Paper Citation Record · LEDGER

VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2112.06825.

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

pith.paper-citation-record.v1
2112.06825 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:25:16.164974Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T22:43:10.958330Z

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 01bd34fb-8607-4703-afe1-3ceb26800f99 · inbound

Adding Conditional Control to Text-to-Image Diffusion Models cites this paper.

Adding Conditional Control to Text-to-Image Diffusion Models VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:43:10.960796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e4c1be25-08e9-41e9-b295-26b980c32234 · inbound

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges cites this paper.

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks

Reference 160

Resolution: unresolved; no resolver link, observed 2026-08-11T22:41:19.417860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebd31945-0bfb-46e5-b4ee-fb1db3017b2d · inbound

A Brief Review for Compression and Transfer Learning Techniques in DeepFake Detection cites this paper.

A Brief Review for Compression and Transfer Learning Techniques in DeepFake Detection VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T05:25:16.164974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 334e8862-9114-439e-8fe3-400ec4db514b · inbound

Optimising Language Models for Downstream Tasks: A Post-Training Perspective cites this paper.

Optimising Language Models for Downstream Tasks: A Post-Training Perspective VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks

Reference 215

Resolution: unresolved; no resolver link, observed 2026-08-06T22:44:44.573305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d87c586-bd2e-466c-87f9-765b1b0dfff9 · inbound

PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint cites this paper.

PHLoRA: data-free Post-hoc Low-Rank Adapter extraction from full-rank checkpoint VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T17:22:08.981291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f38f4bd-820e-489f-bc11-6ba1d81e41f6 · inbound

GeoStack: A Framework for Quasi-Abelian Knowledge Composition in VLMs cites this paper.

GeoStack: A Framework for Quasi-Abelian Knowledge Composition in VLMs VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:56:06.902083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.