Journal for Language Technology and Computational Linguistics. Special issue on LLM fails – failed experiments with generative AI and what we can learn from them
- This JLCL special issue focuses on linguistic and NLP experiments with generativeAI that did not yield the desired results. All papers explore the extent in which their failed experiment can contribute to knowledge gain regarding the work with generative AI.
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| URN: | urn:nbn:de:bsz:mh39-132590 |
|---|---|
| URL: | https://jlcl.org/issue/view/69 |
| ISSN: | 2190-6858 |
| Publisher: | Gesellschaft für Sprachtechnologie und Computerlinguistik |
| Editor: | Ngoc Duyen Tanja TuORCiDGND, Annelen BrunnerORCiDGND, Christian LangORCiDGND |
| Document Type: | Part of Periodical |
| Language: | English |
| Year of first Publication: | 2025 |
| Date of Publication (online): | 2025/07/10 |
| Publishing Institution: | Leibniz-Institut für Deutsche Sprache (IDS) |
| Publicationstate: | Veröffentlichungsversion |
| Reviewstate: | Peer-Review |
| Tag: | LLM fails; failed experiments; methodological reflection |
| GND Keyword: | Automatische Sprachanalyse; Computerlinguistik; Generative KI; Großes Sprachmodell; Methodologie |
| Volume: | 38 |
| Issue: | 2 |
| Page Number: | VII; 138 |
| DDC classes: | 400 Sprache / 400 Sprache, Linguistik / 400 Sprache |
| Open Access?: | ja |
| Linguistics-Classification: | Computerlinguistik |
| Program areas: | Grammatik |
| Program areas: | Lexik |
| Licence (English): |  Creative Commons - Attribution-ShareAlike 4.0 International |