Paper Citation Record · LEDGER

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection

As of 22 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.23461.

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

pith.paper-citation-record.v1
2507.23461 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:50:59.447686Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

46 of 46 outbound references displayed

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verified fuzzy37
unresolved8
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 84072829-1952-4e5b-9525-cce8711d757a · outbound

This paper cites Federated learning for iot devices with domain generalization,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Federated learning for iot devices with domain generalization,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.354852Z

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Observation 4211d081-2e19-4e28-bfad-b82fde8090d9 · outbound

This paper cites Communication-efficient federated learning for wireless edge intelligence in iot,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Communication-efficient federated learning for wireless edge intelligence in iot,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.335701Z

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Observation 81ac2915-0d1a-4b98-a171-e61cdf178bbe · outbound

This paper cites Edge intelligence: The confluence of edge computing and artificial intelligence,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Edge intelligence: The confluence of edge computing and artificial intelligence,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.316120Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bf15a92f-50b0-48e6-ad33-f582ffaf08bb · outbound

This paper cites Wireless edge computing with latency and reliability guarantees,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Wireless edge computing with latency and reliability guarantees,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.296775Z

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Observation 9d7fa7f5-3aed-4127-ad09-ce523af5242b · outbound

This paper cites Decentralized edge intelligence: A dynamic resource allocation framework for hierarchical federated learning,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Decentralized edge intelligence: A dynamic resource allocation framework for hierarchical federated learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.267726Z

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Observation 902c19ee-eb4f-4795-ad8e-2ecf4cf384d4 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Communication-efficient learning of deep networks from decentralized data,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.248267Z

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Observation 20f0bccc-8ee3-48de-97f8-8b0945bd479f · outbound

This paper cites Federated learning: Challenges, methods, and future directions,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Federated learning: Challenges, methods, and future directions,

Reference 7

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Observation ee1e062d-9cca-48af-b3f4-0a523e2f9521 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Federated optimization in heterogeneous networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.213783Z

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Observation 3b80822f-b009-41b5-8849-b399b3f26a1b · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Scaffold: Stochastic controlled averaging for federated learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.193709Z

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Observation 3de1fcb2-585c-45f9-b00d-93854aa14c4d · outbound

This paper cites Simple baselines for human pose estimation and tracking,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Simple baselines for human pose estimation and tracking,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.168413Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9581aaa2-5e48-445a-8724-8c049f595473 · outbound

This paper cites Vitpose: Simple vision transformer baselines for human pose estimation,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Vitpose: Simple vision transformer baselines for human pose estimation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.150895Z

Source-reported events for the cited work

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Observation c4db34d2-c445-45b6-aa52-98af48cb88a0 · outbound

This paper cites Deep high-resolution repre- sentation learning for human pose estimation,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Deep high-resolution repre- sentation learning for human pose estimation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.131469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 70c6e142-0e83-4b58-a954-3572a0222a22 · outbound

This paper cites Redefining non-iid data in federated learning for computer vision tasks: Migrating from labels to embeddings for task-specific data distributions,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Redefining non-iid data in federated learning for computer vision tasks: Migrating from labels to embeddings for task-specific data distributions,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.108206Z

Source-reported events for the cited work

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Observation 7c07f221-c9df-4ecd-9c53-4388920045c0 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Distilling the Knowledge in a Neural Network

Reference 14

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Observation 9df53b79-6f34-46f7-aaca-63b63b731eb2 · outbound

This paper cites Self-distillation amplifies regularization in hilbert space,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Self-distillation amplifies regularization in hilbert space,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.081235Z

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Observation e26535b3-8d4b-4011-9761-59465c4ba6ff · outbound

This paper cites Revisiting knowledge distillation via label smoothing regularization,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Revisiting knowledge distillation via label smoothing regularization,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.051798Z

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Observation 07ae4827-a764-4bce-8a2c-dcc0837be56c · outbound

This paper cites Resformer: Scaling vits with multi-resolution training,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Resformer: Scaling vits with multi-resolution training,

Reference 17

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Observation 685b76db-80cd-488e-968e-d46ac3184383 · outbound

This paper cites Tackling the ob- jective inconsistency problem in heterogeneous federated optimization,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Tackling the ob- jective inconsistency problem in heterogeneous federated optimization,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:51:00.007675Z

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Observation 5fc9bdbe-7717-43e9-996b-6cd1de48308b · outbound

This paper cites Model-contrastive federated learning,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Model-contrastive federated learning,

Reference 19

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Observation 04d64ab3-c76b-424a-9061-be1ecf083d82 · outbound

This paper cites Feddyn: A dynamic and efficient federated distillation approach on recommender system,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Feddyn: A dynamic and efficient federated distillation approach on recommender system,

Reference 20

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Observation e7572121-5665-476a-8daf-1c66e071b5bd · outbound

This paper cites Attention is all you need,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Attention is all you need,

Reference 21

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Observation 3f723030-8e6d-4d23-8ee5-cf2d17b2c094 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.935836Z

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Observation 952b0054-4065-420a-9417-30b62795e6a9 · outbound

This paper cites GPT-4 Technical Report.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection GPT-4 Technical Report

Reference 23

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Observation e911fdb1-9126-4a69-a4c2-70f462d8dd26 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection LLaMA: Open and Efficient Foundation Language Models

Reference 24

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Observation f6cd316c-689e-4eac-8460-81ee4ac5d8f1 · outbound

This paper cites Large Concept Models: Language Modeling in a Sentence Representation Space.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Large Concept Models: Language Modeling in a Sentence Representation Space

Reference 25

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Observation 4e3d9598-39e3-4da3-8b6b-73039b00eb90 · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection An image is worth 16x16 words: Trans- formers for image recognition at scale,

Reference 26

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Observation 9cdb88e2-7274-4e98-9806-02bc4a3b29e1 · outbound

This paper cites Training data-efficient image transformers & distillation through attention,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Training data-efficient image transformers & distillation through attention,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.902725Z

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Observation 04e2bca0-4900-4c16-9188-0d3cdc22a722 · outbound

This paper cites Scalable diffusion models with transformers,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Scalable diffusion models with transformers,

Reference 28

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Observation c16a4eb3-2c46-48d4-b968-1fa216a88f86 · outbound

This paper cites Dinov2: Learning robust visual features without supervi- sion,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Dinov2: Learning robust visual features without supervi- sion,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.869700Z

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Observation a76f687e-9605-41c8-8739-ad873a2ddc62 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.851113Z

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Observation a5e6459a-8716-4a72-822b-4fb6fa87edf2 · outbound

This paper cites Audiolm: A language modeling approach to audio gen- eration,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Audiolm: A language modeling approach to audio gen- eration,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.832406Z

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Observation c24f7a16-6326-49a9-ad12-9daaf5c69c82 · outbound

This paper cites Ast: Audio spectrogram transformer,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Ast: Audio spectrogram transformer,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.814153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1ca6f2a2-0915-4cd3-841e-8e5aa422c120 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Learning transferable visual models from natural language supervision,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.794825Z

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Observation 925dc212-b911-4f4a-8353-d789d77dc418 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.777101Z

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Observation 5175cd84-3b41-4d1e-919b-e4d8d36429f8 · outbound

This paper cites Visual instruction tuning,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Visual instruction tuning,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.760406Z

Source-reported events for the cited work

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Observation c21fc75f-2b1f-4df7-af2b-9317e9f38c9a · outbound

This paper cites The prospect of enhancing large-scale heterogeneous federated learning with foundation models,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection The prospect of enhancing large-scale heterogeneous federated learning with foundation models,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.745168Z

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Observation 1c208ca9-2b89-42c1-bd65-878d2c3098be · outbound

This paper cites FedYolo: Augmenting Federated Learning with Pretrained Transformers.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection FedYolo: Augmenting Federated Learning with Pretrained Transformers

Reference 37

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Observation 53c3dc91-dcd0-47d7-a14f-c5c043300399 · outbound

This paper cites Deep high-resolution representation learning for visual recognition,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Deep high-resolution representation learning for visual recognition,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.728707Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 46a36c6b-aa04-42b5-aaab-25561eed4359 · outbound

This paper cites Bootstrap your own latent – a new approach to self- supervised learning,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Bootstrap your own latent – a new approach to self- supervised learning,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.710219Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 91962131-793a-4f99-96fe-ae73cce4c088 · outbound

This paper cites On lazy training in differentiable programming,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection On lazy training in differentiable programming,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.689724Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5b8f9e71-51bc-427b-8380-fbcb950f25fb · outbound

This paper cites Gradient descent maximizes the margin of ho- mogeneous neural networks,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Gradient descent maximizes the margin of ho- mogeneous neural networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.672528Z

Source-reported events for the cited work

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Observation 7faf076a-a0ea-4537-9273-a673f4f83da0 · outbound

This paper cites Prevalence of neural collapse during the terminal phase of deep learning training,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Prevalence of neural collapse during the terminal phase of deep learning training,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.654156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6e4c1f47-4e0e-4461-9bc9-18b1ecfccc3a · outbound

This paper cites On the convergence of fedavg on non-iid data,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection On the convergence of fedavg on non-iid data,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.638188Z

Source-reported events for the cited work

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Observation 7220b2bb-4a4a-4cdc-b3da-c52204b96109 · outbound

This paper cites 2d human pose estimation: New benchmark and state of the art analysis,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection 2d human pose estimation: New benchmark and state of the art analysis,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.620779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8d4d7e05-501e-4b98-a5ae-bb0ab72b858b · outbound

This paper cites Deep residual learning for image recognition,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Deep residual learning for image recognition,

Reference 45

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Source-reported events for the cited work

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Observation 33d322c6-fb9a-4a64-a95a-92f7f15c3dae · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Mitigating Resolution-Drift in Federated Learning: Case of Keypoint Detection Fully convolutional networks for semantic segmentation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T10:50:59.593481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.