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Paper Citation Record · LEDGER

Training Multilingual Pre-trained Language Model with Byte-level Subwords

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2101.09469.

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

pith.paper-citation-record.v1
2101.09469 v2

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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:51:59.387040Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T15:01:03.856781Z

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 b906ff0d-0944-4135-a322-b7bc7ef414a4 · inbound

ASR-EC Benchmark: Evaluating Large Language Models on Chinese ASR Error Correction cites this paper.

ASR-EC Benchmark: Evaluating Large Language Models on Chinese ASR Error Correction Training Multilingual Pre-trained Language Model with Byte-level Subwords

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T22:51:59.387040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:51:59.387040Z digest=sha256:761927b2f020cf846529958fabca4f427225b2db28d05222f0e48b40800c601d

Observation 0ce89640-3128-476a-bb37-f449e427888c · inbound

The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices? cites this paper.

The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices? Training Multilingual Pre-trained Language Model with Byte-level Subwords

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-16T15:01:03.859206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-16T14:59:02.533789Z digest=sha256:c66568d8bc8290c29c52cbc6dc57e2712355796a44a375608231b03797b38c6d