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Paper Citation Record · LEDGER

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications

As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2512.08211.

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

pith.paper-citation-record.v1
2512.08211 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T17:47:51.694630Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T14:26:16.480948Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T14:28:21.190776Z

Reference resolution

47 of 47 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved44
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation adceb667-25aa-4dff-8f32-45e2848eeed8 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:46.935077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:46.935077Z digest=sha256:6fa2b72821a1adfc56dd2fb354eb9a9331063e0c0ce93d9209cf2f8dd5687337

Observation e383cc45-69f9-4e5b-b8f7-813b5ab7f382 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:46.991653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:46.991653Z digest=sha256:54793de9e36472a57c712bad7080f3eabbf065f7186a6fae20594b2eb3b13afc

Observation ec72b4d0-0408-42a8-b6df-f474e66c2bbb · outbound

This paper cites Flower: A Friendly Federated Learning Research Framework.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Flower: A Friendly Federated Learning Research Framework

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:47.164669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:47.164669Z digest=sha256:97dd3f331dd8d1a67989e432db30a0e4a7319159e8c0c8e68de86077b3e3023b

Observation 36939b69-3eb2-417b-865f-d930aa0ee4cb · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:47.254784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:47.254784Z digest=sha256:a2fd0bc46175f00b2e25462895f313a0646987d9ed95b1ae9ce309f610fdb603

Observation 7463a3dc-adec-49a6-b68d-980baa4aae16 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:47.334398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:47.334398Z digest=sha256:6872b065d3ed670e75bdc099289b059c5ac086b5386f2d2124f1f8a4c9d2f7de

Observation 1fbdd16b-6d79-4a78-9433-e8ce138b3c0d · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:47.533910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:47.533910Z digest=sha256:770cbb404fc1f71608e4e5739ec7837cc840a663bd6e51b0d48b42acd9dfbfa3

Observation 421f1fc8-7fd3-4279-8497-c3f05b1d3645 · outbound

This paper cites 2016.Reg- ulation (EU) 2016/679 of the European Parliament and of the Council.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications 2016.Reg- ulation (EU) 2016/679 of the European Parliament and of the Council

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:47.686559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:47.686559Z digest=sha256:91287d8e1618828039dcfe1d83a1c0c880521acded93cc8661b53e8067579883

Observation 0e1a89d6-fb25-4a8d-b70e-48718b10a8b6 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 8

Resolution
verified exact
doi, observed 2026-08-03T17:48:37.040405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-03T17:47:47.763922Z digest=sha256:9d8fb90207385e2688c70fae29c13044cff0210ec31008b6bdb02b252d51d3e5

Observation 43176b41-9002-404e-995d-93b5b1b24c66 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:47.897010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:47.897010Z digest=sha256:d32ccb0ee6542311ec59bc5ab29e2dfcf8f0e1ae5061e7f11be72bbaf33c4d8c

Observation cb8262ff-a1b4-4e8f-abdf-c19ba22c049d · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:48.135900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:48.135900Z digest=sha256:d0b0cbb1205c86c2afe492afbdd515086362fca149cd72ba7a53a66847c8d0dc

Observation 58fe930f-668b-43a1-877a-904cc92ac2d6 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:48.240018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:48.240018Z digest=sha256:e9478222dcac915d6022415c759d42f22e1d514f66ac00a07713c6b53c68e78c

Observation 8ea44ed1-35f7-44e0-b5a1-20d8cebc0147 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Measuring Massive Multitask Language Understanding

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:48.459863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:48.459863Z digest=sha256:5c772cfb98cde77dae0bad8a75221946d297b9afea29aee10e9080a97e7c2a96

Observation ddb25f28-644a-4861-894a-1e88d9e5e0f0 · outbound

This paper cites Scaling Laws for Neural Language Models.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Scaling Laws for Neural Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:48.577744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:48.577744Z digest=sha256:178a739c6f88af075fb990b3c2b03517703beab6d965c7c02d96ddc58e639d02

Observation 4fc5cf84-41f6-4e48-a18d-2216118976c3 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 15

Resolution
malformed identifier
no resolver link, observed 2026-08-03T17:47:48.711247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:48.711247Z digest=sha256:656f7a6fb02cb85b8d7527b7c27f804b39c49da0db4237112710e18bf71c6dc9

Observation 6d9610ac-061c-4f99-b6c2-c5b4260483d0 · outbound

This paper cites MobiLLM: Enabling LLM Fine-Tuning on the Mobile Device via Server Assisted Side Tuning.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications MobiLLM: Enabling LLM Fine-Tuning on the Mobile Device via Server Assisted Side Tuning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:48.835209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:48.835209Z digest=sha256:d9e1ca9f771bc75514c688f357995836a018f9223a6d9bcfafb951eba452dd91

Observation 7dbc715f-7ae1-40ae-891f-d74821b4f309 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:48.912536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:48.912536Z digest=sha256:86ea312ea3d26a685a6ab64787cda2a235c9a30575666550f2ed9c9893c6de16

Observation 7d6fd130-8bb9-4888-bf85-38e5d83e8dcc · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.020299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.020299Z digest=sha256:995afeae7e1e7766815cfbe84d34efdf7fb51005371a81716626f35424510056

Observation d1835f65-b049-4cd4-a5ae-0e60cec1f965 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.089702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.089702Z digest=sha256:14fbdd806524b9ecafc34b7f043ecd12c05a187a081357bab41e904eaa62ebaf

Observation ad214917-8298-4317-a947-b2c675d398b2 · outbound

This paper cites GPT-4 Technical Report.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications GPT-4 Technical Report

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.198926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.198926Z digest=sha256:d8d01274c68740c7c0395420cfbbc0f739fcfd88b207c24b2dcd7e0b93e7dcd9

Observation 1d646492-888d-465d-8ad0-d40573cb6a32 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.330440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.330440Z digest=sha256:34377e676a2f4b43d879d687ccb4119207fcc04d75bf5ad88aa47d8bc2fad944

Observation 0e017cac-54f6-4ff4-a99e-f277618a1a26 · outbound

This paper cites InProceedings of the Workshop on Edge and Mobile Foundation Models(Minato-ku, Tokyo, Japan)(EdgeFM ’24).

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications InProceedings of the Workshop on Edge and Mobile Foundation Models(Minato-ku, Tokyo, Japan)(EdgeFM ’24)

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:48.957400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:48.957400Z digest=sha256:11b9b181e4fe6f284d9adf30003affe0322908ecc9234fc14ce95856d92221c6

Observation 809cdd51-6beb-4e60-8a5d-e934f4fec282 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.549561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.549561Z digest=sha256:1d33c23a3370e90746dcce6bed1579e9c2f0f93a6ebd34f2f397ec0793a71abd

Observation a9f82803-aa96-4bcd-bef7-9febc994c47b · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.680464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.680464Z digest=sha256:1c36c8cf9bd14ceacecac9c1e8f47a945b3a8dd2cbb03a68c331f356073fc5de

Observation eaa2f9b7-3f11-46d7-9d57-166cadb1a1fa · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.877966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.877966Z digest=sha256:d20fe8d1b473a906f56c45961955b8afb6e11338067dcf00af811c57b5136478

Observation e8949ee1-4704-4856-8729-b95bea4ada9d · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.990398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.990398Z digest=sha256:6c1611e03f08688be0d0faf4dfae8b4ca2d866d4a6e6655d95e487796b675b1c

Observation 7bbc37e1-de9c-4bd0-9291-c2e56e339fa3 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:49.431963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:49.431963Z digest=sha256:b88de6e232aa7ef9ed6628f7d955c81fd165e6e9f8aa0461fdb7eeb265362734

Observation b5f33162-4264-475d-be3e-13ce93618974 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:50.357871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:50.357871Z digest=sha256:814600ac6171828fc30cfd31d6922eb44689c950b5ba25787a88e1f6e46e0e53

Observation 538dd811-8a7e-4977-8913-e13c7bb3cfc0 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:50.516949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:50.516949Z digest=sha256:ea02c28c39a4e5e6ca6cd976dd0c2bdb2cc59f4ec2ebdb6aa551629d36b4ac38

Observation 8aa27b3d-e19a-4b56-bac9-5b936567e77e · outbound

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

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications LLaMA: Open and Efficient Foundation Language Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:50.632060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:50.632060Z digest=sha256:b67e8f3c044b1b50c05eed0394a379333cd42bfe5e39e5ad1c44d9376c000c3e

Observation 571c5578-f93d-4ad8-96c9-cbae0af64abb · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:50.699916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:50.699916Z digest=sha256:775757285239a7ca9d8c90a0942ef7a0e595a3678a9f4eaa92ea70586bc06063

Observation 87314f51-e371-4f9a-acca-a3f0c099b962 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:50.778913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:50.778913Z digest=sha256:ea5ddf7ab2ce07b7788d1b050ae6504ec7aed313e05b7bd69c7f73c8d745880e

Observation bf4f1a56-a9f3-4068-88a8-45ca7c951ca6 · outbound

This paper cites Gemma 3 Technical Report.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Gemma 3 Technical Report

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:50.246906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:50.246906Z digest=sha256:4d868923dbb31b7129b5878afab76cc39efa4c2f002107d1fc2eb7b78cee6b83

Observation 4ef67e81-b50a-4f41-8e42-412ba8cda4db · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:50.963190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:50.963190Z digest=sha256:5f25618af4d7a572fcc8ba8eb97598157958e9cb3332a33be801ae7d1e50eaed

Observation 76a45413-21a2-4924-b031-3e02049d70f5 · outbound

This paper cites Smith, Iz Beltagy, and Hannaneh Hajishirzi.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Smith, Iz Beltagy, and Hannaneh Hajishirzi

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:51.035932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:51.035932Z digest=sha256:b99e3210728aeef8ef859e3af73ad582fc1eed44912f555506c00a112b2c1d8b

Observation a3bed4f8-f0ec-461d-8e86-17793e865c7f · outbound

This paper cites Smith, Daniel Khashabi, and Hannaneh Hajishirzi.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Smith, Daniel Khashabi, and Hannaneh Hajishirzi

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:51.118351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:51.118351Z digest=sha256:312e7374736ae028892c7a51dbdbacc6460d7091440109f7cbd4aeecab0150cb

Observation c5b4c9e3-0674-4170-bb2f-5d00e5fac613 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:51.212022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:47:51.212022Z digest=sha256:69a02fe38521a18d598e402af66904c123a51b793a2a1bc475df2ca14eef4b0d

Observation 0e5acd4e-1e75-4e46-8dba-cffaecf2589c · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-03T17:47:51.316867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 025878f6-a1f8-402d-9a37-801e40aa8092 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 39

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Observation 0081fb05-e2c7-4088-a1af-c36ffa71978e · outbound

This paper cites PAE MobiLLM: Privacy-Aware and Efficient LLM Fine-Tuning on the Mobile Device via Additive Side-Tuning.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications PAE MobiLLM: Privacy-Aware and Efficient LLM Fine-Tuning on the Mobile Device via Additive Side-Tuning

Reference 40

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Observation c428768f-5c42-4c0e-8a25-3b4936d0a534 · outbound

This paper cites Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Flexible Personalized Split Federated Learning for On-Device Fine-Tuning of Foundation Models

Reference 41

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Observation 41272a2a-80ec-483c-989e-9e697c472457 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 42

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Observation 058799e7-a1bd-4c21-be9b-88ba0f43d700 · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications BloombergGPT: A Large Language Model for Finance

Reference 45

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Observation 2c924511-6b1d-435f-b665-60cb3473ca9f · outbound

This paper cites InNorth American Chapter of the Association for Computational Linguistics.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications InNorth American Chapter of the Association for Computational Linguistics

Reference 2019

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no resolver link, observed 2026-08-03T17:47:47.612269Z

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Observation af7064ec-ec67-424f-9fb3-2c78a5b3b314 · outbound

This paper cites InProceedings of the International Conference for High Perfor- mance Computing, Networking, Storage and Analysis(Atlanta, Georgia) (SC ’20).

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications InProceedings of the International Conference for High Perfor- mance Computing, Networking, Storage and Analysis(Atlanta, Georgia) (SC ’20)

Reference 2020

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Observation 0ae48ac5-40e1-44b8-8c73-d2caaf724493 · outbound

This paper cites InProceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen (Eds.).

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications InProceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, Yaser Al-Onaizan, Mohit Bansal, and Yun-Nung Chen (Eds.)

Reference 2024

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Observation c588bc0a-b143-4a1a-afa0-ac6abc451bb7 · outbound

This paper cites IEEE Transactions on Knowledge and Data Engineering37, 7 (2025), 4314–4337.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications IEEE Transactions on Knowledge and Data Engineering37, 7 (2025), 4314–4337

Reference 2025

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no resolver link, observed 2026-08-03T17:47:47.942964Z

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Observation 65bd863b-07f0-4057-abd6-063c28622be4 · outbound

This paper cites an unresolved cited work.

MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications Unresolved cited work

Reference 3731

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

Observation d6381128-3bb8-40da-88a3-d3b3a6acbfa0 · inbound

OpenJarvis: Personal AI, On Personal Devices cites this paper.

OpenJarvis: Personal AI, On Personal Devices MobileFineTuner: A Mobile-Native Framework for On-Device LLM Fine-Tuning in Real-World Embedded AI Applications

Reference 12

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arxiv_id, observed 2026-06-11T02:08:38.778813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T14:26:16.480948Z digest=sha256:65967a7922a9b8b0511222be397f704d3c248adace8be4b9c4e70fedd9e86744