A new parameter adaptation method for Genetic Algorithms and Ant Colony Optimization algorithms. - Adam Byerly; Alexander Uskov (EIT, 2016)

OpenCL and CUDA software implementations of encryption/decryption algorithms for IPsec VPNs. - Colleen Heinemann; Sai Shankar Chaduvu; Adam Byerly; Alexander Uskov (EIT, 2016)

Optimal Design of IPsec-Based Mobile Virtual Private Networks for Secure Transfer of Multimedia Data. - Alexander V. Uskov; Natalia A. Serdyukova; Vladimir I. Serdyukov; Adam Byerly; Colleen Heinemann (IIMSS, 2016)

A New Method of Exploring a Range of Genetic Parameters During the Execution of a Genetic Algorithm. - Adam Byerly; Alexander Uskov (Int. J. Comput. Sci. Appl., 2016)

Advanced Encryption Standard Analysis with Multimedia Data on Intel® AES-NI Architecture. - Alexander Uskov; Adam Byerly; Colleen Heinemann (Int. J. Comput. Sci. Appl., 2016)

A novel approach to avoiding early stagnation in Ant Colony Optimization algorithms. - Adam Byerly; Alexander Uskov (Int. J. Knowl. Based Intell. Eng. Syst., 2016)

Multi objective optimization of VPN design by linear programming with risks models. - Alexander Uskov; Nataliya Serdyukova; Vladimir I. Serdyukov; Colleen Heinemann; Adam Byerly (Int. J. Knowl. Based Intell. Eng. Syst., 2016)

Machine Learning-based Predictive Analytics of Student Academic Performance in STEM Education. - Vladimir L. Uskov; Jeffrey P. Bakken; Adam Byerly; Ashok Shah (EDUCON, 2019)

Analysis of Region-Based Integral Calculus Problems. - Chris Alvin; Adam Byerly (FLAIRS, 2020)

A Branching and Merging Convolutional Network with Homogeneous Filter Capsules. - Adam Byerly; Tatiana Kalganova; Ian Dear (CoRR, 2020)

On the Importance of Capturing a Sufficient Diversity of Perspective for the Classification of Micro-PCBs. - Adam Byerly; Tatiana Kalganova; Anthony J. Grichnik (KES-IDT, 2021)

Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks. - Adam Byerly; Tatiana Kalganova (IEEE Access, 2021)

No routing needed between capsules. - Adam Byerly; Tatiana Kalganova; Ian Dear (Neurocomputing, 2021)

The Current State of the Art in Deep Learning for Image Classification: A Review. - Adam Byerly; Tatiana Kalganova; Richard Ott (SAI (2), 2022)

Class Density and Dataset Quality in High-Dimensional, Unstructured Data. - Adam Byerly; Tatiana Kalganova (CoRR, 2022)

Towards an Analytical Definition of Sufficient Data. - Adam Byerly; Tatiana Kalganova (SN Comput. Sci., 2023)

Insights into LLM Long-Context Failures: When Transformers Know but Don't Tell. - Muhan Gao; Taiming Lu; Kuai Yu; Adam Byerly; Daniel Khashabi (EMNLP (Findings), 2024)

Tur[k]ingBench: A Challenge Benchmark for Web Agents. - Kevin Xu; Yeganeh Kordi; Kate Sanders 002; Yizhong Wang; Adam Byerly; Jack Zhang; Benjamin Van Durme; Daniel Khashabi (CoRR, 2024)

How Effective Is Self-Consistency for Long-Context Problems? - Adam Byerly; Daniel Khashabi (CoRR, 2024)

TurkingBench: A Challenge Benchmark for Web Agents. - Kevin Xu; Yeganeh Kordi; Tanay Nayak; Adi Asija; Yizhong Wang; Kate Sanders 002; Adam Byerly; Jingyu Zhang; Benjamin Van Durme; Daniel Khashabi (NAACL (Long Papers), 2025)