Paper Citation Record · LEDGER

Unsupervised Prompt Learning for Vision-Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2204.03649.

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

pith.paper-citation-record.v1
2204.03649 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:40:10.674930Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T05:00:54.660838Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 7251aa30-897d-4433-b243-ebd3990d7106 · inbound

FDBPL: Faster Distillation-Based Prompt Learning for Region-Aware Vision-Language Models Adaptation cites this paper.

FDBPL: Faster Distillation-Based Prompt Learning for Region-Aware Vision-Language Models Adaptation Unsupervised Prompt Learning for Vision-Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:10.674930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3891254f-71f4-4730-9ff1-ce7483f3b9ab · inbound

Advancing Reliable Test-Time Adaptation of Vision-Language Models under Visual Variations cites this paper.

Advancing Reliable Test-Time Adaptation of Vision-Language Models under Visual Variations Unsupervised Prompt Learning for Vision-Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T18:00:23.407854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5ba3e4d-2e7e-4bf6-bda4-1ead158abbc5 · inbound

Towards Fine-Grained Adaptation of CLIP via a Self-Trained Alignment Score cites this paper.

Towards Fine-Grained Adaptation of CLIP via a Self-Trained Alignment Score Unsupervised Prompt Learning for Vision-Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T18:00:31.658407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07480e7d-8ea4-490c-aede-0d5208e0cd0b · 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 Unsupervised Prompt Learning for Vision-Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T12:42:03.122890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48c1c659-a79f-4589-9f5f-fadd3d913c03 · inbound

Prototype-Guided Pseudo-Labeling with Neighborhood-Aware Consistency for Unsupervised Adaptation cites this paper.

Prototype-Guided Pseudo-Labeling with Neighborhood-Aware Consistency for Unsupervised Adaptation Unsupervised Prompt Learning for Vision-Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T15:04:16.864287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3942aff-a4f6-4c99-945b-09a255845dd3 · inbound

Adapting Vision-Language Models Without Labels: A Comprehensive Survey cites this paper.

Adapting Vision-Language Models Without Labels: A Comprehensive Survey Unsupervised Prompt Learning for Vision-Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T23:17:04.343681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe9b617e-54bf-4a0b-819c-ac6a4fa8dcdd · inbound

Vision-Language Models display a strong gender bias cites this paper.

Vision-Language Models display a strong gender bias Unsupervised Prompt Learning for Vision-Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T20:05:43.121211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 890f41c0-a26b-4de1-a016-5442a921a842 · inbound

$\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization cites this paper.

$\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization Unsupervised Prompt Learning for Vision-Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T10:14:07.605827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 991138d7-eadc-440a-a76e-3e9e8411bc91 · inbound

Bi-CoG: Bi-Consistency-Guided Self-Training for Vision-Language Models cites this paper.

Bi-CoG: Bi-Consistency-Guided Self-Training for Vision-Language Models Unsupervised Prompt Learning for Vision-Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-18T05:00:54.664079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b29b9be6-d5ad-4ced-a10a-eb204d2a8be3 · inbound

Bi-CoG: Bi-Consistency-Guided Self-Training for Vision-Language Models cites this paper.

Bi-CoG: Bi-Consistency-Guided Self-Training for Vision-Language Models Unsupervised Prompt Learning for Vision-Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T08:29:07.684257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39b54202-3c61-405f-a9ab-c3ab3872880a · inbound

USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning cites this paper.

USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning Unsupervised Prompt Learning for Vision-Language Models

Reference 80

Resolution: unresolved; no resolver link, observed 2026-07-11T23:10:08.033785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4877e3ab-2079-4b1a-8a80-ea349dde6ede · inbound

C-GAP: Class-Aware and Online Prompting Improves Vision-Language Models on Imbalanced Classes cites this paper.

C-GAP: Class-Aware and Online Prompting Improves Vision-Language Models on Imbalanced Classes Unsupervised Prompt Learning for Vision-Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-13T01:03:27.721212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.