3 papers
cs.SE2026
SAGE: Tool-Augmented LLM Task Solving Strategies in Scalable Multi-Agent Environments
Robert K. Strehlow, Tobias Küster, Oskar F. Kupke +3
Large language models (LLMs) have proven to work well in question-answering scenarios, but real-world applications often require access to tools for live information or actuation.…
cs.CV2025
Streamlining the Development of Active Learning Methods in Real-World Object Detection
Moussa Kassem Sbeyti, Nadja Klein, Michelle Karg +2
Active learning (AL) for real-world object detection faces computational and reliability challenges that limit practical deployment. Developing new AL methods requires training mul…
cs.RO2025
APR-Transformer: Initial Pose Estimation for Localization in Complex Environments through Absolute Pose Regression
Srinivas Ravuri, Yuan Xu, Martin Ludwig Zehetner +2
Precise initialization plays a critical role in the performance of localization algorithms, especially in the context of robotics, autonomous driving, and computer vision. Poor loc…