Pith. sign in

Paper Citation Record · LEDGER

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge

As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 2 inbound Pith citation observations for arXiv:2508.18663.

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

pith.paper-citation-record.v1
2508.18663 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:22:25.583269Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T09:29:03.234211Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:49:44.425417Z

Reference resolution

41 of 41 outbound references displayed

  • verified exact2
  • verified fuzzy7
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c774c6b6-66aa-4c63-ad25-4cd49238625d · outbound

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

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge , " * write output.state after.block = add.period write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.370442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.370442Z digest=sha256:509f4b44616878748c62ca067bde055dacb7b9ce40674166794b5d5805012612

Observation 31915552-a4b9-4456-a22d-9d88b3b3d91f · outbound

This paper cites write newline.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge write newline

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.376117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.376117Z digest=sha256:0b3de24042b91f0a02b0779e5fd511a4bbb833df8ae84e39da36514d7e750085

Observation 238e4225-0935-4437-bc94-47db97f9ce79 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.312571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.381979Z digest=sha256:cf325a7bc586d87ad460619ea034b3cb99134b1cc62e90087de7ac008e3f0098

Observation e0d5e685-6c9e-4a4e-81c4-aab92c0784d2 · outbound

This paper cites Scalable Artificial Intelligence for Science: Perspectives, Methods and Exemplars.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Scalable Artificial Intelligence for Science: Perspectives, Methods and Exemplars

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:22:25.747326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.387885Z digest=sha256:4ff895e530ad75f7e7d7cf24491144d012ece16a2a71697576d3f5904dced112

Observation ab0ed24a-d37e-42ed-a734-01786517ac25 · outbound

This paper cites X.; and Xu, M.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge X.; and Xu, M

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:22:26.295258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.394438Z digest=sha256:112bedc9345eea046f15f45ca85350d5afa3e5ea19c120b4486e931325621699

Observation 792d9617-3b4b-494d-b41c-9fa1cef38bc8 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.275432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.401083Z digest=sha256:80f5e79415e7746a26bc540ffef38701836dd581e2758da04d893542eab057f5

Observation 13cb8eb2-2951-40f5-99a1-3af6ab6ef283 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.255931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.406705Z digest=sha256:6ed90c22f56cd09f0c8614e3c8c8271ac1670c2dcf23a61d1e19f4532363257f

Observation 568312da-4501-4183-9090-1d88fbb90b90 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.239120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.412702Z digest=sha256:7d8337bb205d483363ea7e50cfe66744144d99ddc10b69d59f37aae04e5508ac

Observation cd58f7a6-7d79-41a2-bd6e-166b9a9e903a · outbound

This paper cites Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.418475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.418475Z digest=sha256:ce0c12a46ee3e46390ec8e321659e7ae0b0d44444fafb01974614ec1856aa888

Observation ceeac16c-a177-408b-b455-c5e0590730c7 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.424730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.424730Z digest=sha256:a4f46c2f9f56bbe313f2945040b6e3c5d7fa3f509056a84af80368c57315f3ca

Observation 07bc5713-0f55-490b-a425-238384592d25 · outbound

This paper cites G.; and Goldstein, T.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge G.; and Goldstein, T

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:22:26.208597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.430323Z digest=sha256:898fcc404daa41ce3e6d0f733cdbceab0ca2d66f7c6baedfd10b0f2503961255

Observation bbfdd448-49ec-422a-96b8-e6dbe5b93757 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.189564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.436388Z digest=sha256:91f78cb35e4f1347c036e0b87e2ca2c45cf00e515113ea3b1c2d10e48f0514eb

Observation 1b76d721-b10f-47d9-a92b-e13ecabcfed3 · outbound

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

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge J.; yelong shen; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:22:26.172054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.441620Z digest=sha256:b020f8203b515201c5682258e7f0f88f6e17e5d7a9108b5939134a920b87f7ee

Observation ce49f988-2075-4a24-b4a1-a6b8283b8947 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.153925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.446452Z digest=sha256:58cd1976ddb432549b6524194e4c4eabea1368b23570c21b9a9944fb7e01d4d0

Observation cbef3a7f-c6c2-44a7-b34f-db56cd5d7139 · outbound

This paper cites B.; Avent, B.; Bellet, A.; Bennis, M.; Bhagoji, A.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge B.; Avent, B.; Bellet, A.; Bennis, M.; Bhagoji, A

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:22:26.136200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.450949Z digest=sha256:cd200e8b3385a41c1b803b32ed2e7092f1acb7f8ccca9e7c6596a138eb0e0466

Observation f5a378d7-9d77-449e-bdbe-739ef60a7bff · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.117401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.456020Z digest=sha256:5b9fb98f1e883ef6c08678b9aa711c31fc80fe1f9091a9ad668b515f6df550d7

Observation 9fa7398f-3b77-4206-84f2-21d2f6d7868f · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.100804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.460963Z digest=sha256:2afecc770611bf4e29e7ce54c3d78f53602b7c7ba8e3eb06e93f4ede3c651798

Observation 26566256-e179-42ae-a809-5bc3d060fa88 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.083018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.465906Z digest=sha256:8557711277059ae008bb92ff9a4df85ba51089739d7bfa9d1818a36dbac7efa7

Observation c8e21d53-fa6d-4e5a-9db4-c6ac92ae16dc · outbound

This paper cites Resource-Efficient Federated Fine-Tuning Large Language Models for Heterogeneous Data.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Resource-Efficient Federated Fine-Tuning Large Language Models for Heterogeneous Data

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:22:25.703254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.471054Z digest=sha256:f707c87af058bc80a1a3be8b48bc0069aa08ddbe4e238a796bc5b1a32ba88879

Observation 89c28913-22c7-4fef-8d13-344e92ef65cd · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.065797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.478177Z digest=sha256:26023c725474719bb5a8fec7f6f7963cb7a679daa61a53b16fab3f617bc0cb8b

Observation 66c642d7-1089-4797-a0a6-f77d7fc6e08f · outbound

This paper cites FedMoE: Personalized Federated Learning via Heterogeneous Mixture of Experts.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge FedMoE: Personalized Federated Learning via Heterogeneous Mixture of Experts

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.483701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.483701Z digest=sha256:e68dea30762edf083958ae9413aa7b069091d872f8522b6053fc0dc37c3a2ed2

Observation aa3a1092-0954-4e85-a58b-6f398cb810b4 · outbound

This paper cites K.; Jonnalagadda, A.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge K.; Jonnalagadda, A

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:22:26.048018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.490289Z digest=sha256:d5b42a3968866aed3fc8ffd679b63e0339b886f59900d10425166f8e7bbc3b72

Observation 64d21c20-29aa-459b-b7b8-90d4eb5d7736 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.029087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.495083Z digest=sha256:11eddf7c855c564ce5bfbff219bb20a4d95387352aa25e7e2d1df28811eab4b6

Observation f7eef584-1da0-4299-a807-e5d99202b3f2 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:26.003149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.499731Z digest=sha256:9ebead5f9d8b93b5a6b928c274d6ea8f60e26784d81f20b4940557a285abb900

Observation 71abbc87-b442-455b-bf3b-c7c1a9b53ed0 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.504764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.504764Z digest=sha256:23c608ebfd7960fc86acf7d494ff29828686ddd0797fae65cae7bcfd6cb11004

Observation ae414031-2a40-400a-8591-5a39e89030a4 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.971355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.509317Z digest=sha256:b1e19c469f57251b96022dfc3e371269130e7712e631b3f18f669a3688cdf0e5

Observation 49c03f7c-cbc7-46e5-b151-99d93cb39389 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.955528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.514028Z digest=sha256:7d3364a2b2ed9ba9c7f5bb0a424a0295e3428110b83a303fa83df0d550340d1b

Observation 3765bc65-ac7d-4b75-8293-899abc884a9b · outbound

This paper cites H.; and Pham, V.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge H.; and Pham, V

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:22:25.938836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.519063Z digest=sha256:aa3e2aab52bf3afa1a14423e9e05bb81d962518f66d8f2a7392134041d500796

Observation 5691ae14-8cd8-4cac-887a-102267721cde · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.919811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.523777Z digest=sha256:074e6d33cb5f2e2892a7f96d7812cdd655c08f0bad41dc95a0bb0404f5f0c19c

Observation 33b8518d-da2f-447d-a858-356dd09d21fd · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.902965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.528328Z digest=sha256:4d7e5e3d02dfb088e5e5bc54bbad8db23240bd9f21da428eeef14826a4bc5ade

Observation 093a9f81-8683-4e1b-99bf-e02c5beb27d0 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.886911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.533603Z digest=sha256:819ee6738475b3e9396e95a503c253e090759fc9ef51094452b0a2bf7d45b72b

Observation 2f3d38ee-a558-4ccb-b7e9-40d4391afc26 · outbound

This paper cites FeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge FeDeRA:Efficient Fine-tuning of Language Models in Federated Learning Leveraging Weight Decomposition

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.538325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.538325Z digest=sha256:9188d1260aa5b2d0702ccce92d36fc87315e7518180216c26b4c522091a2ce46

Observation be730c2f-2d52-454d-ad5b-17a377dd6e3a · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.870688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.543751Z digest=sha256:818ef8903d2bffbe9513e377750037701a6b37dc058d3c7b95d1db7e1c5b8138

Observation 15e700d4-e4e0-4846-93d3-38fd702f1e52 · outbound

This paper cites FedMoE-DA: Federated Mixture of Experts via Domain Aware Fine-grained Aggregation.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge FedMoE-DA: Federated Mixture of Experts via Domain Aware Fine-grained Aggregation

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.548290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.548290Z digest=sha256:857428c911e5591158084af28b49286b3129fab764e6bf48212945e4e21d556b

Observation 9c2e49c8-db44-4c50-93a5-8bdbec7997b6 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.854888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.553351Z digest=sha256:2940fb1f573ce69e510a18b2945e5af8146cc384cdeb929bdd6dd52f469faab0

Observation e88f9537-4fee-486e-a007-f201d0ed2627 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.837908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.558629Z digest=sha256:b453068537067de675b6d03fdb8a32f5cc708a4e46c74d2139345d014caed52b

Observation d5ccaac9-237d-422e-bf55-b4db6ab09198 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.820726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.563460Z digest=sha256:7ba0b0162c6df6f34e78a8b31ed6a62140395499b777e6cee8e9ae6cbf7fac29

Observation 3cd456ab-afb0-49f8-9590-f544e98381a0 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.804657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.568691Z digest=sha256:b2060c46098d82cf29facf0d92f047ffaf3e74af482dd5b831fcbb9da18ce1c0

Observation f1596c53-921a-4b73-95b0-c567aa4af1ee · outbound

This paper cites A Survey of Large Language Models.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge A Survey of Large Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T16:22:25.573331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:22:25.573331Z digest=sha256:0c9436e2c8e91b6229edfeefc2c73248f457da6a9294c0000725b7c7787b416b

Observation 8fce0adf-c42b-4565-a7d7-142becf0c521 · outbound

This paper cites M.; Chen, z.; Le, Q.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge M.; Chen, z.; Le, Q

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:22:25.785641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.578286Z digest=sha256:2b0c6f2baa81824061c16e15f687f66679c4939dc071719dd79ff87b4d442806

Observation c97ff0c6-d97a-4ad1-b0f6-00438566c029 · outbound

This paper cites an unresolved cited work.

FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:22:25.765971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-05T16:22:25.583269Z digest=sha256:da342c5892fd2ddc4daca38c641fd73e0dd0849313376a1d3b6dab1b91fc1422

Pith citing papers

Observation 4048f409-845f-49f5-b452-5a8b11168b3e · inbound

Enhancing Cross-Problem Vehicle Routing via Federated Learning cites this paper.

Enhancing Cross-Problem Vehicle Routing via Federated Learning FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:06:02.383975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-10T15:39:47.782902Z digest=sha256:4393d311f157ccdbf45d7d74c0ce3e918aaaa84d39713f4d810971ed16e78c2b

Observation ce84f098-2229-45e3-ae9b-e756142a298f · inbound

Priority-Aware Learning-Unlearning Correction for Dynamic Decentralized LoRA Fine-Tuning cites this paper.

Priority-Aware Learning-Unlearning Correction for Dynamic Decentralized LoRA Fine-Tuning FFT-MoE: Efficient Federated Fine-Tuning for Foundation Models via Large-scale Sparse MoE under Heterogeneous Edge

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-07-04T09:49:44.427045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T09:29:03.234211Z digest=sha256:6f5eb5a79f77ec462bb308c0a43f07c7acaa6d3c62eba144bdb91f86f28ceedc