Learning to Generate Novel Scientific Directions with Contextualized Literature-based Discovery

Table of Contents

• Overview

• Requirements

• Quickstart

• Citation

Overview

Requirements

Environment

• Python 3.8.5

• Ubuntu 22.04

Environment Setup Instructions

To set up the environment for this repository, please follow the steps below:

Step 1: Create a Python environment (optional) If you wish to use a specific Python environment, you can create one using the following:

conda create -n pyt1.11 python=3.8.5

Step 2: Install PyTorch with CUDA (optional) If you want to use PyTorch with CUDA support, you can install it using the following:

conda install pytorch==1.11 torchvision torchaudio cudatoolkit=11.3 -c pytorch

Step 3: Install Python dependencies To install the required Python dependencies, run the following command:

pip install -r requirements.txt

Data Setup

1. Unzip all the zip files located in the data folder, including its subfolders.
2. Place the following folders, extracted from their respective zip files, under the data folder: kg,ct, and gold_subset
3. Locate the local_context_dataset folder unzipped from data/idea-sentence/local_context_dataset.zip.Move it to idea-sentence/models/T5.
4. Find the local_dataset folder unzipped from data/idea-node/local_dataset.zip. Place them in idea-node/models/Dual_Encoder.
5. Copy the file e2t.json and paste it into the following folders: idea-node\models\GPT3.5*\, idea-node\preprocess\, idea-sentence\models\GPT3.5*\, and idea-sentence\preprocess\

Data Preprocess

1. Navigate to the idea-node\preprocess and run the bash preprocess.sh
2. Navigate to the idea-sentence\preprocess and run the bash preprocess.sh

Data and Code Description

The project data includes the following components:

1. data/local_context_dataset: This folder contains the training, validation, and testing files for idea sentence generation.
2. data/local_dataset: This folder contains the training, validation, and testing files for idea node prediction.
3. data/kg/*.json: The data/kg directory contains files that store the original Information Extraction (IE) results for all paper abstracts.
4. data/ct/*.csv: The data/ct directory contains files that represent the citation network for all papers.
5. data/gold_subset: This directory contains our gold annotation subsets.
6. idea-node/evaluation and idea-sentence/evaluation contain sample evaluation code.

Quickstart

Training

To train the model under *\models\*, run the following command:

bash finetune_*.sh 

Test

To test the model under *\models\*, run the following command:

bash eval_*.sh 

Citation