Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2207.05501.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T19:33:08.804743Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, 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
138
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 46d3185b-4bdc-4a68-950e-132df9a8a925 · inbound
Faster Segment Anything: Towards Lightweight SAM for Mobile Applications cites this paper.
Faster Segment Anything: Towards Lightweight SAM for Mobile Applications Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T22:41:43.523599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation e5eb6ccc-8c74-492c-b035-4c28345ed52e · inbound
EMOv2: Pushing 5M Vision Model Frontier cites this paper.
EMOv2: Pushing 5M Vision Model Frontier Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T19:33:08.804743Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c3ec414e-ab6b-41a9-9d2a-e64e0a12b782 · inbound
RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone cites this paper.
RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:28:55.483030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fdaa095-ca5e-4259-a662-9a9aba734c93 · inbound
Parallel Sequence Modeling via Generalized Spatial Propagation Network cites this paper.
Parallel Sequence Modeling via Generalized Spatial Propagation Network Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:16:43.629784Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f70342b7-0247-445e-a0e0-ef1df39084f1 · inbound
Illicit object detection in X-ray imaging using deep learning techniques: A comparative evaluation cites this paper.
Illicit object detection in X-ray imaging using deep learning techniques: A comparative evaluation Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:50:15.345499Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd415c8f-6075-4e97-98a1-95b276c6817a · inbound
Insights from Visual Cognition: Understanding Human Action Dynamics with Overall Glance and Refined Gaze Transformer cites this paper.
Insights from Visual Cognition: Understanding Human Action Dynamics with Overall Glance and Refined Gaze Transformer Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T05:26:01.540334Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 0294f178-87d3-4203-b401-6c003b59f8ad · inbound
ShellfishNet: A Domain-Specific Benchmark for Visual Recognition of Marine Molluscs cites this paper.
ShellfishNet: A Domain-Specific Benchmark for Visual Recognition of Marine Molluscs Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T04:40:58.274219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation eb90327f-2c86-40d9-ba6a-d13a9de3c97d · inbound
TextTeacher: What Can Language Teach About Images? cites this paper.
TextTeacher: What Can Language Teach About Images? Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T07:26:12.680735Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 2c0f9cbf-c362-4b18-a234-caeb4dc91e84 · inbound
Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders cites this paper.
Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios
Reference 54
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-28T19:32:35.294812Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.