Paper Citation Record · LEDGER

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching

As of 21 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2506.08518.

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

pith.paper-citation-record.v1
2506.08518 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:14:33.918662Z

measured 61 of 61 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T19:02:26.047252Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T06:05:34.771915Z

Reference resolution

60 of 60 outbound references displayed

verified exact2
verified fuzzy46
unresolved12
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 049ab2c1-7057-4d49-a899-5ddf2fee8bab · outbound

This paper cites Towards principled disentanglement for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Towards principled disentanglement for domain generalization

Reference 1

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Observation e4948baf-b37a-4262-87c0-d2c844b01c7c · outbound

This paper cites Learning to learn single domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Learning to learn single domain generalization

Reference 2

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Observation b960ed0f-a46b-4410-b682-75606604d479 · outbound

This paper cites Balaji, S.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Balaji, S

Reference 3

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Observation 45f1851f-bc09-4ca4-b1bf-034e67bd1c57 · outbound

This paper cites Domain generalization via invariant feature representation.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generalization via invariant feature representation

Reference 4

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Observation 98558007-f53a-4082-b05f-95da822cff35 · outbound

This paper cites Learning to generalize: Meta-learning for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Learning to generalize: Meta-learning for domain generalization

Reference 5

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Observation 55b055e9-3dda-4323-8985-4fdf34e410cc · outbound

This paper cites Semantic data augmentation based distance metric learning for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Semantic data augmentation based distance metric learning for domain generalization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.798446Z

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Observation 71d5530c-e960-47f2-9957-4503cf5b4d07 · outbound

This paper cites Domain generalization via entropy regularization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generalization via entropy regularization

Reference 7

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Observation dff43189-9484-4ab7-9207-28aa9504987a · outbound

This paper cites Sharpness-Aware Minimization for Efficiently Improving Generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Sharpness-Aware Minimization for Efficiently Improving Generalization

Reference 8

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Observation b6219562-3f00-4476-a594-64a5450711c9 · outbound

This paper cites Escaping saddle points for effective generalization on class-imbalanced data.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Escaping saddle points for effective generalization on class-imbalanced data

Reference 9

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Observation c88b8ab5-5d33-4087-97eb-e693c751260f · outbound

This paper cites Domain adaptation for semantic segmentation with maximum squares loss.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain adaptation for semantic segmentation with maximum squares loss

Reference 10

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Observation ce2f4981-86a5-4c26-ae65-e67196f5324c · outbound

This paper cites Semi-supervised learning by entropy minimization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Semi-supervised learning by entropy minimization

Reference 11

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Source-reported events for the cited work

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Observation eb2cfc73-0c12-40ec-9167-7ced98b2dea5 · outbound

This paper cites Domain-adversarial training of neural networks.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain-adversarial training of neural networks

Reference 12

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Observation 1e695509-688e-45c1-a396-36a594e51f9e · outbound

This paper cites Domain generalization with adversarial feature learning.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generalization with adversarial feature learning

Reference 13

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Observation 20f3af28-9173-4d47-bb5c-6fab277f8a93 · outbound

This paper cites Learning de-biased represen- tations with biased representations.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Learning de-biased represen- tations with biased representations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.700842Z

Source-reported events for the cited work

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Observation c2b004dc-70bf-42a9-8063-29b57f2d02b8 · outbound

This paper cites Adaptive risk minimization: Learning to adapt to domain shift.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Adaptive risk minimization: Learning to adapt to domain shift

Reference 15

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Observation d3f68e51-e5b6-456e-8603-00c3ebed5efe · outbound

This paper cites Domain generalization via model-agnostic learning of semantic features.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generalization via model-agnostic learning of semantic features

Reference 16

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Observation d8ebe0ad-83fe-41ff-bba6-cc6e684fac6b · outbound

This paper cites Domain adaptive ensemble learning.IEEE Transactions on Image Processing, 30:8008–8018, 2021.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain adaptive ensemble learning.IEEE Transactions on Image Processing, 30:8008–8018, 2021

Reference 17

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Observation 31c0ca77-c1f5-4774-81e2-55455ad58872 · outbound

This paper cites Generalizing across domains via cross-gradient training.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Generalizing across domains via cross-gradient training

Reference 18

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Observation f63bc897-6f9f-407b-914b-8264a665dbd9 · outbound

This paper cites Domain generaliza- tion by solving jigsaw puzzles.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generaliza- tion by solving jigsaw puzzles

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.616066Z

Source-reported events for the cited work

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Observation f6f2ef75-3df7-48de-a5f8-2f6d409da64c · outbound

This paper cites Domain agnostic learning with disentangled representations.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain agnostic learning with disentangled representations

Reference 20

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Observation b49badf1-1bcf-4da7-8a7a-72acef56ed3e · outbound

This paper cites Undoing the damage of dataset bias.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Undoing the damage of dataset bias

Reference 21

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Observation 7610cc33-24a6-4f98-82e4-498431857262 · outbound

This paper cites Cross-domain face presentation attack detection via multi-domain disentangled representation learning.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Cross-domain face presentation attack detection via multi-domain disentangled representation learning

Reference 22

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Observation 0613829f-86d2-4ff9-bd99-934b15c2cba4 · outbound

This paper cites Out-of-distribution generalization via risk extrapolation (rex).

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Out-of-distribution generalization via risk extrapolation (rex)

Reference 23

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Observation 40ace62e-f138-495c-b298-1dbfc7ba01e9 · outbound

This paper cites Invariant Risk Minimization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Invariant Risk Minimization

Reference 24

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Observation 474a707e-2d33-4ae3-8b64-b6ce258d0474 · outbound

This paper cites Domain generalization via gradient surgery.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generalization via gradient surgery

Reference 25

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Observation b05dead3-8db3-45a5-a970-eb8d3bfe2316 · outbound

This paper cites Towards efficient and scalable sharpness- aware minimization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Towards efficient and scalable sharpness- aware minimization

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.526232Z

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Observation fea65bef-241c-4e69-9eac-953206a2b205 · outbound

This paper cites Efficient Sharpness-aware Minimization for Improved Training of Neural Networks.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Efficient Sharpness-aware Minimization for Improved Training of Neural Networks

Reference 27

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Observation 624d08ff-0bab-431f-b254-902ccb16c0d0 · outbound

This paper cites Simplifying neural nets by discovering flat minima.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Simplifying neural nets by discovering flat minima

Reference 28

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Observation 9bc757ae-6693-4fa7-8a77-e6b961accbbe · outbound

This paper cites On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima

Reference 29

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FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Sharp minima can generalize for deep nets

Reference 30

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Observation 3ef41c5d-ed87-4503-9f54-ae30f022e98e · outbound

This paper cites Swad: Domain generalization by seeking flat minima.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Swad: Domain generalization by seeking flat minima

Reference 31

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Observation fc415053-421e-49c3-aa1f-051447aad58e · outbound

This paper cites Learning from extrinsic and intrinsic supervisions for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Learning from extrinsic and intrinsic supervisions for domain generalization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.468869Z

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Observation 22e5d78b-a814-4c13-a669-78815dd068c3 · outbound

This paper cites Sharpness-aware model-agnostic long-tailed domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Sharpness-aware model-agnostic long-tailed domain generalization

Reference 33

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Observation 46685b49-5f13-4106-8694-67bb794b4d7b · outbound

This paper cites Unsupervised domain adaptation by backpropagation.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Unsupervised domain adaptation by backpropagation

Reference 34

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Observation 2f162ac7-b821-4081-b6b7-a28920f7efd8 · outbound

This paper cites Sharpness-aware gradient matching for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Sharpness-aware gradient matching for domain generalization

Reference 35

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Observation deb4f385-a706-4e40-bd71-85b73c7f2fff · outbound

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FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Unresolved cited work

Reference 36

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This paper cites Deep hashing network for unsupervised domain adaptation.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Deep hashing network for unsupervised domain adaptation

Reference 37

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This paper cites Learning to generate novel domains for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Learning to generate novel domains for domain generalization

Reference 38

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FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Unresolved cited work

Reference 39

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FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching D’Innocente and B

Reference 40

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FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Statistical learning theory

Reference 41

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FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Epi-fcr: Episodic fine-grained cross-domain few-shot learning via feature calibration and relation alignment

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.314533Z

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Observation 0c41da8d-6f21-49b8-8d6f-96faf6780fd9 · outbound

This paper cites Heterogeneous Domain Generalization via Domain Mixup.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Heterogeneous Domain Generalization via Domain Mixup

Reference 43

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FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Hospedales

Reference 44

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Observation 4f740510-5d49-4c10-8a07-c193ce50e733 · outbound

This paper cites Embracing the dark knowledge: Domain generalization using regularized knowledge distillation.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Embracing the dark knowledge: Domain generalization using regularized knowledge distillation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.284691Z

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Observation a82e41f5-62f9-4432-b30a-1aff62c846e3 · outbound

This paper cites Symmetric self-paced learning for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Symmetric self-paced learning for domain generalization

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.270457Z

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This paper cites Domain generalization via entropy regularization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generalization via entropy regularization

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.254493Z

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Observation a15aae32-ee7c-4c3b-8822-a565ff1076c4 · outbound

This paper cites Deep domain-adversarial image generation for domain generalisation.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Deep domain-adversarial image generation for domain generalisation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.239549Z

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Observation 81a27670-fa20-4c41-973a-9c0f3d9416df · outbound

This paper cites A sentence speaks a thousand images: Domain generalization through distilling clip with language guidance.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching A sentence speaks a thousand images: Domain generalization through distilling clip with language guidance

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.225322Z

Source-reported events for the cited work

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Observation 705798bf-813f-409c-b95f-f77d858cf6a9 · outbound

This paper cites Self-challenging improves cross-domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Self-challenging improves cross-domain generalization

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.210556Z

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 121d3a4a-1496-4d65-8b01-a60b25ac8434 · outbound

This paper cites A fourier-based framework for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching A fourier-based framework for domain generalization

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.195363Z

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Observation 1d578ede-5da4-4d46-a712-b6a3afad2cf8 · outbound

This paper cites Domain generalization using causal matching.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generalization using causal matching

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.179536Z

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Observation ae645b15-f1e4-4002-9823-c88610f2eca6 · outbound

This paper cites Feature stylization and domain-aware contrastive learning for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Feature stylization and domain-aware contrastive learning for domain generalization

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.162374Z

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Observation 2941771e-6d2e-4ea4-998a-669e111754d1 · outbound

This paper cites Domain generalization via frequency-domain-based feature disentanglement and interaction.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Domain generalization via frequency-domain-based feature disentanglement and interaction

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.146669Z

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 82655380-a728-4780-8b85-f4dcab1e3594 · outbound

This paper cites Pcl: Proxy- based contrastive learning for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Pcl: Proxy- based contrastive learning for domain generalization

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.129116Z

Source-reported events for the cited work

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Observation 3dc4ab31-a8e1-412e-adf6-c7da7fb3d710 · outbound

This paper cites Style neophile: Constantly seeking novel styles for domain generalization.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Style neophile: Constantly seeking novel styles for domain generalization

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.113355Z

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Observation 5df3bf79-52b5-42e5-8d02-dd80e0265a00 · outbound

This paper cites Improving generalization with domain convex game.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Improving generalization with domain convex game

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.095730Z

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Observation 2035e985-53d2-4a44-b5e7-3f7d37af44db · outbound

This paper cites Deep residual learning for image recognition.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Deep residual learning for image recognition

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:14:34.079327Z

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Observation 9ad99fd5-1ac7-43db-968f-3da2e5d6b479 · outbound

This paper cites an unresolved cited work.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:14:34.063536Z

Source-reported events for the cited work

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Observation 94863eb9-73ad-4d8f-b2c3-0079878c0b36 · outbound

This paper cites A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance.

FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:14:33.963512Z

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Pith citing papers

Observation b082e14c-4dd9-4a28-8cb7-09cbe3f55694 · inbound

Manifold-Constrained Adversarial Training for Long-Tailed Robustness via Geometric Alignment cites this paper.

Manifold-Constrained Adversarial Training for Long-Tailed Robustness via Geometric Alignment FEDTAIL: Federated Long-Tailed Domain Generalization with Sharpness-Guided Gradient Matching

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:05:34.773826Z

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.