Paper Citation Record · LEDGER

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity

As of 10 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2507.22633.

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

pith.paper-citation-record.v1
2507.22633 v2

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:37:43.419658Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

45 of 45 outbound references displayed

verified exact2
verified fuzzy11
unresolved32
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 090b6642-268f-4c69-8330-0a32d12c82ac · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.226866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 34363827-261b-4920-aa9d-8531edecca26 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.221172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c02cb925-844b-4bef-bafd-5365165b5ef8 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.215438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 690c545e-75b0-487d-886b-1a3ed3bce1a9 · outbound

This paper cites Qwen Technical Report.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Qwen Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:38.709543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a2aa4aa-9614-472f-a18f-79f8c5209cb4 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.209786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 78f34b7d-c3c2-42fd-ba1b-74b174b6c041 · outbound

This paper cites Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:38.913679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bc7c8a0-6a95-4e3a-936f-f36429a6c129 · outbound

This paper cites Chen and A.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Chen and A

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:45.204220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1f625428-9dac-45d7-9add-9ae290821c8b · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.198500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3afe39fc-2436-4ff9-b530-5c4840e3abd5 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.192562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 07f30dd1-28da-480b-bef2-168820f32023 · outbound

This paper cites Cheng, J.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Cheng, J

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:39.478119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2ef39e7-2b29-4764-ac33-3ec5d6e07759 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.186413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8d9714c3-9ad1-471f-9d75-347e43ee1594 · outbound

This paper cites HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:39.849590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e71844b3-6467-4ca1-8fb8-5fdf5b53d6a4 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.180376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c6e06366-347f-4897-a80e-b25459562318 · outbound

This paper cites The Llama 3 Herd of Models.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity The Llama 3 Herd of Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:40.128580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 259e232d-d880-4c3a-87b6-489dd0a1c08b · outbound

This paper cites Approximation Methods for Bilevel Programming.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Approximation Methods for Bilevel Programming

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:40.255726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6af03f47-6e8c-4e8c-a72e-a13ec4c66587 · outbound

This paper cites Ghadimi, G.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Ghadimi, G

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:45.174406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5eb30e1e-f2c2-4c7f-b1ea-230a65c673da · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:40.436900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10569929-b9ef-4df5-a0e3-19eb33ae21b7 · outbound

This paper cites Horvath, S.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Horvath, S

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:45.168502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2bf62b09-0550-46c4-95d5-0f62b99e1b7e · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity LoRA: Low-Rank Adaptation of Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:40.782404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ff9618c-7b27-41d6-9648-9ca51927cc36 · outbound

This paper cites Huang, J.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Huang, J

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:45.162443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b4421382-8406-4c36-b5a2-b8328f12f42c · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.156559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c01c419c-f8ba-4262-a2ee-006b1ae1a44c · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.150605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dbb67af8-fe81-4a99-9a1b-ba3812409ef9 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.144214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dedbf651-814f-4e14-b107-41a8b62b1d5f · outbound

This paper cites HeteroTune: Efficient Federated Learning for Large Heterogeneous Models.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity HeteroTune: Efficient Federated Learning for Large Heterogeneous Models

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-06T11:37:43.817031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 54e4715d-9b4c-4975-aa39-5728d8da8b65 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.137990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cd85b0a9-c448-4b5d-ae8f-902235cba9a3 · outbound

This paper cites Jiang, H.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Jiang, H

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:45.131442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9beac73b-2d34-4697-aedb-781b960fc492 · outbound

This paper cites Kuang, B.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Kuang, B

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:45.124649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2013c1b1-9160-479e-a136-42359acb7ba3 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.118453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d2e1c1e1-11cc-4295-956a-9b25fe928a0e · outbound

This paper cites HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-06T11:37:43.640647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ff4b47d5-8ec9-45cb-87af-c16d5dcd0890 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.112024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89c37522-d0cc-49c2-9025-ea10151b47dd · outbound

This paper cites Rajput, A.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Rajput, A

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:45.105707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 64f808df-e955-4269-aa97-0e4a01210bf2 · outbound

This paper cites Federated Mutual Learning.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Federated Mutual Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:42.411641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa08bc88-69e4-4fcf-8787-4161e0ae2059 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Gemma: Open Models Based on Gemini Research and Technology

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:42.517801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edd6b025-1ad0-4dff-82c7-698590731c6a · outbound

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

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity LLaMA: Open and Efficient Foundation Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:42.612644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63d505ef-d29a-48e9-8946-6ecd18af993a · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:42.689264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d951e32e-8f09-4f81-b04d-376654036ce8 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:45.099157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5f5439c1-fcf1-4ca4-9d1c-5f4f55d1bd2d · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:42.787292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f588f620-07f3-4136-8601-99e778b740b7 · outbound

This paper cites an unresolved cited work.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:37:44.860726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51e82633-3e6c-48fb-bc1d-3885e73d7253 · outbound

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

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:42.938314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 238cdb14-ebd1-4e70-829e-b27067238c01 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Yi: Open Foundation Models by 01.AI

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:43.007872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d0b860a-7902-4882-8626-5269e2bba019 · outbound

This paper cites MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T11:37:43.139476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6de8fd76-9e57-4b13-9f07-349cf2561d9e · outbound

This paper cites Zhang, S.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Zhang, S

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:44.639990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cbff5148-776f-4992-85cb-d1cde4ec77a5 · outbound

This paper cites Zhang, L.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity Zhang, L

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:44.402663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bf4113f9-6b49-4266-b8e0-ddcc557c8baf · outbound

This paper cites L2 1 − 2 L2 + α τ 1 α + 2 L2 + α L2L4 α + L3 ∆ 1 − 2 L2+α · α τ 1 − 2 L2+α · α − L2−α L2+α #2 + 4L2 2∆2. (36) Thus, we have: − ∥Gτ −1 t ∥2 ≤ −1 2 ∥ ˜Gτ −1 t ∥2 + 2(L2 + L2 2 α )2.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity L2 1 − 2 L2 + α τ 1 α + 2 L2 + α L2L4 α + L3 ∆ 1 − 2 L2+α · α τ 1 − 2 L2+α · α − L2−α L2+α #2 + 4L2 2∆2. (36) Thus, we have: − ∥Gτ −1 t ∥2 ≤ −1 2 ∥ ˜Gτ −1 t ∥2 + 2(L2 + L2 2 α )2

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:44.219883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f39dad86-3b0b-4b8d-81f6-bb234b01127a · outbound

This paper cites (43) Thus, we complete the proof of Theorem 1.

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity (43) Thus, we complete the proof of Theorem 1

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:37:44.065237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.