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Paper Citation Record · LEDGER

The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2311.09807.

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

pith.paper-citation-record.v1
2311.09807 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:10:46.550220Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

8
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5bbd5ca4-7aec-43ff-af50-de81897a7f42 · inbound

Benchmarking LLMs for Mimicking Child-Caregiver Language in Interaction cites this paper.

Benchmarking LLMs for Mimicking Child-Caregiver Language in Interaction The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T17:10:46.550220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:10:46.550220Z digest=sha256:5c8788f6b2e06f29238aa3dc1c0c8d969df978dde3a4d9fab095d700d69c4de1

Observation 9e073b28-c120-49c2-aa09-604ca23051cc · inbound

BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation cites this paper.

BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-09T17:09:15.278911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:09:15.278911Z digest=sha256:a8de7e050548e4bd8459f02ca35ba56e922141e0f67b36d3057146b0915f8f4b

Observation 3a617063-816c-4668-a12f-0be74055f795 · inbound

The Anatomy of Speech Persuasion: Linguistic Shifts in LLM-Modified Speeches cites this paper.

The Anatomy of Speech Persuasion: Linguistic Shifts in LLM-Modified Speeches The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T23:20:13.379300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:20:13.379300Z digest=sha256:4506509c00367fa41b1561b86b87aebab797c8372949f53f56388cabb2a3d377

Observation d43b8f4d-bb3b-462c-8989-9ac16ce16723 · inbound

What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning cites this paper.

What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T23:12:18.948737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:18.948737Z digest=sha256:086280cd22349c1e19bd4d79434691a670997227686e46a156964249c8856749

Observation c2822921-98b7-4968-8c90-f1459a61e799 · inbound

A Penalty Goes a Long Way: Measuring Lexical Diversity in Synthetic Texts Under Prompt-Influenced Length Variations cites this paper.

A Penalty Goes a Long Way: Measuring Lexical Diversity in Synthetic Texts Under Prompt-Influenced Length Variations The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T15:46:27.757714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:46:27.757714Z digest=sha256:82344f4d3110180bc2de9b46b0084637b2f4a663388982990b793f71bf08d8c7

Observation 0f22bac7-b672-4349-a610-eaf3bd30727e · inbound

Generative artificial intelligence reduces social welfare through model collapse cites this paper.

Generative artificial intelligence reduces social welfare through model collapse The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:56:05.941773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T13:26:57.925635Z digest=sha256:f1f2e230883152948282a07a84463023e0b334239754c7eb5a6acc769a5fd855

Observation 43e676dc-a2e9-478b-adba-0cdf7a8bec5e · inbound

Iterative Finetuning is Mostly Idempotent cites this paper.

Iterative Finetuning is Mostly Idempotent The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:51:44.514005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-09T19:04:36.210200Z digest=sha256:50b921d06d465a1f9413b670746d24f9d1db3651a7fc0dc5faa6aabd740b297e

Observation 8dde98ac-b9d1-40b3-ba19-c46568f05408 · inbound

When transformers learn "impossible" languages, what do they learn? cites this paper.

When transformers learn "impossible" languages, what do they learn? The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-07-01T02:15:14.451413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-07-01T02:13:58.839175Z digest=sha256:6298ecff4eb9070514f6a72406b38063f9efe9eead056543b5cb792db4233ab8