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Paper Citation Record · LEDGER

DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2405.06368.

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

pith.paper-citation-record.v1
2405.06368 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:03:19.312360Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T01:44:30.374665Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation df1c34de-b181-4750-b8ee-9c45eedf809a · inbound

Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models cites this paper.

Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T15:35:30.651284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:35:30.651284Z digest=sha256:c3bff0ce43bfa92cd2c11d408765ee2e566b006c93abd0696ac53c783fda95a3

Observation c36953e8-7620-41b7-b2bb-9c4e32b038a9 · inbound

Federated Large Language Models: Feasibility, Robustness, Security and Future Directions cites this paper.

Federated Large Language Models: Feasibility, Robustness, Security and Future Directions DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 119

Resolution
unresolved
no resolver link, observed 2026-08-15T22:03:19.312360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:03:19.312360Z digest=sha256:b38767382686267f1c573a80322c539cabfa03aeab0136aef80789ccb6caf1ef

Observation edb72cab-4573-489a-81ed-1fa30f92671d · inbound

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? cites this paper.

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks? DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-15T20:31:40.357085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:31:40.357085Z digest=sha256:5f1bd43ecf4e52f5a301ec91ffe6a131e5fb42f6b1b4c2ad070bbc0591f99745

Observation f7e41d73-09ee-4e6e-91eb-0428b14a00d7 · inbound

FedShield-LLM: A Secure and Scalable Federated Fine-Tuned Large Language Model cites this paper.

FedShield-LLM: A Secure and Scalable Federated Fine-Tuned Large Language Model DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-22T01:44:30.376743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-22T01:43:44.406488Z digest=sha256:6530bcee2b919ea7a27fc8318a5e58b13252ac54834dd43b4634931e60c2c0b0

Observation 74063e11-2fcd-4a22-8120-97bc65a464a8 · inbound

Differentially Private Clustered Federated Learning with Privacy-Preserving Initialization and Normality-Driven Aggregation cites this paper.

Differentially Private Clustered Federated Learning with Privacy-Preserving Initialization and Normality-Driven Aggregation DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:29:46.931363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T00:29:43.521902Z digest=sha256:aa38d73251224e6f5f1e7a17b52c7a7f5840e902629b49487a24c948453f5e6c

Observation 684aab1b-71ca-49d1-86ec-68c87d9cd203 · inbound

Toward Efficient Membership Inference Attacks against Federated Large Language Models: A Projection Residual Approach cites this paper.

Toward Efficient Membership Inference Attacks against Federated Large Language Models: A Projection Residual Approach DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-09T22:49:16.397365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-09T22:12:29.249623Z digest=sha256:45c612f5df856417afcdb8170ed9df3a25219bf7023d44b21413c44e449f97a5

Observation 1233cc05-6658-471b-8118-653d9b0f9c8d · inbound

Improving Parameter-Efficient Federated Learning with Differentially Private Refactorization cites this paper.

Improving Parameter-Efficient Federated Learning with Differentially Private Refactorization DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:21:25.383037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T01:13:23.245929Z digest=sha256:a291dcf421d0b85eecb0abd67fbcb0d639f1c41eb9dd077defd1722a6f841c0e

Observation 5cbb91f8-118f-49e3-912d-4a3970552881 · inbound

DP-LAC: Lightweight Adaptive Clipping for Differentially Private Federated Fine-tuning of Language Models cites this paper.

DP-LAC: Lightweight Adaptive Clipping for Differentially Private Federated Fine-tuning of Language Models DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:31:25.435665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T05:11:50.859348Z digest=sha256:29cbd4c204e4987dd270a27acc1a4ffe596aed162814a4a3b10150eef62defc9