A Scalable and Adaptive System to Infer the Industry Sectors of Companies: Prompt + Model Tuning of Generative Language Models
Lele Cao, Vilhelm von Ehrenheim, Astrid Berghult, Cecilia Henje, Richard Anselmo Stahl, Joar Wandborg, Sebastian Stan, Armin Catovic, Erik Ferm, Hannes Ingelhag
- Anthology ID:
- 2023.finnlp-1.5
- Volume:
- Proceedings of the Fifth Workshop on Financial Technology and Natural Language Processing and the Second Multimodal AI For Financial Forecasting
- Month:
- 20 August
- Year:
- 2023
- Address:
- Macao
- Editors:
- Chung-Chi Chen, Hiroya Takamura, Puneet Mathur, Remit Sawhney, Hen-Hsen Huang, Hsin-Hsi Chen
- Venues:
- FinNLP | WS
- SIG:
- Publisher:
- -
- Note:
- Pages:
- 55–62
- Language:
- URL:
- https://aclanthology.org/2023.finnlp-1.5
- DOI:
- Cite (ACL):
- Lele Cao, Vilhelm von Ehrenheim, Astrid Berghult, Cecilia Henje, Richard Anselmo Stahl, Joar Wandborg, Sebastian Stan, Armin Catovic, Erik Ferm, and Hannes Ingelhag. 2023. A Scalable and Adaptive System to Infer the Industry Sectors of Companies: Prompt + Model Tuning of Generative Language Models. In Proceedings of the Fifth Workshop on Financial Technology and Natural Language Processing and the Second Multimodal AI For Financial Forecasting, pages 55–62, Macao. -.
- Cite (Informal):
- A Scalable and Adaptive System to Infer the Industry Sectors of Companies: Prompt + Model Tuning of Generative Language Models (Cao et al., FinNLP-WS 2023)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/2023.finnlp-1.5.pdf