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Paper Citation Record · LEDGER

Federated Lightweight Fine-Tuning

As of 7 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.18343.

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

pith.paper-citation-record.v1
2607.18343 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:36:05.988695Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

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  • verified fuzzy0
  • unresolved31
  • parse uncertain0
  • malformed identifier1
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External citation measurements

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Outbound references

Observation 2a138027-0f71-4838-a31c-fb8a8b351a74 · outbound

This paper cites In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP).

Federated Lightweight Fine-Tuning In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Reference 1

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Observation 63dab1ab-9c47-4ff9-86e9-5402ce5a07e2 · outbound

This paper cites In: Advances in Neural In- formation Processing Systems 30 (NeurIPS) (2017).

Federated Lightweight Fine-Tuning In: Advances in Neural In- formation Processing Systems 30 (NeurIPS) (2017)

Reference 2

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Observation 2a75eeef-8191-400b-a0e9-7659da47fa83 · outbound

This paper cites In: Proceedings of the 35th Inter- national Conference on Machine Learning (ICML) (2018).

Federated Lightweight Fine-Tuning In: Proceedings of the 35th Inter- national Conference on Machine Learning (ICML) (2018)

Reference 3

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Observation 9af537d4-6616-4640-b91c-312e68d56377 · outbound

This paper cites Transactions on Machine Learning Research (2026), accepted by TMLR.

Federated Lightweight Fine-Tuning Transactions on Machine Learning Research (2026), accepted by TMLR

Reference 4

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Observation 19bc8e28-174c-4e81-9325-4f63e772b91f · outbound

This paper cites DiLoCo: Distributed Low-Communication Training of Language Models.

Federated Lightweight Fine-Tuning DiLoCo: Distributed Low-Communication Training of Language Models

Reference 5

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Observation 5d371fca-ffa7-4369-b23f-029e6fdcf121 · outbound

This paper cites In: International Conference on Learning Representations (2018).

Federated Lightweight Fine-Tuning In: International Conference on Learning Representations (2018)

Reference 6

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Observation 96891c5a-bef9-486e-8157-471f7f090194 · outbound

This paper cites In: Proceedings of the 37th International Conference on Machine Learning (ICML) (2020).

Federated Lightweight Fine-Tuning In: Proceedings of the 37th International Conference on Machine Learning (ICML) (2020)

Reference 7

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Observation b2239e63-e5be-4913-852f-3ab1a8da4d6a · outbound

This paper cites In: International Conference on Learning Representations (2022).

Federated Lightweight Fine-Tuning In: International Conference on Learning Representations (2022)

Reference 8

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Observation 6adbe5db-3536-4405-817e-9072e99cdf61 · outbound

This paper cites Advances and Open Problems in Federated Learning.

Federated Lightweight Fine-Tuning Advances and Open Problems in Federated Learning

Reference 9

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Observation ac63450f-dfd5-450f-aa58-8b029df6082f · outbound

This paper cites SCAFFOLD: Stochastic Controlled Averaging for Federated Learning.

Federated Lightweight Fine-Tuning SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

Reference 10

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Observation e9ec1f76-954a-460b-935e-ec071df69464 · outbound

This paper cites In: Proceedings of the 36th International Conference on Machine Learning (ICML) (2019).

Federated Lightweight Fine-Tuning In: Proceedings of the 36th International Conference on Machine Learning (ICML) (2019)

Reference 11

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Observation 31b09d6e-72f6-4124-838d-8b36ab7a7176 · outbound

This paper cites In: Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS).

Federated Lightweight Fine-Tuning In: Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS)

Reference 12

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Observation 70841e6f-5c1e-42e3-9dd4-2330122df7ab · outbound

This paper cites In: Proceedings of The 28th International Conference on Artificial In- telligence and Statistics.

Federated Lightweight Fine-Tuning In: Proceedings of The 28th International Conference on Artificial In- telligence and Statistics

Reference 13

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Observation bc8958d9-eb0c-4994-a7ea-a99c2c39ee73 · outbound

This paper cites In: International Conference on Learning Representations (2018).

Federated Lightweight Fine-Tuning In: International Conference on Learning Representations (2018)

Reference 14

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Observation 433e6942-168b-4133-9aa1-3e56899999b5 · outbound

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

Federated Lightweight Fine-Tuning FedMD: Heterogenous Federated Learning via Model Distillation

Reference 15

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Observation 30db0ea8-885a-4f37-b116-cfe958aa2877 · outbound

This paper cites Federated Optimization in Heterogeneous Networks.

Federated Lightweight Fine-Tuning Federated Optimization in Heterogeneous Networks

Reference 16

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Observation cd66fa4a-a4ff-49f8-87c6-d5e67a24234c · outbound

This paper cites In: International Conference on Learning Representations (2021).

Federated Lightweight Fine-Tuning In: International Conference on Learning Representations (2021)

Reference 17

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Observation d12fd1dd-a778-4fba-94e5-76a9f2aebd29 · outbound

This paper cites In: Proceedings of the Forty-first Con- ference on Uncertainty in Artificial Intelligence.

Federated Lightweight Fine-Tuning In: Proceedings of the Forty-first Con- ference on Uncertainty in Artificial Intelligence

Reference 18

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Observation ff97ef09-7bf0-470d-ab93-433abd82e2b4 · outbound

This paper cites Ensemble Distillation for Robust Model Fusion in Federated Learning.

Federated Lightweight Fine-Tuning Ensemble Distillation for Robust Model Fusion in Federated Learning

Reference 19

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Observation b1d80a6a-169a-4998-b247-b43a82023ca5 · outbound

This paper cites In: International Conference on Learning Representations (2018).

Federated Lightweight Fine-Tuning In: International Conference on Learning Representations (2018)

Reference 20

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Observation 3a18e896-d884-400a-8f6f-9b3691921d34 · outbound

This paper cites In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS).

Federated Lightweight Fine-Tuning In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS)

Reference 21

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Observation 531fe87b-5920-4c71-8e18-971603af00fe · outbound

This paper cites In: International Conference on Learning Representations (2022).

Federated Lightweight Fine-Tuning In: International Conference on Learning Representations (2022)

Reference 22

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Observation 06b0c284-a2af-424d-9dbc-9994815900d0 · outbound

This paper cites Proceedings of the National Academy of Sciences117(40), 24652–24663 (2020).

Federated Lightweight Fine-Tuning Proceedings of the National Academy of Sciences117(40), 24652–24663 (2020)

Reference 23

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Observation f7297887-ad67-4d3a-8769-67afb1bdd6a4 · outbound

This paper cites IEEE Transactions on Neural Networks and Learning Systems (2021).

Federated Lightweight Fine-Tuning IEEE Transactions on Neural Networks and Learning Systems (2021)

Reference 24

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Observation 6569da29-a6da-4c31-9049-cb64f669a91e · outbound

This paper cites Adaptive Federated Optimization.

Federated Lightweight Fine-Tuning Adaptive Federated Optimization

Reference 25

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Observation 59f31a6c-0776-4ee5-a5c7-d86a9ab76e4b · outbound

This paper cites arXiv preprint arXiv:2602.19134 (2026).

Federated Lightweight Fine-Tuning arXiv preprint arXiv:2602.19134 (2026)

Reference 26

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Observation ce308131-badb-4e36-b998-ac6cc884f7d5 · outbound

This paper cites In: International Conference on Learning Representations (2019).

Federated Lightweight Fine-Tuning In: International Conference on Learning Representations (2019)

Reference 27

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This paper cites In: Pro- ceedings of the 42nd International Conference on Machine Learning.

Federated Lightweight Fine-Tuning In: Pro- ceedings of the 42nd International Conference on Machine Learning

Reference 28

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Observation f808a0a9-1c65-471d-b94d-f41f7f12427d · outbound

This paper cites In: Advances in Neural Information Pro- cessing Systems 32 (NeurIPS) (2019).

Federated Lightweight Fine-Tuning In: Advances in Neural Information Pro- cessing Systems 32 (NeurIPS) (2019)

Reference 29

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This paper cites In: International Conference on Learning Repre- sentations (2020).

Federated Lightweight Fine-Tuning In: International Conference on Learning Repre- sentations (2020)

Reference 30

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Observation e58ce9b5-f259-4e96-8bd7-ba991913cae7 · outbound

This paper cites In: Proceedings of the European Conference on Computer Vision (ECCV) (2018).

Federated Lightweight Fine-Tuning In: Proceedings of the European Conference on Computer Vision (ECCV) (2018)

Reference 31

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Observation b4a78803-83c0-4347-a7f4-70823573ee18 · outbound

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Federated Lightweight Fine-Tuning Unresolved cited work

Reference 32

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Pith citing papers

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