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Paper Citation Record · LEDGER

Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1809.02839.

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

pith.paper-citation-record.v1
1809.02839 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:33:18.119891Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:57:09.414715Z

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 a9f70b44-adca-4f76-9177-b3c6defd25a8 · inbound

Priority-Aware Model-Distributed Inference at Edge Networks cites this paper.

Priority-Aware Model-Distributed Inference at Edge Networks Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T14:12:32.692315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:12:32.692315Z digest=sha256:591760888432ed1250a42d78f8dd2f2044ebaf05d4cc7c6d97fc754b10818458

Observation 3fd4e7a3-dcb0-40dc-9765-de4d9b5941d9 · inbound

Nesterov Method for Asynchronous Pipeline Parallel Optimization cites this paper.

Nesterov Method for Asynchronous Pipeline Parallel Optimization Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-16T04:33:18.119891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:33:18.119891Z digest=sha256:303e99176acca4b342e9bef1e435546d4769bf1a38b54a3c7d12026d6c4732b8

Observation d24732bd-f917-4735-aaf3-297cf917e126 · inbound

EfficientLLM: Efficiency in Large Language Models cites this paper.

EfficientLLM: Efficiency in Large Language Models Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform

Reference 242

Resolution
unresolved
no resolver link, observed 2026-08-15T20:13:38.331260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:13:38.331260Z digest=sha256:535bb936adbbfd6fb4e51c138278be9cc31ef1050bcc99939d9b06722770fec8

Observation 14bde1c9-433b-453a-8ca4-c658c49ce72e · inbound

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

Efficient Training on Multiple Consumer GPUs with RoundPipe Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:31:26.836229Z

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=pdf_text observed=2026-05-07T10:37:22.251566Z digest=sha256:2d1b91352f0fa28c28a66fb53766ebc6645041e971f1a6ce6567952ae645e3eb

Observation a5f17598-e62b-4a0f-bb74-5696981623ed · 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 Efficient and Robust Parallel DNN Training through Model Parallelism on Multi-GPU Platform

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-02T16:57:09.416353Z

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=pdf_text observed=2026-06-27T22:19:15.307830Z digest=sha256:1a817058b0ae12c68ecdabb29b6b8b42231a2f3ad71a3a17b3c64d1ccdf32ae7