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Found 8 papers, 5 papers with code
Network Formation and Dynamics Among Multi-LLMs
Social networks shape opinions, behaviors, and information dissemination in human societies.
Group Decision-Making among Privacy-Aware Agents
How can individuals exchange information to learn from each other despite their privacy needs and security concerns?
Leveraging Large Language Models for Collective Decision-Making
In various work contexts, such as meeting scheduling, collaborating, and project planning, collective decision-making is essential but often challenging due to diverse individual preferences, varying work focuses, and power dynamics among members.
Differentially Private Distributed Estimation and Learning
We show that the noise that minimizes the convergence time to the best estimates is the Laplace noise, with parameters corresponding to each agent's sensitivity to their signal and network characteristics.
GLINKX: A Scalable Unified Framework For Homophilous and Heterophilous Graphs
On the other hand, shallow (or node-level) models using ego features and adjacency embeddings work well in heterophilous graphs.
Core-periphery Models for Hypergraphs
Our inference algorithm is capable of learning embeddings that correspond to the reputation (rank) of a node within the hypergraph.
Sublinear Domination and Core-Periphery Networks
In this paper we devise a generative random network model with core-periphery properties whose core nodes act as sublinear dominators, that is, if the network has $n$ nodes, the core has size $o(n)$ and dominates the entire network.
Social and Information Networks
Truncated Log-concave Sampling with Reflective Hamiltonian Monte Carlo
We introduce Reflective Hamiltonian Monte Carlo (ReHMC), an HMC-based algorithm, to sample from a log-concave distribution restricted to a convex body.
