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Paper Citation Record · LEDGER

How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2404.05090.

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

pith.paper-citation-record.v1
2404.05090 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:59:48.929912Z

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

3
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 41537235-2c53-4a97-a0a3-da565367e547 · inbound

Using Sign Language Production as Data Augmentation to enhance Sign Language Translation cites this paper.

Using Sign Language Production as Data Augmentation to enhance Sign Language Translation How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T04:47:50.676984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:47:50.676984Z digest=sha256:2d22fe7aeabb8debe7b6826a24c3b2af64dbac9ab8b5cfad4a0e9d310dfa7bfb

Observation da71ca6e-0197-49cb-a9c3-d7a7f5be4859 · inbound

LLM Web Dynamics: Tracing Model Collapse in a Network of LLMs cites this paper.

LLM Web Dynamics: Tracing Model Collapse in a Network of LLMs How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T13:59:48.929912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:59:48.929912Z digest=sha256:88ce6bb9da924ff916641864ca4acf019fac69ee404caca9c78bbec9875f377b

Observation 9e77a416-a27a-4afa-88bf-749bc2797c13 · 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 How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T23:12:18.999831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:12:18.999831Z digest=sha256:bbaf8a110296ac1ae389e768c428a6f23b0d95f7bab51d4a3c277a49f9a45c83

Observation e9860435-a193-4322-89ae-96683773c6f5 · inbound

Unlocking Speech Instruction Data Potential with Query Rewriting cites this paper.

Unlocking Speech Instruction Data Potential with Query Rewriting How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T18:21:34.589888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:21:34.589888Z digest=sha256:a62f366acc18da636a1c97a7e53d3b8a9e3de2da2c6a924921cc22af74972ecb

Observation de233454-e05b-4173-837b-d657cdc9e7b2 · 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 How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T15:46:27.825071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:46:27.825071Z digest=sha256:4a2d919b10320a5d3d8caf82fd325d2c874b4be88026849e8a330fbd31d12a24

Observation 8bd8742f-9ea8-4afa-882f-10fa73018190 · inbound

A Generative Foundation Model for Chest Radiography cites this paper.

A Generative Foundation Model for Chest Radiography How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T10:38:07.338196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:38:07.338196Z digest=sha256:19b04fd8b0f238a70bb6f149ff1ebb03988938e45c2430a4bc16b4ca00355479

Observation 4f6ba3b3-58aa-49b0-ad13-64481b3a74e9 · inbound

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback cites this paper.

The Anti-Ouroboros Effect: Emergent Resilience in Large Language Models from Recursive Selective Feedback How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T12:04:03.464968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:04:03.464968Z digest=sha256:7b7a33494ba129d3d326af67c82cd3df2717a2962cb6ce2510d618a45d56e252

Observation d301647f-202c-40ee-812f-fd91324aeb54 · inbound

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

Generative artificial intelligence reduces social welfare through model collapse How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:56:05.954915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T13:26:57.925635Z digest=sha256:e2acbf993a18d8e38ce992475f62e4cac836a1c33eb6bf9bad943ecfb37cfa46

Observation e8c76f88-3021-4b45-bfa5-d9d524545786 · inbound

Iterative Finetuning is Mostly Idempotent cites this paper.

Iterative Finetuning is Mostly Idempotent How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T15:51:44.493288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-09T19:04:36.210200Z digest=sha256:c854c2fee2d5ceb1532db8fa5c8a6f041392043a434e0ab9be5ac5a953b9fac3

Observation 8a7e45be-ce65-4361-8a97-09e0b8041153 · inbound

Position: the Stochastic Parrot in the Coal Mine. Model Collapse is a Threat to Low-Resource Communities cites this paper.

Position: the Stochastic Parrot in the Coal Mine. Model Collapse is a Threat to Low-Resource Communities How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:35:40.856430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T18:16:51.881163Z digest=sha256:ee881f744437a84edf1e34d30e93b789df9a3e9c92fcd9353a19dda711c68846

Observation a1682d1f-71b2-41c1-8e89-604c1c312f94 · inbound

Self-Training Doesn't Flatten Language -- It Restructures It: Surface Markers Amplify While Deep Syntax Dies cites this paper.

Self-Training Doesn't Flatten Language -- It Restructures It: Surface Markers Amplify While Deep Syntax Dies How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:49:41.082711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-21T05:46:07.176408Z digest=sha256:16492d9ec270919b4141c10ff79451c6a4c41c6cf15decdd86972c3ff66aef1b

Observation bd86a422-b354-42b2-a0d1-f1764d53e3c9 · inbound

Model Collapse as Cultural Evolution cites this paper.

Model Collapse as Cultural Evolution How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:35:23.455429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-25T05:30:31.504863Z digest=sha256:a8f5ed64d0a398f269c067faed6f120ab08db110f4c2ddd5db88160453c4aac1

Observation 0741d3d5-8942-4747-b3ab-676ee7135479 · inbound

Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection cites this paper.

Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:03:29.933958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T13:53:27.306664Z digest=sha256:af0e278b12d50080b8da30ece6cd3acb2a12c01ade80a009e2ee007dd6142811

Observation 7f84393b-0640-4913-883a-bf65095ac936 · inbound

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs cites this paper.

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse

Reference 151

Resolution
verified exact
arxiv_id, observed 2026-06-30T01:34:09.458265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-30T01:29:42.919461Z digest=sha256:24e534c40cdd2400a423d9eb092bc8875659a9ea8b170296c393d92126b6734b