667 citations · 843 across the 29 of their papers we have counts for
8 papers · 1 filter
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…
Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer
Yunyun Huang, Xiaoyu Shen, Chuanyi Li +2
Given the fact of a case, Legal Judgment Prediction (LJP) involves a series of sub-tasks such as predicting violated law articles, charges and term of penalty. We propose leveragin…
AST-Transformer: Encoding Abstract Syntax Trees Efficiently for Code Summarization
Ze Tang, Chuanyi Li, Jidong Ge +3
Code summarization aims to generate brief natural language descriptions for source code. As source code is highly structured and follows strict programming language grammars, its A…
Preventing Author Profiling through Zero-Shot Multilingual Back-Translation
David Ifeoluwa Adelani, Miaoran Zhang, Xiaoyu Shen +3
Documents as short as a single sentence may inadvertently reveal sensitive information about their authors, including e.g. their gender or ethnicity. Style transfer is an effective…
The SelectGen Challenge: Finding the Best Training Samples for Few-Shot Neural Text Generation
Ernie Chang, Xiaoyu Shen, Alex Marin +1
We propose a shared task on training instance selection for few-shot neural text generation. Large-scale pretrained language models have led to dramatic improvements in few-shot te…
On Training Instance Selection for Few-Shot Neural Text Generation
Ernie Chang, Xiaoyu Shen, Hui-Syuan Yeh +1
Large-scale pretrained language models have led to dramatic improvements in text generation. Impressive performance can be achieved by finetuning only on a small number of instance…
Learning Fine-grained Fact-Article Correspondence in Legal Cases
Jidong Ge, Yunyun huang, Xiaoyu Shen +2
Automatically recommending relevant law articles to a given legal case has attracted much attention as it can greatly release human labor from searching over the large database of…
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…