Fine-Grained and Complex Food Entity Recognition Benchmark for Ingredient Substitution-Reference-Cited by-同舟云学术

Fine-Grained and Complex Food Entity Recognition Benchmark for Ingredient Substitution

Published:2023-12-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 12th Knowledge Capture Conference 2023
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Author:

Lawrynowicz Agnieszka¹^ORCID,Wróblewska Anna²^ORCID,Kaliska Agnieszka³^ORCID,Pawlowski Maciej⁴^ORCID,Wiśniewski Dawid⁴^ORCID,Sosnowski Witold⁵^ORCID,Dutkiewicz Jakub⁴^ORCID

Affiliation:

1. Faculty of Computing and Telecommunications, Poznan University of Technology, Poland

2. Warsaw University of Technology, Poland

3. Adam Mickiewicz University, Poland

4. Poznan University of Technology, Poland

5. Polish-Japanese Academy of Information Technology, Poland

Funder

Norway Grants 2014-2021 via the National Centre for Research and Development

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3587259.3627543

Reference28 articles.

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2. BuTTER: BidirecTional LSTM for Food Named-Entity Recognition

3. Fernando De la Torre, Jessica Hodgins, Adam Bargteil, Xavier Martin, Justin Macey, Alex Collado, and Pep Beltran. 2008. Guide to the carnegie mellon university multimodal activity (cmu-mmac) database. Robotics Institute (2008).

4. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv:1810.04805 [cs] (May 2019). http://arxiv.org/abs/1810.04805 arXiv:1810.04805.