[PromptEng] Second International Workshop on Prompt Engineering for Pre-Trained Language Models
The recent achievements and availability of Large Language Models have paved the road to a new range of applications and use-cases. Pre-trained language models are now being involved at-scale in many fields where they were until now absent from. More specifically, the progress made by causal generative models has open the door to using them through textual instructions aka. prompts. Unfortunately, the performances of these prompts are highly dependent on the exact phrasing used and therefore practitioners need to adopt fail-retry strategies. Based on the success of the past edition, this second international workshop on prompt engineering gathers practitioners (both from Academia and Industry) to exchange about good practices, optimizations, results and novel paradigms about the design of efficient and safe prompts.
Authors
- Sébastien Montella (ORCID: https://orcid.org/0000-0002-2605-7238)
- Hajira Jabeen (ORCID: https://orcid.org/0000-0003-1476-2121)
- Damien Graux (ORCID: https://orcid.org/0000-0003-3392-3162)
- Jeff Z. Pan (ORCID: https://orcid.org/0000-0002-9779-2088)
- Claire Gardent (ORCID: https://orcid.org/0000-0002-3805-6662)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Klinik und Poliklinik für Psychosomatik und Psychotherapie (DE)
- Laboratoire Lorrain de Recherche en Informatique et ses Applications (FR)
- Huawei Technologies (United Kingdom) (GB)
- Université de Lorraine (FR)
- University of Edinburgh (GB)
Publication Details
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1145/3701716.3717816
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00