Paper Citation Record · LEDGER

MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2209.15159.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2209.15159 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:03:10.894323Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T14:28:31.423884Z

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 b267acd9-40c0-47ef-ac0e-f47ef4c1d4aa · inbound

Geo-RepNet: Geometry-Aware Representation Learning for Surgical Phase Recognition in Endoscopic Submucosal Dissection cites this paper.

Geo-RepNet: Geometry-Aware Representation Learning for Surgical Phase Recognition in Endoscopic Submucosal Dissection MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T18:03:10.894323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37362bec-78a8-4af0-aa91-394fc35d1a7c · inbound

Exploring Superposition and Interference in State-of-the-Art Low-Parameter Vision Models cites this paper.

Exploring Superposition and Interference in State-of-the-Art Low-Parameter Vision Models MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T15:28:08.948462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1e03874-7f7e-4d6c-8392-85880a73af37 · inbound

TransLPRNet: Lite Vision-Language Network for Single/Dual-line Chinese License Plate Recognition cites this paper.

TransLPRNet: Lite Vision-Language Network for Single/Dual-line Chinese License Plate Recognition MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T14:58:59.305380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e23693a0-b095-40a5-96cb-67e4ec258d19 · inbound

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications cites this paper.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T13:10:19.586800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c94871be-7c59-4075-b0db-9628c3612609 · inbound

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms cites this paper.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T05:44:19.893331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b6abaaf-97f9-43ef-ac7d-e1f9896a27ee · inbound

MR2-ByteTrack: CNN and Transformer-based Video Object Detection for AI-augmented Embedded Vision Sensor Nodes cites this paper.

MR2-ByteTrack: CNN and Transformer-based Video Object Detection for AI-augmented Embedded Vision Sensor Nodes MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-19T15:27:38.873687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e9962085-922c-49a2-a201-4c7e9026b734 · inbound

Towards Effective Waste Segmentation for Automated Waste Recycling in Cluttered Background cites this paper.

Towards Effective Waste Segmentation for Automated Waste Recycling in Cluttered Background MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:28:31.425289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.