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Paper Citation Record · LEDGER

FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.01172.

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

pith.paper-citation-record.v1
2309.01172 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T12:29:35.403453Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:40:00.410252Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7d7f853b-e695-49f8-9ea5-b34f2480fe83 · inbound

On Harnessing Idle Compute at the Edge for Foundation Model Training cites this paper.

On Harnessing Idle Compute at the Edge for Foundation Model Training FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-16T22:31:19.185684Z

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.

source=pdf_text observed=2026-05-16T22:29:25.686525Z digest=sha256:c4d3ad8af9f3c74b9c4fc8325bec82ad102ee00640728ec74acd5581e17440fd

Observation 935b8f21-0e9a-4442-b8c2-04f8b34eeab5 · inbound

Decentralised AI Training and Inference with BlockTrain cites this paper.

Decentralised AI Training and Inference with BlockTrain FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:40:00.411798Z

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.

source=arxiv_source observed=2026-06-25T23:32:43.585170Z digest=sha256:a7467615a43efb44791e4c19f89c8570d3b985cafdad3147b16f265f006446dd

Observation 47e69b2b-95f3-4a1d-afc4-e5ac12db2217 · inbound

Decentralised AI Training and Inference with BlockTrain cites this paper.

Decentralised AI Training and Inference with BlockTrain FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-12T12:29:35.403453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T12:29:35.403453Z digest=sha256:69526bda0ab95bb686a085b7ba999e57634d203af3a66feba587d93fa6b95997