SHROOM-INDElab at SemEval-2024 Task 6: Zero- and Few-Shot LLM-Based Classification for Hallucination Detection

arXiv:2404.03732v1 Announce Type: new
Abstract: We describe the University of Amsterdam Intelligent Data Engineering Lab team's entry for the SemEval-2024 Task 6 competition. The SHROOM-INDElab system builds on previous work on using prompt programming and in-context learning with large language models (LLMs) to build classifiers for hallucination detection, and extends that work through the incorporation of context-specific definition of task, role, and target concept, and automated generation of examples for use in a few-shot prompting approach. The resulting system achieved …

abstract arxiv build classification classifiers competition context cs.ai cs.cl data data engineering detection engineering few-shot hallucination in-context learning intelligent lab language language models large language large language models llm llms programming prompt team type university work