Paper Citation Record · LEDGER

Exploring Visual Prompts for Adapting Large-Scale Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 40 inbound Pith citation observations for arXiv:2203.17274.

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

pith.paper-citation-record.v1
2203.17274 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 40 of 40 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 40 of 40 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:23:25.342323Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:49:19.216124Z

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 755e325f-8756-4f26-80a1-c00a64f254ca · inbound

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications cites this paper.

A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-12T21:52:10.367192Z

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 22f8bcea-76f0-4749-9573-44fb78f5fbc3 · inbound

Subgraph-level Universal Prompt Tuning cites this paper.

Subgraph-level Universal Prompt Tuning Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-24T03:38:50.032879Z

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 fcea3cc7-99b8-40a1-b527-79e7f7f54ad0 · inbound

Robust Adaptation of Foundation Models with Black-Box Visual Prompting cites this paper.

Robust Adaptation of Foundation Models with Black-Box Visual Prompting Exploring Visual Prompts for Adapting Large-Scale Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-23T23:23:36.348169Z

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 509017f4-7d0c-47fd-8829-f6d09806e771 · inbound

LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation cites this paper.

LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation Exploring Visual Prompts for Adapting Large-Scale Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T17:23:25.342323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daa4f87e-5307-4586-b804-5939b38108c3 · inbound

Revisiting the Auxiliary Data in Backdoor Purification cites this paper.

Revisiting the Auxiliary Data in Backdoor Purification Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T13:30:03.452514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3177020-49a8-40e6-b885-eefd51385243 · inbound

Seeing the Trees for the Forest: Rethinking Weakly-Supervised Medical Visual Grounding cites this paper.

Seeing the Trees for the Forest: Rethinking Weakly-Supervised Medical Visual Grounding Exploring Visual Prompts for Adapting Large-Scale Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:21.565626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2f9bdee-b5ef-488f-a24b-645e8e0715c4 · inbound

Dual-Path Stable Soft Prompt Generation for Domain Generalization cites this paper.

Dual-Path Stable Soft Prompt Generation for Domain Generalization Exploring Visual Prompts for Adapting Large-Scale Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:37.658386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f41d087e-c57c-4113-99e1-ae1913b0af76 · inbound

MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning cites this paper.

MetaWriter: Personalized Handwritten Text Recognition Using Meta-Learned Prompt Tuning Exploring Visual Prompts for Adapting Large-Scale Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T13:58:03.278749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef5adab9-0979-4da1-a0f1-c8cbb3a616de · inbound

Model Reprogramming Demystified: A Neural Tangent Kernel Perspective cites this paper.

Model Reprogramming Demystified: A Neural Tangent Kernel Perspective Exploring Visual Prompts for Adapting Large-Scale Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T12:09:48.866213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a91bcad-9e1b-4a6a-8e5e-861009a9bf32 · inbound

Exploring Visual Prompting: Robustness Inheritance and Beyond cites this paper.

Exploring Visual Prompting: Robustness Inheritance and Beyond Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:38.655882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 355dc0b5-766f-4a70-8abe-601b140d994b · inbound

CoCoA-Mix: Confusion-and-Confidence-Aware Mixture Model for Context Optimization cites this paper.

CoCoA-Mix: Confusion-and-Confidence-Aware Mixture Model for Context Optimization Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T05:40:28.964278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f059a6d5-a6e6-4e84-a65e-8b9f95e79385 · inbound

Casper: Inferring Diverse Intents for Assistive Teleoperation with Vision Language Models cites this paper.

Casper: Inferring Diverse Intents for Assistive Teleoperation with Vision Language Models Exploring Visual Prompts for Adapting Large-Scale Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T00:14:15.210742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4201aed3-822e-4e97-8a35-cf388bf94315 · inbound

Generalizing vision-language models to novel domains: A comprehensive survey cites this paper.

Generalizing vision-language models to novel domains: A comprehensive survey Exploring Visual Prompts for Adapting Large-Scale Models

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:44.918777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8a31ae4-53dd-4930-936c-bc8d7851bbba · inbound

Visual Textualization for Image Prompted Object Detection cites this paper.

Visual Textualization for Image Prompted Object Detection Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T21:37:03.071096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f44d106a-f5ca-47ae-bd2e-9146376fb124 · inbound

Visual Instance-aware Prompt Tuning cites this paper.

Visual Instance-aware Prompt Tuning Exploring Visual Prompts for Adapting Large-Scale Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T18:37:35.090755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a810cc3f-b520-4e8b-837c-051629199850 · inbound

DynImg: Key Frames with Visual Prompts are Good Representation for Multi-Modal Video Understanding cites this paper.

DynImg: Key Frames with Visual Prompts are Good Representation for Multi-Modal Video Understanding Exploring Visual Prompts for Adapting Large-Scale Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T15:34:44.361412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d48289a5-6a7c-46c4-803c-462a4ce5110f · inbound

DepthDark: Robust Monocular Depth Estimation for Low-Light Environments cites this paper.

DepthDark: Robust Monocular Depth Estimation for Low-Light Environments Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T14:44:24.547505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 535c30e0-6bf9-4295-9d97-e9e7b4d222eb · inbound

Progressive Homeostatic and Plastic Prompt Tuning for Audio-Visual Multi-Task Incremental Learning cites this paper.

Progressive Homeostatic and Plastic Prompt Tuning for Audio-Visual Multi-Task Incremental Learning Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T12:42:01.672805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94857fbf-9c66-4aef-9382-bfa295a1ce11 · inbound

Twistronics and moir\'e superlattice physics in 2D transition metal dichalcogenides cites this paper.

Twistronics and moir\'e superlattice physics in 2D transition metal dichalcogenides Exploring Visual Prompts for Adapting Large-Scale Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T05:32:05.603281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7148a55f-e9ee-4945-82d2-a17bde025b00 · inbound

Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design cites this paper.

Invisible Watermarks, Visible Gains: Steering Machine Unlearning with Bi-Level Watermarking Design Exploring Visual Prompts for Adapting Large-Scale Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T21:01:26.913858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6ee39eb-6a72-406f-b9a7-db5ef07de65b · inbound

Polarization-Resolved Chlorophyll Imaging for Non-Invasive Plant Tissue Assessment Using a Silicon-Rich Nitride Metalens Array cites this paper.

Polarization-Resolved Chlorophyll Imaging for Non-Invasive Plant Tissue Assessment Using a Silicon-Rich Nitride Metalens Array Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T18:45:08.262623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f707f0b5-ef9f-4cda-befb-c3de0ebc6f3d · inbound

CLIPSym: Delving into Symmetry Detection with CLIP cites this paper.

CLIPSym: Delving into Symmetry Detection with CLIP Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T18:48:34.686795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5d17cd1-77ae-4eec-b466-b453eb082bc1 · inbound

Adaptive Point-Prompt Tuning: Fine-Tuning Heterogeneous Foundation Models for 3D Point Cloud Analysis cites this paper.

Adaptive Point-Prompt Tuning: Fine-Tuning Heterogeneous Foundation Models for 3D Point Cloud Analysis Exploring Visual Prompts for Adapting Large-Scale Models

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-05T13:45:43.985537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 241f9d26-79d5-4ac8-af64-68c4e92693a7 · inbound

Parameter-Efficient Adaptation of mPLUG-Owl2 via Pixel-Level Visual Prompts for NR-IQA cites this paper.

Parameter-Efficient Adaptation of mPLUG-Owl2 via Pixel-Level Visual Prompts for NR-IQA Exploring Visual Prompts for Adapting Large-Scale Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T10:55:55.673736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1128d73f-a5d9-4deb-8e6a-35935c20d013 · inbound

Few-Shot Query Intent Detection via Relation-Aware Prompt Learning cites this paper.

Few-Shot Query Intent Detection via Relation-Aware Prompt Learning Exploring Visual Prompts for Adapting Large-Scale Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T05:21:30.834999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1f09176-d956-4c63-863b-08ddb346d4e6 · inbound

AttriPrompt: Dynamic Prompt Composition Learning for CLIP cites this paper.

AttriPrompt: Dynamic Prompt Composition Learning for CLIP Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T04:50:27.627722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48c90f39-0524-4b32-a760-c8df16b39471 · inbound

Improving Adversarial Robustness of Zero-Shot CLIP with Confidence-Aware Weighting cites this paper.

Improving Adversarial Robustness of Zero-Shot CLIP with Confidence-Aware Weighting Exploring Visual Prompts for Adapting Large-Scale Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T12:41:48.171666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 092ca34d-4bbb-4d74-a258-365ccec9222e · inbound

MMLoP: Multi-Modal Low-Rank Prompting for Efficient Vision-Language Adaptation cites this paper.

MMLoP: Multi-Modal Low-Rank Prompting for Efficient Vision-Language Adaptation Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T21:07:44.774219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7971877d-d16b-49bd-a150-b07fa417ab01 · inbound

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

Visual prompting reimagined: The power of the Activation Prompts Exploring Visual Prompts for Adapting Large-Scale Models

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:45:53.794408Z

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 201de585-a328-4a43-9536-40209c69348f · inbound

Generalized Category Discovery under Domain Shifts: From Vision to Vision-Language Models cites this paper.

Generalized Category Discovery under Domain Shifts: From Vision to Vision-Language Models Exploring Visual Prompts for Adapting Large-Scale Models

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:16:11.008917Z

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 ec967b38-6f25-4f53-bf50-3cf01355e7cf · inbound

Plug-and-play Class-aware Knowledge Injection for Prompt Learning with Visual-Language Model cites this paper.

Plug-and-play Class-aware Knowledge Injection for Prompt Learning with Visual-Language Model Exploring Visual Prompts for Adapting Large-Scale Models

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T16:36:09.441123Z

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 76d31edb-a4dc-4c31-a012-6a4a56115b0a · inbound

Efficient Prompt Learning for Traffic Forecasting cites this paper.

Efficient Prompt Learning for Traffic Forecasting Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T08:06:26.680493Z

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 49a774fc-4d22-4a12-8921-c6917544589a · inbound

Thermal-Det: Language-Guided Cross-Modal Distillation for Open-Vocabulary Thermal Object Detection cites this paper.

Thermal-Det: Language-Guided Cross-Modal Distillation for Open-Vocabulary Thermal Object Detection Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:26:19.261914Z

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 fb7d82dc-8cbe-4dba-aa84-4215614ca838 · inbound

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models cites this paper.

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models Exploring Visual Prompts for Adapting Large-Scale Models

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:23:21.477774Z

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 05ef2002-a4ca-4796-933e-7f588ddeefca · inbound

BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning cites this paper.

BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning Exploring Visual Prompts for Adapting Large-Scale Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-01T19:56:11.303547Z

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 f0cfe145-e2b6-4d75-98ab-eca2f337e9dc · inbound

Latent Diffusion Pretraining for Crystal Property Prediction cites this paper.

Latent Diffusion Pretraining for Crystal Property Prediction Exploring Visual Prompts for Adapting Large-Scale Models

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T19:32:34.856001Z

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 718df71c-c640-413d-8ccd-de9d456989a1 · inbound

Fine-tuning Multi-modal LLMs with ART: Art-based Reinforcement Training cites this paper.

Fine-tuning Multi-modal LLMs with ART: Art-based Reinforcement Training Exploring Visual Prompts for Adapting Large-Scale Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-03T09:07:48.149675Z

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 b409a6b4-2b1c-469c-a19c-41e9306614ba · inbound

Language-Instructed Vision Embeddings for Controllable and Generalizable Perception cites this paper.

Language-Instructed Vision Embeddings for Controllable and Generalizable Perception Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:49:19.219783Z

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 6ff0bf58-5ded-477b-9455-b7faf87feed8 · inbound

One Scene, Two Depths: Probing Geometric Ambiguity in Monocular Foundation Models cites this paper.

One Scene, Two Depths: Probing Geometric Ambiguity in Monocular Foundation Models Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T07:04:21.640534Z

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 085e645b-ba73-4dbc-98ac-2d97d35e2bfc · inbound

Visual prompt engineering for video models cites this paper.

Visual prompt engineering for video models Exploring Visual Prompts for Adapting Large-Scale Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T02:13:12.362932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.