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Public story · 2026-03-10 · source-backed
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. arXiv 2603.08221
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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...
Jim Fan's team preparing to launch NemoClaw — open-source platform for enterprise AI agents. Positions NVIDIA not just as hardware but as agent infrastructure competing with AWS AgentCore and Microsoft's offerings. Open-source approach differentiates from proprietary alternati...
First principled framework for selecting and orchestrating 200-200K skills via capability tree and DAG-based pipelines. Code released. Directly actionable for multi-skill agent systems. arXiv 2603.02176
Policy Compiler for Secure Agentic Systems introduces deterministic enforcement — a reference monitor intercepts all agent actions and blocks violations before execution. Compliance jumps from 48% to 93% across frontier models with zero violations in instrumented runs. Directl...
Single-digit microsecond startup vs hundreds of milliseconds for full Python. Filesystem, network, and env vars blocked by default. Directly solves "how do agents safely execute Python" without Docker. 6.3K stars. GitHub
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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