3 citations · 7 across the 11 of their papers we have counts for
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cs.IR2024
On the Role of Long-tail Knowledge in Retrieval Augmented Large Language Models
Dongyang Li, Junbing Yan, Taolin Zhang +5
Retrieval augmented generation (RAG) exhibits outstanding performance in promoting the knowledge capabilities of large language models (LLMs) with retrieved documents related to us…
cs.CL2024
TRELM: Towards Robust and Efficient Pre-training for Knowledge-Enhanced Language Models
Junbing Yan, Chengyu Wang, Taolin Zhang +5
KEPLMs are pre-trained models that utilize external knowledge to enhance language understanding. Previous language models facilitated knowledge acquisition by incorporating knowled…
cs.CL2024★ 3 cited
Do Large Language Models Understand Logic or Just Mimick Context?
Junbing Yan, Chengyu Wang, Jun Huang +1
Over the past few years, the abilities of large language models (LLMs) have received extensive attention, which have performed exceptionally well in complicated scenarios such as l…