3 papers
cs.IR2026
PeReGrINE: Evaluating Personalized Review Fidelity with User Item Graph Context
Steven Au, Baihan Lin
We introduce PeReGrINE, a benchmark and evaluation framework for personalized review generation grounded in graph-structured user--item evidence. PeReGrINE restructures Amazon Revi…
cs.CL2026
Beyond Social Pressure: Benchmarking Epistemic Attack in Large Language Models
Steven Au, Sujit Noronha
Large language models (LLMs) can shift their answers under pressure in ways that reflect accommodation rather than reasoning. Prior work on sycophancy has focused mainly on disagre…
cs.CL2025
Personalized Graph-Based Retrieval for Large Language Models
Steven Au, Cameron J. Dimacali, Ojasmitha Pedirappagari +7
As large language models (LLMs) evolve, their ability to deliver personalized and context-aware responses offers transformative potential for improving user experiences. Existing p…