24 citations · 75 across the 24 of their papers we have counts for
4 papers · 1 filter
Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and Ordering
Zhiyong Wu, Yaoxiang Wang, Jiacheng Ye +1
Despite the surprising few-shot performance of in-context learning (ICL), it is still a common practice to randomly sample examples to serve as context. This paper advocates a new…
ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback
Jiacheng Ye, Jiahui Gao, Jiangtao Feng +3
Recently, dataset-generation-based zero-shot learning has shown promising results by training a task-specific model with a dataset synthesized from large pre-trained language model…
Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning
Jiahui Gao, Renjie Pi, Yong Lin +7
There is a rising interest in further exploring the zero-shot learning potential of large pre-trained language models (PLMs). A new paradigm called data-generation-based zero-shot…
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Jiacheng Ye, Jiahui Gao, Qintong Li +5
There is a growing interest in dataset generation recently due to the superior generative capacity of large pre-trained language models (PLMs). In this paper, we study a flexible a…