5 papers
Autonomous Research for Open-Ended Problems: A Case Study on Telecom Ticket Retrieval
Junghyun Min, Huseyin Uzunalioglu, Mohamed Trabelsi
Recent breakthroughs in LLM-based systems and their abilities in problem solving and coding have allowed progress in the AI for Science paradigm, potentially replacing human roles…
ASTRA - Agentic System for Ticket Resolution and Analysis
Shashidhar Reddy Javaji, Mohamed Trabelsi, Jin Cao +1
Technical operations teams resolve large volumes of incidents by synthesizing fragmented evidence from ticket text, historical cases, system logs, and technical documentation. Exis…
TeleDoCTR: Domain-Specific and Contextual Troubleshooting for Telecommunications
Mohamed Trabelsi, Huseyin Uzunalioglu
Ticket troubleshooting refers to the process of analyzing and resolving problems that are reported through a ticketing system. In large organizations offering a wide range of servi…
Time Series Language Model for Descriptive Caption Generation
Mohamed Trabelsi, Aidan Boyd, Jin Cao +1
The automatic generation of representative natural language descriptions for observable patterns in time series data enhances interpretability, simplifies analysis and increases cr…
Increasing Interpretability of Neural Networks By Approximating Human Visual Saliency
Aidan Boyd, Mohamed Trabelsi, Huseyin Uzunalioglu +1
Understanding specifically where a model focuses on within an image is critical for human interpretability of the decision-making process. Deep learning-based solutions are prone t…