Paper Citation Record · LEDGER

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook

As of 20 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2607.00839.

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

pith.paper-citation-record.v1
2607.00839 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-02T14:30:24.768627Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact3
verified fuzzy26
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e63cc7b4-1b5b-4ecd-931f-fe9f301e0d0e · outbound

This paper cites The emerging trends of multi-label learning,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook The emerging trends of multi-label learning,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.123841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e79e2fad-fdeb-4a46-ac2b-2bb02c0277bf · outbound

This paper cites Automl for multi-label classification: Overview and empirical evaluation,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Automl for multi-label classification: Overview and empirical evaluation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.125539Z

Source-reported events for the cited work

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Observation 716f1682-f44c-4dc1-bbb1-8d0aed5109eb · outbound

This paper cites A review of methods for imbalanced multi-label classification,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook A review of methods for imbalanced multi-label classification,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.120513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2814d5ab-baa7-4fd4-937e-a3f1159f35a0 · outbound

This paper cites Fine-grained image analysis with deep learning: A survey,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Fine-grained image analysis with deep learning: A survey,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.122148Z

Source-reported events for the cited work

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Observation 9f287724-e48e-4ff4-8e96-d816117a928b · outbound

This paper cites Compre- hensive comparative study of multi-label classification methods,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Compre- hensive comparative study of multi-label classification methods,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.116919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 92e0fce4-1199-4312-8764-3c39bc574f05 · outbound

This paper cites A Survey on Extreme Multi-label Learning.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook A Survey on Extreme Multi-label Learning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-02T14:37:03.131149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2c1a1052-56cf-49a1-9c61-fcfce69683ab · outbound

This paper cites A survey of multi-label text classification based on deep learning,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook A survey of multi-label text classification based on deep learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.107985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f49432d4-bdef-4052-8bcd-f3f8678fbf2a · outbound

This paper cites A survey of multi- label classification based on supervised and semi-supervised learning,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook A survey of multi- label classification based on supervised and semi-supervised learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.106229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c13e526f-7474-415f-bb21-bf456d7cbfe4 · outbound

This paper cites A survey on multi- label feature selection from perspectives of label fusion,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook A survey on multi- label feature selection from perspectives of label fusion,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.111354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1c8a131b-237a-4bad-a966-4e3f6e3c0f2a · outbound

This paper cites Deep Learning for Multi-Label Learning: A Comprehensive Survey.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Deep Learning for Multi-Label Learning: A Comprehensive Survey

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-02T14:37:03.136786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4a9b0ea2-5def-4bb9-a38c-06f658c589a6 · outbound

This paper cites Towards long-tailed, multi-label disease classification from chest x-ray: Overview of the cxr- lt challenge,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Towards long-tailed, multi-label disease classification from chest x-ray: Overview of the cxr- lt challenge,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.113174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 32e989ab-c0c3-43c6-a968-3c64aad37b2d · outbound

This paper cites A survey on multi-label classification for images,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook A survey on multi-label classification for images,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.115055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ec911b4d-e839-45a2-9cb9-db47fd0d6593 · outbound

This paper cites The pascal visual object classes (voc) challenge,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook The pascal visual object classes (voc) challenge,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.118751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 06b043c7-cbda-480c-84a1-5b12b557cfe5 · outbound

This paper cites Microsoft coco: Common objects in context,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Microsoft coco: Common objects in context,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.109651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bd17f698-b83b-466e-809d-81904e0e0bb8 · outbound

This paper cites Nus-wide: a real-world web image database from national university of singapore,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Nus-wide: a real-world web image database from national university of singapore,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.146241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 376c52c7-2e80-46ef-9b89-657f1d87a4ef · outbound

This paper cites Learning semantic-specific graph representation for multi-label image recognition,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Learning semantic-specific graph representation for multi-label image recognition,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.144303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bb4852db-6168-4b86-9c8b-358ff98ea07b · outbound

This paper cites Visual genome: Connecting language and vision using crowdsourced dense image annotations,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Visual genome: Connecting language and vision using crowdsourced dense image annotations,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.148241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5ccda1c0-0b74-44c2-906c-50ad38f36629 · outbound

This paper cites Human attribute recognition by deep hierarchical contexts,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Human attribute recognition by deep hierarchical contexts,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.152013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 610670be-152c-4668-ae5e-000490de09c7 · outbound

This paper cites Orderless recurrent models for multi-label classification,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Orderless recurrent models for multi-label classification,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.142596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 64c4a5b3-af1a-49af-bb9d-21b21c43f554 · outbound

This paper cites The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.140782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 74123bcc-0038-4df1-a28f-e2f7dd7ee112 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Imagenet: A large-scale hierarchical image database,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.149998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b2cebee3-6071-4cfc-8746-dae4103b0754 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Imagenet classification with deep convolutional neural networks,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.139069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d03b1794-fd1a-4871-98fb-fe11dd4aea77 · outbound

This paper cites Very deep convolutional networks for large-scale image recognition,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Very deep convolutional networks for large-scale image recognition,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.137182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a3c7c14d-33a2-4807-83ec-965060a1e9db · outbound

This paper cites Deep residual learning for image recognition,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Deep residual learning for image recognition,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.132898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 259c2780-d05a-4d76-ae53-a968336eb4bc · outbound

This paper cites Aggregated residual transformations for deep neural networks,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Aggregated residual transformations for deep neural networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.130952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2f20f965-2773-46bf-94f9-c8ce75eed7cd · outbound

This paper cites Tresnet: High performance gpu-dedicated architecture,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Tresnet: High performance gpu-dedicated architecture,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.135243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bb72ebb6-ce84-401a-938d-e06cce1a57fc · outbound

This paper cites Attention is all you need,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Attention is all you need,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.129075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ceaeea2e-c339-4b9b-97ec-ea7e0b1752c0 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-07-02T14:37:03.133687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3de87f78-c458-4b81-bcc3-dad763f9fea3 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Rethinking Multi-Label Image Classification With Deep Learning: Taxonomy, Challenge, and Outlook Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T00:21:41.127386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.