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Paper Citation Record · LEDGER

Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessment

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2304.14672.

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

pith.paper-citation-record.v1
2304.14672 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 2026-08-06T21:03:03.344353Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T16:35:48.020424Z

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 70d7df66-ca36-4264-a377-393f977edf37 · inbound

Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels cites this paper.

Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessment

Reference 214

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:35:48.024344Z

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=arxiv_source observed=2026-05-15T16:35:47.826165Z digest=sha256:e51ffa9bdb45e079b4f52ddd9abfb2518e77be48ed6b20b79dfa969e4c19ca2f

Observation 0a260f00-d68f-45bf-a610-f9dc01f934ab · inbound

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation cites this paper.

AIGVE-MACS: Unified Multi-Aspect Commenting and Scoring Model for AI-Generated Video Evaluation Towards Robust Text-Prompted Semantic Criterion for In-the-Wild Video Quality Assessment

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T21:03:03.344353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:03:03.344353Z digest=sha256:fb62bcb3db35941e396736e54b6b521351d9ddaa59eb15befa148251cbb13eb5