Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Return of the Devil in the Details: Delving Deep into Convolutional Nets
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1405.3531.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T00:35:49.041557Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-06-30T18:55:00.109712Z
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 d31fa9a3-38b8-4049-aa66-ab6f0294d6f6 · inbound
DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory cites this paper.
DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory Return of the Devil in the Details: Delving Deep into Convolutional Nets
Reference 133
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T13:03:58.112246Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0307df1d-95d9-4a95-b6e4-659146f83bcf · inbound
Efficient Audiovisual Speech Processing via MUTUD: Multimodal Training and Unimodal Deployment cites this paper.
Efficient Audiovisual Speech Processing via MUTUD: Multimodal Training and Unimodal Deployment Return of the Devil in the Details: Delving Deep into Convolutional Nets
Reference 76
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T00:35:49.041557Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 08349494-44fd-48ab-af0d-aa204748e271 · inbound
Acute Lymphoblastic Leukemia Diagnosis Employing YOLOv11, YOLOv8, ResNet50, and Inception-ResNet-v2 Deep Learning Models cites this paper.
Acute Lymphoblastic Leukemia Diagnosis Employing YOLOv11, YOLOv8, ResNet50, and Inception-ResNet-v2 Deep Learning Models Return of the Devil in the Details: Delving Deep into Convolutional Nets
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:30:17.287903Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d577d845-d8a9-4887-9a6b-77a05ec1abf1 · inbound
A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation cites this paper.
A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation Return of the Devil in the Details: Delving Deep into Convolutional Nets
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T15:18:25.607429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f887b6d8-f6cf-4185-be27-34b6990f9ced · inbound
A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation cites this paper.
A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation Return of the Devil in the Details: Delving Deep into Convolutional Nets
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T18:55:00.110935Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.