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https://arxiv.org/abs/1204.1956 [1204.1956] Learning Topic Models - Going beyond SVD Abstract page for arXiv paper 1204.1956: Learning Topic Models - Going beyond SVD topic models going beyond 1204 1956 learning https://www.ascd.org/el/articles/models-of-reform-a-comparative-guide Special Topic / Models of Reform: A Comparative Guide A comparison of 12 of the most widely implemented education programs for at-risk students can help educators choose a direction as they respond to increasing... special topic models reform comparative guide https://deepai.org/publication/gibbs-max-margin-topic-models-with-data-augmentation Gibbs Max-margin Topic Models with Data Augmentation | DeepAI Oct 10, 2013 - 10/10/13 - Max-margin learning is a powerful approach to building classifiers and structured output predictors. Recent work on max-margin sup... max margin topic models data augmentation gibbs deepai https://aclanthology.org/2021.findings-acl.382/ Benchmarking Neural Topic Models: An Empirical Study - ACL Anthology Thanh-Nam Doan, Tuan-Anh Hoang. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. 2021. topic models empirical study benchmarking neural acl https://aclanthology.org/2022.findings-emnlp.390/ Are Neural Topic Models Broken? - ACL Anthology Alexander Hoyle, Pranav Goel, Rupak Sarkar, Philip Resnik. Findings of the Association for Computational Linguistics: EMNLP 2022. 2022. topic models neural broken acl anthology https://aclanthology.org/N15-2017/ Speeding Document Annotation with Topic Models - ACL Anthology Forough Poursabzi-Sangdeh, Jordan Boyd-Graber. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational... topic models speeding document annotation acl https://www.nist.gov/publications/traditional-topic-models-llm-topic-models-can-large-language-models-replace-traditional From Traditional Topic Models to LLM Topic Models: Can Large Language Models Replace Traditional... Dec 11, 2025 - A common use of NLP is to facilitate the understanding of large document collections, with models based on Large Language Models (LLMs) replacing probabilistic topic models traditional llm large language https://aclanthology.org/D11-1024/ Optimizing Semantic Coherence in Topic Models - ACL Anthology David Mimno, Hanna Wallach, Edmund Talley, Miriam Leenders, Andrew McCallum. Proceedings of the 2011 Conference on Empirical Methods in Natural Language... topic models optimizing semantic coherence acl https://www.jmlr.org/papers/v22/21-0089.html Contrastive Estimation Reveals Topic Posterior Information to Linear Models contrastive estimation reveals topic posterior