EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models | Paper Citation Record

Observation 40531e69-5158-4c02-82d2-26ea2b0c9060 · outbound

This paper cites Deep learning with differential privacy.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Deep learning with differential privacy

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:42.875887Z

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Observation 3e74ee74-17ae-454d-9e1f-27443cbf526b · outbound

This paper cites FedPromo : Federated lightweight proxy models at the edge bring new domains to foundation models.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models FedPromo : Federated lightweight proxy models at the edge bring new domains to foundation models

Reference 2

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Observation eb2f6dcd-47bf-4658-b934-7e8fa3b61348 · outbound

This paper cites Eclipse mosquitto [software].

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Eclipse mosquitto [software]

Reference 3

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Observation bf27f08e-4865-4b2a-9eb4-54fab0ecffeb · outbound

This paper cites Graphana dashboard [software].

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Graphana dashboard [software]

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:42.672422Z

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Observation 06b0a2f6-b349-4736-9c3d-7da968a07298 · outbound

This paper cites Prometheus [software].

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Prometheus [software]

Reference 5

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Observation b1e4b720-272c-4c32-b7ab-21872089341b · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 6

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Observation 79da9d41-f3d3-4b66-9ec6-ac7c892f9fc2 · outbound

This paper cites Sonoff [hardware].

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Sonoff [hardware]

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:42.620550Z

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Observation 03d47e1e-e105-4da7-a375-c37235924d28 · outbound

This paper cites Tasmota firmware [software].

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Tasmota firmware [software]

Reference 8

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Observation a629a110-c82c-45b1-82f1-02a2be72ec5c · outbound

This paper cites Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory

Reference 9

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Observation c442bccf-8d62-4d2b-9104-e5b21259da72 · outbound

This paper cites SL o RA : Federated parameter efficient fine-tuning of language models.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models SL o RA : Federated parameter efficient fine-tuning of language models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:42.539456Z

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Observation fad7fd5a-c1af-4589-b42a-e40a1cbb1e0e · outbound

This paper cites Cross-architecture auxiliary feature space translation for efficient few-shot personalized object detection.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Cross-architecture auxiliary feature space translation for efficient few-shot personalized object detection

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:42.484042Z

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Observation 0458461b-23be-4c4c-ba75-fe52ae1e94c9 · outbound

This paper cites Flower: A Friendly Federated Learning Research Framework.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Flower: A Friendly Federated Learning Research Framework

Reference 12

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Observation 3d788904-5ba0-4bcb-9d6e-9cdbae25a05e · outbound

This paper cites Food-101--mining discriminative components with random forests.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Food-101--mining discriminative components with random forests

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:42.405768Z

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Observation 274e2d23-81b5-4e50-901f-112d994d2ecb · outbound

This paper cites Emerging properties in self-supervised vision transformers.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Emerging properties in self-supervised vision transformers

Reference 14

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Observation 6efa2daa-2493-4307-9097-5e8652cb5256 · outbound

This paper cites On the importance and applicability of pre-training for federated learning.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models On the importance and applicability of pre-training for federated learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:42.240823Z

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Observation cc94b1c7-e0a5-4e2b-89e1-96cfd569277e · outbound

This paper cites Fair federated learning under domain skew with local consistency and domain diversity.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Fair federated learning under domain skew with local consistency and domain diversity

Reference 16

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Observation 138ed5df-2f0e-49f7-94d5-3a76049b9fee · outbound

This paper cites an unresolved cited work.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Unresolved cited work

Reference 17

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Observation 7709e38d-70a1-4ff4-850d-ed3b9a5c6348 · outbound

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

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 18

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Observation 82f72d7d-e8a7-4e65-87ac-1ff09e5d8ec8 · outbound

This paper cites Source-Free Unsupervised Domain Adaptation: A Survey.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Source-Free Unsupervised Domain Adaptation: A Survey

Reference 19

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Observation 37767a9a-6656-4a48-b6cc-c5b2144a529d · outbound

This paper cites Evaluating federated dino’s performance on the segmentation task across diverse domains.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Evaluating federated dino’s performance on the segmentation task across diverse domains

Reference 20

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Observation 47467b8e-9ac1-40eb-8889-75c2def835f1 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Distilling the Knowledge in a Neural Network

Reference 21

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Observation e6bb6a5f-5e2f-45d7-b0f9-8a58cd442f21 · outbound

This paper cites Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer

Reference 22

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Observation 9f822ab3-2d6c-4c3e-9f43-6d398fc86489 · outbound

This paper cites Searching for mobilenetv3.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Searching for mobilenetv3

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:42.068819Z

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Observation aea0cf74-2f93-4fa0-8800-4100b86d84ce · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 24

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Observation edd75ac8-2024-45ab-9155-b4f00a8d2ab8 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Lora: Low-rank adaptation of large language models

Reference 25

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Observation 415691c4-c757-4e5d-99fc-59cb7fbc35f3 · outbound

This paper cites Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

Reference 26

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Observation 6cc138a3-b33a-4afb-91e1-45684d79a948 · outbound

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

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Scaffold: Stochastic controlled averaging for federated learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T00:28:36.194748Z

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Observation 89a63be8-2cf4-482d-8267-7d26d450175a · outbound

This paper cites Kawano and K.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Kawano and K

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:41.884747Z

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Observation f3e86ccf-5806-4044-a2c8-63d296779728 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick

Reference 29

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Observation 77495845-fcff-4c1b-9198-232da3eccda6 · outbound

This paper cites 3d object representations for fine-grained categorization.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models 3d object representations for fine-grained categorization

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:41.724753Z

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Observation f188946d-d433-43dd-8ce0-378daf753248 · outbound

This paper cites FedMD: Heterogenous Federated Learning via Model Distillation.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models FedMD: Heterogenous Federated Learning via Model Distillation

Reference 31

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Observation 7d602572-d44c-4464-8038-05ce2511ea2c · outbound

This paper cites Model-contrastive federated learning.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Model-contrastive federated learning

Reference 32

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Observation 31779f62-9de5-4e82-b664-7bb5605e0cba · outbound

This paper cites Federated optimization in heterogeneous networks.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Federated optimization in heterogeneous networks

Reference 33

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Observation 86c2cdd4-bcd4-4c69-982b-45af05223aa5 · outbound

This paper cites Fedfms: Exploring federated foundation models for medical image segmentation.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Fedfms: Exploring federated foundation models for medical image segmentation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:41.406876Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9d68f028-9bb8-4437-b8da-20bb28d29589 · outbound

This paper cites Fedclip: Fast generalization and personalization for clip in federated learning.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Fedclip: Fast generalization and personalization for clip in federated learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:41.304748Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 318d69b5-6475-42b9-87e6-d87e3af23b70 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Fine-Grained Visual Classification of Aircraft

Reference 36

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Observation a8c096f4-5ba5-4d8d-a3a8-868c8a03114c · outbound

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

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Communication-efficient learning of deep networks from decentralized data

Reference 37

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Observation 683e8e55-4a52-4c7b-88a8-e0a3d850b45b · outbound

This paper cites Nakamura.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Nakamura

Reference 38

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1bf94387-7a35-45ed-9f38-748c965acac0 · outbound

This paper cites Where to begin? on the impact of pre-training and initialization in federated learning.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Where to begin? on the impact of pre-training and initialization in federated learning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:41.113663Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 08c6bcfe-da7a-44b9-a692-b04ff8bb8e7c · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models DINOv2: Learning Robust Visual Features without Supervision

Reference 40

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Observation 3a2662ef-1dcb-4ffc-ab9e-fbdb3b3ad0ef · outbound

This paper cites Continual learning with foundation models: An empirical study of latent replay.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Continual learning with foundation models: An empirical study of latent replay

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:41.014614Z

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Observation 2541a3d5-805f-4123-a90e-e9219ec63741 · outbound

This paper cites Cats and dogs.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Cats and dogs

Reference 42

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Observation 759dfcf5-0717-4d66-8d2e-91bb8dce4d1e · outbound

This paper cites Pytorch framework [software].

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Pytorch framework [software]

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:40.736887Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4c933397-a764-42b2-bc9b-24d5dffbf9c2 · outbound

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

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Learning transferable visual models from natural language supervision

Reference 44

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Observation a28e95e2-67e2-46d3-b522-b2c53bbd2b08 · outbound

This paper cites Advances and open challenges in federated foundation models.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Advances and open challenges in federated foundation models

Reference 45

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ab73c70e-650a-4f57-8ea1-cde4fc5064b9 · outbound

This paper cites Fedaux: Leveraging unlabeled auxiliary data in federated learning.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Fedaux: Leveraging unlabeled auxiliary data in federated learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:40.697271Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7b68b850-76ae-4bf1-9569-0e3402e7f73c · outbound

This paper cites Learning across domains and devices: Style-driven source-free domain adaptation in clustered federated learning.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Learning across domains and devices: Style-driven source-free domain adaptation in clustered federated learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:40.683449Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a4e95fc5-a274-40c8-a212-9b2e7b3abf31 · outbound

This paper cites Federated learning in computer vision.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Federated learning in computer vision

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:40.570739Z

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Observation 2b780640-0b6c-482d-8025-cc5542f71487 · outbound

This paper cites Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Reference 49

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Observation 3c3a00b2-32c2-4505-beed-88acec165074 · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T00:28:37.136982Z

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Observation 8f39a113-ce9c-4c38-b4dd-e234b50ae3c4 · outbound

This paper cites Torchvision: Pytorch's computer vision library [software].

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Torchvision: Pytorch's computer vision library [software]

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:40.352207Z

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Observation 2846e922-6c8c-484b-a126-538214e124c8 · outbound

This paper cites Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:40.202294Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 63b18569-5d6c-4781-b5e3-ca6ba4dc7651 · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models The caltech-ucsd birds-200-2011 dataset

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:40.055478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 33c3f455-0858-4a2e-abac-4b36cc2380d4 · outbound

This paper cites Tinyvit: Fast pretraining distillation for small vision transformers.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Tinyvit: Fast pretraining distillation for small vision transformers

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:39.934753Z

Source-reported events for the cited work

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Observation 7cf0adce-3a4b-49c5-89e5-12f3f42c6d3b · outbound

This paper cites Exploring the distributed knowledge congruence in proxy-data-free federated distillation.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Exploring the distributed knowledge congruence in proxy-data-free federated distillation

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:39.910648Z

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Observation 32449322-657f-4d1d-834f-2b6af007a73a · outbound

This paper cites A large-scale car dataset for fine-grained categorization and verification.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models A large-scale car dataset for fine-grained categorization and verification

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:39.787059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6b236a0e-05b2-45b9-bd80-c7513ca7ab2f · outbound

This paper cites Fedgkd: Toward heterogeneous federated learning via global knowledge distillation.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Fedgkd: Toward heterogeneous federated learning via global knowledge distillation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:39.554986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6f1b8b86-8b6c-466f-ad48-830d84145107 · outbound

This paper cites pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T00:28:37.401493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33ed6c22-b186-49d6-bd0b-8cc4a26f705c · outbound

This paper cites Decentralized federated learning: A survey and perspective.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Decentralized federated learning: A survey and perspective

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:39.412453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 58eead70-546b-458b-9e71-bdaaa89c4f94 · outbound

This paper cites Fedzkt: Zero-shot knowledge transfer towards resource-constrained federated learning with heterogeneous on-device models.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Fedzkt: Zero-shot knowledge transfer towards resource-constrained federated learning with heterogeneous on-device models

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:39.361532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 451bc0f0-5e4f-4a72-8945-b959ba5a281a · outbound

This paper cites Data-free knowledge distillation for heterogeneous federated learning.

EFFEKT: Efficient Federated Knowledge Transfer to Foundation Models Data-free knowledge distillation for heterogeneous federated learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:28:39.294745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers