Automatic Question-Answer Generation for Long-Tail Knowledge

arXiv:2403.01382v1 Announce Type: new
Abstract: Pretrained Large Language Models (LLMs) have gained significant attention for addressing open-domain Question Answering (QA). While they exhibit high accuracy in answering questions related to common knowledge, LLMs encounter difficulties in learning about uncommon long-tail knowledge (tail entities). Since manually constructing QA datasets demands substantial human resources, the types of existing QA datasets are limited, leaving us with a scarcity of datasets to study the performance of LLMs on tail entities. In this paper, we …

abstract accuracy arxiv attention cs.cl datasets domain human human resources knowledge language language models large language large language models llms question question answering questions resources type types