{"total":31,"rows":[{"id":"2303.04245","title":"How Do Transformers Learn Topic Structure: Towards a Mechanistic Understanding","created":"2023-03-07","cited_by_count":86,"area":null},{"id":"2306.04217","title":"Effective Neural Topic Modeling with Embedding Clustering Regularization","created":"2023-06-07","cited_by_count":46,"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":"2401.15351","title":"A Survey on Neural Topic Models: Methods, Applications, and Challenges","created":"2024-01-27","cited_by_count":18,"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":"2409.19749","title":"NeuroMax: Enhancing Neural Topic Modeling via Maximizing Mutual Information and Group Topic Regularization","created":"2024-09-29","cited_by_count":9,"area":null},{"id":"2410.00134","title":"Semantic-Driven Topic Modeling Using Transformer-Based Embeddings and Clustering Algorithms","created":"2024-09-30","cited_by_count":8,"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":"2509.10697","title":"A Survey on Retrieval And Structuring Augmented Generation with Large Language Models","created":"2025-09-12","cited_by_count":8,"area":null},{"id":"2312.14226","title":"Deep de Finetti: Recovering Topic Distributions from Large Language Models","created":"2023-12-21","cited_by_count":7,"area":null},{"id":"2401.17228","title":"Morality is Non-Binary: Building a Pluralist Moral Sentence Embedding Space using Contrastive Learning","created":"2024-01-30","cited_by_count":7,"area":null},{"id":"2411.16613","title":"Recent Trends in Linear Text Segmentation: a Survey","created":"2024-11-25","cited_by_count":6,"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":"2304.05232","title":"Lady and the Tramp Nextdoor: Online Manifestations of Economic Inequalities in the Nextdoor Social Network","created":"2023-04-11","cited_by_count":3,"area":null},{"id":"2307.00968","title":"REAL: A Representative Error-Driven Approach for Active Learning","created":"2023-07-03","cited_by_count":3,"area":null},{"id":"2406.00697","title":"Comprehensive Evaluation of Large Language Models for Topic Modeling","created":"2024-06-02","cited_by_count":3,"area":null},{"id":"2412.12433","title":"Refining Dimensions for Improving Clustering-based Cross-lingual Topic Models","created":"2024-12-17","cited_by_count":3,"area":null},{"id":"2507.00828","title":"ProxAnn: Use-Oriented Evaluations of Topic Models and Document Clustering","created":"2025-07-01","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":"2506.12242","title":"Large Language Models for History, Philosophy, and Sociology of Science: Interpretive Uses, Methodological Challenges, and Critical Perspectives","created":"2025-06-13","cited_by_count":2,"area":null},{"id":"2410.03964","title":"Variational Language Concepts for Interpreting Foundation Language Models","created":"2024-10-04","cited_by_count":1,"area":null},{"id":"2507.01234","title":"The Medium Is Not the Message: Deconfounding Document Embeddings via Linear Concept Erasure","created":"2025-07-01","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":"2304.06653","title":"Graph2topic: an opensource topic modeling framework based on sentence embedding and community detection","created":"2023-04-13","cited_by_count":0,"area":null},{"id":"2305.09359","title":"Constructing and Interpreting Causal Knowledge Graphs from News","created":"2023-05-16","cited_by_count":0,"area":null},{"id":"2503.02707","title":"Multilingualism, Transnationality, and K-pop in the Online #StopAsianHate Movement","created":"2025-03-04","cited_by_count":0,"area":null},{"id":"2504.05320","title":"Document clustering with evolved multiword search queries","created":"2025-02-24","cited_by_count":0,"area":null},{"id":"2505.06624","title":"The Efficiency of Pre-training with Objective Masking in Pseudo Labeling for Semi-Supervised Text Classification","created":"2025-05-10","cited_by_count":0,"area":null},{"id":"2512.21715","title":"CATCH: A Controllable Theme Detection Framework with Contextualized Clustering and Hierarchical Generation","created":"2025-12-25","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":"2608.19133","title":"Comment-level Topic Drift Analysis in the Reddit Corpus","created":"2026-08-19","cited_by_count":0,"area":null}],"next_cursor":null}