Challenge: In one view, languages exist on a resource continuum and the challenge is to scale existing solutions, bringing under-resourced languages into the high-resource world.
Approach: They propose to scale existing solutions to bring under-resourced languages into the high-resource world by bringing standardised languages into high-level global information society.
Outcome: The proposed language technology agendas address the diverse situations of the world's languages.

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Toward More Meaningful Resources for Lower-resourced Languages (2022.findings-acl)

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Challenge: a new position paper examines how meaningful resources for lower-resourced languages should be developed in connection with the speakers of those languages.
Approach: They propose a position paper on how meaningful resources should be developed for lower-resourced languages . they examine the contents of Wikidata for a few lower-rsourced languages and examine quality issues .
Outcome: The proposed approach is based on the findings of a recent study on the use of multilingual resources in language technology development.
Cross-Lingual Link Discovery for Under-Resourced Languages (2022.lrec-1)

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Challenge: Linked data paradigms can be used to solve under-resourced languages' problem of under-utilization of resources.
Approach: They propose a paradigm for cross-lingual link discovery that can be applied to under-resourced languages . they argue that techniques for cross language linking can be readily applied .
Outcome: The proposed technologies can be applied to under-resourced languages, the authors argue . the authors show that the Linked Data paradigm can be used to solve the problem .
The Zeno’s Paradox of ‘Low-Resource’ Languages (2024.emnlp-main)

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Challenge: 'low resource' languages are understudied by the NLP community, while 'high resource' is referred to as 'achieved', while high-resource languages are referred .
Approach: They qualitatively analyzed 150 papers from the ACL Anthology and popular speech-processing conferences that mention the keyword ‘low-resource.
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Centering the Speech Community (2024.eacl-long)

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Challenge: In remote speech communities, people interact with the outside world using a variety of an institutional language.
Approach: They propose to use local languages to support their collaboration in a remote community in the far north of australia to explore the functional differences between oral and institutional languages.
Outcome: The proposed language technologies are better aligned with local interests and aspirations than the first author's western framing of language as data for exploitation by machines.
How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances (2023.emnlp-main)

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Challenge: Large language models (LLMs) are impressive in solving tasks, but they can quickly be outdated after deployment.
Approach: They provide a review of recent advances in aligning deployed large language models with the ever-changing world knowledge.
Outcome: The proposed models can be used to perform various tasks directly through in-context learning or for further fine-tuning for domain-specific uses.
Building Better: Avoiding Pitfalls in Developing Language Resources when Data is Scarce (2025.acl-long)

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Challenge: Language is a powerful means of communication and should be regarded as more than just a collection of tokens.
Approach: They collect feedback from individuals directly involved in and impacted by NLP artefacts for medium- and low-resource languages and highlight key issues related to data quality, cultural appropriateness and ethics of common annotation practices.
Outcome: The findings highlight key issues related to data quality, cultural appropriateness, and ethics of common annotation practices.
Not always about you: Prioritizing community needs when developing endangered language technology (2022.acl-long)

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Challenge: low-resource languages lack the quantity of data needed to train statistical and machine learning tools and models.
Approach: They propose to use language technology to support endangered languages' revitalization . they propose to work with indigenous speakers to develop technology for such training .
Outcome: The authors discuss the challenges that researchers and indigenous speech community members face when working together to develop language technology to support endangered languages.
Language + Molecules (2024.eacl-tutorials)

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Challenge: In the last year, instruction-following language models have surged in popularity.
Approach: This tutorial will provide an introduction to applying natural language-driven solutions to chemistry problems.
Outcome: This tutorial will provide an introduction to this area of research. it requires no knowledge outside mainstream NLP, and it will enable participants to begin exploring relevant research.
The State and Fate of Linguistic Diversity and Inclusion in the NLP World (2020.acl-main)

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Challenge: a small number of the over 7000 languages of the world are represented in the rapidly evolving language technologies and applications.
Approach: They examine the relationship between types of languages, resources, and their representation in NLP conferences to understand the trajectory that different languages have followed over time.
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Language Technologies as If People Mattered: Centering Communities in Language Technology Development (2024.lrec-main)

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Challenge: Developing and deploying language technologies "as if people mattered" requires a reflexive and receptive approach, argues a new position paper .
Approach: They argue that researchers should address linguistic and algorithmic injustice together with language communities to build strong interdisciplinary teams.
Outcome: The authors argue that researchers should address social and linguistic injustice together with language communities to solve the challenges raised by language technologies.

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