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Paper Citation Record · LEDGER

DiPaCo: Distributed Path Composition

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2403.10616.

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

pith.paper-citation-record.v1
2403.10616 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:47:48.649408Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:40:00.429978Z

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 2cb36128-713c-48a7-8058-5f6d3c61a977 · inbound

Towards Responsible Governing AI Proliferation cites this paper.

Towards Responsible Governing AI Proliferation DiPaCo: Distributed Path Composition

Reference 107

Resolution
unresolved
no resolver link, observed 2026-08-11T12:47:48.649408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:47:48.649408Z digest=sha256:50c2670a9c731f696c8309782769cf804993d4bb1b3e203d5a2236edbf6eba14

Observation e702c6c0-7578-412f-ad1f-6cf7ddfd445c · inbound

Universal Model Routing for Efficient LLM Inference cites this paper.

Universal Model Routing for Efficient LLM Inference DiPaCo: Distributed Path Composition

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T23:48:00.878478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:48:00.878478Z digest=sha256:ae2e14331aa7c5f7411ff150a9a60149a3d0555f76febdcb27c4a124e7ce708f

Observation 4d229f63-2d0b-43a6-bd9c-1b00d23b3a15 · inbound

NoLoCo: No-all-reduce Low Communication Training Method for Large Models cites this paper.

NoLoCo: No-all-reduce Low Communication Training Method for Large Models DiPaCo: Distributed Path Composition

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T04:20:01.483869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:20:01.483869Z digest=sha256:b90f50cb446e3e5db2bbdfbc6729997fb98af4fe84de1e120156bfaadf5869af

Observation 69894451-c349-4560-a1fb-dcb9593e7689 · inbound

FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs cites this paper.

FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs DiPaCo: Distributed Path Composition

Reference 98

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T00:09:15.145226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-26T21:25:15.709652Z digest=sha256:e12ad84b4bfdb0dfbdd450b44ffab5ae1f2076d6a9be8fa8cc1418ef2a1673bc

Observation 79c10cbd-2b7f-49ac-a1c1-83e8df8416a4 · inbound

Decentralised AI Training and Inference with BlockTrain cites this paper.

Decentralised AI Training and Inference with BlockTrain DiPaCo: Distributed Path Composition

Reference 78

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:40:00.431347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-25T23:32:43.585170Z digest=sha256:09b107fe9101d2fbcbb7f8ea8cb5420a8d3eb7e8a42c01c4275821611f7808a8

Observation 51646666-7d4f-4119-ba3b-3c88e434897f · inbound

Decentralised AI Training and Inference with BlockTrain cites this paper.

Decentralised AI Training and Inference with BlockTrain DiPaCo: Distributed Path Composition

Reference 13

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:bad3daf14412f2e5f28a492e6a8d6640ad3ce83f640e13c31234642cef83304b