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Paper Citation Record · LEDGER

AGLLDiff: Guiding Diffusion Models Towards Unsupervised Training-free Real-world Low-light Image Enhancement

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.14900.

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

pith.paper-citation-record.v1
2407.14900 v2

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 2026-08-07T10:29:06.592566Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T05:31:25.756135Z

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 bc92862c-0755-4f3a-8fdd-fcb40a6629e9 · inbound

Track Any Anomalous Object: A Granular Video Anomaly Detection Pipeline cites this paper.

Track Any Anomalous Object: A Granular Video Anomaly Detection Pipeline AGLLDiff: Guiding Diffusion Models Towards Unsupervised Training-free Real-world Low-light Image Enhancement

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T10:29:06.592566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:29:06.592566Z digest=sha256:5c7a5b6f3fd63d358ec42443cf0582b86f86af60fbbde074e166642a36aec7b3

Observation d1d40321-54e8-4c36-a282-b8158f90ef33 · inbound

Enhancing Zero-Shot Brain Tumor Subtype Classification via Fine-Grained Patch-Text Alignment cites this paper.

Enhancing Zero-Shot Brain Tumor Subtype Classification via Fine-Grained Patch-Text Alignment AGLLDiff: Guiding Diffusion Models Towards Unsupervised Training-free Real-world Low-light Image Enhancement

Reference 79

Resolution
verified exact
local_arxiv, observed 2026-08-06T05:31:25.761673Z

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=2026-08-06T05:31:24.478934Z digest=sha256:0122ea7f006491669025a48a74c3bda38a12ff4bec73a1a27ba52741ddf7aade