Alexander M. Berenbeim

According to our database, Alexander M. Berenbeim authored at least 7 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding.

Trilok Padhi, Ramneet Kaur, Adam D. Cobb, Manoj Acharya, Anirban Roy, Colin Samplawski, Brian Matejek, Alexander M. Berenbeim, Nathaniel D. Bastian, Susmit Jha

CoRR, May, 2025

Zero-Shot Detection of Out-of-Context Objects Using Foundation Models.

Anirban Roy, Adam D. Cobb, Ramneet Kaur, Sumit Jha, Nathaniel D. Bastian, Alexander M. Berenbeim, Robert H. Thomson, Iain Cruickshank, Alvaro Velasquez, Susmit Jha

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

2024

Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI.

Ramneet Kaur, Colin Samplawski, Adam D. Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander M. Berenbeim, John A. Pavlik, Nathaniel D. Bastian, Susmit Jha

CoRR, 2024

Post-hoc Uncertainty Quantification for Neurosymbolic Artificial Intelligence.

Alexander M. Berenbeim, Ramneet Kaur, Adam D. Cobb, Anirban Roy, Susmit Jha, Nathaniel D. Bastian

Proceedings of the IEEE Military Communications Conference, 2024

2023

Measuring Classification Decision Certainty and Doubt.

Alexander M. Berenbeim, Iain J. Cruickshank, Susmit Jha, Robert H. Thomson, Nathaniel D. Bastian

CoRR, 2023

Uncertainty-Quantified, Robust Deep Learning for Network Intrusion Detection.

Joshua A. Wong, Alexander M. Berenbeim, David A. Bierbrauer, Nathaniel D. Bastian

Proceedings of the Winter Simulation Conference, 2023

Challenges and Opportunities in Neuro-Symbolic Composition of Foundation Models.

Susmit Jha, Anirban Roy, Adam D. Cobb, Alexander M. Berenbeim, Nathaniel D. Bastian

Proceedings of the IEEE Military Communications Conference, 2023