Paper Citation Record · LEDGER

A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2110.08484.

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

pith.paper-citation-record.v1
2110.08484 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:30:37.348489Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:57:51.311135Z

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 53919e88-c164-4634-a6ee-f6a554998cdd · inbound

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection cites this paper.

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:30:37.348489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fcb7215-61bf-4f0b-a398-6b626f97bd98 · inbound

DiMPLe -- Disentangled Multi-Modal Prompt Learning: Enhancing Out-Of-Distribution Alignment with Invariant and Spurious Feature Separation cites this paper.

DiMPLe -- Disentangled Multi-Modal Prompt Learning: Enhancing Out-Of-Distribution Alignment with Invariant and Spurious Feature Separation A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T22:35:34.634008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a22ace72-afec-46db-b6c9-e384c441b7bd · inbound

Integrated Structural Prompt Learning for Vision-Language Models cites this paper.

Integrated Structural Prompt Learning for Vision-Language Models A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:27:15.893496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52fce76b-5efc-4398-a560-1fd2926a21f2 · inbound

Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 cites this paper.

Multimodal AI for Gastrointestinal Diagnostics: Tackling VQA in MEDVQA-GI 2025 A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:57:51.314658Z

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.