Interchange Formats for Visualization: LIF and MMIF (2020.lrec-1)

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Challenge: In this paper, we discuss the enhanced data visualization capabilities enabled by interoperating computational linguistics and natural language processing (NLP) applications.
Approach: They propose to use interchange formats to enable enhanced data visualization . they propose to combine CL tools with openly available visualization tools .
Outcome: The proposed formats can be used to create visualizations and manipulate annotations in multiple ways.

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Challenge: Existing annotation efforts for multiple languages have focused on discourse connectives, but we have limited it to the class of connectives marking contrast and the additional relations such connectives might convey.
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Converting Legacy Data to CLDF: A FAIR Exit Strategy for Linguistic Web Apps (2024.lrec-main)

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Challenge: a number of web applications that enabled comparative linguistics research became obsolete . cross-linguistic data formats (CLDF) are available for use in linguistic research .
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The Interplay between Metaphors and NLP (2026.acl-tutorials)

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Challenge: This tutorial will provide an overview of the metaphor processing field.
Approach: This tutorial will provide an overview of the metaphor processing field . it will focus on recent directions opened by LLMs for metaphor interpretation .
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High Performance Natural Language Processing (2020.emnlp-tutorials)

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Challenge: a tutorial on scaling natural language processing will recapitulate the state-of-the-art in the field .
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NLP Scholar: An Interactive Visual Explorer for Natural Language Processing Literature (2020.acl-demos)

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Challenge: aCL Anthology and Google Scholar provide a single dataset of NLP papers and their meta-information . authors describe interactive visualizations that present various aspects of the data .
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Connecting Language Technologies with Rich, Diverse Data Sources Covering Thousands of Languages (2024.lrec-main)

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Challenge: Existing data sources for many thousands of languages are rich and diverse . Efforts are ongoing to extend technology to many more of the world's languages .
Approach: They provide an overview of some of the major online data sources available for thousands of languages.
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NLP+Vis: NLP Meets Visualization (2023.emnlp-tutorial)

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Challenge: This tutorial will introduce NLP+Vis with a focus on two main threads of work: NLP for Vis and Vis for NLP.
Approach: tutorial will introduce NLP+Vis with a focus on two main threads of work . overview of research topics on combining NLP and Vis techniques will be covered .
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The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models (2020.emnlp-demos)

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Challenge: Existing tools for modeling and understanding models are limited . existing tools can assist practitioners in understanding and evaluating models .
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A Data-Centric Framework for Composable NLP Workflows (2020.emnlp-demos)

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Challenge: Empirical natural language processing (NLP) systems involve interoperation among multiple components . a wealth of NLP toolkits exist ( 4), such as spaCy, DKPro, CoreNLP.
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The Why and The How: A Survey on Natural Language Interaction in Visualization (2022.naacl-main)

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Challenge: Recent research shows that different forms of natural language-based interaction prove suitable to support users in accomplishing various visualization tasks.
Approach: They propose a taxonomy of visualization tasks and a classification system to illustrate the state-of-the-art of natural language-based interaction in visualization.
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