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Paper Citation Record · LEDGER

Maximizing Parallelism in Distributed Training for Huge Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2105.14450.

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

pith.paper-citation-record.v1
2105.14450 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:18:09.169550Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T17:55:12.935227Z

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 64bc5af2-2650-482d-8c20-a9a99785f031 · inbound

DeepCEE: Efficient Cross-Region Model Distributed Training System under Heterogeneous GPUs and Networks cites this paper.

DeepCEE: Efficient Cross-Region Model Distributed Training System under Heterogeneous GPUs and Networks Maximizing Parallelism in Distributed Training for Huge Neural Networks

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T15:18:09.169550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:18:09.169550Z digest=sha256:a7d1a91642da6e6fe674e947a4dba71fb9895dcb78bacc9abf6952fae1fa3426

Observation 16c73e13-a6d2-4f21-b730-3382a05f53b1 · inbound

TPLA: Tensor Parallel Latent Attention for Efficient Disaggregated Prefill and Decode Inference cites this paper.

TPLA: Tensor Parallel Latent Attention for Efficient Disaggregated Prefill and Decode Inference Maximizing Parallelism in Distributed Training for Huge Neural Networks

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-05T17:55:13.001003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T17:55:11.149864Z digest=sha256:5e68e4346e55b9e7238014a3c8086fddae9a9a414f5c243505f137dd3222e1e6