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Aaron Mueller
Natural Language Processing (NLP)
Machine Learning
Controllable Language Generation
Interpretability Of Language Models
Language Model Capability Analysis
About
Aaron Mueller is an Assistant Professor of Computer Science at Boston University. His research centers on natural language processing and machine learning, with a focus on understanding, improving, and precisely controlling the capabilities and inner workings of systems that can learn and use human language.
Research Performance Summary
2019-2026
Active Research Span
First Recorded Paper
Quantity doesn't buy quality syntax with neural language models
Year:
2019
Citations:
118
Venue:
Empirical Methods in Natural Language Processing (EMNLP)
Latest Recorded Paper
Mechanisms of AI Protein Folding in ESMFold
Year:
2026
Citations:
0
Venue:
arXiv preprint arXiv:2602.06020
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Top Coauthors
Mueller
Linzen
Research Impact by Period
Papers
27
Citations
653
Avg. Citations / Paper
24.2
H-Index
11
Papers
29
Citations
1884
Avg. Citations / Paper
65
H-Index
20
Papers
3
Citations
145
Avg. Citations / Paper
48.3
H-Index
3
Contact and Professional Links
Detected Research Keywords
Neural Language Models
Babylm Challenge Sample
Challenge Sample Efficient
Sample Efficient Pretraining
Efficient Pretraining Developmentally
Pretraining Developmentally Plausible
Developmentally Plausible Corpora
Causal Analysis Syntactic
Analysis Syntactic Agreement
Mechanisms Neural Language