--- title: "Who cites TopicGPT: A Prompt-based Topic — 75 citing papers" description: "75 papers of the Elamur Research library cite «TopicGPT: A Prompt-based Topic Modeling Framework», found in their bibliographies; the…" canonical: "https://research.elamur.ai/free/en/papers/pham-2024-topicgpt-prompt-based-topic-modeling/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/pham-2024-topicgpt-prompt-based-topic-modeling/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [TopicGPT: A Prompt-based Topic Modeling Framework](https://md.research.elamur.ai/free/en/papers/pham-2024-topicgpt-prompt-based-topic-modeling/) / cited by # Who cites «TopicGPT: A Prompt-based Topic Modeling Framework» 75 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «TopicGPT: A Prompt-based Topic Modeling Framework»](https://md.research.elamur.ai/free/en/papers/pham-2024-topicgpt-prompt-based-topic-modeling/) 1. [**Rethinking Interpretability in the Era of Large Language Models arXiv:2402.01761**Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-rethinking-interpretability-era-large-language/) 2. **[Can Unconfident LLM Annotations Be Used for Confident Conclusions?](https://md.research.elamur.ai/free/en/papers/gligoric-2025-can-unconfident-llm-annotations-be/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kristina Gligorić, Tijana Zrnic, Cinoo Lee, et al.*2025 · 19 citations* 3. **[Literature Meets Data: A Synergistic Approach to Hypothesis Generation](https://md.research.elamur.ai/free/en/papers/liu-2025-literature-meets-data-synergistic-approach/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haokun Liu, Yangqiaoyu Zhou, Mingxuan Li, et al.*2025 · 12 citations* 4. **[Beyond Coherence: Improving Temporal Consistency and Interpretability in Dynamic Topic Models](https://md.research.elamur.ai/free/en/papers/nguyen-2026-beyond-coherence-improving-temporal-consistency/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thanh Vinh Nguyen, Ngo Van Dong, Minh Chu Xuan, et al.*2026 · 1 citation* 5. **[Towards Modern Topic Models: A Survey of Taxonomies and Paradigm Shifts from Algorithm-Centric to LLM-Centered Topic Analysis](https://md.research.elamur.ai/free/en/papers/xu-2026-modern-topic-models-survey-taxonomies/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Xu, Zhongliang Yang, Haolun Li, et al.*2026 · 1 citation* 6. [**AIn't Nothing But a Survey? Using Large Language Models for Coding German Open-Ended Survey Responses on Survey Motivation arXiv:2506.14634 · Survey Research Methods (2025)**Leah von der Heyde, Anna-Carolina Haensch, Bernd Weiß, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/heyde-2025-ain-t-nothing-but-survey/) 7. **[CobwebTM: Probabilistic Concept Formation for Lifelong and Hierarchical Topic Modeling](https://md.research.elamur.ai/free/en/papers/singaravadivelan-2026-cobwebtm-probabilistic-concept-formation-lifelong/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Karthik Singaravadivelan, Anant Gupta, Zekun Wang, et al.*2026* 8. **[Evaluating Language Model Pluralism through In-the-wild Crowd Discussions](https://md.research.elamur.ai/free/en/papers/mundada-2026-evaluating-language-model-pluralism-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gagan Mundada, Rohan Surana, Nandhini Swaminathan, et al.*2026* 9. **[From Documents to Segments: A Contextual Reformulation for Topic Assignment](https://md.research.elamur.ai/free/en/papers/yoon-2026-documents-segments-contextual-reformulation-topic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoonsang Yoon, Takyoung Kim, Wonkee Lee, et al.*2026* 10. **[Launch and Aftermath: Contrasting Social Media Responses to Chatbot Releases. The Cases of Meta's Galactica and OpenAI's ChatGPT](https://md.research.elamur.ai/free/en/papers/weber-2026-launch-aftermath-contrasting-social-media/) [Workshop on Natural Language Processing and Computational Social Science](https://md.research.elamur.ai/free/en/venues/nlpcss/)**Maximilian Weber, Johannes B. Gruber*2026* 11. **[LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models](https://md.research.elamur.ai/free/en/papers/xuan-2026-llm-xtm-enhancing-cross-lingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minh Chu Xuan, Tien-Phat Nguyen, Linh Ngo Van, et al.*2026* 12. **[Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/zheng-2026-model-directions-not-words-mechanistic/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Carolina Zheng, Nicolas Beltran-Velez, Sweta Karlekar, et al.*2026* 13. **[Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation](https://md.research.elamur.ai/free/en/papers/ma-2026-too-open-opinion-embracing-open/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bolei Ma, Yong Cao, Indira Sen, et al.*2026* 62 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/pham-2024-topicgpt-prompt-based-topic-modeling/) — TopicGPT: A Prompt-based Topic Modeling Framework