
Network interdiction problems are combinatorial optimization problems involving two players: one aims to solve an optimization problem on a network, while the other seeks to modify…
XFlow: Benchmarking Flow Behaviors over Graphs
Zijian Zhang, Zonghan Zhang, Zhiqian Chen
The occurrence of diffusion on a graph is a prevalent and significant phenomenon, as evidenced by the spread of rumors, influenza-like viruses, smart grid failures, and similar eve…
Memetic algorithms for Spatial Partitioning problems
Subhodip Biswas, Fanglan Chen, Zhiqian Chen +2
Spatial optimization problems (SOPs) are characterized by spatial relationships governing the decision variables, objectives, and/or constraint functions. In this article, we focus…
Demystifying Graph Convolution with a Simple Concatenation
Zhiqian Chen, Zonghan Zhang
Graph convolution (GConv) is a widely used technique that has been demonstrated to be extremely effective for graph learning applications, most notably node categorization. On the…
Understanding Influence Maximization via Higher-Order Decomposition
Zonghan Zhang, Zhiqian Chen
Given its vast application on online social networks, Influence Maximization (IM) has garnered considerable attention over the last couple of decades. Due to the intricacy of IM, m…
Sampling-based techniques for designing school boundaries
Subhodip Biswas, Fanglan Chen, Zhiqian Chen +2
Recently, an increasing number of researchers, especially in the realm of political redistricting, have proposed sampling-based techniques to generate a subset of plans from the va…
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information
Padmaksha Roy, Shailik Sarkar, Subhodip Biswas +4
Modeling the spatiotemporal nature of the spread of infectious diseases can provide useful intuition in understanding the time-varying aspect of the disease spread and the underlyi…
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Zhiqian Chen, Fanglan Chen, Lei Zhang +7
Deep learning's performance has been extensively recognized recently. Graph neural networks (GNNs) are designed to deal with graph-structural data that classical deep learning does…