5 papers
Births are difficult to predict even with rich survey and full-population register data
Elizaveta Sivak, Emily M. Cantrell, Thomas Emery +109
Major life events have proven difficult to predict. Does this reflect limits of theory, data, and algorithms, or the large role of chance? We examine one outcome - having a child w…
Belief Coevolution in a Social Network of Generalist and Specialist Large Language Models
Germans Savcisens, Samantha Dies, Courtney Maynard +1
Large language models (LLMs) are increasingly deployed in multi-agent environments. However, the processes by which beliefs form and propagate among interacting LLMs remain poorly…
Epistemic Familiarity is Associated With Belief Stability in Large Language Models
Samantha Dies, Courtney Maynard, Germans Savcisens +1
Large language models (LLMs) are widely used as information sources, yet small changes in semantic assumptions can destabilize their beliefs. We introduce P-StaT (Perturbation Stab…
The Trilemma of Truth in Large Language Models
Germans Savcisens, Tina Eliassi-Rad
The public often attributes human-like qualities to large language models (LLMs), assuming that they "know" certain things. In reality, LLMs encode information retained during trai…
REGE: A Method for Incorporating Uncertainty in Graph Embeddings
Zohair Shafi, Germans Savcisens, Tina Eliassi-Rad
Machine learning models for graphs in real-world applications are prone to two primary types of uncertainty: (1) those that arise from incomplete and noisy data and (2) those that…