research

BenchMarker: An Education-Inspired Toolkit for Highlighting Flaws in Multiple-Choice Benchmarks

Nishant Balepur, Bhavya Rajasekaran, Jane Oh, Michael Xie, Atrey Desai, Jordan Boyd-Graber

A Preview of Computational Animal Linguistics

Atrey Desai, Tirza Panunto, Lindsay Pike, Theron S. Wang, Tuan M. Dang, Hridayesh Lekhak, Kenny Q. Zhu

Filling in the Mechanisms: How do LMs Learn Filler-Gap Dependencies under Developmental Constraints?

Atrey Desai, Sathvik Nair

Longitudinal Phonetic Adaptation in YouTube BookTube Creators

Atrey Desai

We analyze how YouTube "BookTube" creators adapt their phonetic features over time, finding that they significantly reduce vocal fry and increase pitch range as they gain experience. These changes correlate with higher audience engagement, suggesting that long-form content creators professionalize their speech to signal competence and credibility.

From LOL to LLM: Measuring Multilingual Multi-Turn Humor Understanding in AI

Atrey Desai, Leo Du, James van Doorn, Kamala Sreepada

We introduce a multilingual benchmark to evaluate how Large Language Models (LLMs) understand multi-turn humor in English and Spanish through joke classification and line-purpose identification tasks. We find that while larger open-source models (32B) significantly outperform smaller ones, all models struggle with nuanced humor comprehension and are highly sensitive to adversarial perturbations and cross-cultural linguistic differences.