mlsanityData to 14 Oct 2026

PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs

arXiv 2305.12392 ↗First posted 21 May 2023cs.CLcited by 44

Not on the map. Why?

Abstract (arXiv)

Large language models (LLMs) have shown great abilities of solving various natural language tasks in different domains. Due to the training objective of LLMs and their pre-training data, LLMs are not very well equipped for tasks involving structured data generation. We propose a framework, Prompting with Iterative Verification (PiVe), to improve graph-based generative capability of LLMs. We show how a small language model could be trained to act as a verifier module for the output of an LLM~(i.e., ChatGPT, GPT-4), and to iteratively improve its performance via fine-grained corrective instructions. We also show how the verifier module could apply iterative corrections offline for a more cost-effective solution to the text-to-graph generation task. Experiments on three graph-based datasets show consistent improvement gained via PiVe. Additionally, we create GenWiki-HIQ and highlight that the verifier module can be used as a data augmentation tool to help improve the quality of automatically generated parallel text-graph datasets.

Key facts. Cited by 44 papers in the map (data through 14 Oct 2026). Builds on 25 of its 44 references that are in the map. First posted on arXiv 21 May 2023.

Builds on

25 of 44 references.

References · 25

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  4. 2023GPT-4 Technical Reportcited by 18,396
  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  6. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  7. 2021Training Verifiers to Solve Math Word Problemscited by 10,109
  8. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  9. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
  10. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  11. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  12. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,470
13 more
  1. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
  2. 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,135
  3. 2022Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Taskscited by 868
  4. 2023The Flan Collection: Designing Data and Methods for Effective Instruction Tuningcited by 739
  5. 2021Cross-Task Generalization via Natural Language Crowdsourcing Instructionscited by 699
  6. 20218-bit Optimizers via Block-wise Quantizationcited by 403
  7. 2022Generating Sequences by Learning to Self-Correctcited by 277
  8. 2023InstructUIE: Multi-task Instruction Tuning for Unified Information Extractioncited by 170
  9. 2023Controlled Text Generation with Natural Language Instructionscited by 87
  10. 2021ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoningcited by 58
  11. 2020CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Trainingcited by 38
  12. 2022Self-supervised Graph Masking Pre-training for Graph-to-Text Generationcited by 8
  13. 2022INFINITY: A Simple Yet Effective Unsupervised Framework for Graph-Text Mutual Conversioncited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 25; 2025: 10; 2026: 5.

44 papers.

Sort:

By area:

  1. 2023Unifying Large Language Models and Knowledge Graphs: A Roadmapcited by 668
  2. 2024HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Modelscited by 281
  3. 2023Language is All a Graph Needscited by 220
  4. 2023When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunitiescited by 90
  5. 2024InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignmentcited by 56
  6. 2024DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literaturecited by 50
  7. 2024Can LLM Graph Reasoning Generalize beyond Pattern Memorization?cited by 47
  8. 2024SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graphscited by 31
  9. 2024GraphEval: A Knowledge-Graph Based LLM Hallucination Evaluation Frameworkcited by 30
  10. 2024Large Model Based Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trendscited by 26
  11. 2024Graph-Based Retriever Captures the Long Tail of Biomedical Knowledgecited by 20
  12. 2024A Survey of Large Language Models on Generative Graph Analytics: Query, Learning, and Applicationscited by 17
32 more
  1. 2024Actionable Cyber Threat Intelligence using Knowledge Graphs and Large Language Modelscited by 14
  2. 2024Efficient Knowledge Infusion via KG-LLM Alignmentcited by 13
  3. 2024Can LLMs be Good Graph Judge for Knowledge Graph Construction?cited by 11
  4. 2024Strategies for Improving NL-to-FOL Translation with LLMs: Data Generation, Incremental Fine-Tuning, and Verificationcited by 10
  5. 2025AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Constructioncited by 7
  6. 2024A Comparative Analysis of Conversational Large Language Models in Knowledge-Based Text Generationcited by 6
  7. 2024Large language models as oracles for instantiating ontologies with domain-specific knowledgecited by 6
  8. 2024Scaling Knowledge Graph Construction through Synthetic Data Generation and Distillationcited by 6
  9. 2025Large Language Models Meet Text-Attributed Graphs: A Survey of Integration Frameworks and Applicationscited by 6
  10. 2025MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graphcited by 5
  11. 2024Improving Cross-Domain Low-Resource Text Generation through LLM Post-Editing: A Programmer-Interpreter Approachcited by 3
  12. 2024MIDGARD: Self-Consistency Using Minimum Description Length for Structured Commonsense Reasoningcited by 3
  13. 2024Assessing LLMs Suitability for Knowledge Graph Completioncited by 3
  14. 2024Ontology-Free General-Domain Knowledge Graph-to-Text Generation Dataset Synthesis using Large Language Modelcited by 3
  15. 2025Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignmentcited by 3
  16. 2025Language Models Coupled with Metacognition Can Outperform Reasoning Modelscited by 3
  17. 2025From Instructions to ODRL Usage Policies: An Ontology Guided Approachcited by 2
  18. 2024Teaching Models to Improve on Tapecited by 1
  19. 2024A Neurosymbolic Fast and Slow Architecture for Graph Coloringcited by 1
  20. 2024A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseasescited by 1
  21. 2025Enhancing Knowledge Graph Construction: Evaluating with Emphasis on Hallucination, Omission, and Graph Similarity Metricscited by 1
  22. 2025DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinementcited by 1
  23. 2023Reward Engineering for Generating Semi-structured Explanationcited by 0
  24. 2024Detecting text level intellectual influence with knowledge graph embeddingscited by 0
  25. 2024Graph-DPEP: Decomposed Plug and Ensemble Play for Few-Shot Document Relation Extraction with Graph-of-Thoughts Reasoningcited by 0
  26. 2025Explore-Construct-Filter: An Automated Framework for Rich and Reliable API Knowledge Graph Constructioncited by 0
  27. 2025InvertiTune: High-Quality Data Synthesis for Cost-Effective Single-Shot Text-to-Knowledge Graph Generationcited by 0
  28. 2026Construction of Knowledge Graph based on Language Modelcited by 0
  29. 2026Small Language Model Helps Resolve Semantic Ambiguity of LLM Promptcited by 0
  30. 2026SHARC: SHAP-Based Interpretability in Machine Learning Risk Models for Regulatory Capital under ICAAP and CCARcited by 0
  31. 2026FashionKG-RAG: Knowledge Graph-Enhanced Retrieval-Augmented Generation for Fashion Question Answeringcited by 0
  32. 2026XQDT: eXplainable and Quantitative Data-Text Alignment Metric with Feedback Signalscited by 0