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Paper Citation Record · LEDGER

VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.12273.

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

pith.paper-citation-record.v1
2312.12273 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:49:53.440763Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T22:23:31.221244Z

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 f4f5768a-8b27-457a-a64a-0a18b7bcd07b · inbound

Fashion Image-to-Image Translation for Complementary Item Retrieval cites this paper.

Fashion Image-to-Image Translation for Complementary Item Retrieval VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:23:31.223870Z

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=2026-05-23T22:22:47.889637Z digest=sha256:1ef0abbdd77694eaeb6044cfe71587f613d9e003eccbf4dd05a743e36318bdd9

Observation 7e026fbc-b4f4-4fb3-806c-4d987713efd9 · inbound

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks cites this paper.

MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T05:49:53.440763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:49:53.440763Z digest=sha256:ee3865cdda6f8dd894dbf32bb07fa0f61696b2a5d1a3b0b314439163a7a358db