The corpus-linguistic sections of the Department of English and the Department of German at Justus Liebig University (JLU) Giessen, Germany, jointly host the conference ‘Corpus Linguistics in the AI Era’, which will take place in-person only at Schloss Rauischholzhausen from May 07 to May 09 2026. Approximately 40 papers, which we plan to spread over two sections and frame by plenary talks, can be presented. The language of the conference will be English. The conference seeks to establish and widely explore the relations through which corpus-linguistic theory and practice connect with principles and applications of artificial intelligence – with a particular emphasis on large language models. Corpus linguistics and artificial intelligence as manifested in large language models are both rooted in and dedicated to the analysis of large amounts of texts and thus appear naturally connected. Yet, in comparison to the rapid integration of large language models in the field of computational linguistics, corpus linguists – at least as far as their output at relevant conferences and in dedicated journals is concerned – have so far been more hesitant in adopting large language models in their research. This relative hesitance of corpus linguistics regarding AI may be motivated by theoretical as well as practical considerations, which is why the conference provides a platform to articulate and discuss the integration of AI into corpus linguistics from various angles that can relate, but are not limited to discussions of the following research questions: Corpus-linguistic theory in the light of AI: - Should AI-generated texts be featured in linguistic corpora? - Are adjustments in corpus compilation – especially with established families of corpora that have followed comparable designs for decades – necessary and/or desirable under consideration of the increase of AI-generated texts? - What are opportunities and threats of AI for corpus linguistics? - How can the replicability of corpus-linguistic studies be ensured when AI as a black box takes on central roles in the research process? Corpus-linguistic practice in the light of AI: - How can AI help in the compilation of spoken and written data? - Can AI replace and potentially outperform traditional corpus-linguistic software such as AntConc or WordSmith? - How reliably can AI perform often labour-intensive tasks of data annotation (e. g. part-of-speech tagging or parsing, but also qualitative classification)? - To what extent can AI help with statistically modelling carefully annotated corpus-linguistic datasets? - How do earlier, non-generative AI approaches in corpus linguistics – often based on neural networks – compare to today’s use of large language models and how might the two approaches complement each other? - To what extent can large language models help in the use of programmable NLP pipelines such as NLTK, Stanza or spaCy?
