183 citations · 1.2k across the 49 of their papers we have counts for
6 papers · 1 filter
On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark
Hao Sun, Guangxuan Xu, Jiawen Deng +6
Dialogue safety problems severely limit the real-world deployment of neural conversational models and have attracted great research interests recently. However, dialogue safety pro…
EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training
Hao Zhou, Pei Ke, Zheng Zhang +11
Although pre-trained language models have remarkably enhanced the generation ability of dialogue systems, open-domain Chinese dialogue systems are still limited by the dialogue dat…
CPM-2: Large-scale Cost-effective Pre-trained Language Models
Zhengyan Zhang, Yuxian Gu, Xu Han +16
In recent years, the size of pre-trained language models (PLMs) has grown by leaps and bounds. However, efficiency issues of these large-scale PLMs limit their utilization in real-…
JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
Pei Ke, Haozhe Ji, Yu Ran +5
Existing pre-trained models for knowledge-graph-to-text (KG-to-text) generation simply fine-tune text-to-text pre-trained models such as BART or T5 on KG-to-text datasets, which la…
NAST: A Non-Autoregressive Generator with Word Alignment for Unsupervised Text Style Transfer
Fei Huang, Zikai Chen, Chen Henry Wu +3
Autoregressive models have been widely used in unsupervised text style transfer. Despite their success, these models still suffer from the content preservation problem that they us…
A Semantic-based Method for Unsupervised Commonsense Question Answering
Yilin Niu, Fei Huang, Jiaming Liang +3
Unsupervised commonsense question answering is appealing since it does not rely on any labeled task data. Among existing work, a popular solution is to use pre-trained language mod…