4 papers
Evaluating Multimodal LLMs as Generalist Vision-Language-Action Agents for Drone Control: Commanding, Approaching, Tracking and Searching
Jaewoo Park, Minyoung Lee, Sukmin Seo +11
Multimodal large language models (MLLMs) are increasingly used to make decisions for drones, but existing evaluations are mostly limited to simulation, to a single drone, and to ta…
Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models
Geewook Kim, Hodong Lee, Daehee Kim +7
Recent advances in Large Language Models (LLMs) have stimulated a surge of research aimed at extending their applications to the visual domain. While these models exhibit promise i…
Supervised Contrastive ResNet and Transfer Learning for the In-vehicle Intrusion Detection System
Thien-Nu Hoang, Daehee Kim
High-end vehicles have been furnished with a number of electronic control units (ECUs), which provide upgrading functions to enhance the driving experience. The controller area net…
Detecting In-vehicle Intrusion via Semi-supervised Learning-based Convolutional Adversarial Autoencoders
Thien-Nu Hoang, Daehee Kim
With the development of autonomous vehicle technology, the controller area network (CAN) bus has become the de facto standard for an in-vehicle communication system because of its…