Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2101.12037.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T22:45:38.974210Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
0
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 73f56067-558d-4379-9aaf-05158a3cb4db · inbound
MC2SleepNet: Multi-modal Cross-masking with Contrastive Learning for Sleep Stage Classification cites this paper.
MC2SleepNet: Multi-modal Cross-masking with Contrastive Learning for Sleep Stage Classification BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T22:45:38.974210Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9780fed-ca2f-4979-b2e5-8dfde624d75e · inbound
STST-JEPA: Shallow-Target Spatio-Temporal Joint Embedding Prediction Architecture For EEG Self-Supervised Learning cites this paper.
STST-JEPA: Shallow-Target Spatio-Temporal Joint Embedding Prediction Architecture For EEG Self-Supervised Learning BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-07-11T01:07:41.817689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.