Pith. sign in

Paper Citation Record · LEDGER

Quality Assessment in the Era of Large Models: A Survey

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.00031.

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

pith.paper-citation-record.v1
2409.00031 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 2026-08-07T11:20:51.339568Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:45:12.407173Z

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 b867e270-bff2-4937-9781-54cc721f97b6 · inbound

NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results cites this paper.

NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results Quality Assessment in the Era of Large Models: A Survey

Reference 107

Resolution
unresolved
no resolver link, observed 2026-08-07T11:20:51.339568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:20:51.339568Z digest=sha256:6d23f7bfc8de425d4ed83b1246198de39f11b5888aa4d512f5c5d1989a8068db

Observation e7dec906-f5ca-4e2e-92a6-9172643a28d9 · inbound

Leveraging Vision-Language Models to Select Trustworthy Super-Resolution Samples Generated by Diffusion Models cites this paper.

Leveraging Vision-Language Models to Select Trustworthy Super-Resolution Samples Generated by Diffusion Models Quality Assessment in the Era of Large Models: A Survey

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:45:12.414407Z

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=2026-08-06T22:45:12.043964Z digest=sha256:3d903803efa67098aa848c8911dc36ca056a71de2b294d9f11fc8267ca3c71c8