Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2302.03751.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T14:36:42.198139Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T22:37:26.278082Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 5c8bdd71-b7c8-4df0-b2cc-c02e959a4f86 · inbound
Self-Supervised Ultrasound-Video Segmentation with Feature Prediction and 3D Localised Loss cites this paper.
Self-Supervised Ultrasound-Video Segmentation with Feature Prediction and 3D Localised Loss Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:36:42.198139Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5bfcb139-975c-4df1-9cbb-fd2622743dab · inbound
Efficient optimization of expensive black-box simulators via marginal means, with application to neutrino detector design cites this paper.
Efficient optimization of expensive black-box simulators via marginal means, with application to neutrino detector design Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:23:21.146510Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 58fbf54d-627f-47d1-8f04-6ab2f6953bc8 · inbound
eMamba: Efficient Acceleration Framework for Mamba Models in Edge Computing cites this paper.
eMamba: Efficient Acceleration Framework for Mamba Models in Edge Computing Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T20:34:29.764331Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0158103e-9795-4759-885f-5fbc015ae4a9 · inbound
Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients cites this paper.
Warming Up for Zeroth-Order Federated Pre-Training with Low Resource Clients Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T10:59:57.055832Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f820ee77-c09f-4bf2-9df2-63db6c2e5b9e · inbound
Forward-Only Convolutional Neural Networks with Learnable Channel-Class Assignment cites this paper.
Forward-Only Convolutional Neural Networks with Learnable Channel-Class Assignment Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T22:37:26.279645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.