12 citations · 29 across the 8 of their papers we have counts for
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cs.CL2022
Explanation Regeneration via Information Bottleneck
Qintong Li, Zhiyong Wu, Lingpeng Kong +1
Explaining the black-box predictions of NLP models naturally and accurately is an important open problem in natural language generation. These free-text explanations are expected t…
cs.CL2022
Event Transition Planning for Open-ended Text Generation
Qintong Li, Piji Li, Wei Bi +3
Open-ended text generation tasks, such as dialogue generation and story completion, require models to generate a coherent continuation given limited preceding context. The open-end…
cs.CL2022★ 6 cited
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…