22 citations · 46 across the 18 of their papers we have counts for
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cs.CL2023★ 19 cited
Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering
Yike Wu, Nan Hu, Sheng Bi +4
Despite their competitive performance on knowledge-intensive tasks, large language models (LLMs) still have limitations in memorizing all world knowledge especially long tail knowl…
cs.CL2023
An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering
Nan Hu, Yike Wu, Guilin Qi +4
Large-scale pre-trained language models (PLMs) such as BERT have recently achieved great success and become a milestone in natural language processing (NLP). It is now the consensu…
cs.CL2023★ 22 cited
Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM Family
Yiming Tan, Dehai Min, Yu Li +4
ChatGPT is a powerful large language model (LLM) that covers knowledge resources such as Wikipedia and supports natural language question answering using its own knowledge. Therefo…