Pith. sign in

Paper Citation Record · LEDGER

Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2210.08773.

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

pith.paper-citation-record.v1
2210.08773 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:21:45.111786Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T07:25:28.419990Z

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 3c1f6acb-6bf3-4fcc-ac9f-1485723f535a · inbound

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models cites this paper.

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-10T20:37:01.977401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T20:37:01.617345Z digest=sha256:a5920cd3e35d605d14077db715bf99525124b5fc3084785e62194c46d61f43f5

Observation 38a70ab9-d8cb-4f4f-afd1-4c0e5a1b75f7 · inbound

The ART of Composition: Attention-Regularized Training for Compositional Visual Grounding cites this paper.

The ART of Composition: Attention-Regularized Training for Compositional Visual Grounding Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-23T07:25:28.422147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T07:24:01.527093Z digest=sha256:79a1b0e2d9727472424672e81aae72aa26d5379edeed3fdff44b99cdf4f69242

Observation cdc83392-a7dd-44c7-aef0-d7180cef1400 · inbound

GC-KBVQA: A New Four-Stage Framework for Enhancing Knowledge Based Visual Question Answering Performance cites this paper.

GC-KBVQA: A New Four-Stage Framework for Enhancing Knowledge Based Visual Question Answering Performance Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:21:45.111786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:21:45.111786Z digest=sha256:8c26744f633f7f457db78880fe64932b6fc9950cac40ee5e900d9c0cc4bc89a1

Observation 33457ebf-634d-4ef1-b733-f6263fcfa8da · inbound

FREE: Fast and Robust Vision Language Models with Early Exits cites this paper.

FREE: Fast and Robust Vision Language Models with Early Exits Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T05:53:44.511807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:53:44.511807Z digest=sha256:3fae971018ef828396f56eff08a8f41e36586901eb01b486cbd302a7227113f9

Observation a6482387-ad91-4f2c-a910-881bb09f6f81 · inbound

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding cites this paper.

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:31:03.955460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T15:26:55.369840Z digest=sha256:ddb916c47e3b78a9af084a2ba7caef8032a5fa18627b0ddc317f303dc5a2ef25