Communications of the ACM

Formal Reasoning Meets LLMs: Toward AI for Mathematics and Verification

Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.
Rochester Institute of Technology

Researchers develop new method for predicting chaos

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

AI model uses molecular energy to predict the most stable atom arrangements

Whether a smartphone battery lasts longer or a new drug can be developed to treat incurable diseases depends on how stably ...
Frontiers

Signal Processing for Representation Learning: Theoretical Foundations and Emerging Applications

Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...
IEEE

Hybrid Tree-Based Machine Learning Models for State-of-Charge and Core Temperature Estimation in EV Batteries

Abstract: Accurate estimation of State-of-Charge (SoC) and core temperature is fundamental to optimizing the performance, safety, and longevity of Lithium-Ion Batteries (LiBs), particularly in ...
IEEE

Enhancing the Sustainability of Machine Learning-Based Malware Detection Techniques for Android Applications

Abstract: The rapid increase in smartphone usage has led to a corresponding rise in malicious Android applications, making it important to develop efficient and sustainable malware detection methods ...