Yuanbin Wu

A Learning Error Analysis for Structured Prediction with Approximate Inference

2017 · Neural Information Processing Systems

In this work, we try to understand the differences between exact and approximate inference algorithms in structured prediction. We compare the estimation and approximation error of both underestimate and overestimate models. The result shows that, …

The CoNLL-2013 Shared Task on Grammatical Error Correction

2025 · arXiv (Cornell University)

The CoNLL-2013 shared task was devoted to grammatical error correction. In this paper, we give the task definition, present the data sets, and describe the evaluation metric and scorer used in the shared task. We …

Boosting the Speed of Entity Alignment 10 ×: Dual Attention Matching Network with Normalized Hard Sample Mining

2021

Seeking the equivalent entities among multi-source Knowledge Graphs (KGs) is the pivotal step to KGs integration, also known as entity alignment (EA). However, most existing EA methods are inefficient and poor in scalability. A recent …

Explore Unsupervised Structures in Pretrained Models for Relation Extraction

2022

Syntactic trees have been widely applied in relation extraction (RE). However, since parsing qualities are not stable on different text domains and a pre-defined grammar may not well fit the target relation schema, the introduction …

Graph-based Dependency Parsing with Graph Neural Networks

2019

We investigate the problem of efficiently incorporating high-order features into neural graph-based dependency parsing. Instead of explicitly extracting high-order features from intermediate parse trees, we develop a more powerful dependency tree node representation which captures …