Paper Citation Record · LEDGER

Evaluating Language Models as Synthetic Data Generators

As of 21 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 2 inbound Pith citation observations for arXiv:2412.03679.

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

pith.paper-citation-record.v1
2412.03679 v2

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:17:42.790137Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:43:12.690861Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T12:52:47.936710Z

Reference resolution

51 of 51 outbound references displayed

verified exact0
verified fuzzy22
unresolved29
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 33ad2754-4767-4156-97b4-347ae0d7c65d · outbound

This paper cites write newline.

Evaluating Language Models as Synthetic Data Generators write newline

Reference 1

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Source-reported events for the cited work

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Observation 95dd5733-6fa2-44f4-94d9-828a89d12325 · outbound

This paper cites Claude 3.5 sonnet model card addendum.

Evaluating Language Models as Synthetic Data Generators Claude 3.5 sonnet model card addendum

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.514615Z

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Observation 43e4570c-8554-418b-9c79-8b0be5fc2f57 · outbound

This paper cites Program Synthesis with Large Language Models.

Evaluating Language Models as Synthetic Data Generators Program Synthesis with Large Language Models

Reference 3

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Source-reported events for the cited work

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Observation 1e7b8c13-915e-4f5a-a229-b9814cc8077d · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

Evaluating Language Models as Synthetic Data Generators D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.500324Z

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Observation 16b05f5f-003e-4b92-ab0c-fb7a9331b0d2 · outbound

This paper cites A survey on evaluation of large language models.

Evaluating Language Models as Synthetic Data Generators A survey on evaluation of large language models

Reference 5

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Source-reported events for the cited work

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Observation 0c015cf2-a048-43a0-933e-697d94028af7 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Evaluating Language Models as Synthetic Data Generators Evaluating Large Language Models Trained on Code

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:42.594460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a3c1d0c-c392-4d9e-9e77-e619a9e33697 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Evaluating Language Models as Synthetic Data Generators Training Verifiers to Solve Math Word Problems

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:42.598818Z

Source-reported events for the cited work

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Observation 944a104c-b2d5-4ac8-89b1-b6f180b95b50 · outbound

This paper cites How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition.

Evaluating Language Models as Synthetic Data Generators How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:42.604209Z

Source-reported events for the cited work

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Observation 594600ba-6f3c-421c-b74c-e8af2b740dd1 · outbound

This paper cites The Llama 3 Herd of Models.

Evaluating Language Models as Synthetic Data Generators The Llama 3 Herd of Models

Reference 9

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Source-reported events for the cited work

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Observation 00050036-8117-4f64-bd7b-778fa7ba162a · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Evaluating Language Models as Synthetic Data Generators Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:42.615359Z

Source-reported events for the cited work

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Observation 195f3afa-1c63-431c-a28c-29b23407f0be · outbound

This paper cites Textbooks Are All You Need.

Evaluating Language Models as Synthetic Data Generators Textbooks Are All You Need

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:42.620046Z

Source-reported events for the cited work

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Observation bab42ba8-c35d-4cc3-8fd7-51d0647ecae7 · outbound

This paper cites Evaluating Large Language Models: A Comprehensive Survey.

Evaluating Language Models as Synthetic Data Generators Evaluating Large Language Models: A Comprehensive Survey

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:42.625582Z

Source-reported events for the cited work

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Observation da5b93db-b078-410f-9e9d-fae597d9bdd4 · outbound

This paper cites Measuring mathematical problem solving with the math dataset.

Evaluating Language Models as Synthetic Data Generators Measuring mathematical problem solving with the math dataset

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.479773Z

Source-reported events for the cited work

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Observation 8d9c00dc-4ed3-47d1-bb44-abdccf0ec347 · outbound

This paper cites Instruction Induction: From Few Examples to Natural Language Task Descriptions.

Evaluating Language Models as Synthetic Data Generators Instruction Induction: From Few Examples to Natural Language Task Descriptions

Reference 14

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Source-reported events for the cited work

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Observation 8dbad316-0276-4d41-9bf1-b1bcaef4d180 · outbound

This paper cites Unnatural instructions: Tuning language models with (almost) no human labor.

Evaluating Language Models as Synthetic Data Generators Unnatural instructions: Tuning language models with (almost) no human labor

Reference 15

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Source-reported events for the cited work

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Observation 046b8588-a987-498c-ae0e-030d9a9f3927 · outbound

This paper cites GPT-4o System Card.

Evaluating Language Models as Synthetic Data Generators GPT-4o System Card

Reference 16

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Source-reported events for the cited work

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Observation 6e56eb8a-aa3c-4b10-9b83-32a942fbbf66 · outbound

This paper cites The cot collection: Improving zero-shot and few-shot learning of language models via chain-of-thought fine-tuning.

Evaluating Language Models as Synthetic Data Generators The cot collection: Improving zero-shot and few-shot learning of language models via chain-of-thought fine-tuning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.458366Z

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Observation 7666c8da-dd40-46dc-ad19-4e01800b4c9f · outbound

This paper cites J., Jang, Y., Chae, H., and Yeo, J.

Evaluating Language Models as Synthetic Data Generators J., Jang, Y., Chae, H., and Yeo, J

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.444855Z

Source-reported events for the cited work

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Observation 72bb17d2-8df0-46d1-af06-41bd539ad79d · outbound

This paper cites Y., Shin, J., Welleck, S., Neubig, G., Lee, M., Lee, K., and Seo, M.

Evaluating Language Models as Synthetic Data Generators Y., Shin, J., Welleck, S., Neubig, G., Lee, M., Lee, K., and Seo, M

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.433147Z

Source-reported events for the cited work

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Observation b9251161-cb98-473a-927b-3e2923bfeb0f · outbound

This paper cites RewardBench: Evaluating Reward Models for Language Modeling.

Evaluating Language Models as Synthetic Data Generators RewardBench: Evaluating Reward Models for Language Modeling

Reference 20

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Source-reported events for the cited work

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Observation bf27756e-c868-4022-897d-6918a600534a · outbound

This paper cites From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline.

Evaluating Language Models as Synthetic Data Generators From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline

Reference 21

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Observation b48413b9-c263-4357-9b4b-423464317c1b · outbound

This paper cites Universal and Context-Independent Triggers for Precise Control of LLM Outputs.

Evaluating Language Models as Synthetic Data Generators Universal and Context-Independent Triggers for Precise Control of LLM Outputs

Reference 22

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Observation abbd0eb3-0e65-40b8-9832-a71f5f281618 · outbound

This paper cites Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs.

Evaluating Language Models as Synthetic Data Generators Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs

Reference 23

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Observation 0df4b114-d9d0-4278-8f44-5fbcb9b48e69 · outbound

This paper cites S., Wang, Y., and Zhang, L.

Evaluating Language Models as Synthetic Data Generators S., Wang, Y., and Zhang, L

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.422026Z

Source-reported events for the cited work

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Observation d4b95646-4797-41f9-af2a-fc89e8ec71ec · outbound

This paper cites Best practices and lessons learned on synthetic data.

Evaluating Language Models as Synthetic Data Generators Best practices and lessons learned on synthetic data

Reference 25

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Observation d978c7cb-0e42-4560-ae7b-a3e4c0b2d942 · outbound

This paper cites What makes good data for alignment? a comprehensive study of automatic data selection in instruction tuning.

Evaluating Language Models as Synthetic Data Generators What makes good data for alignment? a comprehensive study of automatic data selection in instruction tuning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.399378Z

Source-reported events for the cited work

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Observation 06634d93-e4fa-4ce3-a8ae-0ec6e609f183 · outbound

This paper cites W., Tay, Y., Zhou, D., Le, Q.

Evaluating Language Models as Synthetic Data Generators W., Tay, Y., Zhou, D., Le, Q

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.388496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0a96d054-4045-4552-9aa4-3dbbf51032da · outbound

This paper cites Introducing meta llama 3: The most capable openly available llm to date.

Evaluating Language Models as Synthetic Data Generators Introducing meta llama 3: The most capable openly available llm to date

Reference 28

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Observation 687e6f50-30c2-4071-8bc2-be266aa06e30 · outbound

This paper cites Cross-task generalization via natural language crowdsourcing instructions.

Evaluating Language Models as Synthetic Data Generators Cross-task generalization via natural language crowdsourcing instructions

Reference 29

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Observation 09599f1f-c83e-463e-8b42-ae8e0f0c9692 · outbound

This paper cites Mteb: Massive text embedding benchmark.

Evaluating Language Models as Synthetic Data Generators Mteb: Massive text embedding benchmark

Reference 30

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Observation cc2d283d-a704-4151-bd17-15527faae4ea · outbound

This paper cites S., Shen, S., Yong, Z.

Evaluating Language Models as Synthetic Data Generators S., Shen, S., Yong, Z

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.334381Z

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Observation b06efdcd-f87b-4d7c-ba83-b1e3caf1b24d · outbound

This paper cites Orca: Progressive Learning from Complex Explanation Traces of GPT-4.

Evaluating Language Models as Synthetic Data Generators Orca: Progressive Learning from Complex Explanation Traces of GPT-4

Reference 32

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Observation 579fa552-fd6e-4d87-a6f0-2ec01010cb04 · outbound

This paper cites Mixeval: Deriving wisdom of the crowd from LLM benchmark mixtures.

Evaluating Language Models as Synthetic Data Generators Mixeval: Deriving wisdom of the crowd from LLM benchmark mixtures

Reference 33

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Observation 93def1ed-bf4e-486b-8093-3d23b0c7ca8f · outbound

This paper cites Leverage the Latest Open Models for Synthetic Data Generation with NVIDIA Nemotron-4-340B.

Evaluating Language Models as Synthetic Data Generators Leverage the Latest Open Models for Synthetic Data Generation with NVIDIA Nemotron-4-340B

Reference 34

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Observation e89988d4-74fd-4d1d-b144-d5138375d3b4 · outbound

This paper cites J., and Hashimoto, T.

Evaluating Language Models as Synthetic Data Generators J., and Hashimoto, T

Reference 35

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Observation 7a43803c-c023-4f8c-a036-e3576bc2aca1 · outbound

This paper cites StructuredRAG: JSON Response Formatting with Large Language Models.

Evaluating Language Models as Synthetic Data Generators StructuredRAG: JSON Response Formatting with Large Language Models

Reference 36

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Observation e2fe7637-65c4-426c-b53f-6b68b1a196fe · outbound

This paper cites Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models.

Evaluating Language Models as Synthetic Data Generators Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models

Reference 37

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Observation 9acbc3db-5856-498a-9ae8-093f04e6c16c · outbound

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Evaluating Language Models as Synthetic Data Generators Unresolved cited work

Reference 38

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Evaluating Language Models as Synthetic Data Generators Qwen2.5: A party of foundation models, September 2024

Reference 39

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Evaluating Language Models as Synthetic Data Generators Prompt2model: Generating deployable models from natural language instructions

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.268621Z

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Observation d87ef1bf-0ac0-4b75-8224-832e1f3ad6d5 · outbound

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Evaluating Language Models as Synthetic Data Generators S., Arunkumar, A., Stap, D., et al

Reference 41

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Observation 40a1efc5-4eed-4295-bb0c-a3b0107e7c5a · outbound

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Evaluating Language Models as Synthetic Data Generators A., Khashabi, D., and Hajishirzi, H

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.249846Z

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Observation 43ab9403-95d6-4d4c-97af-53699b861a46 · outbound

This paper cites W., Lester, B., Du, N., Dai, A.

Evaluating Language Models as Synthetic Data Generators W., Lester, B., Du, N., Dai, A

Reference 43

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Observation 3beb33d4-e37a-4246-9214-3c7da17da208 · outbound

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Evaluating Language Models as Synthetic Data Generators Wizard LM : Empowering large pre-trained language models to follow complex instructions

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.228008Z

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Observation c5bddd7b-9eaa-48c6-be1f-a4a52ff6b0d7 · outbound

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Evaluating Language Models as Synthetic Data Generators Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Reference 45

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Observation b9602ff3-1d60-4ea9-a0f5-ed1e6452a33e · outbound

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Evaluating Language Models as Synthetic Data Generators Stronger Models are NOT Stronger Teachers for Instruction Tuning

Reference 46

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Observation 64013046-f12a-4531-b3de-0cf9980d0f9d · outbound

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Evaluating Language Models as Synthetic Data Generators Learning to mine aligned code and natural language pairs from stack overflow

Reference 47

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Source-reported events for the cited work

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Observation 582dd6c1-3f76-44d6-aa3d-c8f204a52e55 · outbound

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Evaluating Language Models as Synthetic Data Generators Mammoth: Building math generalist models through hybrid instruction tuning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.214350Z

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Observation fb2244ec-cdbd-4bf9-b474-a34caa413e3f · outbound

This paper cites MA mmo TH 2: Scaling instructions from the web.

Evaluating Language Models as Synthetic Data Generators MA mmo TH 2: Scaling instructions from the web

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T22:17:43.200095Z

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Observation 73f717a3-22a9-4cc4-b302-a6b6ca6ad351 · outbound

This paper cites Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning.

Evaluating Language Models as Synthetic Data Generators Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:42.786222Z

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Observation f9ebf507-8894-4ff7-89e9-8d5428b0746d · outbound

This paper cites Lima: Less is more for alignment.

Evaluating Language Models as Synthetic Data Generators Lima: Less is more for alignment

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T22:17:42.790137Z

Source-reported events for the cited work

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Pith citing papers

Observation b1dbf21a-397a-47f7-9126-0a21164927d5 · inbound

Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era cites this paper.

Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era Evaluating Language Models as Synthetic Data Generators

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T15:43:12.690861Z

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Observation f8e4fb39-e225-44b3-bf99-d4e8c0d65e5c · inbound

Modular Techniques for Synthetic Long-Context Data Generation in Language Model Training and Evaluation cites this paper.

Modular Techniques for Synthetic Long-Context Data Generation in Language Model Training and Evaluation Evaluating Language Models as Synthetic Data Generators

Reference 18

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Source-reported events for the cited work

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