Content embeddings from SBERT enable AUROC above 0.89 for attack detection in MCP tool-call sessions, with tree ensembles on pooled embeddings reaching 0.975 and outperforming GNNs when using task-stratified splits instead of random ones.
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GA-S2S integrates T5 with RGAT to jointly process text and k-hop subgraph topology for knowledge graph link prediction, reporting up to 19% relative accuracy gain over seq2seq baselines on CoDEx.
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Content-Aware Attack Detection in LLM Agent Tool-Call Traffic: An Empirical Study of Features, Architectures, and Evaluation Protocols
Content embeddings from SBERT enable AUROC above 0.89 for attack detection in MCP tool-call sessions, with tree ensembles on pooled embeddings reaching 0.975 and outperforming GNNs when using task-stratified splits instead of random ones.
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Leveraging Graph Structure in Seq2Seq Models for Knowledge Graph Link Prediction
GA-S2S integrates T5 with RGAT to jointly process text and k-hop subgraph topology for knowledge graph link prediction, reporting up to 19% relative accuracy gain over seq2seq baselines on CoDEx.