3 papers
cs.LG2026
Four Ways to Grow a Classifier and Why One of Them Cannot Learn
Cagri Temel
Constructive classifiers add structure while they train: a level to a tree, a unit to a hidden layer, a split at a leaf. This paper asks what each of four such growth decisions buy…
cs.RO2026
CT-SAFR: Safe and Interpretable Chain-of-Thought Reasoning for Autonomous Robots: A Multi-Layered Verification Framework for Trustworthy AI-Driven Robotic Decision Making
Cagri Temel
Chain-of-Thought (CoT) prompting enables LLMs to perform explicit, step-by-step reasoning, creating opportunities for sophisticated autonomous robots. However, recent research reve…
cs.RO2026
Towards Trustworthy Autonomous Robots: An Explainable AI-Based Decision Framework
Cagri Temel
Autonomous robots powered by deep learning face a fundamental auditability challenge: when incidents occur, investigators cannot reconstruct why the system made specific decisions.…