Measuring and Modeling Language Change (N19-5)

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Challenge: This tutorial will help researchers answer questions fundamental to the social sciences and humanities .
Approach: This tutorial is designed to help researchers answer questions in the social sciences and humanities . it synthesizes recent computational techniques for handling and modeling temporal data .
Outcome: The tutorial will synthesize recent techniques for handling and modeling temporal data, such as dynamic word embeddings, and identify useful tools for social scientists and digital humanities scholars.

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Computational modeling of semantic change (2024.eacl-tutorials)

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Challenge: Languages change constantly over time, influenced by social, technological, cultural and political factors that affect how people express themselves.
Approach: They propose to categorise the types of change, the causes and the mechanisms underlying the different types of changes using large diachronic corpora and evaluation benchmarks.
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Diachronic word embeddings and semantic shifts: a survey (C18-1)

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Challenge: Existing methods for tracing time-related semantic shifts with word embedding models lack the cohesion, common terminology and shared practices of more established areas of natural language processing.
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Text-based inference of moral sentiment change (D19-1)

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Challenge: Existing work in NLP treats moral sentiment as a flat classification problem, but our framework probes moral sentiment change at multiple levels and captures moral dynamics concerning relevance, polarity, and finegrained categories informed by Moral Foundations Theory.
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Understanding Computational Models of Semantic Change: New Insights from the Speech Community (2023.emnlp-main)

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Challenge: Using type-level and token-level word embeddings, we obtain semantic change estimates from type-based models and empirical linguistic properties.
Approach: They analyze 40 target words with type-level and token-level word embeddings, empirical linguistic properties, and speaker-provided acceptability ratings and qualitative remarks.
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Diachronic degradation of language models: Insights from social media (P18-2)

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Challenge: Existing studies have explored whether and how language models degrade over time, i.e. why they fail to work on contemporary language.
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Findings of the Association for Computational Linguistics: ACL 2024 (2024.findings-acl)

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Challenge: . - (EN)
Approach: . - (EN)
Outcome: . - (EN)
A Survey of Code-switching: Linguistic and Social Perspectives for Language Technologies (2021.acl-long)

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Challenge: linguistic and social aspects of code-switching are not discussed in the literature in linguistics.
Approach: They propose to examine linguistic and social aspects of code-switching across a wide range of languages in a survey of the literature in linguistics and language technologies.
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Synthetic Data in the Era of Large Language Models (2025.acl-tutorials)

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Challenge: 'synthetic data' is a data generated with the assistance of large language models to make dataset construction faster and cheaper.
Approach: This tutorial seeks to build a shared understanding of recent progress in synthetic data generation from NLP and related fields by grouping and describing major methods, applications, and open problems.
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Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (2025.acl-demo)

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Challenge: ACL 2025 System Demonstration Track accepted 64 papers based on reviews . short-listed 7 papers for Best System Demo award .
Approach: the ACL 2025 System Demonstration Track is a conference for papers describing system demonstrations . the track received a record 187 submissions, of which 178 papers were valid with required materials .
Outcome: the ACL 2025 System Demonstration Track received 187 submissions . 178 papers were valid with required materials .
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (2023.acl-demo)

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Challenge: 58 papers were selected for inclusion in the program, while a small number received only two reviews.
Approach: the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023) will be held in london from July 9-14, 2023 . 58 submissions were selected for inclusion in the program, with an acceptance rate of 37%)
Outcome: the system demonstration track received a record number of submissions . 58 papers were selected for inclusion in the program .

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