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Topic modeling is a well-established technique for exploring text corpora.
Discriminative Topic Mining via Category-Name Guided Text Embedding
Yu Meng, Jiaxin Huang, Guangyuan Wang, Zihan Wang, Chao Zhang, Yu Zhang, and Jiawei Han. 2020 · 1908
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A mathematical theory of communication
Claude Elwood Shannon. 1948 · 1948
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Objective criteria for the evaluation of clustering methods
William M Rand. 1971 · 1971
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Reasons for staying alive when you are thinking of killing yourself: the reasons for living inventory
Marsha M Linehan, Judith L Goodstein, Stevan L Nielsen, and John A Chiles. 1983 · 1983
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Comparing partitions
Lawrence Hubert and Phipps Arabie. 1985 · 1985
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Gibbs sampling in the generative model of latent dirichlet allocation
Tom Griffiths. 2002 · 2002
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Mallet: A machine learning for language toolkit
Andrew Kachites McCallum. 2002 · 2002
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Cluster ensembles—a knowledge reuse framework for combining multiple partitions
Alexander Strehl and Joydeep Ghosh. 2002 · 2002
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Latent dirichlet allocation
David M Blei, Andrew Y Ng, and Michael I Jordan. 2003 · 2003
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Hierarchical topic models and the nested chinese restaurant process
Thomas Griffiths, Michael Jordan, Joshua Tenenbaum, and David Blei. 2003 · 2003
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Three approaches to qualitative content analysis
Hsiu-Fang Hsieh and Sarah E Shannon. 2005 · 2005
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Criterion Functions for Document Clustering
Ying Zhao. 2005 · 2005
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Hierarchical Dirichlet Processes
Yee Whye Teh, Michael I Jordan, Matthew J Beal, and David M Blei. 2006 · 2006
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Automatic labeling of multinomial topic models
Qiaozhu Mei, Xuehua Shen, and ChengXiang Zhai. 2007 · 2007
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Comparing clusterings—an information based distance
Marina Meilă. 2007 · 2007
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Mixtures of hierarchical topics with pachinko allocation
David Mimno, Wei Li, and Andrew McCallum. 2007 · 2007
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A comparison of extrinsic clustering evaluation metrics based on formal constraints
Enrique Amigó, Julio Gonzalo, Javier Artiles, and Felisa Verdejo. 2009 · 2009
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Latent Dirichlet Allocation with Topic-in-Set Knowledge
David Andrzejewski and Xiaojin Zhu. 2009 · 2009
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Reading tea leaves: How humans interpret topic models
Jonathan Chang, Sean Gerrish, Chong Wang, Jordan Boyd-Graber, and David Blei. 2009 · 2009
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Information theoretic measures for clusterings comparison: is a correction for chance necessary?
Nguyen Xuan Vinh, Julien Epps, and James Bailey. 2009 · 2009
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Rethinking lda: Why priors matter
Hanna Wallach, David Mimno, and Andrew McCallum. 2009 · 2009
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Automatic evaluation of topic coherence
David Newman, Jey Han Lau, Karl Grieser, and Timothy Baldwin. 2010 · 2010
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Topic Modeling with Contextualized Word Representation Clusters
Laure Thompson and David Mimno. 2020 · 2010
Cited alongside, same era.
Automatic labelling of topic models
Jey Han Lau, Karl Grieser, David Newman, and Timothy Baldwin. 2011 · 2011
Cited alongside, same era.
Partially labeled topic models for interpretable text mining
Daniel Ramage, Christopher D. Manning, and Susan Dumais. 2011 · 2011
Cited alongside, same era.
Incorporating Lexical Priors into Topic Models
Jagadeesh Jagarlamudi, Hal Daumé III, and Raghavendra Udupa. 2012 · 2012
Cited alongside, same era.
A Topic Coverage Approach to Evaluation of Topic Models
Damir Korenčić, Strahil Ristov, Jelena Repar, and Jan Šnajder. 2021 · 2012
Cited alongside, same era.
Ethical and social risks of harm from language models
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, et al. 2021 · 2021
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Bertopic: Neural topic modeling with a class-based tf-idf procedure
Maarten Grootendorst. 2022 · 2022
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Are neural topic models broken?
Alexander Miserlis Hoyle, Pranav Goel, Rupak Sarkar, and Philip Resnik. 2022 · 2022
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A step-by-step protocol for curation of topic models by subject matter experts
Philip Resnik, Pranav Goel, Alexander Hoyle, Rupak Sarkar, Josh Hagedorn, Maeve Gearing, and Carol Bruce. 2022 · 2022
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Inductive content analysis: A guide for beginning qualitative researchers
Danya F Vears and Lynn Gillam. 2022 · 2022
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Jason Chuang, Sonal Gupta, Christopher Manning, and Jeffrey Heer. 2013 · 2013
Cited alongside, same era.
Interactive topic modeling
Yuening Hu, Jordan Boyd-Graber, Brianna Satinoff, and Alison Smith. 2014 · 2014
Cited alongside, same era.
Nested hierarchical dirichlet processes
John Paisley, Chong Wang, David M Blei, and Michael I Jordan. 2014 · 2014
Cited alongside, same era.
Alto: Active learning with topic overviews for speeding label induction and document labeling
Forough Poursabzi-Sangdeh, Jordan Boyd-Graber, Leah Findlater, and Kevin Seppi. 2016 · 2016
Cited alongside, same era.
Automatic labeling of topic models using text summaries
Xiaojun Wan and Tianming Wang. 2016 · 2016
Cited alongside, same era.
Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge
Ryan J. Gallagher, Kyle Reing, David Kale, and Greg Ver Steeg. 2017 · 2017
Cited alongside, same era.
Topic modelling for qualitative studies
Sergey I Nikolenko, Sergei Koltcov, and Olessia Koltsova. 2017 · 2017
Cited alongside, same era.
Llm-assisted content analysis: Using large language models to support deductive coding
Robert Chew, John Bollenbacher, Michael Wenger, Jessica Speer, and Annice Kim. 2023 · 2023
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Natural language decompositions of implicit content enable better text representations
Alexander Hoyle, Rupak Sarkar, Pranav Goel, and Philip Resnik. 2023 · 2023
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Not all languages are created equal in llms: Improving multilingual capability by cross-lingual-thought prompting
Haoyang Huang, Tianyi Tang, Dongdong Zhang, Wayne Xin Zhao, Ting Song, Yan Xia, and Furu Wei. 2023 · 2023
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Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
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Bactrian-x : A multilingual replicable instruction-following model with low-rank adaptation
Haonan Li, Fajri Koto, Minghao Wu, Alham Fikri Aji, and Timothy Baldwin. 2023 · 2023
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Abstractive summarization of large document collections using gpt
Sengjie Liu and Christopher G Healey. 2023 · 2023
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OpenAI. 2023 · 2023
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Towards Interpreting Topic Models with ChatGPT: The 20th World Congress of the International Fuzzy Systems Association
Emil Rijcken, Floortje Scheepers, Kalliopi Zervanou, Marco Spruit, Pablo Mosteiro, and Uzay Kaymak. 2023 · 2023
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Reflexion: Language agents with verbal reinforcement learning
Noah Shinn, Federico Cassano, Beck Labash, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023
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Revisiting automated topic model evaluation with large language models
Dominik Stammbach, Vilém Zouhar, Alexander Hoyle, Mrinmaya Sachan, and Elliott Ash. 2023 · 2023
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Pearl: Prompting large language models to plan and execute actions over long documents
Simeng Sun, Yang Liu, Shuohang Wang, Chenguang Zhu, and Mohit Iyyer. 2023 · 2023
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Use of large language models to aid analysis of textual data
Robert H Tai, Lillian R Bentley, Xin Xia, Jason M Sitt, Sarah C Fankhauser, Ana M Chicas-Mosier, and Barnas G Monteith. 2023 · 2023
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Large language models enable few-shot clustering
Vijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, Tongshuang Wu, and Graham Neubig. 2023 · 2023
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Goal-driven explainable clustering via language descriptions
Zihan Wang, Jingbo Shang, and Ruiqi Zhong. 2023 · 2023
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ClusterLLM: Large Language Models as a Guide for Text Clustering
Yuwei Zhang, Zihan Wang, and Jingbo Shang. 2023 · 2023
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Is Automated Topic Model Evaluation Broken? The Incoherence of Coherence
Alexander Hoyle, Pranav Goel, Andrew Hian-Cheong, Denis Peskov, Jordan Boyd-Graber, and Philip Resnik. 2021 · 2033
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