mlsanityData to 7 Oct 2026

Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction

arXiv 2303.04132 ↗First posted 7 Mar 2023cs.CL cs.AI cs.LGcited by 89

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Abstract (arXiv)

Large language models (LLMs) have great potential for synthetic data generation. This work shows that useful data can be synthetically generated even for tasks that cannot be solved directly by LLMs: for problems with structured outputs, it is possible to prompt an LLM to perform the task in the reverse direction, by generating plausible input text for a target output structure. Leveraging this asymmetry in task difficulty makes it possible to produce large-scale, high-quality data for complex tasks. We demonstrate the effectiveness of this approach on closed information extraction, where collecting ground-truth data is challenging, and no satisfactory dataset exists to date. We synthetically generate a dataset of 1.8M data points, establish its superior quality compared to existing datasets in a human evaluation, and use it to finetune small models (220M and 770M parameters), termed SynthIE, that outperform the prior state of the art (with equal model size) by a substantial margin of 57 absolute points in micro-F1 and 79 points in macro-F1. Code, data, and models are available at https://github.com/epfl-dlab/SynthIE.

Key facts. Cited by 89 papers in the map (data through 7 Oct 2026). Builds on 21 of its 39 references that are in the map. First posted on arXiv 7 Mar 2023.

Builds on

21 of 39 references.

References · 21

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
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  8. 2022Unnatural Instructions: Tuning Language Models with (Almost) No Human Laborcited by 395
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  10. 2022Generating Training Data with Language Models: Towards Zero-Shot Language Understandingcited by 199
  11. 2021Generating Datasets with Pretrained Language Modelscited by 192
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9 more
  1. 2020Data Augmentation using Pre-trained Transformer Modelscited by 168
  2. 2022PEER: A Collaborative Language Modelcited by 86
  3. 2021Towards Zero-Label Language Learningcited by 76
  4. 2023Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Modelscited by 61
  5. 2021GenIE: Generative Information Extractioncited by 53
  6. 2022Language Models in the Loop: Incorporating Prompting into Weak Supervisioncited by 51
  7. 2022Data Augmentation for Intent Classification with Off-the-shelf Large Language Modelscited by 49
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Citing papers per year: 2023: 17; 2024: 27; 2025: 29; 2026: 16.

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  1. 2024Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Modelscited by 552
  2. 2024On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Surveycited by 240
  3. 2023Grammar-Constrained Decoding for Structured NLP Tasks without Finetuningcited by 186
  4. 2023Large Language Models for Generative Information Extraction: A Surveycited by 183
  5. 2023Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!cited by 119
  6. 2023Large Language Models and Knowledge Graphs: Opportunities and Challengescited by 71
  7. 2024Enhancing Large Vision Language Models with Self-Training on Image Comprehensioncited by 70
  8. 2024Self-Exploring Language Models: Active Preference Elicitation for Online Alignmentcited by 63
  9. 2024Agents' Room: Narrative Generation through Multi-step Collaborationcited by 57
  10. 2024What is the Role of Small Models in the LLM Era: A Surveycited by 41
  11. 2023Generating Faithful Synthetic Data with Large Language Models: A Case Study in Computational Social Sciencecited by 37
  12. 2023People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detectioncited by 25
38 more
  1. 2023A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepediacited by 24
  2. 2023Evaluating Generative Models for Graph-to-Text Generationcited by 16
  3. 2023Self-Improving for Zero-Shot Named Entity Recognition with Large Language Modelscited by 15
  4. 2023Getting Sick After Seeing a Doctor? Diagnosing and Mitigating Knowledge Conflicts in Event Temporal Reasoningcited by 12
  5. 2024Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning through Logical Fallacy Understandingcited by 12
  6. 2025Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones?cited by 12
  7. 2024Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMscited by 10
  8. 2024Understanding Synthetic Context Extension via Retrieval Headscited by 10
  9. 2025Anyprefer: An Agentic Framework for Preference Data Synthesiscited by 10
  10. 2024Sketch-Guided Constrained Decoding for Boosting Blackbox Large Language Models without Logit Accesscited by 9
  11. 2024Getting Serious about Humor: Crafting Humor Datasets with Unfunny Large Language Modelscited by 9
  12. 2024DiffLM: Controllable Synthetic Data Generation via Diffusion Language Modelscited by 9
  13. 2026Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMscited by 9
  14. 2024Merging Improves Self-Critique Against Jailbreak Attackscited by 8
  15. 2024Grounding Data Science Code Generation with Input-Output Specificationscited by 7
  16. 2024Improving Event Definition Following For Zero-Shot Event Detectioncited by 7
  17. 2024The Effects of Hallucinations in Synthetic Training Data for Relation Extractioncited by 7
  18. 2025The Quest for Efficient Reasoning: A Data-Centric Benchmark to CoT Distillationcited by 7
  19. 2023STAR: Boosting Low-Resource Information Extraction by Structure-to-Text Data Generation with Large Language Modelscited by 6
  20. 2025Automatic Prompt Optimization for Knowledge Graph Construction: Insights from an Empirical Studycited by 6
  21. 2025Wikontic: Constructing Wikidata-Aligned, Ontology-Aware Knowledge Graphs with Large Language Modelscited by 6
  22. 2023Few-shot Event Detection: An Empirical Study and a Unified Viewcited by 5
  23. 2023Linking Surface Facts to Large-Scale Knowledge Graphscited by 5
  24. 2025Mutual Reinforcement of LLM Dialogue Synthesis and Summarization Capabilities for Few-Shot Dialogue Summarizationcited by 5
  25. 2025A Cooperative Multi-Agent Framework for Zero-Shot Named Entity Recognitioncited by 5
  26. 2025Attributes as Textual Genes: Leveraging LLMs as Genetic Algorithm Simulators for Conditional Synthetic Data Generationcited by 5
  27. 2023KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large Language Modelscited by 4
  28. 2024InstaSynth: Opportunities and Challenges in Generating Synthetic Instagram Data with ChatGPT for Sponsored Content Detectioncited by 4
  29. 2024Curating Grounded Synthetic Data with Global Perspectives for Equitable AIcited by 4
  30. 2024Retrieval Augmented Instruction Tuning for Open NER with Large Language Modelscited by 4
  31. 2025Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applicationscited by 4
  32. 2025StructText: A Synthetic Table-to-Text Approach for Benchmark Generation with Multi-Dimensional Evaluationcited by 4
  33. 2024Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learningcited by 3
  34. 2025GuideX: Guided Synthetic Data Generation for Zero-Shot Information Extractioncited by 3
  35. 2025Aligning Large Language Models via Fully Self-Synthetic Datacited by 3
  36. 2025Polypersona: Persona-Grounded LLM for Synthetic Survey Responsescited by 3
  37. 2026OntoLearner: A Modular Python Library for Ontology Learning with Large Language Modelscited by 3
  38. 2023Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generationcited by 2

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