Paper Citation Record · LEDGER

Vision Graph Prompting via Semantic Low-Rank Decomposition

As of 17 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2505.04121.

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

pith.paper-citation-record.v1
2505.04121 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:40:51.655016Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:08:17.400666Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T18:08:17.750518Z

Reference resolution

18 of 18 outbound references displayed

verified exact0
verified fuzzy3
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2345bfd0-d435-4d69-b7fd-2d4ea24f0897 · outbound

This paper cites Exploring Visual Prompts for Adapting Large-Scale Models.

Vision Graph Prompting via Semantic Low-Rank Decomposition Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.562082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18c39589-bd16-4d3e-85e0-7f12e740e986 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Vision Graph Prompting via Semantic Low-Rank Decomposition Imagenet: A large-scale hierarchical image database

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.578904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2fa5582-3b1c-49df-be63-a156bf82194c · outbound

This paper cites Our approach does not require the re-training of the entire model, which helps to mitigate the computational cost typically associated with full fine-tuning.

Vision Graph Prompting via Semantic Low-Rank Decomposition Our approach does not require the re-training of the entire model, which helps to mitigate the computational cost typically associated with full fine-tuning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:40:51.859710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a8c038bf-8617-4b5b-99de-135b9a905eb6 · outbound

This paper cites Strategies for Pre-training Graph Neural Networks.

Vision Graph Prompting via Semantic Low-Rank Decomposition Strategies for Pre-training Graph Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.600578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9aae785-4c89-4b16-a528-2ba9fcffe9d0 · outbound

This paper cites Y ., et al.

Vision Graph Prompting via Semantic Low-Rank Decomposition Y ., et al

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.629430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f11fc5d6-f47f-4b1d-801b-f0b260409c28 · outbound

This paper cites and Zisserman, A.

Vision Graph Prompting via Semantic Low-Rank Decomposition and Zisserman, A

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.634091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66457339-fafd-4b72-92e7-3ac03b50650f · outbound

This paper cites Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference.

Vision Graph Prompting via Semantic Low-Rank Decomposition Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.639527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dbe0964-6e3b-43f1-a38b-72c2c93c9166 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Vision Graph Prompting via Semantic Low-Rank Decomposition An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.583768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3013800d-db9d-44cd-aabf-1f8273e33538 · outbound

This paper cites Variational Graph Auto-Encoders.

Vision Graph Prompting via Semantic Low-Rank Decomposition Variational Graph Auto-Encoders

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.606058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 978ffd11-2a5b-45bf-863a-5a499f4cf13d · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

Vision Graph Prompting via Semantic Low-Rank Decomposition D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.573663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8beead0d-e8a9-4a06-a6d9-37821bbdfd69 · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset,.

Vision Graph Prompting via Semantic Low-Rank Decomposition The caltech-ucsd birds-200-2011 dataset,

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.644964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c707e766-a2be-40bd-9da4-f54e961b768c · outbound

This paper cites The learning rate is set as 0.001 and the weight decay is 0.05.

Vision Graph Prompting via Semantic Low-Rank Decomposition The learning rate is set as 0.001 and the weight decay is 0.05

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:40:51.842538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 26e49f25-fa80-46cb-9746-39154f3d3e1c · outbound

This paper cites Universal Prompt Tuning for Graph Neural Networks.

Vision Graph Prompting via Semantic Low-Rank Decomposition Universal Prompt Tuning for Graph Neural Networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.588945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8faba2cf-2be8-4bc7-a0eb-cc7fe17c5362 · outbound

This paper cites Graphprompt: Uni- fying pre-training and downstream tasks for graph neural networks.

Vision Graph Prompting via Semantic Low-Rank Decomposition Graphprompt: Uni- fying pre-training and downstream tasks for graph neural networks

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:40:51.906581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2844a3e1-6ba5-4767-bf38-7ad4d64a91ab · outbound

This paper cites Food-101– mining discriminative components with random forests.

Vision Graph Prompting via Semantic Low-Rank Decomposition Food-101– mining discriminative components with random forests

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.568333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 924ec6b3-02ec-4cbe-80b2-63a42601cc5f · outbound

This paper cites E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning.

Vision Graph Prompting via Semantic Low-Rank Decomposition E^2VPT: An Effective and Efficient Approach for Visual Prompt Tuning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.593986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf43350f-4fd7-4823-a478-39c56cb331a7 · outbound

This paper cites STOP: Integrated Spatial-Temporal Dynamic Prompting for Video Understanding.

Vision Graph Prompting via Semantic Low-Rank Decomposition STOP: Integrated Spatial-Temporal Dynamic Prompting for Video Understanding

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.617779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c55a2cad-f46f-4023-8ad6-b7b3fd045874 · outbound

This paper cites Decoupled Weight Decay Regularization.

Vision Graph Prompting via Semantic Low-Rank Decomposition Decoupled Weight Decay Regularization

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-15T23:40:51.623920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d50b440b-ca9d-4b26-8462-489d9d272e05 · inbound

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis cites this paper.

UPP: Unified Point-Level Prompting for Robust Point Cloud Analysis Vision Graph Prompting via Semantic Low-Rank Decomposition

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:08:17.757573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.