151 citations · 498 across the 65 of their papers we have counts for
12 papers · 1 filter
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting
Chengyu Dong, Liyuan Liu, Jingbo Shang
We show that label noise exists in adversarial training. Such label noise is due to the mismatch between the true label distribution of adversarial examples and the label inherited…
Coarse2Fine: Fine-grained Text Classification on Coarsely-grained Annotated Data
Dheeraj Mekala, Varun Gangal, Jingbo Shang
Existing text classification methods mainly focus on a fixed label set, whereas many real-world applications require extending to new fine-grained classes as the number of samples…
BFClass: A Backdoor-free Text Classification Framework
Zichao Li, Dheeraj Mekala, Chengyu Dong +1
Backdoor attack introduces artificial vulnerabilities into the model by poisoning a subset of the training data via injecting triggers and modifying labels. Various trigger design…
LayoutReader: Pre-training of Text and Layout for Reading Order Detection
Zilong Wang, Yiheng Xu, Lei Cui +2
Reading order detection is the cornerstone to understanding visually-rich documents (e.g., receipts and forms). Unfortunately, no existing work took advantage of advanced deep lear…
Weakly Supervised Named Entity Tagging with Learnable Logical Rules
Jiacheng Li, Haibo Ding, Jingbo Shang +2
We study the problem of building entity tagging systems by using a few rules as weak supervision. Previous methods mostly focus on disambiguation entity types based on contexts and…
UCPhrase: Unsupervised Context-aware Quality Phrase Tagging
Xiaotao Gu, Zihan Wang, Zhenyu Bi +4
Identifying and understanding quality phrases from context is a fundamental task in text mining. The most challenging part of this task arguably lies in uncommon, emerging, and dom…
Unsupervised Deep Keyphrase Generation
Xianjie Shen, Yinghan Wang, Rui Meng +1
Keyphrase generation aims to summarize long documents with a collection of salient phrases. Deep neural models have demonstrated a remarkable success in this task, capable of predi…
News Meets Microblog: Hashtag Annotation via Retriever-Generator
Xiuwen Zheng, Dheeraj Mekala, Amarnath Gupta +1
Hashtag annotation for microblog posts has been recently formulated as a sequence generation problem to handle emerging hashtags that are unseen in the training set. The state-of-t…
"Average" Approximates "First Principal Component"? An Empirical Analysis on Representations from Neural Language Models
Zihan Wang, Chengyu Dong, Jingbo Shang
Contextualized representations based on neural language models have furthered the state of the art in various NLP tasks. Despite its great success, the nature of such representatio…
Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks
Xinyang Zhang, Chenwei Zhang, Luna Xin Dong +2
Text categorization is an essential task in Web content analysis. Considering the ever-evolving Web data and new emerging categories, instead of the laborious supervised setting, i…
Data Quality Matters For Adversarial Training: An Empirical Study
Chengyu Dong, Liyuan Liu, Jingbo Shang
Multiple intriguing problems are hovering in adversarial training, including robust overfitting, robustness overestimation, and robustness-accuracy trade-off. These problems pose g…
Sensei: Self-Supervised Sensor Name Segmentation
Jiaman Wu, Dezhi Hong, Rajesh Gupta +1
A sensor name, typically an alphanumeric string, encodes the key context (e.g., function and location) of a sensor needed for deploying smart building applications. Sensor names, h…