A constraint-first run-time that compiles every agent action, whether a tool call, a retrieval, a semantic operator, or a final recommendation, into a constrained, provenance-tracked query plan is sketched, and the open questions it raises for the data-management community are outlined.
This manuscript reports the system design, verified capability boundary, deterministic software artifacts, and a reproducible evaluation protocol for BloClaw, an AI4S workstation built around a simple principle: a scientific agent should know what it can do, show how it did it, and state what remains unvalidated.
Yao Qin, Jin-Hua Pang, Xiao-Ming Zhang· bioRxiv· 0 citations
Tool-using AI agents can invoke internal APIs, retrieve documents, update records, and coordinate enterprise workflows. These capabilities create a runtime security problem: an agent may select an unauthorized tool, hallucinate an endpoint, follow malicious instructions embedded in retrieved context, rely on poisoned m...
Swapneswar Ray· International Journal of Glo...· 0 citations
The results show that MetaPermit produces 31% more consistent authorization decisions than LLM-driven authorization and outperforms the state-of-the-art defenses CaMeL and IPIGuard in both task completion and robustness to IPI attacks, with no malicious tool calls executed.
Han-Zhang Ma, Alicia Y. Hariri, Tian-Xiang Shen et al.· 0 citations
Praxist is introduced, a lineage-centered generational system that converts reproducible artifacts and evaluator outcomes into a typed evidence graph of findings, lane-structured frontiers, and agendas, and Separating local artifact construction from cohort-level evidence synthesis lets later attempts inherit validated...
Jin Li, Ahmed Murtadha, Zhiying Wang et al.· 0 citations
RADAR is an auditable runtime that makes an agent's analytical choices inspectable and supports their revision through execution feedback and rejects the operation or provides diagnostic feedback, allowing the agent to revise its choices before errors propagate.
Han-Xu Yan, Lang-Xuan Deng, Zheng-Le Wang et al.· 0 citations
LLM agents can produce harmful effects through sequences of ordinary operations. Judging such actions requires establishing both the authority that permits them and the origin of the data they carry. We present AGATE, an authorization and data-provenance gate at instrumented agent-harness boundaries. Operator declarati...
Xiao-Ru Zhang, Zhuo-Ran Cheng, Kai-Lin Liu et al.· 0 citations
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