Temporal Knowledge Question Answering via Abstract Reasoning Induction

arXiv:2311.09149v2 Announce Type: replace
Abstract: In this study, we address the challenge of enhancing temporal knowledge reasoning in Large Language Models (LLMs). LLMs often struggle with this task, leading to the generation of inaccurate or misleading responses. This issue mainly arises from their limited ability to handle evolving factual knowledge and complex temporal logic. To overcome these limitations, we propose Abstract Reasoning Induction (ARI) framework, which divides temporal reasoning into two distinct phases: Knowledge-agnostic and Knowledge-based. This framework offers factual …

abstract arxiv cs.ai cs.cl knowledge question question answering reasoning replace temporal type via