Strand A. Formal linguistic theories, data, and empirical methods

1. What are the (abstract) rules revealed by language data that account for cross-linguistic commonalities and differences?

2. How can we model these linguistic rules in a formally explicit grammatical theory, with the consideration of different types of linguistic information—in particular, syntax, semantics, and discourse?

3. How do different grammatical theories capture these linguistic rules? What are their advantages and limitations?

4. How can empirical methods, such as corpus analyses and acceptability-judgment experiments, combined with inferential statistical models, inform formal-linguistic analyses and facilitate the replicability of research findings?

Strand B. Computational grammar engineering and its applications

1. How can we computationally implement formally explicit, mathematically precise linguistic analyses to develop computer-processable grammars? [knowledge-based grammar engineering]

2. What are the applications of computer-processable grammars? For example, how can we make good use of these grammars to create parsed treebanks (notated with in-depth linguistic information) that have further natural-language processing (NLP) purposes?

3. What is the potential of knowledge-based grammar engineering in the current AI/LLM-driven landscape?

Strand C.  Language contact and multi-language acquisition

1. How can we extract insights from large-scale language-development corpora to identify factors (e.g., structural, cognitive, social) that shape multi-language acquisition?