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Paper Citation Record · LEDGER

pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2310.13283.

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

pith.paper-citation-record.v1
2310.13283 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:42:38.927051Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation efed6137-f862-4e14-a0ec-99b200f1839f · inbound

Many-Task Federated Fine-Tuning via Unified Task Vectors cites this paper.

Many-Task Federated Fine-Tuning via Unified Task Vectors pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 39

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no resolver link, observed 2026-08-08T15:42:38.927051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:42:38.927051Z digest=sha256:19a8cce90c691ef158c5d4b111439833c72f7c8cdf4e89fb0fe61a046d0cdbb3

Observation 9f46647d-9fed-4505-9f0f-264338aba46d · inbound

AI-in-the-Loop Sensing and Communication Joint Design for Edge Intelligence cites this paper.

AI-in-the-Loop Sensing and Communication Joint Design for Edge Intelligence pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 11

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no resolver link, observed 2026-08-07T19:06:34.325400Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:06:34.325400Z digest=sha256:8b600fec00d5395c7a4c1344909cad4c44dad0847279643ddbd2c6e174cf2084

Observation 5783d2c9-c093-4d08-a8b1-de00eeae7cd1 · inbound

A Survey on Foundation Models for Personalized Federated Intelligence cites this paper.

A Survey on Foundation Models for Personalized Federated Intelligence pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 161

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verified exact
arxiv_id, observed 2026-05-22T15:34:57.832381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T15:32:15.293888Z digest=sha256:bfe44073908b9314f154a57864157bf3651b973d8b7d1a588fbaebd6765e7e34

Observation c4348a06-c253-475e-92d0-cf96b3b1f29b · inbound

FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation cites this paper.

FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 43

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no resolver link, observed 2026-08-07T14:36:21.677787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:36:21.677787Z digest=sha256:562e66958f8916e19d678d94043a740904c6999c823e3c82a50087b7c6c031af

Observation 9e08e8e9-fb8c-48c3-83cd-29e8c2cc37bd · inbound

DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models cites this paper.

DeCAF: Decentralized Consensus-And-Factorization for Low-Rank Adaptation of Foundation Models pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 20

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no resolver link, observed 2026-08-07T13:42:46.689800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:42:46.689800Z digest=sha256:ca719ae162496efd5634987847100b0d83bea20f6ec3c021a7ecbe0d82e8e57d

Observation 0047f39b-76cf-4c92-9bc7-602f9159a942 · inbound

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA cites this paper.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 91

Resolution
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no resolver link, observed 2026-08-07T11:57:25.407448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.407448Z digest=sha256:208c4977a2904ef47829787057991c7d08e175f524e48c02ef81425cc74a1660

Observation 9a7a39a3-a973-4c5f-b328-f240de099609 · inbound

FedNano: Toward Lightweight Federated Tuning for Pretrained Multimodal Large Language Models cites this paper.

FedNano: Toward Lightweight Federated Tuning for Pretrained Multimodal Large Language Models pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 30

Resolution
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no resolver link, observed 2026-08-07T04:18:32.419377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:18:32.419377Z digest=sha256:dc7a886a2be55a30ca97b874f6d28c29cbb5256354863958f242a16e85fdf8c2

Observation 44a6a76e-799a-4d98-91c3-4c54004c57c8 · inbound

A New Pathway to Integrated Learning and Communication (ILAC): Large AI Model and Hyperdimensional Computing for Communication cites this paper.

A New Pathway to Integrated Learning and Communication (ILAC): Large AI Model and Hyperdimensional Computing for Communication pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 85

Resolution
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no resolver link, observed 2026-08-06T23:20:52.818307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:20:52.818307Z digest=sha256:cc25e77cd8808f6bc3ffcc89957f9a88976e4235bb49c3fcb34e96ec90dd5f6c

Observation 51e82633-3e6c-48fb-bc1d-3885e73d7253 · inbound

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity cites this paper.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 39

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unresolved
no resolver link, observed 2026-08-06T11:37:42.938314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:37:42.938314Z digest=sha256:75675d1a90723f3cceeca21c24ccd9f8c52214683a28f8b9dade162da8b0687f

Observation 859e7550-2011-4ccb-abfd-d5861bb8a326 · inbound

Convergence Analysis of Aggregation-Broadcast in LoRA-enabled Distributed Fine-Tuning cites this paper.

Convergence Analysis of Aggregation-Broadcast in LoRA-enabled Distributed Fine-Tuning pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 34

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no resolver link, observed 2026-08-06T05:47:56.706388Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:47:56.706388Z digest=sha256:bbb4342e68085d2d74920bfee9a895ddd9cae1c10283b391fe5dba53109eda1c

Observation be8594b7-7976-473c-a935-59d1f0d7bb4d · inbound

FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints cites this paper.

FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-21T22:00:41.048937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-21T21:58:12.430340Z digest=sha256:ce18facf2061e6eaa29aac24d800c800532f87fe5c30ee453d65f04b17e072ca

Observation 6d926b82-54ac-4214-9eea-e07015f7676c · inbound

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion cites this paper.

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 82

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:56:05.943226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T02:35:40.593397Z digest=sha256:b3c04433e42425163caf045f6131a75046e269a4fd1c670f50b1b6e69ee8503b

Observation 04674954-0028-4266-89df-e22cce8421bf · inbound

Adaptive Selection of LoRA Components in Privacy-Preserving Federated Learning cites this paper.

Adaptive Selection of LoRA Components in Privacy-Preserving Federated Learning pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:41:09.268036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T14:50:12.857642Z digest=sha256:0692ba73130d622807d28cdd8dd5de50be642f047e3fbed922856875419236d9

Observation a8c4b1c8-7500-4ce1-87b7-0c82d5524e70 · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:16:27.496171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T04:26:50.410397Z digest=sha256:681aa38dec265792a46dd7d8f867639cb44cdabef296c4f29d0a5806927504c4

Observation 2f8e6630-3611-41c1-96f4-ee97d0b5b9b7 · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:23:47.963447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T22:21:03.637418Z digest=sha256:664500980550867934af2d8b01b1b14fb15815917489e84a15bb507eb108ea42

Observation 5a19f077-6def-46e6-a371-7157702168c1 · inbound

FedSDR: Federated Self-Distillation with Rectification cites this paper.

FedSDR: Federated Self-Distillation with Rectification pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T12:18:16.307225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-20T12:18:10.362573Z digest=sha256:b9e74974f149ea93bf264fb999c61dc387a9ef7b2f052ba0c903f403514b0a1f

Observation bf1eeb4e-4da7-40fd-b203-265c4687d866 · inbound

Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation cites this paper.

Shift-Dependent Asymmetry: Orthogonal Inverse Low-Rank Adaptation for Federated Medical Segmentation pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 80

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arxiv_id, observed 2026-07-02T23:07:27.012327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T18:27:47.338007Z digest=sha256:4b6db3693face5ca3e5943e2c7f3eaa9d6b204e56f8eec7bc031a4caeca7755a

Observation c19a935e-8252-44b3-99d7-3ac1812f742d · inbound

Dysco: Dynamic Subspace Boosting to Mitigate LoRA Interference in Federated Learning cites this paper.

Dysco: Dynamic Subspace Boosting to Mitigate LoRA Interference in Federated Learning pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 48

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no resolver link, observed 2026-08-02T02:23:31.403903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T02:23:31.403903Z digest=sha256:50676dd925a6560469f7cb65f507c876a9fdf6e5d7cd5dad2524c8ffae8efe92

Observation 9ec82f62-bce2-4826-9e20-b4df55ea28e3 · inbound

LAARA: Layer-Aware Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning cites this paper.

LAARA: Layer-Aware Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 75

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no resolver link, observed 2026-08-02T09:01:51.169227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T09:01:51.169227Z digest=sha256:b33a4e40dc1b15d4f1300f9498c797d173a1a591a7c0aac17c63d84932b416aa

Observation af1b5c7c-4115-45bc-9ebe-5bf1174286da · inbound

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense cites this paper.

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 19

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no resolver link, observed 2026-08-01T12:07:44.278166Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:07:44.278166Z digest=sha256:8fdd976a928d924bb563865820b3f0dca523f3aa12680a110a9b052ef6cc23e2

Observation acef721a-b04a-48af-bee3-934db06a1a94 · inbound

Rethinking Personalized Reward Modeling for LLMs under Preference Heterogeneity via Group-Debiased Federated Learning cites this paper.

Rethinking Personalized Reward Modeling for LLMs under Preference Heterogeneity via Group-Debiased Federated Learning pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 53

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no resolver link, observed 2026-08-07T00:14:24.328798Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:14:24.328798Z digest=sha256:e3a5050c0447cb3323734fc7ca2c5c9aa4ad9985f2bb3eba594056ae32a5c37f