Knowledge-enhanced Prompt Learning for Open-domain Commonsense Reasoning
Publication Date: 7/3/2024
Event: NEC Technical Journal, Special Issue on Revolutionizing Business Practices with Generative AI
Reference: Vol. 17, No. 2, pp 102-106, 2024
Authors: Xujiang Zhao, NEC Laboratories America, Inc.; Yanchi Liu, NEC Laboratories America, Inc.; Wei Cheng, NEC Laboratories America, Inc.; Mika Oishi, NEC Digital Business Platform Unit; Takao Osaki, NEC Digital Business Platform Unit; Katsushi Matsuda, NEC Digital Business Platform Unit; Haifeng Chen, NEC Laboratories America, Inc.
Abstract: Neural language models for commonsense reasoning often formulate the problem as a QA task and make predictions based on learned representations of language after fine-tuning. However, without providing any fine-tuning data and pre-defined answer candidates, can neural language models still answer commonsense reasoning questions only relying on external knowledge? In this work, we investigate a unique yet challenging problem-open-domain commonsense reasoning that aims to answer questions without providing any answer candidates and fine-tuning examples. A team comprising NECLA (NEC Laboratories America) and NEC Digital Business Platform Unit proposed method leverages neural language models to iteratively retrieve reasoning chains on the external knowledge base, which does not require task-specific supervision. The reasoning chains can help to identify the most precise answer to the commonsense question and its corresponding knowledge statements to justify the answer choice. This technology has proven its effectiveness in a diverse array of business domains.
Publication Link: https://www.nec.com/en/global/techrep/journal/g23/n02/g2302pa.html#anc-anchor-01