Paper Citation Record · LEDGER

XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1911.04610.

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

pith.paper-citation-record.v1
1911.04610 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:33:18.127596Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:57:09.414556Z

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 6263b47d-7a6d-4a0d-9dc7-801cdcd5a309 · inbound

Nesterov Method for Asynchronous Pipeline Parallel Optimization cites this paper.

Nesterov Method for Asynchronous Pipeline Parallel Optimization XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-16T04:33:18.127596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42139d6c-cbc9-4868-9f4d-cbe870189d6e · inbound

Efficient Training on Multiple Consumer GPUs with RoundPipe cites this paper.

Efficient Training on Multiple Consumer GPUs with RoundPipe XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:31:26.827187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 51e65c00-dfa2-4b1a-aa8c-93077f346761 · inbound

Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency cites this paper.

Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:57:09.416074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c5f39593-7af5-4f2b-91e1-7906d886eeaf · inbound

One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining cites this paper.

One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining XPipe: Efficient Pipeline Model Parallelism for Multi-GPU DNN Training

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-30T06:44:18.859613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.