Four-Axis Decision Alignment for Long-Horizon Enterprise AI Agents explores A novel four-axis framework for evaluating enterprise AI agents, measuring factual precision, reasoning coherence, compliance reconstruction, and calibrated abstention to ensure alignment with regulatory and decisional standards.. Commercial viability score: 8/10 in Agents.
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This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Page Freshness
Canonical route: /paper/four-axis-decision-alignment-for-long-horizon-enterprise-ai-agents
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID four-axis-decision-alignment-for-long-horizon-enterprise-ai-agents | Route /paper/four-axis-decision-alignment-for-long-horizon-enterprise-ai-agents
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/four-axis-decision-alignment-for-long-horizon-enterprise-ai-agentsMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.19457"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "Four-Axis Decision Alignment for Long-Horizon Enterprise AI Agents",
"normalized_query": "2604.19457",
"route": "/paper/four-axis-decision-alignment-for-long-horizon-enterprise-ai-agents",
"paper_ref": "four-axis-decision-alignment-for-long-horizon-enterprise-ai-agents",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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Dimensions overall score 8.0
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