mlsanityData to 14 Oct 2026

Large Language Models Enable Few-Shot Clustering

arXiv 2307.00524 ↗First posted 2 Jul 2023cs.CLcited by 72

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Abstract (arXiv)

Unlike traditional unsupervised clustering, semi-supervised clustering allows users to provide meaningful structure to the data, which helps the clustering algorithm to match the user's intent. Existing approaches to semi-supervised clustering require a significant amount of feedback from an expert to improve the clusters. In this paper, we ask whether a large language model can amplify an expert's guidance to enable query-efficient, few-shot semi-supervised text clustering. We show that LLMs are surprisingly effective at improving clustering. We explore three stages where LLMs can be incorporated into clustering: before clustering (improving input features), during clustering (by providing constraints to the clusterer), and after clustering (using LLMs post-correction). We find incorporating LLMs in the first two stages can routinely provide significant improvements in cluster quality, and that LLMs enable a user to make trade-offs between cost and accuracy to produce desired clusters. We release our code and LLM prompts for the public to use.

Key facts. Cited by 72 papers in the map (data through 14 Oct 2026). Builds on 21 of its 45 references that are in the map. First posted on arXiv 2 Jul 2023.

Builds on

21 of 45 references.

References · 21

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  3. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,307
  4. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  5. 2015Unsupervised Deep Embedding for Clustering Analysiscited by 767
  6. 2020Efficient Intent Detection with Dual Sentence Encoderscited by 433
  7. 2019An Evaluation Dataset for Intent Classification and Out-of-Scope Predictioncited by 386
  8. 2023GPTScore: Evaluate as You Desirecited by 361
  9. 2022One Embedder, Any Task: Instruction-Finetuned Text Embeddingscited by 333
  10. 2021Supporting Clustering with Contrastive Learningcited by 90
  11. 2023ClusterLLM: Large Language Models as a Guide for Text Clusteringcited by 70
  12. 2017A Data-Driven Analysis of Workers' Earnings on Amazon Mechanical Turkcited by 39
9 more
  1. 2019CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Informationcited by 28
  2. 2019A Framework for Deep Constrained Clustering -- Algorithms and Advancescited by 24
  3. 2023IDAS: Intent Discovery with Abstractive Summarizationcited by 22
  4. 2019OPIEC: An Open Information Extraction Corpuscited by 20
  5. 2022Learning Dialogue Representations from Consecutive Utterancescited by 17
  6. 2013Local algorithms for interactive clusteringcited by 14
  7. 2020Open Knowledge Graphs Canonicalization using Variational Autoencoderscited by 9
  8. 2022Multi-View Clustering for Open Knowledge Base Canonicalizationcited by 5
  9. 2014Which Clustering Do You Want? Inducing Your Ideal Clustering with Minimal Feedbackcited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 5; 2024: 27; 2025: 26; 2026: 14.

72 papers.

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  1. 2023Art or Artifice? Large Language Models and the False Promise of Creativitycited by 172
  2. 2024LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Textscited by 87
  3. 2024Concept Induction: Analyzing Unstructured Text with High-Level Concepts Using LLooMcited by 78
  4. 2024Are Large Language Models Good Prompt Optimizers?cited by 37
  5. 2024Tool-Planner: Task Planning with Clusters across Multiple Toolscited by 33
  6. 2024CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Supportcited by 29
  7. 2023Image Clustering Conditioned on Text Criteriacited by 26
  8. 2025TaxoAdapt: Aligning LLM-Based Multidimensional Taxonomy Construction to Evolving Research Corporacited by 23
  9. 2024Explaining Datasets in Words: Statistical Models with Natural Language Parameterscited by 21
  10. 2024Knowledge Navigator: LLM-guided Browsing Framework for Exploratory Search in Scientific Literaturecited by 17
  11. 2024Text Clustering as Classification with LLMscited by 16
  12. 2024OntoChat: a Framework for Conversational Ontology Engineering using Language Modelscited by 15
38 more
  1. 2024Dial-In LLM: Human-Aligned LLM-in-the-loop Intent Clustering for Customer Service Dialoguescited by 11
  2. 2024DiscipLink: Unfolding Interdisciplinary Information Seeking Process via Human-AI Co-Explorationcited by 10
  3. 2025Context-Aware Hierarchical Taxonomy Generation for Scientific Papers via LLM-Guided Multi-Aspect Clusteringcited by 10
  4. 2024Context-Aware Clustering using Large Language Modelscited by 9
  5. 2025LLLMs: A Data-Driven Survey of Evolving Research on Limitations of Large Language Modelscited by 9
  6. 2025From Papers to Panoramas: Building Hierarchies of Scientific Literature at Scalecited by 8
  7. 2024A Survey of Few-Shot Learning for Biomedical Time Seriescited by 7
  8. 2024Organizing Unstructured Image Collections using Natural Languagecited by 7
  9. 2024EEG Emotion Copilot: Optimizing Lightweight LLMs for Emotional EEG Interpretation with Assisted Medical Record Generationcited by 6
  10. 2024A Survey of Ontology Expansion for Conversational Understandingcited by 6
  11. 2024The Evolution of LLM Adoption in Industry Data Curation Practicescited by 6
  12. 2023Linking Surface Facts to Large-Scale Knowledge Graphscited by 5
  13. 2026Reasoning-Driven Synthetic Data Generation and Evaluationcited by 5
  14. 2023Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketchingcited by 4
  15. 2024Exploring Key Point Analysis with Pairwise Generation and Graph Partitioningcited by 4
  16. 2025Summaries as Centroids for Interpretable and Scalable Text Clusteringcited by 4
  17. 2025LLM-guided Hierarchical Search for End-to-end Reasoning Intensive Retrievalcited by 4
  18. 2025Dataset Featurization: Uncovering Natural Language Features through Unsupervised Data Reconstructioncited by 3
  19. 2025Cequel: Cost-Effective Querying of Large Language Models for Text Clusteringcited by 3
  20. 2025LLM-as-a-qualitative-judge: automating error analysis in natural language generationcited by 3
  21. 2025HERCULES: Hierarchical Embedding-based Recursive Clustering Using LLMs for Efficient Summarizationcited by 3
  22. 2025Co-DETECT: Collaborative Discovery of Edge Cases in Text Classificationcited by 3
  23. 2024Information-Theoretic Generative Clustering of Documentscited by 2
  24. 2025SPILL: Domain-Adaptive Intent Clustering based on Selection and Pooling with Large Language Modelscited by 2
  25. 2025On Synthesizing Data for Context Attribution in Question Answeringcited by 2
  26. 2025MuseScorer: Idea Originality Scoring At Scalecited by 2
  27. 2025Bootstrap Deep Spectral Clustering with Optimal Transportcited by 2
  28. 2025LLMs Enable Bag-of-Texts Representations for Short-Text Clusteringcited by 2
  29. 2026Bridging the Semantic Gap for Categorical Data Clustering via Large Language Modelscited by 2
  30. 2026RAL2M: Retrieval Augmented Learning-To-Match Against Hallucination in Compliance-Guaranteed Service Systemscited by 2
  31. 2026Optimized Algorithms for Text Clustering with LLM-Generated Constraintscited by 2
  32. 2023TopicGPT: A Prompt-based Topic Modeling Frameworkcited by 1
  33. 2024Large Language Model Enhanced Clustering for News Event Detectioncited by 1
  34. 2024ZeroDL: Zero-shot Distribution Learning for Text Clustering via Large Language Modelscited by 1
  35. 2024Interactive Topic Models with Optimal Transportcited by 1
  36. 2024RWKV-edge: Deeply Compressed RWKV for Resource-Constrained Devicescited by 1
  37. 2025ClusterFusion: Hybrid Clustering with Embedding Guidance and LLM Adaptationcited by 1
  38. 2026PRISM: LLM-Guided Semantic Clustering for High-Precision Topicscited by 1

50 most cited of 72 All 72 (JSON)