no code implementations • 2 Apr 2024 • Raffaele Galliera, Thies Möhlenhof, Alessandro Amato, Daniel Duran, Kristen Brent Venable, Niranjan Suri
Effective operation and seamless cooperation of robotic systems are a fundamental component of next-generation technologies and applications.
1 code implementation • 14 Feb 2024 • Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi
This paper considers the challenges that Large Language Models (LLMs) face when reasoning over text that includes information involving uncertainty explicitly quantified via probability values.
1 code implementation • 25 Aug 2023 • Raffaele Galliera, Kristen Brent Venable, Matteo Bassani, Niranjan Suri
Efficient information dissemination is crucial for supporting critical operations across domains like disaster response, autonomous vehicles, and sensor networks.
no code implementations • 22 May 2023 • Aliakbar Nafar, Kristen Brent Venable, Parisa Kordjamshidi
In this paper, we evaluate the capability of transformer-based language models in making inferences over uncertain text that includes uncertain rules of reasoning.
no code implementations • 5 Oct 2021 • Marianna Bergamaschi Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh, Jon Lenchner, Andrea Loreggia, Nicholas Mattei, Francesca Rossi, Biplav Srivastava, Kristen Brent Venable
AI systems have seen dramatic advancement in recent years, bringing many applications that pervade our everyday life.