28 citations · 96 across the 21 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.CL2023★ 3 cited
Unified Demonstration Retriever for In-Context Learning
Xiaonan Li, Kai Lv, Hang Yan +6
In-context learning is a new learning paradigm where a language model conditions on a few input-output pairs (demonstrations) and a test input, and directly outputs the prediction.…
cs.CL2023
Candidate Soups: Fusing Candidate Results Improves Translation Quality for Non-Autoregressive Translation
Huanran Zheng, Wei Zhu, Pengfei Wang +1
Non-autoregressive translation (NAT) model achieves a much faster inference speed than the autoregressive translation (AT) model because it can simultaneously predict all tokens du…