Large Language Models

Our paper Language Models as Reasoners for Out-of-Distribution Detection has been presented at the Workshop on AI Safety Engineering (WAISE) 2024 and recieved the best paper award by popular vote. It constitutes a basic extension of our idea of Out-of-Distribution Detection with Logical Reasoning, where we replaced the prolog-based reasoning component with a LLM. Abstract Deep neural networks (DNNs) are prone to making wrong predictions with high confidence for data that does not stem from their training distribution.