LInDA: Workshop on Linguistic Information for Downstream Applications

News

• LInDA will be co-located with EACL 2027!
• The LInDA 2027 website is online.
• October 13, 2026, The first Call for Papers is out.

About

LInDA studies how linguistic information can improve downstream NLP applications.

Many languages remain underrepresented in large language models (LLMs), resulting in limited performance on downstream tasks. However, many languages have other resources: dictionaries, grammars, morphological analyses, and other forms of annotated texts. According to Glottolog, about 63% of the world's languages have at least a grammar sketch.

Linguistic annotations and resources have gained attention in the NLP community as a means of providing auxiliary information for various NLP tasks, such as machine translation. Linguistic information can help models to better process and represent languages, particularly in low-resource settings where conventional training data are scarce.

LInDA brings these two sides together: linguistic information and NLP applications. We want to understand how linguistic resources and annotations can improve downstream tasks, especially for low-resource and underrepresented languages. We also aim to know which types of information are useful, and for which tasks.

The workshop has two goals:

1. To evaluate strategies that integrate linguistic information into language models, and to measure their impact on specific applications.
2. To explore how language models can help create or extract linguistic information.

We welcome researchers with a background in linguistics, in computer science, or in both. This is the first edition of LInDA. It will be co-located with EACL 2027 in Athens, Greece.