4 papers
Extracting Probabilistic Knowledge from Large Language Models for Bayesian Network Parameterization
Aliakbar Nafar, Kristen Brent Venable, Zijun Cui +1
In this work, we evaluate the potential of Large Language Models (LLMs) in building Bayesian Networks (BNs) by approximating domain expert priors. LLMs have demonstrated potential…
Natural Language Interaction with Databases on Edge Devices in the Internet of Battlefield Things
Christopher D. Molek, Roberto Fronteddu, K. Brent Venable +1
The expansion of the Internet of Things (IoT) in the battlefield, Internet of Battlefield Things (IoBT), gives rise to new opportunities for enhancing situational awareness. To inc…
Learning vs Retrieval: The Role of In-Context Examples in Regression with Large Language Models
Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi
Generative Large Language Models (LLMs) are capable of being in-context learners. However, the underlying mechanism of in-context learning (ICL) is still a major research question,…
Reasoning over Uncertain Text by Generative Large Language Models
Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi
This paper considers the challenges Large Language Models (LLMs) face when reasoning over text that includes information involving uncertainty explicitly quantified via probability…