Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DRACO-DehazeNet: An Efficient Image Dehazing Network Combining Detail Recovery and a Novel Contrastive Learning Paradigm
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.14595.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T18:02:36.198214Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T05:20:54.329149Z
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 74cadd5f-34c2-4bd5-884f-ed7030c59d24 · inbound
Continual Learning-Based Unified Model for Unpaired Image Restoration Tasks cites this paper.
Continual Learning-Based Unified Model for Unpaired Image Restoration Tasks DRACO-DehazeNet: An Efficient Image Dehazing Network Combining Detail Recovery and a Novel Contrastive Learning Paradigm
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T18:02:36.198214Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4de7d3fa-85d8-4329-8cd9-3c47dfc92a98 · inbound
Enhancing Few-Shot Classification of Benchmark and Disaster Imagery with ABHFA-Net cites this paper.
Enhancing Few-Shot Classification of Benchmark and Disaster Imagery with ABHFA-Net DRACO-DehazeNet: An Efficient Image Dehazing Network Combining Detail Recovery and a Novel Contrastive Learning Paradigm
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T05:20:54.330908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.