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Expand Up @@ -212,6 +212,8 @@ AI agents increasingly use external tools, plugins, and skills to interact with
- 📄 **[TrustAgent: Towards Safe and Trustworthy LLM-based Agents](https://arxiv.org/abs/2402.01586)** — Agent Constitution for safety-aware planning with pre/post-action inspection.
- 📄 **[Autoformalization of Agent Instructions into Policy-as-Code](https://arxiv.org/abs/2606.26649)** — Mondl et al., 2026. Uses an LLM generator-critic loop to automatically translate natural-language agent instructions and policy documents into formally enforceable Cedar policies, achieving broader coverage than hand-coded symbolic enforcement while avoiding the no-guarantees weakness of probabilistic guardrails on medical agent benchmarks.
- 📄 **[Governing Actions, Not Agents: Institutional Attestation as a Governance Model for Autonomous AI Systems](https://arxiv.org/abs/2606.26298)** — Salfeld-Nebgen et al., 2026. Formalizes an institutional governance model where an autonomous agent keeps full planning autonomy but must present independently attested evidence at the point of consequential, irreversible action (e.g., clinical prescribing, production deployment) rather than having its reasoning monitored.
- 📄 **[Monotonic Narrowing for Agent Authority](https://doi.org/10.5281/zenodo.18932404)** — Pidlisnyi, 2026. Models delegated agent authority as an element of a product lattice and delegation as a monotone map, so capability can only attenuate along a delegation chain, never amplify.
- 📄 **[Faceted Authority Attenuation](https://doi.org/10.5281/zenodo.19260073)** — Pidlisnyi, 2026. Extends monotonic narrowing to seven independent constraint dimensions (scope, spend, depth, time, reputation, values, reversibility) with per-dimension evaluation and structured denial at the failing dimension.
- 📄 **[A Deterministic Control Plane for LLM Coding Agents](https://arxiv.org/abs/2606.26924)** — Madatha, 2026. Proposes Rel(AI)Build, treating coding-agent definitions as a managed supply chain with content addressing, permission enforcement, and audit logging, arguing governance of the agent-config layer must be deterministic and tool-agnostic rather than delegated to further LLM orchestration.
- 📄 **[A Dual-Helix Governance Approach for Reliable Agentic AI](https://arxiv.org/abs/2603.04390)** — 3-track architecture (Knowledge, Behavior, Skills) using knowledge graphs.
- 📄 **[Talk Freely, Execute Strictly: Schema-Gated Agentic AI](https://arxiv.org/abs/2603.XXXXX)** — Schema-gated orchestration for trustworthy agent deployment in regulated domains.
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