# Analogical Proportions and Creativity: A Preliminary Study

arXiv: https://arxiv.org/abs/2310.13500 · HTML: https://mlsanity.com/paper/2310.13500/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 47 references that are in the map.
- First posted on arXiv 20 Oct 2023.

## Builds on (most cited first, 9 of 9)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Emergent Analogical Reasoning in Large Language Models](https://mlsanity.com/paper/2212.09196/) (2022)
- [In-Context Analogical Reasoning with Pre-Trained Language Models](https://mlsanity.com/paper/2305.17626/) (2023)
- [Analogical Dissimilarity: Definition, Algorithms and Two Experiments in Machine Learning](https://mlsanity.com/paper/1401.3427/) (2014)
- [ANALOGICAL -- A Novel Benchmark for Long Text Analogy Evaluation in Large Language Models](https://mlsanity.com/paper/2305.05050/) (2023)
- [Learning to Rank based on Analogical Reasoning](https://mlsanity.com/paper/1711.10207/) (2017)

## Abstract (arXiv)

Analogical proportions are statements of the form "a is to b as c is to d", which expresses that the comparisons of the elements in pair (a, b) and in pair (c, d) yield similar results. Analogical proportions are creative in the sense that given 3 distinct items, the representation of a 4th item d, distinct from the previous items, which forms an analogical proportion with them can be calculated, provided certain conditions are met. After providing an introduction to analogical proportions and their properties, the paper reports the results of an experiment made with a database of animal descriptions and their class, where we try to "create" new animals from existing ones, retrieving rare animals such as platypus. We perform a series of experiments using word embeddings as well as Boolean features in order to propose novel animals based on analogical proportions, showing that word embeddings obtain better results.