Paper Citation Record · LEDGER

On the Diversity of Synthetic Data and its Impact on Training Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2410.15226.

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

pith.paper-citation-record.v1
2410.15226 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:36:27.187131Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T01:05:16.441022Z

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 de6d5b97-cada-44eb-b0e1-02327be1b867 · inbound

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices cites this paper.

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:05:16.443483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 19a490b8-8506-42a9-acf6-c02471a8b6ee · inbound

Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation cites this paper.

Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translation On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T21:42:11.341426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e1b02181-3a81-4300-a01c-574aa08769c7 · inbound

A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:12.926530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7769956-febd-4cb5-9cfd-3a11cdce4331 · inbound

Diversity and Inclusion in AI: Insights from a Survey of AI/ML Practitioners cites this paper.

Diversity and Inclusion in AI: Insights from a Survey of AI/ML Practitioners On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:27.187131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6b33bc2-bc30-45a3-9220-ff8d696581bb · inbound

Improving Multilingual Math Reasoning for African Languages cites this paper.

Improving Multilingual Math Reasoning for African Languages On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T14:10:22.223731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 554c546f-1901-4c8e-a9e3-7f8222d36398 · inbound

From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning cites this paper.

From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T12:18:34.656149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5165d9af-17c1-4889-9451-44f121e702a9 · inbound

Facts Do Care About Your Language: Assessing Answer Quality of Multilingual LLMs cites this paper.

Facts Do Care About Your Language: Assessing Answer Quality of Multilingual LLMs On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T11:13:38.936758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89491718-442f-463f-aaa7-146c097564c0 · 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 On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T23:12:18.881689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1252be6c-09c8-4d9d-a801-dbb63384c66b · inbound

Decoding Machine Translationese in English-Chinese News: LLMs vs. NMTs cites this paper.

Decoding Machine Translationese in English-Chinese News: LLMs vs. NMTs On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T22:18:43.992346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 607080ba-3337-4ebf-9fee-1b5d0d7c9046 · inbound

Towards Integrated Alignment cites this paper.

Towards Integrated Alignment On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-05T22:56:28.179383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 940f0155-255a-47b8-b72c-44ddd6090555 · inbound

One Joke to Rule them All? On the (Im)possibility of Generalizing Humor cites this paper.

One Joke to Rule them All? On the (Im)possibility of Generalizing Humor On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T15:53:34.195737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence cites this paper.

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 bd88e7af-3de9-47bd-a9b4-7d91d00be7a0 · inbound

Synthetic Eggs in Many Baskets: The Impact of Synthetic Data Diversity on LLM Fine-Tuning cites this paper.

Synthetic Eggs in Many Baskets: The Impact of Synthetic Data Diversity on LLM Fine-Tuning On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-18T01:20:34.760847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d7b76357-7cb1-45c1-a438-10c4e08f1b75 · inbound

LLM Harms: A Taxonomy and Discussion cites this paper.

LLM Harms: A Taxonomy and Discussion On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-17T00:31:24.718186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 41d6d484-1029-41bd-b685-8a92f3c91341 · inbound

LLM Harms: A Taxonomy and Discussion cites this paper.

LLM Harms: A Taxonomy and Discussion On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T18:19:14.106904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c7b28c0-ef08-497d-96f3-d7f216c7bd3f · inbound

Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders cites this paper.

Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T01:17:11.720224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 630e7589-959c-4a62-b376-41c94716e8c5 · inbound

Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation cites this paper.

Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:21:03.324208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b41115f6-2f7f-419d-8633-a73a02c5371a · inbound

Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation cites this paper.

Polyglot Teachers: Evaluating Language Models for Multilingual Synthetic Data Generation On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-12T22:04:56.445021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 664fb5a8-2388-4f86-8985-57cc40083518 · inbound

StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning cites this paper.

StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning On the Diversity of Synthetic Data and its Impact on Training Large Language Models

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:32:20.304263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.