UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution

UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution | Signal Canvas | ScienceToStartup

Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/ucan-unified-convolutional-attention-network-for-expansive-receptive-fields-in-lightweight-super-resolution

stale

Proof freshness: stale
Proof status: unverified
Display score: 3/10
Last proof check: 2026-04-02
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 0
Source count: 0
Coverage: 17%

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 ucan-unified-convolutional-attention-network-for-expansive-receptive-fields-in-lightweight-super-resolution | Route /signal-canvas/ucan-unified-convolutional-attention-network-for-expansive-receptive-fields-in-lightweight-super-resolution

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/ucan-unified-convolutional-attention-network-for-expansive-receptive-fields-in-lightweight-super-resolution

MCP example

{
  "tool": "search_signal_canvas",
  "arguments": {
    "mode": "paper",
    "paper_ref": "ucan-unified-convolutional-attention-network-for-expansive-receptive-fields-in-lightweight-super-resolution",
    "query_text": "Summarize UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution"
  }
}

source_context

{
  "surface": "signal_canvas",
  "mode": "paper",
  "query": "UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution",
  "normalized_query": "2603.11680",
  "route": "/signal-canvas/ucan-unified-convolutional-attention-network-for-expansive-receptive-fields-in-lightweight-super-resolution",
  "paper_ref": "ucan-unified-convolutional-attention-network-for-expansive-receptive-fields-in-lightweight-super-resolution",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Evidence Receipt

Route status: building

Claims: 0

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution

PDF: https://arxiv.org/pdf/2603.11680v1

Source count: Pending verification

Coverage: 17%

Last proof check: 2026-04-02T02:30:40.136Z

Signal Canvas receipt window

Not build-ready: UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution

/buildability/ucan-unified-convolutional-attention-network-for-expansive-receptive-fields-in-lightweight-super-resolution

Ignoreblocked

Subject: UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution

Verdict

Ignore

Verdict is Ignore because current viability and proof state do not clear the buildability gate.

UCAN: Unified Convolutional Attention Network for Expansive Receptive Fields in Lightweight Super-Resolution

Use Signal Canvas as the narrative proof surface

Use this Signal Canvas via API or MCP

Signal Canvas proof surface