3 papers
cs.LG2026
Understanding Truncated Positional Encodings for Graph Neural Networks
James Flora, Mitchell Black, Weng-Keen Wong +1
Positional encodings (PEs) enhance the power of graph neural networks (GNNs), both theoretically and empirically. Two of the most popular families of PEs - spectral (e.g., Laplacia…
cs.DS2026
Reconstructing Bounded Treelength Graphs with Linearithmic Shortest Path Distance Queries
Chirag Kaudan, Amir Nayyeri
We consider the following graph reconstruction problem: given an unweighted connected graph with visible vertex set and an oracle which takes two vertices $u,v \in…
cs.SE2025
A Privacy-Preserving Recommender for Filling Web Forms Using a Local Large Language Model
Amirreza Nayyeri, Abbas Rasoolzadegan
Web applications are increasingly used in critical domains such as education, finance, and e-commerce. This highlights the need to ensure their failure-free performance. One effect…