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This repository contains codes of Jung et al's EACL 2023 paper titled "Cluster-Guided Label Generation in Extreme Multi-Label Classification"

Requirements

We use python 3.6.5. Please run pip install -r requirement.txt to install python dependencies.

Running XLGen with EUR-Lex dataset

We provide an example of XLGen training/evaluation on EUR-Lex dataset with t5-base model. To test with other benchmark datasets (e.g., Wiki10-31K, AmazonCat-13K, Wiki-500K) or t5 model (e.g., t5-large), simply change the corresponding arguments.

Data Download

bash ./download_data/download_data.sh EUR-Lex

Get Label Clusters

  1. Get t5 label representations
bash ./cluster/run_t5_rep.sh EUR-Lex t5-base
  1. Get kmeans label clusters
bash ./cluster/run_cluster.sh EUR-Lex t5-base

Running XLGen models

  1. Train XLGen-base / XLGen-bcl / XGLEN-mcg
bash ./xlgen/run_train.sh EUR-Lex t5-base base
bash ./xlgen/run_train.sh EUR-Lex t5-base bcl
bash ./xlgen/run_train.sh EUR-Lex t5-base mcg
  1. Inference for XLGen-base / XLGen-bcl / XGLEN-mcg
bash ./xlgen/run_test.sh EUR-Lex t5-base base
bash ./xlgen/run_test.sh EUR-Lex t5-base bcl
bash ./xlgen/run_test.sh EUR-Lex t5-base mcg

Evaluation

bash ./evaluation/run_fscores.sh EUR-Lex t5-base base
bash ./evaluation/run_fscores.sh EUR-Lex t5-base bcl
bash ./evaluation/run_fscores.sh EUR-Lex t5-base mcg

Citation

@Inproceedings{Jung2023, author = {Taehee Jung and Joo-Kyung Kim and Sungjin Lee and Dongyeop Kang}, title = {Cluster-guided label generation in extreme multi-label classification}, year = {2023}, url = {https://www.amazon.science/publications/cluster-guided-label-generation-in-extreme-multi-label-classification}, booktitle = {EACL 2023}, }