Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Route this paper proof surface into REST, MCP, or developer workflows while preserving the same evidence receipt and related-resource context.
Page Freshness
Canonical route: /signal-canvas/tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning | Route /signal-canvas/tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learningMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning",
"query_text": "Summarize Tool-Aware Optimization with Entropy Guidance for Efficient Agentic Reinforcement Learning"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "Tool-Aware Optimization with Entropy Guidance for Efficient Agentic Reinforcement Learning",
"normalized_query": "2606.03762",
"route": "/signal-canvas/tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning",
"paper_ref": "tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: Tool-Aware Optimization with Entropy Guidance for Efficient Agentic Reinforcement Learning
PDF: https://arxiv.org/pdf/2606.03762v1
Repository: https://github.com/WhyNot22222/TAO-RL
Source count: 4
Coverage: 83%
Last proof check: 2026-06-03T20:32:57.998Z
Signal Canvas receipt window
/buildability/tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning
Subject: Tool-Aware Optimization with Entropy Guidance for Efficient Agentic Reinforcement Learning
Verdict
Preparing verified analysis
Dimensions overall score 7.0
{"file name": "input.pdf", "number of pages": 23, "author": "Hongye Cao; Nuo Yan; Haoyuan Deng; Ziwei Wang; Tianpei Yang; Jing Huo; Yuyao Zhang; Yang Gao"
Implication not extracted yet.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Build Now
Verdict is Build Now because viability and implementation proof cleared the Wave 1 scaffold thresholds.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Receipt path
/buildability/tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning
Paper ref
tool-aware-optimization-with-entropy-guidance-for-efficient-agentic-reinforcement-learning
arXiv id
2606.03762
Generated at
2026-06-03T20:32:57.998Z
Evidence freshness
fresh
Last verification
2026-06-03T20:32:57.998Z
Sources
4
References
0
Coverage
83%
Lineage hash
53a8218b6fa5e1241ef0a45175404998450846b1645a9101b6ec34cfc1e28f6b
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 4 sources / Verification pending
references