198 citations · 236 across the 6 of their papers we have counts for
6 papers
A Data-Centric Framework for Composable NLP Workflows
Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu +15
Empirical natural language processing (NLP) systems in application domains (e.g., healthcare, finance, education) involve interoperation among multiple components, ranging from dat…
Automatic Event Salience Identification
Zhengzhong Liu, Chenyan Xiong, Teruko Mitamura +1
Identifying the salience (i.e. importance) of discourse units is an important task in language understanding. While events play important roles in text documents, little research e…
Graph-Based Decoding for Event Sequencing and Coreference Resolution
Zhengzhong Liu, Teruko Mitamura, Eduard Hovy
Events in text documents are interrelated in complex ways. In this paper, we study two types of relation: Event Coreference and Event Sequencing. We show that the popular tree-like…
Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling
Chenyan Xiong, Zhengzhong Liu, Jamie Callan +1
This paper presents a Kernel Entity Salience Model (KESM) that improves text understanding and retrieval by better estimating entity salience (importance) in documents. KESM repres…
Unsupervised Ranking Model for Entity Coreference Resolution
Xuezhe Ma, Zhengzhong Liu, Eduard Hovy
Coreference resolution is one of the first stages in deep language understanding and its importance has been well recognized in the natural language processing community. In this p…
Harnessing Deep Neural Networks with Logic Rules
Zhiting Hu, Xuezhe Ma, Zhengzhong Liu +2
Combining deep neural networks with structured logic rules is desirable to harness flexibility and reduce uninterpretability of the neural models. We propose a general framework ca…