33 citations · 101 across the 12 of their papers we have counts for
12 papers
An Augmentation Strategy for Visually Rich Documents
Jing Xie, James B. Wendt, Yichao Zhou +2
Many business workflows require extracting important fields from form-like documents (e.g. bank statements, bills of lading, purchase orders, etc.). Recent techniques for automatin…
VRDU: A Benchmark for Visually-rich Document Understanding
Zilong Wang, Yichao Zhou, Wei Wei +2
Understanding visually-rich business documents to extract structured data and automate business workflows has been receiving attention both in academia and industry. Although recen…
Radically Lower Data-Labeling Costs for Visually Rich Document Extraction Models
Yichao Zhou, James B. Wendt, Navneet Potti +2
A key bottleneck in building automatic extraction models for visually rich documents like invoices is the cost of acquiring the several thousand high-quality labeled documents that…
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities
Chaobing Song, Zhengyuan Zhou, Yichao Zhou +2
The optimization problems associated with training generative adversarial neural networks can be largely reduced to certain {\em non-monotone} variational inequality problems (VIPs…
Simplified DOM Trees for Transferable Attribute Extraction from the Web
Yichao Zhou, Ying Sheng, Nguyen Vo +2
There has been a steady need to precisely extract structured knowledge from the web (i.e. HTML documents). Given a web page, extracting a structured object along with various attri…
Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference
Yichao Zhou, Yu Yan, Rujun Han +5
There has been a steady need in the medical community to precisely extract the temporal relations between clinical events. In particular, temporal information can facilitate a vari…
Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction
Rujun Han, Yichao Zhou, Nanyun Peng
Extracting event temporal relations is a critical task for information extraction and plays an important role in natural language understanding. Prior systems leverage deep learnin…
Learning to Create Better Ads: Generation and Ranking Approaches for Ad Creative Refinement
Shaunak Mishra, Manisha Verma, Yichao Zhou +2
In the online advertising industry, the process of designing an ad creative (i.e., ad text and image) requires manual labor. Typically, each advertiser launches multiple creatives…
"The Boating Store Had Its Best Sail Ever": Pronunciation-attentive Contextualized Pun Recognition
Yichao Zhou, Jyun-Yu Jiang, Jieyu Zhao +2
Humor plays an important role in human languages and it is essential to model humor when building intelligence systems. Among different forms of humor, puns perform wordplay for hu…
Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text Classification
Yichao Zhou, Jyun-Yu Jiang, Kai-Wei Chang +1
Adversarial attacks against machine learning models have threatened various real-world applications such as spam filtering and sentiment analysis. In this paper, we propose a novel…
Learning Gender-Neutral Word Embeddings
Jieyu Zhao, Yichao Zhou, Zeyu Li +2
Word embedding models have become a fundamental component in a wide range of Natural Language Processing (NLP) applications. However, embeddings trained on human-generated corpora…
Aztec: A Platform to Render Biomedical Software Findable, Accessible, Interoperable, and Reusable
Wei Wang, Brian Bleakley, Chelsea Ju +9
Precision medicine and health requires the characterization and phenotyping of biological systems and patient datasets using a variety of data formats. This scenario mandates the c…