Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence explores Agent-World is a self-evolving training arena that synthesizes realistic environments and tasks to co-evolve general-purpose AI agents, outperforming proprietary models on challenging benchmarks.. Commercial viability score: 8/10 in Agent Training.
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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/agent-world-scaling-real-world-environment-synthesis-for-evolving-general-agent-intelligence
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID agent-world-scaling-real-world-environment-synthesis-for-evolving-general-agent-intelligence | Route /paper/agent-world-scaling-real-world-environment-synthesis-for-evolving-general-agent-intelligence
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/agent-world-scaling-real-world-environment-synthesis-for-evolving-general-agent-intelligenceMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.18292"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence",
"normalized_query": "2604.18292",
"route": "/paper/agent-world-scaling-real-world-environment-synthesis-for-evolving-general-agent-intelligence",
"paper_ref": "agent-world-scaling-real-world-environment-synthesis-for-evolving-general-agent-intelligence",
"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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