41 citations · 60 across the 5 of their papers we have counts for
11 papers · 1 filter
CAPT: Contrastive Pre-Training for Learning Denoised Sequence Representations
Fuli Luo, Pengcheng Yang, Shicheng Li +2
Pre-trained self-supervised models such as BERT have achieved striking success in learning sequence representations, especially for natural language processing. These models typica…
Inductively Representing Out-of-Knowledge-Graph Entities by Optimal Estimation Under Translational Assumptions
Damai Dai, Hua Zheng, Fuli Luo +3
Conventional Knowledge Graph Completion (KGC) assumes that all test entities appear during training. However, in real-world scenarios, Knowledge Graphs (KG) evolve fast with out-of…
Visual Agreement Regularized Training for Multi-Modal Machine Translation
Pengcheng Yang, Boxing Chen, Pei Zhang +1
Multi-modal machine translation aims at translating the source sentence into a different language in the presence of the paired image. Previous work suggests that additional visual…
Pun-GAN: Generative Adversarial Network for Pun Generation
Fuli Luo, Shunyao Li, Pengcheng Yang +4
In this paper, we focus on the task of generating a pun sentence given a pair of word senses. A major challenge for pun generation is the lack of large-scale pun corpus to guide th…
Key Fact as Pivot: A Two-Stage Model for Low Resource Table-to-Text Generation
Shuming Ma, Pengcheng Yang, Tianyu Liu +3
Table-to-text generation aims to translate the structured data into the unstructured text. Most existing methods adopt the encoder-decoder framework to learn the transformation, wh…
A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer
Fuli Luo, Peng Li, Jie Zhou +4
Unsupervised text style transfer aims to transfer the underlying style of text but keep its main content unchanged without parallel data. Most existing methods typically follow two…