{"total":74,"rows":[{"id":"2203.05794","title":"BERTopic: Neural topic modeling with a class-based TF-IDF procedure","created":"2022-03-11","cited_by_count":801,"area":null},{"id":"2404.12259","title":"Concept Induction: Analyzing Unstructured Text with High-Level Concepts Using LLooM","created":"2024-04-18","cited_by_count":78,"area":null},{"id":"2405.17978","title":"FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Model","created":"2024-05-28","cited_by_count":35,"area":null},{"id":"2407.16711","title":"Benchmarks as Microscopes: A Call for Model Metrology","created":"2024-07-22","cited_by_count":35,"area":null},{"id":"2312.09693","title":"Prompting Large Language Models for Topic Modeling","created":"2023-12-15","cited_by_count":25,"area":null},{"id":"2309.06908","title":"Towards the TopMost: A Topic Modeling System Toolkit","created":"2023-09-13","cited_by_count":21,"area":null},{"id":"2305.14587","title":"Contextualized Topic Coherence Metrics","created":"2023-05-23","cited_by_count":19,"area":null},{"id":"2401.15351","title":"A Survey on Neural Topic Models: Methods, Applications, and Challenges","created":"2024-01-27","cited_by_count":18,"area":null},{"id":"2307.01226","title":"vONTSS: vMF based semi-supervised neural topic modeling with optimal transport","created":"2023-07-03","cited_by_count":16,"area":null},{"id":"2305.05094","title":"Interactive Concept Learning for Uncovering Latent Themes in Large Text Collections","created":"2023-05-08","cited_by_count":15,"area":null},{"id":"2212.06002","title":"Effective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts","created":"2022-12-12","cited_by_count":12,"area":null},{"id":"2402.07577","title":"Topic Modeling as Multi-Objective Contrastive Optimization","created":"2024-02-12","cited_by_count":12,"area":null},{"id":"2509.17946","title":"HICode: Hierarchical Inductive Coding with LLMs","created":"2025-09-22","cited_by_count":12,"area":null},{"id":"2210.16162","title":"Are Neural Topic Models Broken?","created":"2022-10-28","cited_by_count":11,"area":null},{"id":"2404.10259","title":"Uncovering Latent Arguments in Social Media Messaging by Employing LLMs-in-the-Loop Strategy","created":"2024-04-16","cited_by_count":9,"area":null},{"id":"2507.23220","title":"Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders","created":"2025-07-31","cited_by_count":8,"area":null},{"id":"2302.10086","title":"A Two-Sided Discussion of Preregistration of NLP Research","created":"2023-02-20","cited_by_count":6,"area":null},{"id":"2305.11251","title":"Computational thematics: Comparing algorithms for clustering the genres of literary fiction","created":"2023-05-18","cited_by_count":5,"area":null},{"id":"2312.06093","title":"PromptMTopic: Unsupervised Multimodal Topic Modeling of Memes using Large Language Models","created":"2023-12-11","cited_by_count":5,"area":null},{"id":"2403.17308","title":"Neural Multimodal Topic Modeling: A Comprehensive Evaluation","created":"2024-03-26","cited_by_count":5,"area":null},{"id":"2303.00135","title":"Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron","created":"2023-02-28","cited_by_count":4,"area":null},{"id":"2303.14951","title":"Improving Contextualized Topic Models with Negative Sampling","created":"2023-03-27","cited_by_count":4,"area":null},{"id":"2309.08627","title":"Evaluating Dynamic Topic Models","created":"2023-09-12","cited_by_count":4,"area":null},{"id":"2404.02115","title":"GINopic: Topic Modeling with Graph Isomorphism Network","created":"2024-04-02","cited_by_count":4,"area":null},{"id":"2409.15626","title":"Qualitative Insights Tool (QualIT): LLM Enhanced Topic Modeling","created":"2024-09-24","cited_by_count":4,"area":null},{"id":"2204.03208","title":"A Joint Learning Approach for Semi-supervised Neural Topic Modeling","created":"2022-04-07","cited_by_count":3,"area":null},{"id":"2301.02458","title":"Topics as Entity Clusters: Entity-based Topics from Large Language Models and Graph Neural Networks","created":"2023-01-06","cited_by_count":3,"area":null},{"id":"2303.15973","title":"Do Neural Topic Models Really Need Dropout? Analysis of the Effect of Dropout in Topic Modeling","created":"2023-03-28","cited_by_count":3,"area":null},{"id":"2305.12152","title":"Revisiting Automated Topic Model Evaluation with Large Language Models","created":"2023-05-20","cited_by_count":3,"area":null},{"id":"2312.02331","title":"Revisiting Topic-Guided Language Models","created":"2023-12-04","cited_by_count":3,"area":null},{"id":"2405.07278","title":"Human-interpretable clustering of short-text using large language models","created":"2024-05-12","cited_by_count":3,"area":null},{"id":"2410.15136","title":"CAST: Corpus-Aware Self-similarity Enhanced Topic modelling","created":"2024-10-19","cited_by_count":3,"area":null},{"id":"2511.16309","title":"Sparse Autoencoders are Topic Models","created":"2025-11-20","cited_by_count":3,"area":null},{"id":"2112.03104","title":"HTMOT : Hierarchical Topic Modelling Over Time","created":"2021-11-22","cited_by_count":2,"area":null},{"id":"2208.01712","title":"No Pattern, No Recognition: a Survey about Reproducibility and Distortion Issues of Text Clustering and Topic Modeling","created":"2022-08-02","cited_by_count":2,"area":null},{"id":"2304.03797","title":"Bridging Nations: Quantifying the Role of Multilinguals in Communication on Social Media","created":"2023-04-07","cited_by_count":2,"area":null},{"id":"2407.17390","title":"$T^5Score$: A Methodology for Automatically Assessing the Quality of LLM Generated Multi-Document Topic Sets","created":"2024-07-24","cited_by_count":2,"area":null},{"id":"2502.14748","title":"Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of Topic Models","created":"2025-02-20","cited_by_count":2,"area":null},{"id":"2301.04339","title":"Topics in Contextualised Attention Embeddings","created":"2023-01-11","cited_by_count":1,"area":null},{"id":"2302.00493","title":"You Are What You Talk About: Inducing Evaluative Topics for Personality Analysis","created":"2023-02-01","cited_by_count":1,"area":null},{"id":"2303.17324","title":"Topics in the Haystack: Extracting and Evaluating Topics beyond Coherence","created":"2023-03-30","cited_by_count":1,"area":null},{"id":"2311.01449","title":"TopicGPT: A Prompt-based Topic Modeling Framework","created":"2023-11-02","cited_by_count":1,"area":null},{"id":"2403.03607","title":"The Geometric Structure of Topic Models","created":"2024-03-06","cited_by_count":1,"area":null},{"id":"2403.03737","title":"Probabilistic Topic Modelling with Transformer Representations","created":"2024-03-06","cited_by_count":1,"area":null},{"id":"2403.04451","title":"Membership Inference Attacks and Privacy in Topic Modeling","created":"2024-03-07","cited_by_count":1,"area":"safety"},{"id":"2410.18140","title":"Tethering Broken Themes: Aligning Neural Topic Models with Labels and Authors","created":"2024-10-22","cited_by_count":1,"area":null},{"id":"2410.23186","title":"Reliability of Topic Modeling","created":"2024-10-30","cited_by_count":1,"area":null},{"id":"2410.24126","title":"Multi-environment Topic Models","created":"2024-10-31","cited_by_count":1,"area":null},{"id":"2412.17338","title":"Enhancing Topic Interpretability for Neural Topic Modeling through Topic-wise Contrastive Learning","created":"2024-12-23","cited_by_count":1,"area":null},{"id":"2507.12451","title":"S2WTM: Spherical Sliced-Wasserstein Autoencoder for Topic Modeling","created":"2025-07-16","cited_by_count":1,"area":null},{"id":"2211.05599","title":"Moving beyond word lists: towards abstractive topic labels for human-like topics of scientific documents","created":"2022-10-28","cited_by_count":0,"area":null},{"id":"2301.09295","title":"Sensemaking About Contraceptive Methods Across Online Platforms","created":"2023-01-23","cited_by_count":0,"area":null},{"id":"2307.16573","title":"Deep Dive into the Language of International Relations: NLP-based Analysis of UNESCO's Summary Records","created":"2023-07-31","cited_by_count":0,"area":null},{"id":"2311.09438","title":"Labeled Interactive Topic Models","created":"2023-11-15","cited_by_count":0,"area":null},{"id":"2406.09556","title":"$S^3$ -- Semantic Signal Separation","created":"2024-06-13","cited_by_count":0,"area":null},{"id":"2408.09030","title":"Effects of Collaboration on the Performance of Interactive Theme Discovery Systems","created":"2024-08-16","cited_by_count":0,"area":null},{"id":"2410.02441","title":"Embedded Topic Models Enhanced by Wikification","created":"2024-10-03","cited_by_count":0,"area":null},{"id":"2503.18167","title":"Evaluating Negative Sampling Approaches for Neural Topic Models","created":"2025-03-23","cited_by_count":0,"area":null},{"id":"2504.19209","title":"Dynamic Embedded Topic Models: properties and recommendations based on diverse corpora","created":"2025-04-27","cited_by_count":0,"area":null},{"id":"2505.16493","title":"Constrained Non-negative Matrix Factorization for Guided Topic Modeling of Minority Topics","created":"2025-05-22","cited_by_count":0,"area":null},{"id":"2507.19117","title":"Objectifying the Subjective: Cognitive Biases in Topic Interpretations","created":"2025-07-25","cited_by_count":0,"area":null},{"id":"2509.22030","title":"From Outliers to Topics in Language Models: Anticipating Trends in News Corpora","created":"2025-09-26","cited_by_count":0,"area":null},{"id":"2511.18843","title":"A Reproducible Framework for Neural Topic Modeling in Focus Group Analysis","created":"2025-11-24","cited_by_count":0,"area":null},{"id":"2512.06694","title":"TopiCLEAR: Adaptive embedding clustering for interpretable topic discovery from short texts","created":"2025-12-07","cited_by_count":0,"area":null},{"id":"2602.17907","title":"Improving Topic Modeling by Distilling Soft Labels from Language Models","created":"2026-02-20","cited_by_count":0,"area":null},{"id":"2602.19079","title":"TriTopic: Tri-Modal Graph-Based Topic Modeling with Iterative Refinement and Archetypes","created":"2026-02-22","cited_by_count":0,"area":null},{"id":"2603.01945","title":"When Numbers Tell Half the Story: Human-Metric Alignment in Topic Model Evaluation","created":"2026-03-02","cited_by_count":0,"area":null},{"id":"2605.04761","title":"Cognitive Twins: Investigating Personalized Thinking Model Building and Its Performance Enhancement with Human-in-the-Loop","created":"2026-05-06","cited_by_count":0,"area":"lr"},{"id":"2607.03323","title":"From Gentlemen to Frontiermen: Masculine Formations in English-Language Fiction (1771--1930)","created":"2026-07-03","cited_by_count":0,"area":null},{"id":"2608.13835","title":"When Lexical Change Misleads: Rethinking Dynamic Topic Model Evaluation with Traditional and LLM-Based Metrics","created":"2026-08-13","cited_by_count":0,"area":"lr"},{"id":"2608.18101","title":"BERTilda: Explainable Topic Lifecycle Tracking with Split/Merge Detection via Similarity-and-Flow Temporal Graphs","created":"2026-06-09","cited_by_count":0,"area":null},{"id":"2609.06664","title":"EviMap: Evidence-Grounded Hierarchical Topic Maps for Exploring Unlabeled Corpora","created":"2026-09-06","cited_by_count":0,"area":null},{"id":"2609.14256","title":"Document Topic Alignment Metrics for Evaluating Topic Models of Short-Text Public Health Communications on Social Media","created":"2026-09-13","cited_by_count":0,"area":null},{"id":"2609.29630","title":"A Manifold-Aware Topic Modeling Approach via Rank-Based Prototypes","created":"2026-08-29","cited_by_count":0,"area":null}],"next_cursor":null}