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Paper Citation Record · LEDGER

WeLM: A Well-Read Pre-trained Language Model for Chinese

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2209.10372.

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

pith.paper-citation-record.v1
2209.10372 v5

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 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T03:36:43.839708Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T01:35:21.382868Z

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 d7d048b4-1751-41d4-ba4b-97abb0c944d0 · inbound

A Survey of Large Language Models cites this paper.

A Survey of Large Language Models WeLM: A Well-Read Pre-trained Language Model for Chinese

Reference 119

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:46:40.192200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T22:46:39.268353Z digest=sha256:e3af82a814b5da0314c96f62c9429cfb78e7a068473999417c9c4c20e596800a

Observation 663c631f-ef26-4fdb-9505-ab2983a601af · inbound

Scaling Data-Constrained Language Models cites this paper.

Scaling Data-Constrained Language Models WeLM: A Well-Read Pre-trained Language Model for Chinese

Reference 111

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:35:21.386113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-18T01:35:21.150772Z digest=sha256:b235ba99912df7b80bbcbc74dfd401d0a60e880d2ea65df46cf7b0e56c4af2ff

Observation 6f6e8c13-3300-4526-90f7-e31565de98f1 · inbound

ViCA: Efficient Multimodal LLMs with Vision-Only Cross-Attention cites this paper.

ViCA: Efficient Multimodal LLMs with Vision-Only Cross-Attention WeLM: A Well-Read Pre-trained Language Model for Chinese

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-03T03:36:43.839708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:36:43.839708Z digest=sha256:7eaf7704ad576440f43f9858fcc2a675d489cd085e35a3a7348b1c726ada3dce

Observation 8c043259-3480-4540-a9a2-e3667249cc64 · inbound

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models cites this paper.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models WeLM: A Well-Read Pre-trained Language Model for Chinese

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-02T09:43:25.728604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T09:43:25.728604Z digest=sha256:e5f56bb08bc89ac3822908a473051e21d561aca3b5bfa5191a8e7b22a25977a2