arXiv (All)
open access
An Evidence Model for Agentic Processes: Evidence Claims, Trust Assumptions, and Policy Assessment
Agentic AI systems increasingly exchange messages, invoke tools, request approvals, hold structured decision sessions, and modify shared artifacts. Logs and anchors can make selected records tamper-evident, but they can also mislead if their evidentiary meaning is implicit: a hash does not establish
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Agentic AI in Data Commons and GLAM: What Role for the Model Context Protocol?#459204
- An Ethical Code for AI Model Lifecycle Decisions#165327
- From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agents#998246
- CrossAudit: A Git-Native, Cross-Vendor Audit Loop for Agentic Science#792882
- CrossAudit: A Git-Native, Cross-Vendor Audit Loop for Agentic Science#788878
Record · ID 985833
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive