FoodTaxo: Generating Food Taxonomies with Large Language Models
Not on the map. Why?
Abstract (arXiv)
We investigate the utility of Large Language Models for automated taxonomy generation and completion specifically applied to taxonomies from the food technology industry. We explore the extent to which taxonomies can be completed from a seed taxonomy or generated without a seed from a set of known concepts, in an iterative fashion using recent prompting techniques. Experiments on five taxonomies using an open-source LLM (Llama-3), while promising, point to the difficulty of correctly placing inner nodes.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 38 references that are in the map. First posted on arXiv 26 May 2025.
Builds on
14 of 38 references.
References · 14
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2016Enriching Word Vectors with Subword Informationcited by 1,583
- 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 832
- 2022Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLPcited by 318
- 2023Prompting Large Language Model for Machine Translation: A Case Studycited by 250
- 2023In-Context Learning for Text Classification with Many Labelscited by 35
- 2019HiExpan: Task-Guided Taxonomy Construction by Hierarchical Tree Expansioncited by 31
- 2020STEAM: Self-Supervised Taxonomy Expansion with Mini-Pathscited by 31
- 2023DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelinescited by 27
- 2021Taxonomy Completion via Triplet Matching Networkcited by 21
- 2021Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representationscited by 19
Built on by
Not cited yet.