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Paper Citation Record · LEDGER

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA

As of 18 August 2026, this Paper Citation Record lists 97 of 97 outbound references and 0 inbound Pith citation observations for arXiv:2506.01194.

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

pith.paper-citation-record.v1
2506.01194 v1

Coverage vector

measured 97 of 97 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:57:25.432956Z

measured 97 of 97 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

97 of 97 outbound references displayed

  • verified exact4
  • verified fuzzy45
  • unresolved48
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation a3330144-5d95-46bb-ae23-4bde854e8133 · outbound

This paper cites SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA SLoRA: Federated Parameter Efficient Fine-Tuning of Language Models

Reference 1

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source=pdf_text observed=2026-08-07T11:57:24.919860Z digest=sha256:f1d0beced943cccefe2d30db91cbc7cbf34ccdec5e863d82645b0d5942d8e67b

Observation 6f57010f-4df7-434a-bbc3-2893d74b5313 · outbound

This paper cites Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources

Reference 2

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Observation d18c249d-91cf-4fb1-8aaf-0ea5f8dd17ac · outbound

This paper cites Fedalt: Federated fine-tuning through adaptive local training with rest-of-the-world lora.arXiv preprint arXiv:2503.11880, 2025.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Fedalt: Federated fine-tuning through adaptive local training with rest-of-the-world lora.arXiv preprint arXiv:2503.11880, 2025

Reference 3

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Observation e79334de-5c73-43e3-931b-53964c03b9d1 · outbound

This paper cites Lora-fair: Federated lora fine-tuning with aggregation and initialization refinement, 2025.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Lora-fair: Federated lora fine-tuning with aggregation and initialization refinement, 2025

Reference 4

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source=pdf_text observed=2026-08-07T11:57:24.937144Z digest=sha256:392a9c7929903ca79a1a2b5462d0f0cf3874b625237438643a78f459be78d975

Observation 5864e8dd-2103-4cf0-94ef-6d09ea7c52ea · outbound

This paper cites Boerner, Stephen Deems, Thomas R.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Boerner, Stephen Deems, Thomas R

Reference 5

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source=pdf_text observed=2026-08-07T11:57:24.942285Z digest=sha256:f5ec733408212705645efb8c17a717afbc12d62da850c8da090f7a647056a877

Observation e4c24417-a62e-45b8-b111-9702c35f2664 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA On the Opportunities and Risks of Foundation Models

Reference 6

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Observation b0ea9cf9-c1ed-4f03-a901-cf624ede8d8f · outbound

This paper cites On the applications of robust pca in image and video processing.Proceedings of the IEEE, 106(8):1427–1457, 2018.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA On the applications of robust pca in image and video processing.Proceedings of the IEEE, 106(8):1427–1457, 2018

Reference 7

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source=pdf_text observed=2026-08-07T11:57:24.953702Z digest=sha256:8ba656f09bf101b67cb1742d75d16e75cf7d0a52ee9b92b23fe4d9ca83e1dc30

Observation 5e9b2697-af2a-42ab-8478-e88346efc5c7 · outbound

This paper cites Robust pca via principal component pursuit: A review for a comparative evaluation in video surveillance.Computer Vision and Image Understanding, 122:22–34, 2014.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Robust pca via principal component pursuit: A review for a comparative evaluation in video surveillance.Computer Vision and Image Understanding, 122:22–34, 2014

Reference 8

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source=pdf_text observed=2026-08-07T11:57:24.958449Z digest=sha256:dbbf592c7c39d092b4db7d3e619c4dea4a6852ecfd40da2a3e233b5f772503e4

Observation 493be5f1-6e31-4b55-9a6e-2e3df7a51f7b · outbound

This paper cites Distributed optimization and statistical learning via the alternating direction method of multipliers.Foundations and Trends® in Machine Learning, 3(1):1–122, 2011.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Distributed optimization and statistical learning via the alternating direction method of multipliers.Foundations and Trends® in Machine Learning, 3(1):1–122, 2011

Reference 9

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source=pdf_text observed=2026-08-07T11:57:24.963049Z digest=sha256:3c12294fc2c242b076c67915d6d7d2a2f9f1bb9a23e9e8a14e38d6bc67114482

Observation 76c5980b-2ea0-42f5-aea4-df8937041a6b · outbound

This paper cites Language models are few-shot learners.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Language models are few-shot learners

Reference 10

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source=pdf_text observed=2026-08-07T11:57:24.967901Z digest=sha256:296c9f06e4949053c361fdc628a9fe212447a66dfa54e81670461b115cd7c3cd

Observation 40694044-aad4-4f51-92aa-8accb432901c · outbound

This paper cites X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular Design.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular Design

Reference 11

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source=pdf_text observed=2026-08-07T11:57:24.974005Z digest=sha256:66b7a502b7b495e0287251e035f79b2a2fe050ea803edb99c7cd07ba515030aa

Observation 9254b4a3-c7c4-4d5f-a1da-b117798e033f · outbound

This paper cites Learned robust PCA: A scalable deep unfolding approach for high-dimensional outlier detection.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Learned robust PCA: A scalable deep unfolding approach for high-dimensional outlier detection

Reference 12

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source=pdf_text observed=2026-08-07T11:57:24.979341Z digest=sha256:ec0662196c243e86ab5a1c4a95fd135c2c24d83e07fee90437e59f74aaf6f1ee

Observation 157f51e6-6455-43a3-b030-f4ac4f54023a · outbound

This paper cites Robust principal component analysis? Journal of the ACM (JACM), 58(3):1–37, 2011.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Robust principal component analysis? Journal of the ACM (JACM), 58(3):1–37, 2011

Reference 13

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Observation 5cdef30d-fbc9-4688-b226-9e624e9f0249 · outbound

This paper cites Candès, Xiaodong Li, Yi Ma, and John Wright.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Candès, Xiaodong Li, Yi Ma, and John Wright

Reference 14

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Observation 41ab9931-5107-4716-bb40-97d5b9120eb1 · outbound

This paper cites Feddat: An approach for foundation model finetuning in multi-modal heterogeneous federated learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Feddat: An approach for foundation model finetuning in multi-modal heterogeneous federated learning

Reference 15

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Observation 6c402124-5761-40c4-9fd2-a7b27e9fc0ce · outbound

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

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA On the importance and applicability of pre-training for federated learning

Reference 16

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source=pdf_text observed=2026-08-07T11:57:24.999929Z digest=sha256:5ba4eac39f4b1e55515ea492e1c089524bd259d056babb3952a160908fafe4ef

Observation 5198c946-8f49-44c9-b065-9309e5e477bf · outbound

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

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA FedTune: A Deep Dive into Efficient Federated Fine-Tuning with Pre-trained Transformers

Reference 17

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source=pdf_text observed=2026-08-07T11:57:25.007012Z digest=sha256:49091fef276de86218f3fd6dfc9cbf47d55f68133e03ebe7adaeeac16908c320

Observation 7ad379b3-0e62-4431-b488-ac8141aab91d · outbound

This paper cites Heterogeneous LoRA for federated fine-tuning of on-device foundation models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Heterogeneous LoRA for federated fine-tuning of on-device foundation models

Reference 18

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Observation 37ab8632-ab22-4e0c-80ae-e04a4545d048 · outbound

This paper cites AdapterSoup: Weight averaging to improve generalization of pretrained language models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA AdapterSoup: Weight averaging to improve generalization of pretrained language models

Reference 19

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Observation 48392f0e-eb40-4338-a6d2-491210de38c1 · outbound

This paper cites Describing textures in the wild.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Describing textures in the wild

Reference 20

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Observation 427d7d1d-cb18-4a9a-8ad6-2a91e28c79af · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Qlora: Efficient finetuning of quantized llms

Reference 21

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Observation 4d066cdb-d1fa-4cc0-a977-868e518fd4b1 · outbound

This paper cites Parameter competition balancing for model merging.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Parameter competition balancing for model merging

Reference 22

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Observation d38f86a6-b993-49c3-ac28-547a52a16a2a · outbound

This paper cites Online robust pca via stochastic optimization.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Online robust pca via stochastic optimization

Reference 23

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Observation 4a0bb0e4-c531-41e8-83aa-df6edfca9b14 · outbound

This paper cites Online robust PCA via stochastic optimization.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Online robust PCA via stochastic optimization

Reference 24

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Observation b2f8d117-e0f4-49d4-a848-d7217643b4be · outbound

This paper cites Mixture-of-loras: An efficient multitasktuningmethodforlargelanguagemodels.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Mixture-of-loras: An efficient multitasktuningmethodforlargelanguagemodels

Reference 25

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Observation a0017ed0-ce03-4d7a-937a-4bdf85b5db34 · outbound

This paper cites MRQA 2019 shared task: Evaluating generalization in reading comprehension.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA MRQA 2019 shared task: Evaluating generalization in reading comprehension

Reference 26

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Observation 89886c1d-0c2a-46b7-b1f2-8cb7373df19b · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 27

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Observation 8ef20179-d6dd-48a5-b756-cbda59c52b2f · outbound

This paper cites Godec+: Fast and robust low-rank matrix decomposition based on maximum correntropy.IEEE Trans.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Godec+: Fast and robust low-rank matrix decomposition based on maximum correntropy.IEEE Trans

Reference 28

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Observation e4b97527-8334-4f1a-9b07-a2a273671118 · outbound

This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.IEEE J.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.IEEE J

Reference 29

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Observation 6a13c732-b811-40fb-af15-e18cb80ba37d · outbound

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

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 30

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Observation 1d2bbdb1-d54c-4a51-8cf8-ddb4161757f8 · outbound

This paper cites Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022

Reference 31

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Observation 8bb22486-9e90-45d2-8eca-aa0c9c7d22a4 · outbound

This paper cites Fedqlora: Federated quantization- aware lora for large language models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Fedqlora: Federated quantization- aware lora for large language models

Reference 32

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Observation 747234a7-d6ff-4715-a584-48dd69c9d27d · outbound

This paper cites EMR-merging: Tuning- free high-performance model merging.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA EMR-merging: Tuning- free high-performance model merging

Reference 33

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raw_fallback, observed 2026-08-07T11:57:26.998824Z

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Observation 1de45537-a186-495b-84f0-a96baedf0007 · outbound

This paper cites Editing models with task arithmetic.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Editing models with task arithmetic

Reference 34

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Observation 4baa8cb7-e211-42a6-80d4-85fdd103b64d · outbound

This paper cites Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning

Reference 35

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local_arxiv, observed 2026-08-07T11:57:26.063785Z

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

source=pdf_text observed=2026-08-07T11:57:25.115048Z digest=sha256:a9afebb2804badbc956d474ecf35cd3e9e87913cf45952b905883168db50f4a3

Observation 0081333c-9087-4f16-8c53-f92853d29d6e · outbound

This paper cites Fedexp: Speeding up federated averaging via extrapolation.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Fedexp: Speeding up federated averaging via extrapolation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.964982Z

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=2026-08-07T11:57:25.120729Z digest=sha256:2d265f17147b384466cbdf17865c1c4abc52fcb5eb55a2e4ebccc60e12038699

Observation 59eaef63-3446-4d47-bfb8-789519ff40aa · outbound

This paper cites Promoting data and model privacy in federated learning through quantized LoRA.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Promoting data and model privacy in federated learning through quantized LoRA

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.950600Z

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=2026-08-07T11:57:25.124716Z digest=sha256:dea5c2244daacd6f4512cb958bda349326280b32d53b69d764e2802b609a28ba

Observation 805356d4-13e9-4ed1-bb08-e1c355878f10 · outbound

This paper cites Dataless knowledge fusion by merg- ing weights of language models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Dataless knowledge fusion by merg- ing weights of language models

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.936703Z

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=2026-08-07T11:57:25.129328Z digest=sha256:355a86a8ce7d2f62695c8b468147c04093747eec18180dd3f6c720e2312f41b1

Observation 893c623f-bf41-4e1b-8927-81b5b8844908 · outbound

This paper cites Advances and open problems in federated learning.Foundations and trends®in machine learning, 14(1–2):1–210, 2021.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Advances and open problems in federated learning.Foundations and trends®in machine learning, 14(1–2):1–210, 2021

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.922120Z

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=2026-08-07T11:57:25.133761Z digest=sha256:197d6f580c02b99ccd490ffd46d1731e0d9b59ddf19f95031e2a94af63593202

Observation 98c79711-5a27-4a9a-a197-12751899a298 · outbound

This paper cites Reddi, Sebastian U.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Reddi, Sebastian U

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.905917Z

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=2026-08-07T11:57:25.138664Z digest=sha256:6c57d56c67c4bb2a8b53be9fcc2caf1596642394197dc1afbac3eceda60829ee

Observation 68a28ea1-17ce-44ef-a1bb-36098dd7535c · outbound

This paper cites Segment anything.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Segment anything

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.143443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.143443Z digest=sha256:bc7b7a3103c4c3d107f865cac8c63833e72455c43305cea99a502baaebd22689

Observation d18bb700-f4d8-45a7-8abf-52ab8a83a419 · outbound

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

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA 3d object representations for fine-grained categorization

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.876322Z

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=2026-08-07T11:57:25.147865Z digest=sha256:560b254ad55b6c829b5cfa44ca5bbc8318a3c47c412a8b62a50a757564a46f05

Observation c0a123d7-6fee-49a9-939b-0d3bde124afc · outbound

This paper cites Federated LoRA with Sparse Communication.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Federated LoRA with Sparse Communication

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.152017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.152017Z digest=sha256:cf26aac7d7f9f096269d85e34846027838c283a83f5adbbfcb17f231227da75c

Observation ae9d2de0-0d4a-45db-8934-4aa2f9f9feb2 · outbound

This paper cites Newsweeder: Learning to filter netnews.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Newsweeder: Learning to filter netnews

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.860585Z

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=2026-08-07T11:57:25.156007Z digest=sha256:cb21ce755c2a5be5539df8344b496a2b5115cecb856e46c0070448f2f92a505b

Observation 7beb2ecf-249c-4c4b-82dd-9d10d4d04195 · outbound

This paper cites Model-contrastive federated learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Model-contrastive federated learning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.845766Z

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=2026-08-07T11:57:25.160079Z digest=sha256:6ffeb656ce6fe7e88fb09bae65cb23fc5c6ee8c59fa724e2224b5f62484326fd

Observation 1e63ac99-2dff-417f-b6dd-f675ccfea41c · outbound

This paper cites Federated optimization in heterogeneous networks.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Federated optimization in heterogeneous networks

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.832087Z

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=2026-08-07T11:57:25.164041Z digest=sha256:ba9ef276100a8c5743df267d27fc3d37e60fb0df1b51fe46157c1acbcf516788

Observation a1d7a746-9976-4146-94fc-2290b77e0899 · outbound

This paper cites Differentially private low-rank adaptation of large language model using federated learning.ACM Transactions on Management Information Systems, 16(2):1–24, 2025.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Differentially private low-rank adaptation of large language model using federated learning.ACM Transactions on Management Information Systems, 16(2):1–24, 2025

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.818465Z

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=2026-08-07T11:57:25.169906Z digest=sha256:2a1161a685ce81b2fa9362f1acc10e5695d7bc4b8a1da07e8dd9a8c72db75fb7

Observation f5e20662-6553-47d8-9a19-7cbc80ee2fc8 · outbound

This paper cites A survey on lora of large language models.Frontiers of Computer Science, 19(7):197605, 2025.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA A survey on lora of large language models.Frontiers of Computer Science, 19(7):197605, 2025

Reference 48

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unresolved
no resolver link, observed 2026-08-07T11:57:25.174485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.174485Z digest=sha256:49afda5006b4cccd36b52d54ffda9c9eae0e2c6b2be7ddd12769cfa1108ff3fe

Observation a621c230-06e2-4ab5-92fd-c4c240884f54 · outbound

This paper cites Merging models with fisher-weighted averaging.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Merging models with fisher-weighted averaging

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.794121Z

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=2026-08-07T11:57:25.179136Z digest=sha256:c7e8ebb5a21b40710239a5de6b0edfc50403e9d8a72253487031415b2a3b08c6

Observation 78464e8c-8bad-4a56-8dea-bd2a9b646685 · outbound

This paper cites Merging models with fisher-weighted averaging.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Merging models with fisher-weighted averaging

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.778904Z

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=2026-08-07T11:57:25.183887Z digest=sha256:ed36a199bbb52aab7d7143e85b7910047b41d82d9f3f79021211f3a8168a35ef

Observation 55ddf903-9d79-4c8a-b1cd-de64e5622064 · outbound

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

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Communication-efficient learning of deep networks from decentralized data

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.189118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.189118Z digest=sha256:37156b76c46649227e823c9e28d5568600f427c639cb0a115bff93b66547c736

Observation a69d6f65-a008-4c5a-bd38-e80ccce50a06 · outbound

This paper cites an unresolved cited work.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:57:26.751730Z

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=2026-08-07T11:57:25.193575Z digest=sha256:01416b5daae2191a8fd113f24f2bdfbff02ad46268d37f9e716c6d1d7c270f0c

Observation deb09609-93ed-43c2-ba9e-7ff5f748b423 · outbound

This paper cites an unresolved cited work.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:57:26.736781Z

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=2026-08-07T11:57:25.199544Z digest=sha256:e9f5f4b6e25f9ba9114d300c9f25fdf3eedfbe768730f5254bfdcf522b03f278

Observation 783eca74-ad98-491e-80bf-4caa7862478e · outbound

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

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA DINOv2: Learning Robust Visual Features without Supervision

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.204206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.204206Z digest=sha256:7b35be03dc33114a55ec335a56b53c4f0951ccd64baa8fca6939a6ab45b11291

Observation 7a1ec262-d515-442b-9e1a-040153a633e4 · outbound

This paper cites FedPFT: Federated Proxy Fine-Tuning of Foundation Models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA FedPFT: Federated Proxy Fine-Tuning of Foundation Models

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:57:26.003087Z

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=2026-08-07T11:57:25.208692Z digest=sha256:484a9430766b4f79f27cabd20d12d6c477a1c99cbaf61c1a1d01818727a732d1

Observation c5e36850-3f64-41af-ba85-58eb4c6a506f · outbound

This paper cites LoRA Soups: Merging LoRAs for Practical Skill Composition Tasks.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA LoRA Soups: Merging LoRAs for Practical Skill Composition Tasks

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.212897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.212897Z digest=sha256:e03aa17d4f2363c1146e92e6d136b8fa29c7ea249d78341e5c6362918201ca14

Observation 58961e33-ac91-4cc2-b830-741ac29c11d9 · outbound

This paper cites FDLoRA: Personalized Federated Learning of Large Language Model via Dual LoRA Tuning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA FDLoRA: Personalized Federated Learning of Large Language Model via Dual LoRA Tuning

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.218174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.218174Z digest=sha256:700916448ede242ed0e3bc6797ea13d2f4fa4e663dcb01e9e8dbb63e3cac0e90

Observation 7d7ed9f3-8e8a-4479-aca7-bf57ff4aeb70 · outbound

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

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Learning transferable visual models from natural language supervision

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.223161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.223161Z digest=sha256:9c751bf82bf79c6be36abf4fe31d2c56042b2fedb76cafdeff12c8e1e195066d

Observation 960e1f7e-3be8-4acd-ad58-1b6fb637d571 · outbound

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

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Learning transferable visual models from natural language supervision

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.712959Z

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=2026-08-07T11:57:25.227129Z digest=sha256:1d57b8f9eb044ab28a22b8f145290577edcd432800bd08747a8cc6b29bd95439

Observation 36f52b68-cfce-43e0-8a4b-c7b3cec00a00 · outbound

This paper cites Language models are unsupervised multitask learners.OpenAI blog, 1(8):9, 2019.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Language models are unsupervised multitask learners.OpenAI blog, 1(8):9, 2019

Reference 60

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unresolved
no resolver link, observed 2026-08-07T11:57:25.231364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.231364Z digest=sha256:197ba3fb1b185f3e0737c0196a4c3c129fdcd10585bdf582ca2c7f8e3b0809ea

Observation 7579f48f-c854-402e-b1c7-7497a3dc58b5 · outbound

This paper cites an unresolved cited work.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Unresolved cited work

Reference 61

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unresolved
no resolver link, observed 2026-08-07T11:57:25.235201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.235201Z digest=sha256:91d1bbd36cb13d0b53fc8b44ade17924813ec84b9876a71c92e685ddf2ed8aad

Observation ab9101cd-38b7-425c-bfa7-341b8fd39d5d · outbound

This paper cites Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, and Hugh Brendan McMahan.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, and Hugh Brendan McMahan

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.672866Z

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=2026-08-07T11:57:25.240426Z digest=sha256:1d63f12903dc15f96e0fa20993d4215297c1f4416e973fffeb02510baba1533a

Observation bfbeb8ab-3143-4ed5-b2d1-c46a8ac1d9ac · outbound

This paper cites Code Llama: Open Foundation Models for Code.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Code Llama: Open Foundation Models for Code

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.245396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.245396Z digest=sha256:087cf4a81a75f4e331905892415cfa986f6b184b11f9c61d2d606fd593ada111

Observation c54a1220-0047-47d2-ad78-b3ee0d9fe2d7 · outbound

This paper cites Closed-form merging of parameter-efficient modules for federated continual learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Closed-form merging of parameter-efficient modules for federated continual learning

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.655857Z

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=2026-08-07T11:57:25.254886Z digest=sha256:451a6fcb20b22be56f32eee75a4ce4e65859ab772302d232dfc008a5577b1910

Observation 60c0e721-d2b0-4fc1-8393-bbefec95ddc3 · outbound

This paper cites Ziplora: Any subject in any style by effectively merging loras.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Ziplora: Any subject in any style by effectively merging loras

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.636750Z

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=2026-08-07T11:57:25.259531Z digest=sha256:66f7e2cca3240b70404ab337ac0863f288116654407b794e74ed21afce93814f

Observation 50079239-31be-4879-99ad-a508411f4fe6 · outbound

This paper cites LoRA.rar: Learning to Merge LoRAs via Hypernetworks for Subject-Style Conditioned Image Generation.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA LoRA.rar: Learning to Merge LoRAs via Hypernetworks for Subject-Style Conditioned Image Generation

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.263745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.263745Z digest=sha256:8927304995a1f64e838e31daae629d8de738719aa005e873d09f3b17ac4eac83

Observation a2311a79-6793-4917-b9db-c5273e2884cf · outbound

This paper cites Gonzalez, and Ion Stoica.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Gonzalez, and Ion Stoica

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.619169Z

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=2026-08-07T11:57:25.268646Z digest=sha256:44cbaf22803ce73692a9be496eb06696e9749854b3f4a32a44476809dd9d98d5

Observation e3704a03-ff96-45e0-9e67-a1f2b0f0934d · outbound

This paper cites Fed- sb: A silver bullet for extreme communication efficiency and performance in (private) federated lora fine-tuning.arXiv preprint arXiv:2502.15436, 2025.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Fed- sb: A silver bullet for extreme communication efficiency and performance in (private) federated lora fine-tuning.arXiv preprint arXiv:2502.15436, 2025

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.273427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.273427Z digest=sha256:eacbb86f60579eebbe7a168b6076cbfef8fe74fded446f2576fd7e7c963667b2

Observation 2b698605-9db9-4d3b-bea8-1affb7ff7e2f · outbound

This paper cites Fedex-loRA: Exact aggregation for federated parameter-efficient fine-tuning of foundation models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Fedex-loRA: Exact aggregation for federated parameter-efficient fine-tuning of foundation models

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.604558Z

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=2026-08-07T11:57:25.278338Z digest=sha256:83f63392e7825927ec507c68c5848e32c0ccc79980d93dfd698e62c3f8e8b1a1

Observation caaa49c7-0dab-4106-be39-6eba55f69a3d · outbound

This paper cites Improving loRA in privacy-preserving federated learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Improving loRA in privacy-preserving federated learning

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.589082Z

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=2026-08-07T11:57:25.283792Z digest=sha256:e9dd94943ec60d9a9b11ea45ac0bdb45096ec49e518b6c897d5766cb083c2028

Observation 784fe150-94dc-4a91-ab4d-2371c0c54148 · outbound

This paper cites Improving lora in privacy-preserving federated learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Improving lora in privacy-preserving federated learning

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.573171Z

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=2026-08-07T11:57:25.290413Z digest=sha256:d14beed7e00ab9f2822bbe15611e8d9040618cded5f18c352f35c46aa693692e

Observation d61a98b4-f2e5-46c7-8fc2-9cf34e83cb62 · outbound

This paper cites Merging multi-task models via weight-ensembling mixture of experts.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Merging multi-task models via weight-ensembling mixture of experts

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.558218Z

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=2026-08-07T11:57:25.296512Z digest=sha256:ad9e8e4226fa0a10d0bde7191adf10aa0549812e5dfa7c23c88ac3ee80079643

Observation 7c819615-acc5-498c-b613-a858c8820afa · outbound

This paper cites Parameter- efficient multi-task model fusion with partial linearization.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Parameter- efficient multi-task model fusion with partial linearization

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.543113Z

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=2026-08-07T11:57:25.303851Z digest=sha256:0a5dc1a63c756114c9168b8601be9410614f58be7a68cbf0949e944bbe5e8c0d

Observation 8df55f2c-e61b-434c-9c14-b54b47a7457b · outbound

This paper cites Task Arithmetic Through The Lens Of One-Shot Federated Learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Task Arithmetic Through The Lens Of One-Shot Federated Learning

Reference 75

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:57:25.798745Z

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=2026-08-07T11:57:25.312244Z digest=sha256:84b3297ddc2b349ca5c912269547ed43db508608ba47640696dd6f8ee0866122

Observation 0bb1cd62-d518-48ff-8cb3-c19cc8d5cfd5 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA LLaMA: Open and Efficient Foundation Language Models

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.318596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.318596Z digest=sha256:7653a6a0b70be077d0939556883da3058edfb0910c5ca19b22f45867bd7712bb

Observation eb62dece-3c9c-4886-9d73-c9cee7d733c9 · outbound

This paper cites Robust subspace learning: Robust pca, robust subspace tracking, and robust subspace recovery.IEEE signal processing magazine, 35(4):32–55, 2018.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Robust subspace learning: Robust pca, robust subspace tracking, and robust subspace recovery.IEEE signal processing magazine, 35(4):32–55, 2018

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.528093Z

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=2026-08-07T11:57:25.322975Z digest=sha256:3cec0cf860c8fca58c4b7922243d47f95c510a635b0813b04c0c67d2717d01ad

Observation 91a7d04c-140a-4fab-8eb9-729384a32fa2 · outbound

This paper cites LoRA-flow: Dynamic LoRA fusion for large language models in generative tasks.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA LoRA-flow: Dynamic LoRA fusion for large language models in generative tasks

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.513879Z

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=2026-08-07T11:57:25.327126Z digest=sha256:9e35c12657973490b4a764a7438937182b36afdc1ab87d6927e62dec89b6a07e

Observation 42f17d84-4730-4705-bbcb-b70f210e8cc9 · outbound

This paper cites Lo- calizing task information for improved model merging and compression.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Lo- calizing task information for improved model merging and compression

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.498930Z

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=2026-08-07T11:57:25.331508Z digest=sha256:bb61f2d88a75130e731ba45d209c11dbaa06099c7b2c46850ba9547210266886

Observation a73c8438-99ff-47f1-bdf2-23dbc3e729af · outbound

This paper cites Federated fine-tuning for pre-trained foundation models over wireless networks.IEEE Transactions on Wireless Communications, 2025.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Federated fine-tuning for pre-trained foundation models over wireless networks.IEEE Transactions on Wireless Communications, 2025

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.485276Z

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=2026-08-07T11:57:25.343582Z digest=sha256:f863d548f884085ca511aa28b7ca3e7ced8faa4eee3e0126b642ab470f1a4188

Observation ea55f1b6-22e4-4a8d-ac6b-ca3ea4b5b902 · outbound

This paper cites FLoRA: Federated fine-tuning large language models with heterogeneous low-rank adaptations.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA FLoRA: Federated fine-tuning large language models with heterogeneous low-rank adaptations

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.470596Z

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=2026-08-07T11:57:25.348121Z digest=sha256:57d277340272958eedb0ced7ef629128374b5564f9fffb31a7acd1c2d9084d1c

Observation d16a07bb-5d26-4a45-aae6-f3db5fc11ac7 · outbound

This paper cites One communication round is all it needs for federated fine-tuning foundation models.arXiv preprint arXiv:2412.04650, 2024.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA One communication round is all it needs for federated fine-tuning foundation models.arXiv preprint arXiv:2412.04650, 2024

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.352651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.352651Z digest=sha256:7468aef63b32a8fa87c8c2c893e3016a54e4c9f201db3397fa24324f34c2b8f3

Observation 0942ffa2-0f24-45c1-901d-8e5e670db7c7 · outbound

This paper cites Federated fine-tuning of llms on the very edge: The good, the bad, the ugly.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Federated fine-tuning of llms on the very edge: The good, the bad, the ugly

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.454133Z

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=2026-08-07T11:57:25.360623Z digest=sha256:c823e76401e2b313aaa0d7422d1759524c9f8351fd189c3399c86be145e8ecff

Observation f1ee6ff4-acd6-467b-8651-b8ed35673f83 · outbound

This paper cites Mixture of lora experts.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Mixture of lora experts

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.435176Z

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=2026-08-07T11:57:25.365747Z digest=sha256:b52b37d6a6619b0330e6b6776969d55c0223e76716b2aa2f2e88f31637fa42f8

Observation 1c833cdd-412e-4f0a-84ba-8fe929479030 · outbound

This paper cites Robust pca via outlier pursuit.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Robust pca via outlier pursuit

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.419980Z

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=2026-08-07T11:57:25.373170Z digest=sha256:9e11d6cfcbc7c7a91b108749c80281165c6ce6b795aaf34d5f94b2d4ef8a53be

Observation 299ae43c-65a7-4c7a-85ab-7b16d8ccce2e · outbound

This paper cites Raffel, and Mohit Bansal.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Raffel, and Mohit Bansal

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.405816Z

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=2026-08-07T11:57:25.379357Z digest=sha256:81efdfd265700e256446da5cc1cf70c95e9a8b908e3118ab4b9bfca722414f3e

Observation 35d19ffb-2b13-4705-a085-906a1714692c · outbound

This paper cites Qwen2.5 Technical Report.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Qwen2.5 Technical Report

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.385206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.385206Z digest=sha256:df6068ba860c1117ce654195cf04277f10e117df8f68449411dc5bd2dd1d6788

Observation e4b199be-b024-441d-bd39-c35a0f42e869 · outbound

This paper cites Representation surgery for multi-task model merging.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Representation surgery for multi-task model merging

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.390515Z

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=2026-08-07T11:57:25.390168Z digest=sha256:a4ec79b5248ab3b41541130b1f379dd414993d1b21442e11ba522db6ae459e5d

Observation 2b702ae9-984b-4151-8491-891d4c0dd335 · outbound

This paper cites Adamerging: Adaptive model merging for multi-task learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Adamerging: Adaptive model merging for multi-task learning

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.373482Z

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=2026-08-07T11:57:25.398206Z digest=sha256:4a03890b8a0b5ffc74fa1318dd3685a041ea8fab58ca0dd064c50f5c8c6e0473

Observation a633213c-c230-482b-aae9-eb98b2c9f042 · outbound

This paper cites SPD-CFL: Stepwise Parameter Dropout for Efficient Continual Federated Learning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA SPD-CFL: Stepwise Parameter Dropout for Efficient Continual Federated Learning

Reference 90

Resolution
verified exact
local_arxiv, observed 2026-08-07T11:57:25.527114Z

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=2026-08-07T11:57:25.402344Z digest=sha256:6d45d160f908507abf3ed005c031f78e3e0760180ca7640d5ea7a59da37e2c11

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

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

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

Reference 91

Resolution
unresolved
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=sha256:0ea92029f30282ecfbfc2a352115128317312897b9fb80505bcf37ba954c9157

Observation 2ea380f6-5e51-45a8-b877-f1c422bc3759 · outbound

This paper cites Language models are super mario: Absorbing abilities from homologous models as a free lunch.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Language models are super mario: Absorbing abilities from homologous models as a free lunch

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.412108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.412108Z digest=sha256:494719653f8061f5238bebf1b479fd249aacd67b92ab8a470dda1cbe53b791f2

Observation b5ddac4c-9b67-44c6-9668-ea58ab61e468 · outbound

This paper cites Towards building the federatedgpt: Federated instruction tuning.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Towards building the federatedgpt: Federated instruction tuning

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.345969Z

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=2026-08-07T11:57:25.416163Z digest=sha256:b13249e8ba1c12c4d9c798ec17d09e65fa7f78a9dc2c28ab2963b065ed898748

Observation c4f4b4af-b6f7-410a-8ee7-cbc452d4f443 · outbound

This paper cites Composing parameter-efficient modules with arithmetic operation.Advances in Neural Information Processing Systems, 36:12589–12610, 2023.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Composing parameter-efficient modules with arithmetic operation.Advances in Neural Information Processing Systems, 36:12589–12610, 2023

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.327597Z

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=2026-08-07T11:57:25.420102Z digest=sha256:32aaacb3b4096a2d07557afb1abb5d490386d2df57416211f1e9737fad2cd133

Observation 513aebc0-52a2-4871-a2e1-c220f7e9e37e · outbound

This paper cites Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-07T11:57:25.424045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:57:25.424045Z digest=sha256:10f81b2552fef7c24bb081b1c8c85aee43e462d301a918e256b5e655fdbca418

Observation 00ac2a2a-9950-4413-9ee2-386e6694375e · outbound

This paper cites rest-of-the-world.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA rest-of-the-world

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.307129Z

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=2026-08-07T11:57:25.428488Z digest=sha256:d8847fd4d339e5df340b1e5c54fd05db0a6f6160ad714b6d05cc6fc29fbb5fa2

Observation 62e0df7c-800a-4609-a4ff-9c3158979b47 · outbound

This paper cites " " De co mp ose D into low - rank L and sparse S ( M = L + S ).

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA " " De co mp ose D into low - rank L and sparse S ( M = L + S )

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:57:26.287963Z

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=2026-08-07T11:57:25.432956Z digest=sha256:c449c700edb16b4d294066828696fa1934e789bed204af4e41fd3aaea111ee26

Observation 39fbd0b4-980c-4307-8d51-3f931c185b9d · outbound

This paper cites an unresolved cited work.

FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA Unresolved cited work

Reference 2013

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:57:27.099281Z

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=2026-08-07T11:57:25.050558Z digest=sha256:7f353445b1758fe8989298529567e540e73ff5ad12ff06cbe2095e19b7247c55

Pith citing papers

No inbound Pith citation observations are available.