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Supervised fine-tuning (SFT) on offline agent trajectories is the standard approach for training specialized tool-using agents, but forcing models to imitate reasoning and actions token by token may harm other capabilities (e.g., general reasoning, tool calling, code generation) of the base model. In this work, we focu...
AID, Automated IPI Detection, a data-driven system that continuously logs unauthorized access and suspicious behaviors on smartphones is presented, demonstrating AID's potential as an evidence-support tool that complements current clinic-based interpretation and safety-planning.
Three research directions for automating the production of shareable intelligence are derived from a literature survey of academic papers, organizing the CTI lifecycle into three stages: Threat Data Collection, CTI Generation and Sharing, and CTI Consumption.
DeePCAP introduces a query-driven fidelity framework spanning packet- and flow-level queries to tackle the fidelity disconnection, and proposes a novel dimensionality reduction approach using frequency domain encoding to improve cost-fidelity trade-off.
TabQueryBench is a query-centric benchmark that uses SQL-shaped analytical queries as structural assessors for synthetic data fidelity, and provides an extensible foundation for query-centric synthetic-data evaluation.
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