667 citations · 811 across the 12 of their papers we have counts for
12 papers
WeLM: A Well-Read Pre-trained Language Model for Chinese
Hui Su, Xiao Zhou, Houjin Yu +5
Large Language Models pre-trained with self-supervised learning have demonstrated impressive zero-shot generalization capabilities on a wide spectrum of tasks. In this work, we pre…
Knowledge-enhanced Session-based Recommendation with Temporal Transformer
Rongzhi Zhang, Yulong Gu, Xiaoyu Shen +1
Recent research has achieved impressive progress in the session-based recommendation. However, information such as item knowledge and click time interval, which could be potentiall…
PatrickStar: Parallel Training of Pre-trained Models via Chunk-based Memory Management
Jiarui Fang, Zilin Zhu, Shenggui Li +4
The pre-trained model (PTM) is revolutionizing Artificial Intelligence (AI) technology. However, the hardware requirement of PTM training is prohibitively high, making it a game fo…
Neural Data-to-Text Generation with LM-based Text Augmentation
Ernie Chang, Xiaoyu Shen, Dawei Zhu +2
For many new application domains for data-to-text generation, the main obstacle in training neural models consists of a lack of training data. While usually large numbers of instan…
Diversifying Dialogue Generation with Non-Conversational Text
Hui Su, Xiaoyu Shen, Sanqiang Zhao +5
Neural network-based sequence-to-sequence (seq2seq) models strongly suffer from the low-diversity problem when it comes to open-domain dialogue generation. As bland and generic utt…
Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence
Xiaoyu Shen, Ernie Chang, Hui Su +2
The neural attention model has achieved great success in data-to-text generation tasks. Though usually excelling at producing fluent text, it suffers from the problem of informatio…