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Public story · 2026-02-27 · source-backed
Introduces temporal causal diagnostics to distinguish legitimate task execution from injected manipulation in multi-turn agent interactions, plus context purification to neutralize poisoned content. Directly applicable to anyone building agents that call external tools. arXiv 2602.22724
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First defense modeling multi-turn indirect prompt injection as temporal causal takeover. Uses counterfactual re-executions at tool-return boundaries to detect when tool outputs steer agent behavior. Evaluated on AgentDojo across four task suites. Builder-ready pattern for tool...
arXiv 2607.08010 replaces the inference-time coding loop with a pipeline that collects execution traces, observes live backend schemas and values, synthesizes candidate tools, and repairs them against labeled cases. Runtime calls the compiled tool instead of re-deriving it. Th...
Addresses the fundamental privacy dilemma: cloud models need data access but enterprises can't share sensitive information. Splits execution between enterprise-side privacy agents and cloud-side capability agents. Directly relevant to AWS AgentCore and enterprise adoption. arX...
Models multi-hop agent reasoning as a dynamic search tree, transitioning from exploration to exploitation as token budget depletes. Includes formal convergence proof. Directly applicable to any agent loop burning tokens on redundant calls. arXiv 2603.12634
arXiv 2608.05604 names the mismatch precisely: current systems retrieve skills as packages but compress them as prose, which destroys the execution contract. SkillZip does contract-preserving compression over section-level graphs, rewriting recurring valid motifs into reversib...
CAM-DF reframes tool acquisition as a stopping problem, training on the offline gap between stopping now and the best continuation, using the sign to label the decision and the magnitude to weight each error by payoff at stake. Across five domains and 1,343 tasks: 37% fewer to...
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