333 citations · 441 across the 12 of their papers we have counts for
12 papers
On the chromatic number of some ()-free graphs
Rui Li, Jinfeng Li, Di Wu
A hereditary class of graphs is {\em -bounded} if there is a {\em -binding function}, say , such that for every , where …
A tight linear chromatic bound for ()-free graphs
Rui Li, Jinfeng Li, Di Wu
For two vertex disjoint graphs and , we use to denote the graph with vertex set and edge set , and use to denote the graph wit…
Optimal chromatic bound for (, house)-free graphs
Rui Li, Di Wu, Jinfeng Li
Let and be two vertex disjoint graphs. The {\em union} is the graph with and . We use to denote a {\em…
FairRec: Fairness Testing for Deep Recommender Systems
Huizhong Guo, Jinfeng Li, Jingyi Wang +5
Deep learning-based recommender systems (DRSs) are increasingly and widely deployed in the industry, which brings significant convenience to people's daily life in different ways.…
RoChBert: Towards Robust BERT Fine-tuning for Chinese
Zihan Zhang, Jinfeng Li, Ning Shi +6
Despite of the superb performance on a wide range of tasks, pre-trained language models (e.g., BERT) have been proved vulnerable to adversarial texts. In this paper, we present RoC…
Backdoor Pre-trained Models Can Transfer to All
Lujia Shen, Shouling Ji, Xuhong Zhang +6
Pre-trained general-purpose language models have been a dominating component in enabling real-world natural language processing (NLP) applications. However, a pre-trained model wit…