9 citations · 21 across the 9 of their papers we have counts for
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cs.CL2023★ 9 cited
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
Zhenyu Li, Sunqi Fan, Yu Gu +5
Knowledge base question answering (KBQA) is a critical yet challenging task due to the vast number of entities within knowledge bases and the diversity of natural language question…
cs.CL2023★ 9 cited
Can LLMs like GPT-4 outperform traditional AI tools in dementia diagnosis? Maybe, but not today
Zhuo Wang, Rongzhen Li, Bowen Dong +8
Recent investigations show that large language models (LLMs), specifically GPT-4, not only have remarkable capabilities in common Natural Language Processing (NLP) tasks but also e…
cs.CL2023★ 1 cited
Bridging the Language Gap: Knowledge Injected Multilingual Question Answering
Zhichao Duan, Xiuxing Li, Zhengyan Zhang +3
Question Answering (QA) is the task of automatically answering questions posed by humans in natural languages. There are different settings to answer a question, such as abstractiv…