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Paper Citation Record · LEDGER

Algorithmic progress in computer vision

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2212.05153.

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

pith.paper-citation-record.v1
2212.05153 v4

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:47:35.790774Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T16:21:02.649340Z

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 d24d3a58-0779-476b-8b71-a25d96e4093b · inbound

Literature Review Of Multi-Agent Debate For Problem-Solving cites this paper.

Literature Review Of Multi-Agent Debate For Problem-Solving Algorithmic progress in computer vision

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T12:47:35.790774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:47:35.790774Z digest=sha256:dd4265be5dd28a09bba014b6e578f25185171d7fd89883667b9adde8b1d591f3

Observation 8360202a-ba8d-4acc-b2b7-9bb70b20d798 · inbound

Beyond Tokens: Enhancing RTL Quality Estimation via Structural Graph Learning cites this paper.

Beyond Tokens: Enhancing RTL Quality Estimation via Structural Graph Learning Algorithmic progress in computer vision

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:21:02.658702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-05T16:21:01.962716Z digest=sha256:d079ba66b4709db6800f3e2da2e13852145885d97476d1e79008164ddd271e5c