Paper Citation Record · LEDGER

E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2307.13770.

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

pith.paper-citation-record.v1
2307.13770 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:03:48.836848Z

measured 1 of 1 external citation measurements

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

10
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 77a4a302-746c-4f4a-b635-0e337b623cec · inbound

DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformers cites this paper.

DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformers E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:43:55.265616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 648900b7-6414-47fd-a963-7f0abcdc65d5 · inbound

Visual Instance-aware Prompt Tuning cites this paper.

Visual Instance-aware Prompt Tuning E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T18:37:35.229492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5150e9b7-143c-4500-82cb-3923394dd43f · inbound

Visual prompting reimagined: The power of the Activation Prompts cites this paper.

Visual prompting reimagined: The power of the Activation Prompts E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:45:53.883032Z

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.

Observation 2bc504f4-aa6b-49e2-bb2d-e946d3ca3ad4 · inbound

MNAFT: modality neuron-aware fine-tuning of multimodal large language models for image translation cites this paper.

MNAFT: modality neuron-aware fine-tuning of multimodal large language models for image translation E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:23:37.452774Z

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.

Observation 563825e5-841f-4272-a261-2725d5a0bb28 · inbound

Compared to What? Baselines and Metrics for Counterfactual Prompting cites this paper.

Compared to What? Baselines and Metrics for Counterfactual Prompting E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-09T19:05:10.455666Z

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.

Observation 10920560-a95b-4911-897a-c43864d1ac1f · inbound

Exposing Functional Fusion: A New Class of Strategic Backdoor in Dynamic Prompt Architectures cites this paper.

Exposing Functional Fusion: A New Class of Strategic Backdoor in Dynamic Prompt Architectures E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-20T04:53:05.106920Z

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.

Observation a71bad50-c6a4-4139-a28f-76d034784a70 · inbound

Timage: A Generative Text-in-Image Paradigm for Fine-Tuning Vision-Language Models cites this paper.

Timage: A Generative Text-in-Image Paradigm for Fine-Tuning Vision-Language Models E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T03:39:29.897593Z

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.

Observation e3ad8cc2-fbd0-4dab-9c9f-f730021edb71 · 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 E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T08:59:42.692189Z

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.

Observation e26df252-12cd-4732-a043-8c423901b5b2 · inbound

Adapting Vision Foundation Models with Cascaded Semantics cites this paper.

Adapting Vision Foundation Models with Cascaded Semantics E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-08T14:03:48.836848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.