Zero-shot and few-shot learning for 3D Object Detection Using Language Model

This research introduces a novel approach for 3D object detection utilizing language models, with a particular focus on addressing the challenges that have been encountered in the autonomous vehicle domain. The primary objective revolves around addressing the constraints associated with object detection models that rely heavily on labeled data...

Chemical reaction completion: a hybrid rule-based and language model-based approach

Large chemical reaction databases often suffer from incompleteness, such as missing molecules or stoichiometric information. Concurrently, numerous computational models are being developed in predictive chemistry that rely on reaction databases and would hugely benefit from complete reaction equations. Also, research in sustainable chemistry...

Logs to the Rescue: Creating meaningful representations from log files for Anomaly Detection

This thesis offers a comprehensive exploration of log-based anomaly detection within the domain of cybersecurity incident response. The research describes a different approach and explores relevant log features for language model training, experimentation with different language models and training methodologies, and the investigation of the...