Proceedings of the 2018 Conference of the North
Modelling Natural Language, Programs, and their Intersection (N18-6)
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| Challenge: | a tutorial will explore the intersection of programming and natural language to make this goal a reality . |
| Approach: | This tutorial will focus on machine learning models of programs and natural language . it will discuss similarities and differences between programming and natural languages . |
| Outcome: | This tutorial will discuss the intersection of programming and natural language . it will cover automatic explanation of programs in natural language and automatic generation of programs from natural language specifications . |
Deep Learning Approaches to Text Production (N18-6)
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| Challenge: | Text production is a key component of many NLP applications . Claire Gardent is based in France and is pursuing research in text production . |
| Approach: | This tutorial will cover the fundamentals and state-of-the-art research on neural models for text production. |
| Outcome: | This tutorial will cover the fundamentals and the state-of-the-art research on neural models for text production. |
Scalable Construction and Reasoning of Massive Knowledge Bases (N18-6)
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| Challenge: | Existing knowledge mining systems assume abundant human annotations for training high quality machine learning models, which is impractical when trying to deploy IE systems to a broad range of domains, settings and languages. |
| Approach: | They introduce how to extract structured facts from text corpora to construct knowledge bases. |
| Outcome: | The proposed methods are weakly-supervised and domain-independent for knowledge base construction across various domains. |
The interplay between lexical resources and Natural Language Processing (N18-6)
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| Challenge: | linguistic, world and common sense knowledge is an important research area, but processing and storing it in lexical resources is not a straightforward task. |
| Approach: | They propose to use NLP methods to help process of constructing and enriching lexical resources and the use of lexicals for improving NLP applications. |
| Outcome: | The proposed approach aims to speed up and/or ease up the process of resource curation and enrichment. |
Socially Responsible NLP (N18-6)
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| Challenge: | This tutorial will provide an overview of ethical research tools and ethical implications of language technologies. |
| Approach: | This tutorial will provide an overview of ethical research and practical examples . it will discuss ethical tools to ensure data, algorithms, and models are socially responsible . |
| Outcome: | This tutorial will provide an overview of ethical research tools and methods . it will discuss philosophical foundations of ethical work along with state of the art techniques . |
Deep Learning for Conversational AI (N18-6)
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| Challenge: | Spoken Dialogue Systems (SDS) have great commercial potential . the advent of deep learning has led to significant advances in this area of NLP research . |
| Approach: | This tutorial will introduce researchers to the pipeline framework for modelling goal-oriented dialogue systems. |
| Outcome: | This tutorial will familiarise researchers with the latest advances in spoken dialogue systems . the aim of the course is to encourage dialogue research in the NLP community . |