Paper Citation Record · LEDGER

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning

As of 21 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 1 inbound Pith citation observation for arXiv:2412.14424.

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

pith.paper-citation-record.v1
2412.14424 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:20:30.403902Z

measured 57 of 57 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:53:06.566726Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T18:53:06.872735Z

Reference resolution

56 of 56 outbound references displayed

verified exact2
verified fuzzy6
unresolved47
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e515641-9f96-41ff-ba11-9463d5a6583c · outbound

This paper cites , " * write output.state after.block = add.period write newline.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning , " * write output.state after.block = add.period write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.242361Z

Source-reported events for the cited work

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Observation f956ef5f-3aed-4916-b03d-50ed35d5f969 · outbound

This paper cites write newline.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning write newline

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.245921Z

Source-reported events for the cited work

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Observation da35cb02-9b08-4497-b852-3cc7b1b36a80 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.847674Z

Source-reported events for the cited work

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Observation 2dc10c62-5efe-46f8-a367-a7cf61436b31 · outbound

This paper cites Federated Learning Based on Dynamic Regularization.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Federated Learning Based on Dynamic Regularization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.255924Z

Source-reported events for the cited work

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Observation 31f2d318-66de-42f0-abd8-a48b50b61643 · outbound

This paper cites Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Wasserstein Barycenter-based Model Fusion and Linear Mode Connectivity of Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.259929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5eeb80a1-829a-4939-b550-156a43b84ea4 · outbound

This paper cites L.; and Parikh, D.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning L.; and Parikh, D

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:20:30.838997Z

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 074ffc3c-4f0a-4c5a-8cbd-4a11b4338ec2 · outbound

This paper cites Strong Baselines for Parameter Efficient Few-Shot Fine-tuning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Strong Baselines for Parameter Efficient Few-Shot Fine-tuning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.265408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f04e600-6048-4842-b767-583121649825 · outbound

This paper cites A.; Datla, V.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning A.; Datla, V

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:20:30.830472Z

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 58f06ba8-218d-425c-be31-85433e45acc1 · outbound

This paper cites A.; and M \"u ller, H.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning A.; and M \"u ller, H

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:20:30.821151Z

Source-reported events for the cited work

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Observation ee05de79-b6ac-43a2-8539-3291bf79cc9d · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.811390Z

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 d4ae8ad4-597b-4fdf-af97-b881b4957170 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.801006Z

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 e166c689-a544-4484-9b06-f71b5579555f · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.792809Z

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 ff6cd8b9-8433-4500-8d30-89f3b55f0fd2 · outbound

This paper cites FedTune: A Deep Dive into Efficient Federated Fine-Tuning with Pre-trained Transformers.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning FedTune: A Deep Dive into Efficient Federated Fine-Tuning with Pre-trained Transformers

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9968d47b-c5c8-454f-909d-34a8af192974 · outbound

This paper cites Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.283095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f77eefac-615e-479f-8e1f-59b6945c7b29 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.783403Z

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 905b775f-d285-4e14-b06e-2414c2ec7e81 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.776136Z

Source-reported events for the cited work

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Observation a47762c6-38cb-43af-9992-680398d82b14 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.768907Z

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 9039b58b-6b58-4273-b5e7-eaddd202e869 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.761360Z

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 b07dd179-2fd7-46c0-8899-65e7e71f7bb5 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.298060Z

Source-reported events for the cited work

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Observation 1d6cd34b-6094-4548-b2ee-19a103e6afbf · outbound

This paper cites J.; yelong shen; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning J.; yelong shen; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W

Reference 20

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Source-reported events for the cited work

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Observation 8877f61f-9739-471a-b236-3d5cc36ef564 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.743712Z

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 24748586-3e93-4aa7-b531-43b17f51d745 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.733312Z

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 6fc3b5d2-aa3c-4501-bbd3-369001e4521d · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 23

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Source-reported events for the cited work

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Observation 719132a7-88ce-4edd-9ebe-2cf98eff21ce · outbound

This paper cites P.; Kale, S.; Mohri, M.; Reddi, S.; Stich, S.; and Suresh, A.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning P.; Kale, S.; Mohri, M.; Reddi, S.; Stich, S.; and Suresh, A

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:20:30.719131Z

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 48c43fc1-5bb3-4f5f-82a1-cd7b7aae90f3 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.710235Z

Source-reported events for the cited work

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Observation bc6d7daa-1e3c-4b35-877a-f869e0b7405e · outbound

This paper cites J.; Gayen, S.; Ben Abacha, A.; and Demner-Fushman, D.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning J.; Gayen, S.; Ben Abacha, A.; and Demner-Fushman, D

Reference 26

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Observation 3f97d906-805c-4c85-a3b0-4d497ef07e90 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 27

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Observation 42fd5567-fb0e-4b72-8efd-5571f74ee342 · outbound

This paper cites Visual Prompt Based Personalized Federated Learning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Visual Prompt Based Personalized Federated Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.325801Z

Source-reported events for the cited work

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This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 29

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Observation ffdad44d-7ced-4ccc-951d-020f81b0dab9 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 30

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Observation 170b0863-e7ae-4807-b23c-46eba07f3ab2 · outbound

This paper cites K.; Talwalkar, A.; and Smith, V.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning K.; Talwalkar, A.; and Smith, V

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:20:30.681220Z

Source-reported events for the cited work

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Observation a1525d7b-8a7c-43b4-a65f-cd6c16696339 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 32

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Source-reported events for the cited work

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Observation 612d184d-3862-4d97-9e5d-284f5193eb07 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 33

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Observation 45ded793-557a-4114-b680-2a585ed4a010 · outbound

This paper cites Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning

Reference 34

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Observation 11e7cf04-3ba5-4348-84c6-99631022958a · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 35

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Source-reported events for the cited work

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Observation 31df5c71-7daf-4d6d-a2b0-fcfae830602f · outbound

This paper cites FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning

Reference 36

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Observation ffe4c277-76be-4452-8a26-b88d3f655544 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.662533Z

Source-reported events for the cited work

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Observation ffe2c369-c8c9-4654-971a-155c50e4c868 · outbound

This paper cites FLoRA: Enhancing Vision-Language Models with Parameter-Efficient Federated Learning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning FLoRA: Enhancing Vision-Language Models with Parameter-Efficient Federated Learning

Reference 38

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Source-reported events for the cited work

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Observation 38af04ac-b46c-4905-9698-982b34771a51 · outbound

This paper cites AdapterFusion: Non-Destructive Task Composition for Transfer Learning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning AdapterFusion: Non-Destructive Task Composition for Transfer Learning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.357084Z

Source-reported events for the cited work

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Observation 87ea8de7-9722-411c-a001-27d7cb5a4a93 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.654105Z

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 6023bcbb-3d3b-4da5-b2ae-46a681000568 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.647338Z

Source-reported events for the cited work

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Observation 09aae808-68d5-4add-b946-25dae96b698c · outbound

This paper cites Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.364165Z

Source-reported events for the cited work

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Observation 97db2297-55f4-497f-9802-58832ce468a2 · outbound

This paper cites F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics

Reference 43

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Source-reported events for the cited work

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Observation 0c56e495-d734-451b-a23f-989eaf0aebb5 · outbound

This paper cites P.; and Jaggi, M.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning P.; and Jaggi, M

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:20:30.640237Z

Source-reported events for the cited work

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Observation e156d115-8be9-4cb2-b458-8454bf86b9a3 · outbound

This paper cites Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:20:30.482193Z

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 d71ffe6c-89af-447e-a206-2f9e47c35dfe · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.632607Z

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 56d11a1a-8bff-4d0d-aa50-cf026a310268 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.623955Z

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 42c2233b-cb55-4297-9637-10914f882ea9 · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.615235Z

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 475d16e3-15fd-43eb-8af7-01b9c0fc1fa7 · outbound

This paper cites Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities

Reference 49

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FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 50

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Observation 58200b8a-bfb4-4110-87da-f8c82f2fee71 · outbound

This paper cites Multimodal Federated Learning via Contrastive Representation Ensemble.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Multimodal Federated Learning via Contrastive Representation Ensemble

Reference 51

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Observation 88773e93-f613-4294-a37a-761c51d12918 · outbound

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FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.392209Z

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Observation 548d0957-bd61-47c9-9b97-c7ae96e9c19c · outbound

This paper cites From Recognition to Cognition: Visual Commonsense Reasoning.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning From Recognition to Cognition: Visual Commonsense Reasoning

Reference 53

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This paper cites Open-Vocabulary Federated Learning with Multimodal Prototyping.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Open-Vocabulary Federated Learning with Multimodal Prototyping

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.398450Z

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Observation 5d5ffdd3-cdbf-44fd-81e8-97d6b63a7d8d · outbound

This paper cites an unresolved cited work.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:20:30.597053Z

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This paper cites When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions.

FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-11T12:20:30.403902Z

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Pith citing papers

Observation ab236f6d-066f-445a-b29e-0d3428895b07 · inbound

F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics cites this paper.

F$^3$OCUS -- Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-08-12T18:53:06.879156Z

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