6 papers
PALMs: Using Multi Construct-Grounded Rationales for Modeling Population Preferences in LLMs
Priyanka Dey, Brihi Joshi, Preyashi Poddar +2
Large language models are being extensively used to simulate individual user behavior, yet faithfully representing a population requires capturing the systematic variation in value…
RLHF May Not Reflect Genuine Preferences
Bijean Ghafouri, Eun Cheol Choi, Priyanka Dey +1
Reinforcement Learning from Human Feedback (RLHF) assumes that annotation responses reflect genuine human preferences. They often do not. Behavioral scientists have documented for…
Israel-Hamas War on X: A Case Study of Coordinated Campaigns and Information Integrity
TuÄrulcan Elmas, Filipi Nascimento Silva, Manita Pote +8
Coordinated campaigns on social media play a critical role in shaping crisis information environments, particularly during the onset of conflicts when uncertainty is high and verif…
GRAVITY: A Framework for Personalized Text Generation via Profile-Grounded Synthetic Preferences
Priyanka Dey, Daniele Rosa, Wenqing Zheng +3
Personalization in LLMs often relies on costly human feedback or interaction logs, limiting scalability and neglecting deeper user attributes. To reduce the reliance on human annot…
Can LLMs Express Personality Across Cultures? Introducing CulturalPersonas for Evaluating Trait Alignment
Priyanka Dey, Yugal Khanter, Aayush Bothra +2
As LLMs become central to interactive applications, ranging from tutoring to mental health, the ability to express personality in culturally appropriate ways is increasingly import…
Can LLMs Grasp Implicit Cultural Values? Benchmarking LLMs' Cultural Intelligence with CQ-Bench
Ziyi Liu, Priyanka Dey, Jen-tse Huang +6
Cultural Intelligence (CQ) refers to the ability to understand unfamiliar cultural contexts, a crucial skill for large language models (LLMs) to effectively engage with globally di…