Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Vision Transformer for Small-Size Datasets
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2112.13492.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:09:32.434252Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T22:40:43.122763Z
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 ec011436-9703-4faf-ae61-36b73a01b100 · inbound
CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge cites this paper.
CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge Vision Transformer for Small-Size Datasets
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:09:32.434252Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b464d33-8b4f-4436-ac47-0df59a554708 · inbound
DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer cites this paper.
DuoFormer: Leveraging Hierarchical Representations by Local and Global Attention Vision Transformer Vision Transformer for Small-Size Datasets
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:42:00.774613Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49581837-58a3-4d06-80b4-fb864cf09747 · inbound
Multimodal learning enables instant ionizing radiation alerts on unmodified mobile phones for real-world emergency response cites this paper.
Multimodal learning enables instant ionizing radiation alerts on unmodified mobile phones for real-world emergency response Vision Transformer for Small-Size Datasets
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T21:37:26.277881Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aeed180e-77d6-41d9-8f85-4a90dcdc669e · inbound
CoSwin: Convolution Enhanced Hierarchical Shifted Window Attention For Small-Scale Vision cites this paper.
CoSwin: Convolution Enhanced Hierarchical Shifted Window Attention For Small-Scale Vision Vision Transformer for Small-Size Datasets
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:58:22.062214Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f8bbdefb-9705-4d8a-90d4-fd70a2cb2d28 · inbound
CoUn: Empowering Machine Unlearning via Contrastive Learning cites this paper.
CoUn: Empowering Machine Unlearning via Contrastive Learning Vision Transformer for Small-Size Datasets
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T22:40:43.125538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e38ef1d9-e824-4fad-9f53-88320128651f · inbound
Optimal Attention Temperature Improves the Robustness of In-Context Learning under Distribution Shift in High Dimensions cites this paper.
Optimal Attention Temperature Improves the Robustness of In-Context Learning under Distribution Shift in High Dimensions Vision Transformer for Small-Size Datasets
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T01:50:38.555138Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 0e556de1-5949-4f0c-a265-cc48344fb6a7 · inbound
EPIR: An Efficient Patch Tokenization, Integration and Representation Framework for Micro-expression Recognition cites this paper.
EPIR: An Efficient Patch Tokenization, Integration and Representation Framework for Micro-expression Recognition Vision Transformer for Small-Size Datasets
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:41:00.344249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.