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    <abstract>Computational linguistics (CL) has witnessed tremendous advancementsin recent years, with models such as large language models demonstratingexceptional performance in various natural language processing tasks. Theseadvancements highlight their potential to help understand brain languageprocessing, especially through the lens of brain encoding and decoding.Brain encoding involves the mapping of linguistic stimuli to brain activity,while brain decoding is the process of reconstructing linguistic stimulifrom observed brain activities. CL models that excel at capturing andmanipulating linguistic features are crucial for mapping linguistic stimulito brain activities and vice versa. Brain encoding and decoding have vastapplications, from enhancing human-computer interaction to developingassistive technologies for individuals with communication impairments. Thistutorial will focus on elucidating how computational linguistics canfacilitate brain encoding and decoding. We will delve into the principlesand practices of using computational linguistics methods for brain encodingand decoding. We will also discuss the challenges and future directions ofbrain encoding and decoding. Through this tutorial, we aim to provide acomprehensive and informative overview of the intersection betweencomputational linguistics and cognitive neuroscience, inspiring futureresearch in this exciting and rapidly evolving field.</abstract>
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%0 Conference Proceedings
%T Computational Linguistics for Brain Encoding and Decoding: Principles, Practices and Beyond
%A Sun, Jingyuan
%A Wang, Shaonan
%A Chen, Zijiao
%A Li, Jixing
%A Moens, Marie-Francine
%Y Chiruzzo, Luis
%Y Lee, Hung-yi
%Y Ribeiro, Leonardo
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 5: Tutorial Abstracts)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F sun-etal-2024-computational
%X Computational linguistics (CL) has witnessed tremendous advancementsin recent years, with models such as large language models demonstratingexceptional performance in various natural language processing tasks. Theseadvancements highlight their potential to help understand brain languageprocessing, especially through the lens of brain encoding and decoding.Brain encoding involves the mapping of linguistic stimuli to brain activity,while brain decoding is the process of reconstructing linguistic stimulifrom observed brain activities. CL models that excel at capturing andmanipulating linguistic features are crucial for mapping linguistic stimulito brain activities and vice versa. Brain encoding and decoding have vastapplications, from enhancing human-computer interaction to developingassistive technologies for individuals with communication impairments. Thistutorial will focus on elucidating how computational linguistics canfacilitate brain encoding and decoding. We will delve into the principlesand practices of using computational linguistics methods for brain encodingand decoding. We will also discuss the challenges and future directions ofbrain encoding and decoding. Through this tutorial, we aim to provide acomprehensive and informative overview of the intersection betweencomputational linguistics and cognitive neuroscience, inspiring futureresearch in this exciting and rapidly evolving field.
%U https://aclanthology.org/2024.acl-tutorials.1
%P 1-2

Markdown (Informal)

[Computational Linguistics for Brain Encoding and Decoding: Principles, Practices and Beyond](https://aclanthology.org/2024.acl-tutorials.1) (Sun et al., ACL 2024)

• Computational Linguistics for Brain Encoding and Decoding: Principles, Practices and Beyond (Sun et al., ACL 2024)

ACL

• Jingyuan Sun, Shaonan Wang, Zijiao Chen, Jixing Li, and Marie-Francine Moens. 2024. Computational Linguistics for Brain Encoding and Decoding: Principles, Practices and Beyond. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 5: Tutorial Abstracts), pages 1–2, Bangkok, Thailand. Association for Computational Linguistics.