mlsanityData to 14 Oct 2026

Goal-Driven Explainable Clustering via Language Descriptions

arXiv 2305.13749 ↗First posted 23 May 2023cs.CLcited by 58

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Abstract (arXiv)

Unsupervised clustering is widely used to explore large corpora, but existing formulations neither consider the users' goals nor explain clusters' meanings. We propose a new task formulation, "Goal-Driven Clustering with Explanations" (GoalEx), which represents both the goal and the explanations as free-form language descriptions. For example, to categorize the errors made by a summarization system, the input to GoalEx is a corpus of annotator-written comments for system-generated summaries and a goal description "cluster the comments based on why the annotators think the summary is imperfect.''; the outputs are text clusters each with an explanation ("this cluster mentions that the summary misses important context information."), which relates to the goal and precisely explain which comments should (not) belong to a cluster. To tackle GoalEx, we prompt a language model with "[corpus subset] + [goal] + Brainstorm a list of explanations each representing a cluster."; then we classify whether each sample belongs to a cluster based on its explanation; finally, we use integer linear programming to select a subset of candidate clusters to cover most samples while minimizing overlaps. Under both automatic and human evaluation on corpora with or without labels, our method produces more accurate and goal-related explanations than prior methods. We release our data and implementation at https://github.com/ZihanWangKi/GoalEx.

Key facts. Cited by 58 papers in the map (data through 14 Oct 2026). Builds on 29 of its 60 references that are in the map. First posted on arXiv 23 May 2023.

Builds on

29 of 60 references.

References · 29

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  3. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  4. 2022Scaling Instruction-Finetuned Language Modelscited by 3,024
  5. 2015Character-level Convolutional Networks for Text Classificationcited by 2,330
  6. 2022Text Embeddings by Weakly-Supervised Contrastive Pre-trainingcited by 1,253
  7. 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 870
  8. 2016Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filteringcited by 520
  9. 2022One Embedder, Any Task: Instruction-Finetuned Text Embeddingscited by 333
  10. 2022Generalized Category Discoverycited by 211
  11. 2021Open-World Semi-Supervised Learningcited by 165
  12. 2020Unsupervised Domain Clusters in Pretrained Language Modelscited by 160
17 more
  1. 2022Domino: Discovering Systematic Errors with Cross-Modal Embeddingscited by 156
  2. 2022Natural Language Descriptions of Deep Visual Featurescited by 137
  3. 2023Scaling Laws for Generative Mixed-Modal Language Modelscited by 134
  4. 2023Training Language Models with Language Feedback at Scalecited by 128
  5. 2017Automated Phrase Mining from Massive Text Corporacited by 70
  6. 2023Goal Driven Discovery of Distributional Differences via Language Descriptionscited by 62
  7. 2023Explaining black box text modules in natural language with language modelscited by 62
  8. 2022Describing Differences between Text Distributions with Natural Languagecited by 54
  9. 2018TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clusteringcited by 49
  10. 2022Towards Open-Set Object Detection and Discoverycited by 44
  11. 2019Discriminative Topic Mining via Category-Name Guided Text Embeddingcited by 29
  12. 2023Incremental Generalized Category Discoverycited by 25
  13. 2018Unseen Class Discovery in Open-world Classificationcited by 20
  14. 2022GSCLIP : A Framework for Explaining Distribution Shifts in Natural Languagecited by 14
  15. 2018HappyDB: A Corpus of 100,000 Crowdsourced Happy Momentscited by 9
  16. 2023WOT-Class: Weakly Supervised Open-world Text Classificationcited by 6
  17. 2023Open-World Weakly-Supervised Object Localizationcited by 2

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Citing papers per year: 2023: 4; 2024: 18; 2025: 19; 2026: 17.

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  1. 2024Rethinking Interpretability in the Era of Large Language Modelscited by 111
  2. 2024Concept Induction: Analyzing Unstructured Text with High-Level Concepts Using LLooMcited by 78
  3. 2025Organize the Web: Constructing Domains Enhances Pre-Training Data Curationcited by 76
  4. 2024Clio: Privacy-Preserving Insights into Real-World AI Usecited by 72
  5. 2024Hypothesis Generation with Large Language Modelscited by 71
  6. 2023ClusterLLM: Large Language Models as a Guide for Text Clusteringcited by 70
  7. 2024LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Modelscited by 29
  8. 2024CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Supportcited by 29
  9. 2024Answer is All You Need: Instruction-following Text Embedding via Answering the Questioncited by 27
  10. 2025EvalTree: Profiling Language Model Weaknesses via Hierarchical Capability Treescited by 27
  11. 2024TnT-LLM: Text Mining at Scale with Large Language Modelscited by 26
  12. 2024On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMscited by 25
38 more
  1. 2025Measuring General Intelligence with Generated Gamescited by 24
  2. 2024Explaining Datasets in Words: Statistical Models with Natural Language Parameterscited by 21
  3. 2024Knowledge Navigator: LLM-guided Browsing Framework for Exploratory Search in Scientific Literaturecited by 17
  4. 2024Text Clustering as Classification with LLMscited by 16
  5. 2025Behavioral Analysis of Information Salience in Large Language Modelscited by 12
  6. 2025Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Frameworkcited by 10
  7. 2025Context-Aware Hierarchical Taxonomy Generation for Scientific Papers via LLM-Guided Multi-Aspect Clusteringcited by 10
  8. 2023Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulationcited by 9
  9. 2026StoryScope: Investigating idiosyncrasies in AI fictioncited by 9
  10. 2024Automatic Histograms: Leveraging Language Models for Text Dataset Explorationcited by 8
  11. 2025From Papers to Panoramas: Building Hierarchies of Scientific Literature at Scalecited by 8
  12. 2024The Evolution of LLM Adoption in Industry Data Curation Practicescited by 6
  13. 2025Summaries as Centroids for Interpretable and Scalable Text Clusteringcited by 4
  14. 2025From Feedback to Checklists: Grounded Evaluation of AI-Generated Clinical Notescited by 4
  15. 2025Dataset Featurization: Uncovering Natural Language Features through Unsupervised Data Reconstructioncited by 3
  16. 2025Cequel: Cost-Effective Querying of Large Language Models for Text Clusteringcited by 3
  17. 2025RPM: Reasoning-Level Personalization for Black-Box Large Language Modelscited by 3
  18. 2025Co-DETECT: Collaborative Discovery of Edge Cases in Text Classificationcited by 3
  19. 2025Interpreting Language Models Through Concept Descriptions: A Surveycited by 3
  20. 2024Open-world Multi-label Text Classification with Extremely Weak Supervisioncited by 2
  21. 2026Cluster-R1: Large Reasoning Models Are Instruction-following Clustering Agentscited by 2
  22. 2026Who Defines "Best"? Towards Interactive, User-Defined Evaluation of LLM Leaderboardscited by 2
  23. 2023TopicGPT: A Prompt-based Topic Modeling Frameworkcited by 1
  24. 2024ZeroDL: Zero-shot Distribution Learning for Text Clustering via Large Language Modelscited by 1
  25. 2025Latent Factor Models Meets Instructions: Goal-conditioned Latent Factor Discovery without Task Supervisioncited by 1
  26. 2025SQLSpace: A Representation Space for Text-to-SQL to Discover and Mitigate Robustness Gapscited by 1
  27. 2025ClusterFusion: Hybrid Clustering with Embedding Guidance and LLM Adaptationcited by 1
  28. 2026X-Blocks: Linguistic Building Blocks of Natural Language Explanations for Automated Vehiclescited by 1
  29. 2026Going PLACES: Participatory Localized Red Teaming for Text-to-Image Safety in the Global Southcited by 1
  30. 2026Focusing Condition: Inference-Time Self-Contrastive Steering Elicits Better Conditional Text Embeddings in LLMscited by 1
  31. 2023Labeled Interactive Topic Modelscited by 0
  32. 2024DSAI: Unbiased and Interpretable Latent Feature Extraction for Data-Centric AIcited by 0
  33. 2024LITA: An Efficient LLM-assisted Iterative Topic Augmentation Frameworkcited by 0
  34. 2025ConceptCarve: Dynamic Realization of Evidencecited by 0
  35. 2025LogiPart: Local Large Language Models for Data Exploration at Scale with Logical Partitioningcited by 0
  36. 2026Human-Centric Topic Modeling with Goal-Prompted Contrastive Learning and Optimal Transportcited by 0
  37. 2026"What Are You Really Trying to Do?": Co-Creating Life Goals from Everyday Computer Usecited by 0
  38. 2026SC-Taxo: Hierarchical Taxonomy Generation under Semantic Consistency Constraints using Large Language Modelscited by 0

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