Vilhelm Von Ehrenheim — accepted AI-conference papers

2024

Prompt Tuned Embedding Classification for Industry Sector Allocation

Valentin Buchner, Lele Cao, Jan-Christoph Kalo, Vilhelm Von Ehrenheim

NAACL 2024industry

We introduce Prompt Tuned Embedding Classification (PTEC) for classifying companies within an investment firm’s proprietary industry taxonomy, supporting their thematic investment strategy. PTEC assigns companies to the sectors they primarily operate in, conceptualizing this process as a multi-label…

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2021

PAUSE: Positive and Annealed Unlabeled Sentence Embedding

Lele Cao, Emil Larsson, Vilhelm von Ehrenheim, Dhiana Deva Cavalcanti Rocha, Anna Martin, Sonja Horn

EMNLP 2021main

Sentence embedding refers to a set of effective and versatile techniques for converting raw text into numerical vector representations that can be used in a wide range of natural language processing (NLP) applications. The majority of these techniques are either supervised or unsupervised. Compared…

Cited by 3 Source ↗PDF ↗code ↗Scholar ↗