AmbigNLG: Addressing Task Ambiguity in Instruction for NLG

arXiv:2402.17717v1 Announce Type: new
Abstract: In this study, we introduce AmbigNLG, a new task designed to tackle the challenge of task ambiguity in instructions for Natural Language Generation (NLG) tasks. Despite the impressive capabilities of Large Language Models (LLMs) in understanding and executing a wide range of tasks through natural language interaction, their performance is significantly hindered by the ambiguity present in real-world instructions. To address this, AmbigNLG seeks to identify and mitigate such ambiguities, aiming to refine instructions to …

abstract arxiv capabilities challenge cs.cl language language generation language models large language large language models llms natural natural language natural language generation nlg study tasks through type understanding