Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Page Freshness
Canonical route: /signal-canvas/multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learning
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Canonical ID multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learning | Route /signal-canvas/multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learning
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learningMCP example
{
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"arguments": {
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"paper_ref": "multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learning",
"query_text": "Summarize Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning",
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"paper_ref": "multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learning",
"topic_slug": null,
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"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning
PDF: https://arxiv.org/pdf/2605.25210v1
Source count: 3
Coverage: 50%
Last proof check: 2026-05-27T01:09:05.063Z
Signal Canvas receipt window
/buildability/multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learning
Subject: Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning
Verdict
Ignore
Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Preparing verified analysis
Dimensions overall score 0.0
No public code linked for this paper yet.
{"file name": "input.pdf", "number of pages": 27, "author": "Ziheng Cheng; Yixiao Huang; Hanlin Zhu; Haoran Geng; Somayeh Sojoudi; Jitendra Malik; Pieter Abbeel; Xin Guo"
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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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/multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learning
Paper ref
multi-objective-learning-for-diffusion-models-a-statistical-theory-under-semi-supervised-learning
arXiv id
2605.25210
Generated at
2026-05-27T01:09:05.063Z
Evidence freshness
stale
Last verification
2026-05-27T01:09:05.063Z
Sources
3
References
0
Coverage
50%
Lineage hash
5122e305396478d5c7ba289355de1ac6b464bc7438887b5c68d6b2a03e4ded28
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 / 3 sources / Verification pending
repo_url
references