mlsanityData to 7 Oct 2026

Best Practices and Lessons Learned on Synthetic Data

arXiv 2404.07503 ↗First posted 11 Apr 2024cs.CLcited by 104

On the map: Synthetic data and self-improvement for LLMs → LLM synthetic data generation

Abstract (arXiv)

The success of AI models relies on the availability of large, diverse, and high-quality datasets, which can be challenging to obtain due to data scarcity, privacy concerns, and high costs. Synthetic data has emerged as a promising solution by generating artificial data that mimics real-world patterns. This paper provides an overview of synthetic data research, discussing its applications, challenges, and future directions. We present empirical evidence from prior art to demonstrate its effectiveness and highlight the importance of ensuring its factuality, fidelity, and unbiasedness. We emphasize the need for responsible use of synthetic data to build more powerful, inclusive, and trustworthy language models.

Key facts. Cited by 104 papers in the map (data through 7 Oct 2026). Placed in LLM synthetic data generation, one of 13 directions in Synthetic data and self-improvement for LLMs. Builds on 146 of its 190 references that are in the map. First posted on arXiv 11 Apr 2024.

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146 of 190 references.

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  1. 2023Simple synthetic data reduces sycophancy in large language models7 Aug

Other references · 145

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  38. 2015Improving Neural Machine Translation Models with Monolingual Datacited by 784

50 most cited of 145 All 145 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 64; 2025: 33; 2026: 7.

104 papers.

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  1. 2024Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysiscited by 1,375
  2. 2024Scaling Synthetic Data Creation with 1,000,000,000 Personascited by 397
  3. 2024Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothingcited by 341
  4. 2024On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Surveycited by 240
  5. 2024Building and better understanding vision-language models: insights and future directionscited by 169
  6. 2024Self-Exploring Language Models: Active Preference Elicitation for Online Alignmentcited by 63
  7. 2024Instruction Pre-Training: Language Models are Supervised Multitask Learnerscited by 63
  8. 2024On the Diversity of Synthetic Data and its Impact on Training Large Language Modelscited by 56
  9. 2025A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Futurecited by 53
  10. 2025FalseReject: A Resource for Improving Contextual Safety and Mitigating Over-Refusals in LLMs via Structured Reasoningcited by 53
  11. 2025The Best Instruction-Tuning Data are Those That Fitcited by 48
  12. 2024JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Modelscited by 44
38 more
  1. 2024A Survey on Data Synthesis and Augmentation for Large Language Modelscited by 40
  2. 2024Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuningcited by 40
  3. 2025On the generalization of language models from in-context learning and finetuning: a controlled studycited by 39
  4. 2024Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scalecited by 37
  5. 2024How Far Are We From AGI: Are LLMs All We Need?cited by 31
  6. 2024Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Modelscited by 31
  7. 2024Distill Visual Chart Reasoning Ability from LLMs to MLLMscited by 30
  8. 2024CulturalBench: A Robust, Diverse, and Challenging Cultural Benchmark by Human-AI CulturalTeamingcited by 27
  9. 2024DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graphcited by 26
  10. 2025Building a Foundational Guardrail for General Agentic Systems via Synthetic Datacited by 26
  11. 2024How to Synthesize Text Data without Model Collapse?cited by 24
  12. 2024SPaR: Self-Play with Tree-Search Refinement to Improve Instruction-Following in Large Language Modelscited by 23
  13. 2024Synthesizing Post-Training Data for LLMs through Multi-Agent Simulationcited by 22
  14. 2024Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Modelcited by 21
  15. 2024Aloe: A Family of Fine-tuned Open Healthcare LLMscited by 20
  16. 2024The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Bettercited by 19
  17. 2024PRACTIQ: A Practical Conversational Text-to-SQL dataset with Ambiguous and Unanswerable Queriescited by 17
  18. 2024Provable Weak-to-Strong Generalization via Benign Overfittingcited by 16
  19. 2024Preference Optimization with Multi-Sample Comparisonscited by 16
  20. 2024Stronger Models are NOT Stronger Teachers for Instruction Tuningcited by 16
  21. 2024Progressive distillation induces an implicit curriculumcited by 15
  22. 2024HexaCoder: Secure Code Generation via Oracle-Guided Synthetic Training Datacited by 14
  23. 2024LogicPro: Improving Complex Logical Reasoning via Program-Guided Learningcited by 14
  24. 2024Balancing Cost and Effectiveness of Synthetic Data Generation Strategies for LLMscited by 14
  25. 2024Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Modelscited by 13
  26. 2024On Domain-Adaptive Post-Training for Multimodal Large Language Modelscited by 13
  27. 2024Scaling Parameter-Constrained Language Models with Quality Datacited by 12
  28. 2024Montessori-Instruct: Generate Influential Training Data Tailored for Student Learningcited by 12
  29. 2025Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Datacited by 12
  30. 2024Abstraction-of-Thought Makes Language Models Better Reasonerscited by 11
  31. 2024The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resourcescited by 11
  32. 2024Little Giants: Synthesizing High-Quality Embedding Data at Scalecited by 11
  33. 2025LLM-Friendly Knowledge Representation for Customer Supportcited by 11
  34. 2024Understanding Synthetic Context Extension via Retrieval Headscited by 10
  35. 2024Boosting Reward Model with Preference-Conditional Multi-Aspect Synthetic Data Generationcited by 9
  36. 2024A Survey of Data Synthesis Approachescited by 8
  37. 2024Towards Building Specialized Generalist AI with System 1 and System 2 Fusioncited by 8
  38. 2024LlamaDuo: LLMOps Pipeline for Seamless Migration from Service LLMs to Small-Scale Local LLMscited by 8

50 most cited of 104 All 104 (JSON)

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  6. 2024A Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated by Large Language Models
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