Author

Jin-Xi Yu

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#artificial intelligence Preprint Sep 2026

Privacy-Preserving Topology-Guided Safety for LLM-Based Multi-Agent Systems via Federated Graph Learning

Topology-guided safeguards for LLM-based multi-agent systems (MAS) train a GNN over the inter-agent communication graph to localize risky agents and intervene on the topology---but they assume one operator can pool all labeled traces. Across organizations that assumption breaks: episodes contain private prompts, tool o...

Jin-Xi Yu, Eric Jiang, Levina Li et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Codebook Agent: Amortized Topology Design for LLM Multi-Agent Systems

Codebook Agent is the most accurate method on all six benchmarks the authors compare, and an MLP proxy that reads the flattened adjacency, regressed on measured utility and per-task normalized token cost, reranks the top decoded candidates in a single batched forward pass.

Jin-Xi Yu, Yubei Li, Eric Jiang et al. · 1 citation

Jul 2026

RUBRIC: Realism-Utility Balanced Ranking for Imbalanced Classification

This work introduces RUBRIC, a generator-agnostic filtering framework that formulates synthetic sample selection as a quality-over-quantity optimization problem and shows that RUBRIC improves F1-macro and recall while maintaining comparable ROC-AUC across several generators.

Yan-Xuan Yu, Dong Liu, Shu Wang et al. · arXiv.org · 1 citation