Paper Citation Record · LEDGER

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts

As of 21 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2505.15506.

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

pith.paper-citation-record.v1
2505.15506 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:20:30.176902Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

verified exact1
verified fuzzy10
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c7ee413e-738a-4ba4-855d-22e9766e3617 · outbound

This paper cites Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:20:30.472412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 26800e05-b80d-4298-a228-9e415ac059ef · outbound

This paper cites Optimization as a model for few-shot learning.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Optimization as a model for few-shot learning

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:31.769140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b69f08e6-b2e8-4fa3-9a64-e26d66488d8e · outbound

This paper cites E t-SNE Visualizations The t-SNE visualizations of the image embeddings after training with our proposed MMReg module is shown in Fig.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts E t-SNE Visualizations The t-SNE visualizations of the image embeddings after training with our proposed MMReg module is shown in Fig

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:30.674534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 18f29162-7540-4334-bff4-2204242fedb7 · outbound

This paper cites Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:20:29.447891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b7b485b-7b82-4d58-b0f1-385aaa747aaa · outbound

This paper cites No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T15:20:29.556944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cd93179-f8e7-4997-b44c-d124e33a786c · outbound

This paper cites Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:20:29.814257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e888269-3744-42f5-add7-7a6e7a93bfeb · outbound

This paper cites Conditional prompt learning for vision- language models.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Conditional prompt learning for vision- language models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:30.998305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1d181e4d-7f24-4bf4-94a2-84cb7cdaf682 · outbound

This paper cites an unresolved cited work.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:20:30.836803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5388ac0a-8d03-4e83-a7ea-4b4032ae0072 · outbound

This paper cites Chestx- ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and local- ization of common thorax diseases.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Chestx- ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and local- ization of common thorax diseases

Reference 2011

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:31.179800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation abb312ad-be0c-4978-b8dc-6dbaf1b90032 · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-07T15:20:28.941817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7270253a-a6d2-41a4-9171-8cdd03926e96 · outbound

This paper cites Fgvcx fungi classification challenge 2018.Available online: github.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Fgvcx fungi classification challenge 2018.Available online: github

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:31.589535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a1dabbab-02d6-4671-b523-04f00daeba91 · outbound

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

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts The caltech-ucsd birds- 200-2011 dataset

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:31.417971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0516a562-6980-46b7-a411-d6f8bdba80fe · outbound

This paper cites A broader study of cross-domain few-shot learning.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts A broader study of cross-domain few-shot learning

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:32.571071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cb8d8179-4658-4d88-8f20-056b9d990f63 · outbound

This paper cites Detection of traffic signs in real-world images: The german traffic sign detection benchmark.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Detection of traffic signs in real-world images: The german traffic sign detection benchmark

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:32.418314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d78741c0-5308-4f42-aa71-4acab0323820 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Fine-Grained Visual Classification of Aircraft

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T15:20:29.312313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b8e5e96-f4c8-4421-9060-d1fcee825239 · outbound

This paper cites Microsoft coco: Common objects in context.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts Microsoft coco: Common objects in context

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:31.968702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9cdfbbe7-093c-4660-99e2-2b7bab6bc873 · outbound

This paper cites The quick, draw!-ai experiment.Mount View, CA, accessed Feb, 17(2018):4,.

Prompt Tuning Vision Language Models with Margin Regularizer for Few-Shot Learning under Distribution Shifts The quick, draw!-ai experiment.Mount View, CA, accessed Feb, 17(2018):4,

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:20:32.188999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.