🧑‍🔬 Christopher J. MacLellan

🏛️ Affiliations

🎓Georgia Institute of TechnologyAtlanta · United States2022–2026 · 23 papersEmployment since 2022current🎓Carnegie Mellon UniversityPittsburgh · United States2012–2024 · 20 papersEducation 2012–2015🎓Drexel UniversityPhiladelphia · United States2020–2024 · 9 papers🎓Arizona State UniversityTempe · United States2010–2013 · 3 papersEducation 2010–2012🎓University of WyomingLaramie · United States2006–2010Education 2006–2010

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. CobwebTM: Probabilistic Concept Formation for Lifelong and Hierarchical Topic Modeling (2026)
   Topic models usually involve a trade-off. LDA-style probabilistic models need a fixed topic count and bag-of-words input. Neural models are heavily parameterized, trained in batch, and tend to forget earlier topics as new data streams in. Hierarchies are also often added only after flat clustering. CobwebTM addresses…
2. Grounded Concreteness: Human-Like Concreteness Sensitivity in Vision–Language Models (2026)
   The paper asks whether multimodal training gives language models a more human-like sense of how concrete or abstract words are, even when the models only receive text.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Learning Cognitive Models Using Neural Networks ↗Lecture notes in computer science · no summary yetDevendra Singh Chaplot et al.2018 · 12 citations
2. CobwebTM: Probabilistic Concept Formation for Lifelong and Hierarchical Topic ModelingFindings of the Association for Computational LinguisticsKarthik Singaravadivelan, Anant Gupta, Zekun Wang, et al.2026
3. Grounded Concreteness: Human-Like Concreteness Sensitivity in Vision–Language ModelsFindings of the Association for Computational LinguisticsAryan Roy, Zekun Wang, Christopher J. MacLellan2026

🤝 Co-authors here

1 co-author with a page, the most papers together first.

• Zekun Wang ×2

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026 ×2
• Lecture notes in computer science

🔗 Cited by

Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read).

Updated 1 November 2026

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