Search Results for author: Yunyao Li

Found 34 papers, 5 papers with code

Learning Structured Representations of Entity Names using ActiveLearning and Weak Supervision

no code implementations EMNLP 2020 Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa

Structured representations of entity names are useful for many entity-related tasks such as entity normalization and variant generation.

Active Learning

LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking

no code implementations ACL 2021 Hang Jiang, Sairam Gurajada, Qiuhao Lu, Sumit Neelam, Lucian Popa, Prithviraj Sen, Yunyao Li, Alexander Gray

Entity linking (EL), the task of disambiguating mentions in text by linking them to entities in a knowledge graph, is crucial for text understanding, question answering or conversational systems.

Entity Linking Question Answering

Deep Learning on Graphs for Natural Language Processing

no code implementations NAACL 2021 Lingfei Wu, Yu Chen, Heng Ji, Yunyao Li

Due to its great power in modeling non-Euclidean data like graphs or manifolds, deep learning on graph techniques (i. e., Graph Neural Networks (GNNs)) have opened a new door to solving challenging graph-related NLP problems.

graph construction Graph Representation Learning +8

TableLab: An Interactive Table Extraction System with Adaptive Deep Learning

no code implementations16 Feb 2021 Nancy Xin Ru Wang, Douglas Burdick, Yunyao Li

Perfect extraction quality is difficult to achieve with one single out-of-box model due to (1) the wide variety of table styles, (2) the lack of training data representing this variety and (3) the inherent ambiguity and subjectivity of table definitions between end-users.

Table Extraction

CLAR: A Cross-Lingual Argument Regularizer for Semantic Role Labeling

no code implementations Findings of the Association for Computational Linguistics 2020 Ishan Jindal, Yunyao Li, Siddhartha Brahma, Huaiyu Zhu

Although different languages have different argument annotations, polyglot training, the idea of training one model on multiple languages, has previously been shown to outperform monolingual baselines, especially for low resource languages.

Semantic Role Labeling

Learning Structured Representations of Entity Names using Active Learning and Weak Supervision

1 code implementation EMNLP 2020 Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa

Structured representations of entity names are useful for many entity-related tasks such as entity normalization and variant generation.

Active Learning

Jennifer for COVID-19: An NLP-Powered Chatbot Built for the People and by the People to Combat Misinformation

no code implementations ACL 2020 Yunyao Li, Gr, Tyrone ison, Patricia Silveyra, Ali Douraghy, Xinyu Guan, Thomas Kieselbach, Chengkai Li, Haiqi Zhang

Just as SARS-CoV-2, a new form of coronavirus continues to infect a growing number of people around the world, harmful misinformation about the outbreak also continues to spread.

Chatbot Misinformation

Answering Complex Questions by Combining Information from Curated and Extracted Knowledge Bases

no code implementations WS 2020 Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H. Jagadish

Knowledge-based question answering (KB{\_}QA) has long focused on simple questions that can be answered from a single knowledge source, a manually curated or an automatically extracted KB.

Question Answering

Towards Universal Semantic Representation

no code implementations WS 2019 Huaiyu Zhu, Yunyao Li, Laura Chiticariu

Natural language understanding at the semantic level and independent of language variations is of great practical value.

Natural Language Understanding Semantic Role Labeling

HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop

no code implementations ACL 2019 Yiwei Yang, Eser Kandogan, Yunyao Li, Walter S. Lasecki, Prithviraj Sen

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-ML) approaches are too low-level and far-removed from human's conceptual models.

Low-resource Deep Entity Resolution with Transfer and Active Learning

no code implementations ACL 2019 Jungo Kasai, Kun Qian, Sairam Gurajada, Yunyao Li, Lucian Popa

Recent adaptation of deep learning methods for ER mitigates the need for dataset-specific feature engineering by constructing distributed representations of entity records.

Active Learning Entity Resolution +2

DIMSIM: An Accurate Chinese Phonetic Similarity Algorithm Based on Learned High Dimensional Encoding

1 code implementation CONLL 2018 Min Li, Marina Danilevsky, Sara Noeman, Yunyao Li

Phonetic similarity algorithms identify words and phrases with similar pronunciation which are used in many natural language processing tasks.

Spelling Correction

SystemT: Declarative Text Understanding for Enterprise

no code implementations NAACL 2018 Laura Chiticariu, Marina Danilevsky, Yunyao Li, Frederick Reiss, Huaiyu Zhu

The rise of enterprise applications over unstructured and semi-structured documents poses new challenges to text understanding systems across multiple dimensions.

Document Classification Entity Extraction using GAN +4

Multilingual Information Extraction with PolyglotIE

no code implementations COLING 2016 Alan Akbik, Laura Chiticariu, Marina Danilevsky, Yonas Kbrom, Yunyao Li, Huaiyu Zhu

We present PolyglotIE, a web-based tool for developing extractors that perform Information Extraction (IE) over multilingual data.

Semantic Parsing

K-SRL: Instance-based Learning for Semantic Role Labeling

no code implementations COLING 2016 Alan Akbik, Yunyao Li

To overcome this challenge, we propose the use of instance-based learning that performs no explicit generalization, but rather extrapolates predictions from the most similar instances in the training data.

Machine Translation Question Answering +1

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