3 citations · 8 across the 6 of their papers we have counts for
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cs.CL2022★ 3 cited
FewFedWeight: Few-shot Federated Learning Framework across Multiple NLP Tasks
Weilong Dong, Xinwei Wu, Junzhuo Li +3
Massively multi-task learning with large language models has recently made substantial progress on few-shot generalization. However, this is usually performed in a centralized lear…
cs.CL2022
NAPG: Non-Autoregressive Program Generation for Hybrid Tabular-Textual Question Answering
Tengxun Zhang, Hongfei Xu, Josef van Genabith +2
Hybrid tabular-textual question answering (QA) requires reasoning from heterogeneous information, and the types of reasoning are mainly divided into numerical reasoning and span ex…
cs.CL2022★ 1 cited
Unsupervised and Few-shot Parsing from Pretrained Language Models
Zhiyuan Zeng, Deyi Xiong
Pretrained language models are generally acknowledged to be able to encode syntax [Tenney et al., 2019, Jawahar et al., 2019, Hewitt and Manning, 2019]. In this article, we propose…