Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts
Interpretability and Analysis in Neural NLP (2020.acl-tutorials)
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| Challenge: | a tutorial aims to introduce the nascent field of interpretability and analysis of neural networks in NLP . |
| Approach: | This tutorial will introduce the nascent field of interpretability and analysis of neural networks in NLP. |
| Outcome: | This tutorial will introduce the nascent field of interpretability and analysis of neural networks in NLP. |
Integrating Ethics into the NLP Curriculum (2020.acl-tutorials)
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| Challenge: | a tutorial aims to teach students how to ethically apply NLP . the tutorial will focus on examples for university classrooms, but ideas can extend to company-internal workshops or tutorials in a variety of organizations. |
| Approach: | a tutorial aims to empower NLP researchers and practitioners to teach others about ethical NLP . the tutorial will focus on examples for university classrooms, but ideas can extend to company-internal workshops . |
| Outcome: | a tutorial aims to teach students how to ethically apply NLP techniques . the tutorial will include examples for university classrooms, but ideas can extend to company-internal workshops . |
Achieving Common Ground in Multi-modal Dialogue (2020.acl-tutorials)
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| Challenge: | tutorial focuses on three main topic areas: grounding in human-human communication, dialogue systems and multi-modal interactive systems. |
| Approach: | This tutorial examines the use of computational dialogue research to design grounding modules and behaviors in cutting-edge systems. |
| Outcome: | This tutorial examines the results of recent research on grounding in human-human communication . it shows how these results lead to rich and challenging opportunities for doing grounding more flexible and powerful ways . |
Reviewing Natural Language Processing Research (2020.acl-tutorials)
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| Challenge: | a tutorial on reviewing research in natural language processing will cover the theory and practice of reviewing research. |
| Approach: | tutorial covers the theory and practice of reviewing research in natural language processing . authors say reviewers should be more aware of "false negatives" |
| Outcome: | tutorial covers the theory and practice of reviewing research in natural language processing . authors say their reviews leave something to be desired . |
Stylized Text Generation: Approaches and Applications (2020.acl-tutorials)
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| Challenge: | Text generation has played an important role in various applications of natural language processing. |
| Approach: | They present different settings of stylized text generation and introduce machine learning methods to represent style. |
| Outcome: | This paper presents a comprehensive literature review on stylized text generation . it focuses on the challenges and future directions of stylized generation based on machine learning . |
Multi-modal Information Extraction from Text, Semi-structured, and Tabular Data on the Web (2020.acl-tutorials)
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| Challenge: | a tutorial explores the commonalities in the challenges and solutions developed to address information extraction from the World Wide Web. |
| Approach: | This tutorial examines methods for extracting information from the World Wide Web . it explores the commonalities in the challenges and solutions developed to address these different forms of text . |
| Outcome: | This paper examines the commonalities in the challenges and solutions developed to address the World Wide Web. |
Commonsense Reasoning for Natural Language Processing (2020.acl-tutorials)
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| Challenge: | In this tutorial, we will outline the various types of commonsense knowledge and discuss techniques to gather and represent commonsence knowledge. |
| Approach: | This tutorial will provide researchers with the critical foundations and recent advances in commonsense representation and reasoning. |
| Outcome: | This tutorial will outline the various types of commonsense and discuss techniques to gather and represent commonsence knowledge while highlighting the challenges specific to this type of knowledge (e.g., reporting bias). |
Open-Domain Question Answering (2020.acl-tutorials)
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| Challenge: | tutorial provides a comprehensive overview of cutting-edge research in open-domain question answering (QA) |
| Approach: | tutorial provides a comprehensive overview of cutting-edge research in open-domain question answering . focus will shift to cutting- edge models proposed for open- domain QA . |
| Outcome: | The tutorial will cover cutting-edge research in open-domain question answering (QA) it will cover two-stage retriever-reader approaches, dense retriever and end-to-end training, and retriever free methods . |