Paper Citation Record · LEDGER

Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.14325.

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

pith.paper-citation-record.v1
2405.14325 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:39:38.577429Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T04:31:00.087378Z

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 3dfe0797-c086-40cc-bc89-2a7df315aaeb · inbound

ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift cites this paper.

ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T13:39:38.577429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ee964b0-24da-46ab-baa0-77b89bce62f2 · inbound

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning cites this paper.

OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:20:59.197386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf277b10-e481-4b52-872a-344416f49285 · inbound

INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning cites this paper.

INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T11:03:10.328020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 649875e4-947a-4ae8-98db-bf784efd8b1d · inbound

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects cites this paper.

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T17:21:43.868007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 985aee26-20b2-4ed5-a3f7-8b17a64e9fbd · inbound

Multi-View Reconstruction with Global Context for 3D Anomaly Detection cites this paper.

Multi-View Reconstruction with Global Context for 3D Anomaly Detection Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T12:43:21.825025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31000e1f-15d5-46c3-ace4-38501010e925 · inbound

Real-IAD MVN: A Multi-View Normal Vector Dataset and Benchmark for High-Fidelity Industrial Anomaly Detection cites this paper.

Real-IAD MVN: A Multi-View Normal Vector Dataset and Benchmark for High-Fidelity Industrial Anomaly Detection Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:31:00.090120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.