Paper Citation Record · LEDGER

Convolutional Bypasses Are Better Vision Transformer Adapters

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2207.07039.

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

pith.paper-citation-record.v1
2207.07039 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:05:45.976626Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:59:42.703372Z

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 c4be781a-2181-4426-81b2-75cf77a3ef2a · inbound

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 195

Resolution: verified exact; arxiv_id, observed 2026-05-13T11:32:36.955521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1f2d40bf-8add-4c7d-90a0-202392b1e747 · inbound

EDTformer: An Efficient Decoder Transformer for Visual Place Recognition cites this paper.

EDTformer: An Efficient Decoder Transformer for Visual Place Recognition Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T05:05:45.976626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c044a19d-cbbc-4095-a327-76a980e29120 · inbound

When Vision Models Meet Parameter Efficient Look-Aside Adapters Without Large-Scale Audio Pretraining cites this paper.

When Vision Models Meet Parameter Efficient Look-Aside Adapters Without Large-Scale Audio Pretraining Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T20:14:04.647561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ddd6518-31eb-4b6c-85f5-4f17e3ecad79 · inbound

PETALface: Parameter Efficient Transfer Learning for Low-resolution Face Recognition cites this paper.

PETALface: Parameter Efficient Transfer Learning for Low-resolution Face Recognition Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T18:34:29.112740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dca5d446-25ce-42b7-b254-e312ea94abd1 · inbound

ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Experts cites this paper.

ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Experts Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T17:59:15.590307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1cdc2c8-2fc7-4235-bc64-cf09e5577bac · inbound

PromptDet: A Lightweight 3D Object Detection Framework with LiDAR Prompts cites this paper.

PromptDet: A Lightweight 3D Object Detection Framework with LiDAR Prompts Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T14:08:13.970909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b36e0d65-08c1-47e3-a38a-21eb5a9e9eed · inbound

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning cites this paper.

Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T06:02:33.274732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2024713c-f452-4337-99b6-542b9f6833a5 · inbound

Parameter-Efficient Fine-Tuning for Foundation Models cites this paper.

Parameter-Efficient Fine-Tuning for Foundation Models Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T15:38:03.030987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e18d49c-8957-4489-afbf-810c37012e44 · inbound

Weight Spectra Induced Efficient Model Adaptation cites this paper.

Weight Spectra Induced Efficient Model Adaptation Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:56.874725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 967c7d6c-dad3-4300-b192-e839dd0a1f87 · inbound

ViT-Split: Unleashing the Power of Vision Foundation Models via Efficient Splitting Heads cites this paper.

ViT-Split: Unleashing the Power of Vision Foundation Models via Efficient Splitting Heads Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T11:09:29.789945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d2fd441-00c0-457b-a91c-30b862c6541f · inbound

AI-driven Remote Facial Skin Hydration and TEWL Assessment from Selfie Images: A Systematic Solution cites this paper.

AI-driven Remote Facial Skin Hydration and TEWL Assessment from Selfie Images: A Systematic Solution Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T23:55:38.882836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d109a66-0c78-4021-9de9-f58ddfda86b0 · inbound

BGG: Bridging the Geometric Gap between Cross-View images by Vision Foundation Model Adaptation for Geo-Localization cites this paper.

BGG: Bridging the Geometric Gap between Cross-View images by Vision Foundation Model Adaptation for Geo-Localization Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:46:29.937349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9c41c4c4-1f1d-4e85-997e-8f51433a8230 · inbound

Structured Hyperedge Adaptation for Parameter-Efficient Fine-Tuning of Vision Transformers cites this paper.

Structured Hyperedge Adaptation for Parameter-Efficient Fine-Tuning of Vision Transformers Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T08:59:42.704885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 190fca79-4ad6-426b-9dc7-5cc1bac6f579 · inbound

DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images cites this paper.

DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:27:04.719655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c9453281-3e0e-4459-ad74-0d3e38808c62 · inbound

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family cites this paper.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T15:46:57.533891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.