Paper Citation Record · LEDGER

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence

As of 9 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2510.16657.

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

pith.paper-citation-record.v1
2510.16657 v3

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:18:34.943574Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

verified exact0
verified fuzzy0
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cfabcb30-0aa8-474e-9008-071f03e6a5d1 · outbound

This paper cites On the Diversity of Synthetic Data and its Impact on Training Large Language Models.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:33.177856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 307a07fe-489e-410f-9c71-fca1ecb75231 · outbound

This paper cites Universality of the $\pi^2/6$ Pathway in Avoiding Model Collapse.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Universality of the $\pi^2/6$ Pathway in Avoiding Model Collapse

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:33.296977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a76180c-792a-4b57-a99b-00bfc2972297 · outbound

This paper cites A Survey on LLM-as-a-Judge.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence A Survey on LLM-as-a-Judge

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:33.513238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d79d20aa-e602-42be-abda-2e92c333751e · outbound

This paper cites Textbooks Are All You Need.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Textbooks Are All You Need

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:33.623752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79de395f-120f-41e8-a8d1-8017c9068124 · outbound

This paper cites Recursive Learning Without Collapse: A Weighting-Based Stabilization Framework.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Recursive Learning Without Collapse: A Weighting-Based Stabilization Framework

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:33.906541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 166476a0-ce7b-4706-b04e-dce729ce918e · outbound

This paper cites Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:34.357327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a17a585-65bb-4d70-90d1-9c4c0b2c56ea · outbound

This paper cites Synthetic Data Applications in Finance.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Synthetic Data Applications in Finance

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:34.465267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62de2d86-4c36-42ff-9d77-450cff55b27f · outbound

This paper cites Position: Model Collapse Does Not Mean What You Think.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Position: Model Collapse Does Not Mean What You Think

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:34.569592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b35afada-8ee3-4a26-ad83-8c5a2ddb4acd · outbound

This paper cites A Probabilistic Perspective on Model Collapse.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence A Probabilistic Perspective on Model Collapse

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:34.794717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a6a9a49-9d90-4ace-a48e-39fe1d72b3e9 · outbound

This paper cites Bridging the Gap: Enhancing the Utility of Synthetic Data via Post-Processing Techniques.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Bridging the Gap: Enhancing the Utility of Synthetic Data via Post-Processing Techniques

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:34.192615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd396e4-6f47-4344-b2a5-6f8a8bd51607 · outbound

This paper cites Quality matters: Evaluating synthetic data for tool-using llms.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Quality matters: Evaluating synthetic data for tool-using llms

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:34.044246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c251cece-c678-4622-81cd-6b5c4c5978e8 · outbound

This paper cites Resofilter: Fine-grained synthetic data filtering for large language models through data-parameter resonance analysis.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Resofilter: Fine-grained synthetic data filtering for large language models through data-parameter resonance analysis

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:34.709441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d560e9e1-9c89-4225-b03a-939cccc95cb6 · outbound

This paper cites When models don’t collapse: On the consistency of iterative mle.arXiv preprint arXiv:2505.19046,.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence When models don’t collapse: On the consistency of iterative mle.arXiv preprint arXiv:2505.19046,

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:33.015981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70387254-4f81-42c0-8712-7c57faa073f7 · outbound

This paper cites Regurgitative Training: The Value of Real Data in Training Large Language Models.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Regurgitative Training: The Value of Real Data in Training Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:34.943574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e9b0989-ba0d-42d9-8498-2c23755778a0 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:33.775083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cca82ab0-bbd3-4c79-86f2-dd180b9cb7a3 · outbound

This paper cites Escaping collapse: The strength of weak data for large language model training.arXiv preprint arXiv:2502.08924,.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Escaping collapse: The strength of weak data for large language model training.arXiv preprint arXiv:2502.08924,

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:32.936260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15a8d51e-a025-41d9-9139-af991d69e40d · outbound

This paper cites Preventing model collapse under overparametrization: Optimal mixing ratios for interpolation learning and ridge regression.arXiv preprint arXiv:2509.22341,.

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence Preventing model collapse under overparametrization: Optimal mixing ratios for interpolation learning and ridge regression.arXiv preprint arXiv:2509.22341,

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T09:18:33.436748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.