58 citations · 88 across the 9 of their papers we have counts for
9 papers
Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation
Ali Mousavi, Xin Zhan, He Bai +9
Datasets that pair Knowledge Graphs (KG) and text together (KG-T) can be used to train forward and reverse neural models that generate text from KG and vice versa. However models t…
Growing and Serving Large Open-domain Knowledge Graphs
Ihab F. Ilyas, JP Lacerda, Yunyao Li +5
Applications of large open-domain knowledge graphs (KGs) to real-world problems pose many unique challenges. In this paper, we present extensions to Saga our platform for continuou…
PriMeSRL-Eval: A Practical Quality Metric for Semantic Role Labeling Systems Evaluation
Ishan Jindal, Alexandre Rademaker, Khoi-Nguyen Tran +4
Semantic role labeling (SRL) identifies the predicate-argument structure in a sentence. This task is usually accomplished in four steps: predicate identification, predicate sense d…
TableLab: An Interactive Table Extraction System with Adaptive Deep Learning
Nancy Xin Ru Wang, Douglas Burdick, Yunyao Li
Table extraction from PDF and image documents is a ubiquitous task in the real-world. Perfect extraction quality is difficult to achieve with one single out-of-box model due to (1)…
Improved Semantic Role Labeling using Parameterized Neighborhood Memory Adaptation
Ishan Jindal, Ranit Aharonov, Siddhartha Brahma +2
Deep neural models achieve some of the best results for semantic role labeling. Inspired by instance-based learning that utilizes nearest neighbors to handle low-frequency context-…
CLAR: A Cross-Lingual Argument Regularizer for Semantic Role Labeling
Ishan Jindal, Yunyao Li, Siddhartha Brahma +1
Semantic role labeling (SRL) identifies predicate-argument structure(s) in a given sentence. Although different languages have different argument annotations, polyglot training, th…
HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop
Yiwei Yang, Eser Kandogan, Yunyao Li +2
While the role of humans is increasingly recognized in machine learning community, representation of and interaction with models in current human-in-the-loop machine learning (HITL…
Low-resource Deep Entity Resolution with Transfer and Active Learning
Jungo Kasai, Kun Qian, Sairam Gurajada +2
Entity resolution (ER) is the task of identifying different representations of the same real-world entities across databases. It is a key step for knowledge base creation and text…
Bridging the Semantic Gap with SQL Query Logs in Natural Language Interfaces to Databases
Christopher Baik, H. V. Jagadish, Yunyao Li
A critical challenge in constructing a natural language interface to database (NLIDB) is bridging the semantic gap between a natural language query (NLQ) and the underlying data. T…