3 papers
cs.LG2026
Scaffold: Support Graph Theory Based Sparsification for Graph Neural Networks
Siddhartha Shankar Das, Sai Karthik Navuluru, S M Ferdous +7
Graph neural networks (GNNs) rely on message passing over graph edges, making their computational and memory costs strongly dependent on graph density. Graph sparsification offers…
cs.AI2026
Networked Intelligence: Active Shared Context Graphs for Human-AI Team Science
Sutanay Choudhury, Jeffrey J. Czajka, Lummy M. O. Monteiro +15
Most AI-for-science systems focus on scaling a single reasoning process by using better models, larger context windows, long-horizon agentic execution, or digital co-scientists wor…
cs.CL2026
A Cloud-based Multi-Agentic Workflow for Science
Anurag Acharya, Timothy Vega, Rizwan A. Ashraf +3
As Large Language Models (LLMs) become ubiquitous across various scientific domains, their lack of ability to perform complex tasks like running simulations or to make complex deci…