CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignment

CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignment | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/cognitioncapturerpro-towards-high-fidelity-visual-decoding-from-eeg-meg-via-multi-modal-information-and-asymmetric-align

stale

Proof freshness: stale
Proof status: unverified
Display score: 8/10
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 cognitioncapturerpro-towards-high-fidelity-visual-decoding-from-eeg-meg-via-multi-modal-information-and-asymmetric-align | Route /signal-canvas/cognitioncapturerpro-towards-high-fidelity-visual-decoding-from-eeg-meg-via-multi-modal-information-and-asymmetric-align

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/cognitioncapturerpro-towards-high-fidelity-visual-decoding-from-eeg-meg-via-multi-modal-information-and-asymmetric-align

MCP example

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source_context

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Evidence Receipt

Route status: building

Claims: 8

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignment

PDF: https://arxiv.org/pdf/2603.12722v1

Source count: Pending verification

Coverage: 17%

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

Signal Canvas receipt window

Watch and verify: CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignment

/buildability/cognitioncapturerpro-towards-high-fidelity-visual-decoding-from-eeg-meg-via-multi-modal-information-and-asymmetric-align

Watchwatch

Subject: CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignment

Verdict

Preparing verified analysis

GitHub Code Pulse

No public code linked for this paper yet.

Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
By employing a simplified alignment module
Implicationpartial
Explicitly stated in the abstract as part of the methodology.
Verificationpartial
partial
Evidencepartial
and a pre-trained diffusion model
Implicationpartial
Explicitly stated in the abstract as part of the methodology.
Verificationpartial
partial
Evidencepartial
a fusion encoder for integrating shared representations.
Implicationpartial
Explicitly stated in the abstract as a core contribution.
Verificationpartial
partial
Evidencepartial
an uncertainty-weighted similarity scoring mechanism to quantify modality-specific fidelity
Implicationpartial
Explicitly stated in the abstract as a core contribution.
Verificationpartial
partial
Evidencepartial
integrates EEG with multi-modal priors (images, text, depth, and edges) via collaborative training.
Implicationpartial
Explicitly stated in the abstract as a core component of the framework.
Verificationpartial
partial
Evidencepartial
our method significantly outperforms the original CognitionCapturer on the THINGS-EEG dataset
Implicationpartial
Directly stated in the abstract with specific performance improvements.
Verificationpartial
partial
Evidencepartial
improving Top-1 and Top-5 retrieval accuracy by 25.9% and 10.6%, respectively.
Implicationpartial
Specific numerical result directly stated in the abstract.
Verificationpartial
partial
Evidencepartial
improving Top-1 and Top-5 retrieval accuracy by 25.9% and 10.6%, respectively.
Implicationpartial
Specific numerical result directly stated in the abstract.
Verificationpartial
partial

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CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignment

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