Paper Citation Record · LEDGER

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC)

As of 6 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2508.04745.

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

pith.paper-citation-record.v1
2508.04745 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:58:20.415003Z

measured 15 of 15 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

15 of 15 outbound references displayed

verified exact0
verified fuzzy11
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 56d57f3e-3010-41b2-bbf3-6bef94dd24aa · outbound

This paper cites Dreamstyler: Paint by style inversion with text-to-image diffusion models,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Dreamstyler: Paint by style inversion with text-to-image diffusion models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:23.087179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f7ce7041-7db3-4430-a12f-cfc9c246ef57 · outbound

This paper cites Implicit style- content separation using b-lora,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Implicit style- content separation using b-lora,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:22.800143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4dec0d91-1563-428e-a673-c7092d92da4c · outbound

This paper cites Areas of research focus and trends in the research on the application of aigc in healthcare,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Areas of research focus and trends in the research on the application of aigc in healthcare,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:22.504541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c2ecde56-ede6-4789-a80b-24a0ff1e19e8 · outbound

This paper cites Exploring collaborative distributed diffusion-based ai- generated content (aigc) in wireless networks,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Exploring collaborative distributed diffusion-based ai- generated content (aigc) in wireless networks,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:22.328840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 29215888-c44e-494f-9ac8-79971231ec7a · outbound

This paper cites EC-Diff: Fast and High-Quality Edge-Cloud Collaborative Inference for Diffusion Models.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) EC-Diff: Fast and High-Quality Edge-Cloud Collaborative Inference for Diffusion Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T00:58:19.508653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b5201ec-00ef-487a-9de1-1d0daf176802 · outbound

This paper cites Hybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Models.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Hybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T00:58:19.570595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d273b5b-e9fc-470b-a2d2-3b6b72f66bc5 · outbound

This paper cites Efficient multi-user offloading of personalized diffusion models: A drl- convex hybrid solution,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Efficient multi-user offloading of personalized diffusion models: A drl- convex hybrid solution,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:22.202602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c25abc73-8cb3-4898-ba3e-01e9f8648b10 · outbound

This paper cites Fedbip: Heterogeneous one-shot federated learning with personalized latent diffusion models,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Fedbip: Heterogeneous one-shot federated learning with personalized latent diffusion models,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:22.033247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6d95f0b5-b335-4849-9f7b-2bc530679ef1 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Lora: Low-rank adaptation of large language models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T00:58:19.781358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a893fb04-2b6c-4e09-a74f-2fb8d86c74ee · outbound

This paper cites The role of federated learning in a wireless world with foundation models,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) The role of federated learning in a wireless world with foundation models,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:21.802104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 04c482a7-cc9b-4816-85a9-db552ae85bef · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T00:58:20.016340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa05b5f4-44f3-48e7-8dfa-439468afa783 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject- driven generation,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Dreambooth: Fine tuning text-to-image diffusion models for subject- driven generation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:21.469458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e95057b1-7066-4c88-b517-51ee6467d2ab · outbound

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

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Flora: Federated fine-tuning large language models with heterogeneous low- rank adaptations,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:21.035773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f0476ef0-ac88-4fc2-82da-4c54fdb74f57 · outbound

This paper cites Towards personalized federated learning,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Towards personalized federated learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:20.824078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6ab53a99-c506-47e6-8bc5-9e278238e8a4 · outbound

This paper cites Phoenix: A federated gen- erative diffusion model,.

Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC) Phoenix: A federated gen- erative diffusion model,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:58:20.671355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

No inbound Pith citation observations are available.