tinlab studies humans and machines, centered around topics like (linguistic) generalization, meaning, evaluation methods and design, and the nature of computation and representation that underlies language and cognition. tinlab members come from a wide range of academic backgrounds including Linguistics, Cognitive Science, Computer Science, Data Science, and Psychology.
tinlab is led by Najoung Kim, and is affiliated with the Department of Linguistics, Computer Science, and Computing & Data Science at Boston University. The lab is also a part of the SALAMI Consortium, a growing group of researchers at BU interested in computation and language.
The lab website is now live!
RExBench has been accepted to ACL 2026! Work with Nicholas Edwards, Yukyung Lee, Audrey Mao, Yulu Qin, and Sebastian Schuster.
Are they lovers or friends? has been accepted to ACL 2026! Collaboration with KAIST team and Seza :)
“Does Episodic Memory Help Close the Lexical Frequency Gap in Sensitivity to Syntactic Contrasts? A Test Using Retrieval-Augmented Language Models” has been accepted to CogSci 2026! Work with Jing Liu.
Najoung presented “(How) Do Language Models Track Entities Across State Changes?” at MassMutual (work with Peter Tang, Qiao Zhao, Gabriel Franco, Derry Wijaya, Aaron Mueller, and Sebastian Schuster).
Najoung was at Brandeis CL/NLP for a panel discussion.
Najoung presented “Classical Computation in Connectionist Models” at IVADO (work with Aditya Yedetore).
tinlab received GPU support from Cloudexe, thank you!
Death of the Novel(ty): Beyond n-Gram Novelty as a Metric for Textual Creativity has been accepted to ICLR 2026! Work with Arkadiy Saakyan, Smaranda Muresan, and Tuhin Chakrabarty.
tinlab @ BU