CS Ph.D. Student Hillary Owusu Receives ACM-W Scholarship

University of Maryland Department of Computer Science Ph.D. student Hillary Owusu received an ACM-W scholarship to attend the 64th Annual Meeting of the Association for Computational Linguistics, where she will present research examining irrational reasoning behaviors in large language models (LLMs). ACL 2026 is an international conference focused on natural language processing and computational linguistics.

Owusu, who is advised by Affiliate Associate Professor of Computer Science Naomi Feldman, studies how AI systems can be influenced by irrelevant numerical information, a phenomenon related to the anchoring effect in cognitive science.

Her research focuses on improving the reliability of systems that power tools such as ChatGPT. Her paper examines how anchoring appears in language models, how it relates to model uncertainty and how post-training methods can affect model behavior.

“As AI systems become more involved in how people learn, work and make decisions, their reliability has real societal consequences,” Owusu said. “My paper shows that even small, irrelevant details in a prompt can influence a model’s judgment in ways that users may not notice from the final answer alone.”

Research on LLMs has increasingly examined issues related to reasoning reliability, bias and interpretability as AI systems become more widely used in education, health care, business and other sectors. Researchers have also explored how prompting methods and training techniques shape the outputs and decision-making patterns of these systems.

Owusu said identifying and measuring anchoring effects could contribute to the development of AI systems that are more transparent and dependable in settings where accuracy and trust are important.

“Making these effects visible and measurable is an important step toward building AI tools that people can use with greater confidence,” Owusu said.

According to Owusu, the ACM-W scholarship provides a valuable opportunity to present her research to peers with similar interests in the field.

“I am deeply grateful to receive this award,” Owusu said. “This recognition is especially meaningful because it helps make it possible for me to attend ACL 2026 and share my research with the broader AI community.”

Owusu said the recognition also encourages her to continue research connecting computational cognitive science and natural language processing.

The work is part of Owusu’s broader focus on model reliability.

“My future work will focus on moving from diagnosis to intervention, not only identifying when anchoring occurs in large language models, but also understanding how it is represented internally and how its negative effects can be reduced,” Owusu said. “This work brings together computational cognitive science and AI interpretability to support the development of AI systems that are more reliable in real-world use.”

—Story by Samuel Malede Zewdu, CS Communications