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/taming-momentum-rethinking-optimizer-states-through-low-rank-approximation
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 taming-momentum-rethinking-optimizer-states-through-low-rank-approximation | Route /signal-canvas/taming-momentum-rethinking-optimizer-states-through-low-rank-approximation
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/taming-momentum-rethinking-optimizer-states-through-low-rank-approximationMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "taming-momentum-rethinking-optimizer-states-through-low-rank-approximation",
"query_text": "Summarize Taming Momentum: Rethinking Optimizer States Through Low-Rank Approximation"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "Taming Momentum: Rethinking Optimizer States Through Low-Rank Approximation",
"normalized_query": "2602.24283",
"route": "/signal-canvas/taming-momentum-rethinking-optimizer-states-through-low-rank-approximation",
"paper_ref": "taming-momentum-rethinking-optimizer-states-through-low-rank-approximation",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 0
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: Taming Momentum: Rethinking Optimizer States Through Low-Rank Approximation
PDF: https://arxiv.org/pdf/2602.24283v1
Source count: Pending verification
Coverage: 33%
Last proof check: 2026-03-19T21:31:49.672Z
Signal Canvas receipt window
/buildability/taming-momentum-rethinking-optimizer-states-through-low-rank-approximation
Subject: Taming Momentum: Rethinking Optimizer States Through Low-Rank Approximation
Verdict
Watch
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
Preparing verified analysis
Dimensions overall score 8.0
No public code linked for this paper yet.
CLAIM MAP
No public claim map is available for this paper yet.
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Institute of Automation, Chinese Academy of Sciences
Zilei Wang
University of Science and Technology of China
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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/taming-momentum-rethinking-optimizer-states-through-low-rank-approximation
Paper ref
taming-momentum-rethinking-optimizer-states-through-low-rank-approximation
arXiv id
2602.24283
Generated at
2026-03-19T21:31:49.672Z
Evidence freshness
stale
Last verification
2026-03-19T21:31:49.672Z
Sources
0
References
0
Coverage
33%
Lineage hash
7bfa6c639171c236b2694d07fa892259764d1d2e298ddbbb121239fa4bac1a4d
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.
Verification pending / evidence receipt incomplete
repo_url
references