157 citations · 551 across the 19 of their papers we have counts for
26 papers
Unsupervised Explanation Generation via Correct Instantiations
Sijie Cheng, Zhiyong Wu, Jiangjie Chen +3
While large pre-trained language models (PLM) have shown their great skills at solving discriminative tasks, a significant gap remains when compared with humans for explanation-rel…
An Empirical Revisiting of Linguistic Knowledge Fusion in Language Understanding Tasks
Changlong Yu, Tianyi Xiao, Lingpeng Kong +2
Though linguistic knowledge emerges during large-scale language model pretraining, recent work attempt to explicitly incorporate human-defined linguistic priors into task-specific…
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…
The Devil in Linear Transformer
Zhen Qin, XiaoDong Han, Weixuan Sun +4
Linear transformers aim to reduce the quadratic space-time complexity of vanilla transformers. However, they usually suffer from degraded performances on various tasks and corpus.…
Language Models Can See: Plugging Visual Controls in Text Generation
Yixuan Su, Tian Lan, Yahui Liu +5
Generative language models (LMs) such as GPT-2/3 can be prompted to generate text with remarkable quality. While they are designed for text-prompted generation, it remains an open…
Lexical Knowledge Internalization for Neural Dialog Generation
Zhiyong Wu, Wei Bi, Xiang Li +2
We propose knowledge internalization (KI), which aims to complement the lexical knowledge into neural dialog models. Instead of further conditioning the knowledge-grounded dialog (…