Universal Aesthetics (Multimodal Focus): Difference between revisions

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=== Peoms ===  
=== Peoms ===  
For poems, we use the [https://www.kaggle.com/datasets/michaelarman/poemsdataset/data Poems dataset] from Kaggle. This dataset contains 6,322 poems in 135 different types in total. We find this dataset ideal for this project because of the following reasons:
For poems, we use the [https://www.kaggle.com/datasets/michaelarman/poemsdataset/data Poems dataset] from Kaggle. We find this dataset ideal for this project because of the following reasons:
*  As the plain-text dataset contains 1,024 entries, it provides enough poems to yield a substantial amount of data.
*  As the plain-text dataset contains 1,024 entries, it provides enough poems to yield a substantial amount of data.
*  It categorizes the poems into 135 types based on their form (haiku, sonnet, etc.), which could facilitate our further studies.
*  It categorizes the poems into 135 types based on their form (haiku, sonnet, etc.), which could facilitate our further studies.
{| class="wikitable"
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! 列1
! 列2
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| 内容A1
| 内容A2
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| 内容B1
| 内容B2
|}


== References ==
== References ==
<references />
<references />

Revision as of 21:35, 27 November 2025

Introduction

Methods

Data

As for the convergence of language models, we need both plain texts and aesthetic texts. For simplicity, we reuse this text-image dataset, which is also used in Huh et al.'s paper, and then add another poem dataset.

Plain Text

Peoms

For poems, we use the Poems dataset from Kaggle. We find this dataset ideal for this project because of the following reasons:

  • As the plain-text dataset contains 1,024 entries, it provides enough poems to yield a substantial amount of data.
  • It categorizes the poems into 135 types based on their form (haiku, sonnet, etc.), which could facilitate our further studies.


列1 列2
内容A1 内容A2
内容B1 内容B2

References