39 citations · 82 across the 19 of their papers we have counts for
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cs.IR2023★ 7 cited
Fine-Tuning LLaMA for Multi-Stage Text Retrieval
Xueguang Ma, Liang Wang, Nan Yang +2
The effectiveness of multi-stage text retrieval has been solidly demonstrated since before the era of pre-trained language models. However, most existing studies utilize models tha…
cs.IR2023★ 2 cited
Large Search Model: Redefining Search Stack in the Era of LLMs
Liang Wang, Nan Yang, Xiaolong Huang +3
Modern search engines are built on a stack of different components, including query understanding, retrieval, multi-stage ranking, and question answering, among others. These compo…
cs.CL2023★ 2 cited
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
Dawei Zhu, Nan Yang, Liang Wang +4
Large Language Models (LLMs) are trained with a pre-defined context length, restricting their use in scenarios requiring long inputs. Previous efforts for adapting LLMs to a longer…