Anirud Ramani

Low-resource hallucination detection in LLMs on multi-task datasets via iterative pseudo-labeling using confidence thresholding and active learning

A lightweight, semi-supervised, and reproducible framework that achieves competitive performance without relying on resource-intensive models for hallucination detection across three natural language processing tasks, including machine translation, definition modeling, and paraphrase generation is presented.