3 citations · 6 across the 7 of their papers we have counts for
4 papers · 1 filter
What Helps Language Models Predict Human Beliefs: Demographics or Prior Stances?
Joseph Malone, Rachith Aiyappa, Byunghwee Lee +3
Beliefs shape how people reason, communicate, and behave. Rather than existing in isolation, they exhibit a rich correlational structure--some connected through logical dependencie…
Cognitive Linguistic Identity Fusion Score (CLIFS): A Scalable Cognition-Informed Approach to Quantifying Identity Fusion from Text
Devin R. Wright, Jisun An, Yong-Yeol Ahn
Quantifying identity fusion -- the psychological merging of self with another entity or abstract target (e.g., a religious group, political party, ideology, value, brand, belief, e…
A semantic embedding space based on large language models for modelling human beliefs
Byunghwee Lee, Rachith Aiyappa, Yong-Yeol Ahn +2
Beliefs form the foundation of human cognition and decision-making, guiding our actions and social connections. A model encapsulating beliefs and their interrelationships is crucia…
Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance
Rachith Aiyappa, Shruthi Senthilmani, Jisun An +2
We investigate the performance of LLM-based zero-shot stance detection on tweets. Using FlanT5-XXL, an instruction-tuned open-source LLM, with the SemEval 2016 Tasks 6A, 6B, and P-…