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Paper Citation Record · LEDGER

Modern Distributed Data-Parallel Large-Scale Pre-training Strategies For NLP models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2206.06356.

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

pith.paper-citation-record.v1
2206.06356 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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:08:33.686370Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T18:16:14.067578Z

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 45fa7540-30dd-4905-a29e-110b67cda58b · inbound

Parameter-Efficient Checkpoint Merging via Metrics-Weighted Averaging cites this paper.

Parameter-Efficient Checkpoint Merging via Metrics-Weighted Averaging Modern Distributed Data-Parallel Large-Scale Pre-training Strategies For NLP models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T11:08:33.686370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:08:33.686370Z digest=sha256:90887683c5be8e13a3e676852e2951e1ea04208650619c2b34f0d9677883593e

Observation 8b4ec38d-0618-4713-ad7f-e26e52eea656 · inbound

Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language cites this paper.

Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language Modern Distributed Data-Parallel Large-Scale Pre-training Strategies For NLP models

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-15T14:50:57.550867Z

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=2026-08-15T14:50:56.187201Z digest=sha256:a2996c73dbd4ea90d1c6562c6424161c8a563316d12ade83aa7455a8db65fe52