Chau Minh Pham
Chau Minh Pham has 4 papers in our library, in 2024–2026, most of them on Text generation, Vision & language; often with Mohit Iyyer, Simeng Sun, Akriti Jain.
OpenAlex · ORCID · h-index 0 · 3 works · 0 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 90 times in our library · ⭐ Paper Stars ranking: #5765
Affiliations
Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 worksGeneral Social Sciences · 1 workSocial Sciences · 1 workComputer Vision and Pattern Recognition · 1 work
🧭 Topics 2Research subjects and languages the work is about.Text generation · 1 workVision & language · 1 work
💡 Concepts 1Key ideas and methods explained on our concept pages.Topic modeling · 1 work
Works by year
2020s
Papers
- TopicGPT: A Prompt-based Topic Modeling Framework (2024 · 171 citations)
Classic topic models such as LDA describe each theme as a list of probable words. Users must interpret these lists themselves and have little say over how specific or how formatted the topics are. TopicGPT addresses this by having large language models do the topic modeling through prompting, in two stages. In the… - Suri: Multi-constraint Instruction Following in Long-form Text Generation (2024 · 19 citations)
Most instruction-tuning data pairs simple prompts with short answers. This paper addresses a harder setting: requests with many constraints that require outputs thousands of tokens long, such as fiction or detailed non-fiction. - Frankentext: Stitching random text fragments into long-form narratives (2026 · 1 citation)
The paper asks whether a black-box LLM user can cheaply produce long stories that read well and still slip past strong AI-text detectors. - AnalystBench: Benchmarking professional long-form report generation with web-mined multimodal tasks (2026)
Benchmarks for LLM-based report writing usually test isolated subskills, such as summarization or table aggregation. Benchmarks with realistic professional tasks, like GDPval, depend on costly expert-built tasks. AnalystBench aims to evaluate the whole analyst workflow at low cost.
Co-authors here
- Mohit Iyyer ×4
- Simeng Sun ×2
- Akriti Jain
- Aparna Garimella
- Jenna Russell
- Nedim Lipka
- Philip Resnik
- Puneet Mathur
- Varun Manjunatha
- Zichao Wang
Venues
- Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026, Findings of the Association for Computational Linguistics 2024
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- Conference of the North American Chapter of the Association for Computational Linguistics (NAACL): NAACL 2024
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