An Intelligent Hybrid Cross-Entropy System for Maximising Network Homophily via Soft Happy Colouring
2026-03-13T08:52:21Z•82ef30338ea7ec2de28e7d6360760634a756b73ff98a3f82bd78ba8038a748d2
causal-inferencecentralitycommunity-detectioncryptocurrency-kolsde-anonymizationinfluence-operationsllmmisinformationnetwork-analysispolitical-inferenceprivacysocial-mediastochastic-block-modeltrust-modellinguncertainty-quantification
What happened
This collection of arXiv CS/SI papers (Mar 13 2026) covers advances in network analysis, causal selection, misinformation measurement, trust modeling, and privacy risks from LLMs. Key security-relevant findings: a new hybrid Cross-Entropy + local search algorithm (CE+LS) for maximising homophily in graphs and several community-detection improvements (Ricci reweighting) that improve spectral clustering; formalization and scalable algorithms (CauMax) for selecting source groups to maximize causal effects under cross-group interference; an uncertainty-aware framework for estimating mis/disinfopre
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_si
- Record identifier
- 82ef30338ea7ec2de28e7d6360760634a756b73ff98a3f82bd78ba8038a748d2
- Enrichment time
- 2026-03-13T08:52:21Z
- AI-assisted enrichment
- Yes
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