Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning

arXiv:2404.16807v1 Announce Type: new
Abstract: Generative Commonsense Reasoning (GCR) requires a model to reason about a situation using commonsense knowledge, while generating coherent sentences. Although the quality of the generated sentences is crucial, the diversity of the generation is equally important because it reflects the model's ability to use a range of commonsense knowledge facts. Large Language Models (LLMs) have shown proficiency in enhancing the generation quality across various tasks through in-context learning (ICL) using given examples without the need …

abstract arxiv commonsense context cs.cl diversity generated generative improving in-context learning knowledge language language models large language large language models quality reason reasoning type via while