Semantics Preserving Emoji Recommendation with Large Language Models
Zhongyi Qiu, Kangyi Qiu, Hanjia Lyu, Wei Xiong, Jiebo Luo
Accepted for publication in IEEE BigData 2024
Contact
Zhongyi Qiu ([email protected]), Kangyi Qiu ([email protected]), Hanjia Lyu ([email protected]), Wei Xiong ([email protected]), Jiebo Luo ([email protected])
- Ensure Conda is installed. Install Conda if not already available.
- Ensure
requirements.txtis in the same directory assetup_env.sh.
-
Run the setup script:
Use the following command to run the setup script:bash setup_env.sh
Or:
sh setup_env.sh
This creates the emoji_recommendation environment, installs Python 3.10, and installs dependencies from requirements.txt.
-
Activate the environment:
conda activate emoji_recommendation
-
Code:
- The
srcfolder contains all the Jupyter Notebook (.ipynb) files used for data preprocessing and running the models. These notebooks handle tasks such as preparing the dataset, running the emoji recommendation models, and evaluating the results.
- The
-
Dataset:
- src/dataset: Contains the initial raw dataset used for preprocessing and analysis.
- src/dataset_finalOutput: Stores the output results generated by six large language models (LLMs).
- src/human_eval: Includes a small subset of manually labeled data used for evaluating the model predictions.
@article{qiu2024semantics,
title={Semantics Preserving Emoji Recommendation with Large Language Models},
author={Qiu, Zhongyi and Qiu, Kangyi and Lyu, Hanjia and Xiong, Wei and Luo, Jiebo},
journal={arXiv preprint arXiv:2409.10760},
year={2024}
}
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