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LM4OPT: Unveiling the Potential of Large Language Models in Formulating Mathematical Optimization Problems
In the rapidly evolving field of natural language processing, the translation of linguistic descriptions into mathematical formulation of optimization problems presents a formidable challenge, demanding intricate understanding and processing capabilities from Large Language Models (LLMs).
Linguistic Intelligence in Large Language Models for Telecommunications
Despite their evaluation across a multitude of analytical and reasoning tasks in various scientific domains, a comprehensive exploration of their knowledge and understanding within the realm of natural language tasks in the telecommunications domain is still needed.
A Multi-faceted Semi-Synthetic Dataset for Automated Cyberbullying Detection
This paper provides a description of an extensive semi-synthetic cyberbullying dataset that incorporates all of the essential aspects of cyberbullying, including aggression, repetition, peer relationships, and intent to harm.
Utilizing Deep Learning to Identify Drug Use on Twitter Data
The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users.
Algorithms for Optimizing Fleet Scheduling of Air Ambulances
Proper scheduling of air assets can be the difference between life and death for a patient.
Algorithms for Optimizing Fleet Staging of Air Ambulances
These proved superior as the number of test missions increased, while also maintaining the same minimized distance.
A Comprehensive Survey on the Ambulance Routing and Location Problems
Much of the current work has simply been on modifying existing systems through simulation to achieve a more acceptable result.
