Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization

This repository contains data for the paper Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization

@inproceedings{temposum23,
    title="{Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization}",
    author = {Chi Seng Cheang and
                  Hou Pong Chan and
                  Derek F. Wong and
                  Xuebo Liu and
                  Zhaocong Li and
                  Yanming Sun and
                  Shudong Liu and
                  Lidia S. Chao},
    booktitle = "Proceedings of the Conference on Empirical Methods in Natural Language Processing ({EMNLP})",
    month = {December},
    year = "2023",
    publisher = "Association for Computational Linguistics",
    }

Getting the data

Download the datasets from Huggingface Datasets Library

Run the following commands to to load the datasets from Huggingface Datasets Library.

import datasets

# BBC in-distribution test set
dataset = datasets.load_dataset('chiseng-cheang/TempoSum', 'BBC_in-distribution')

# BBC future test set
dataset = datasets.load_dataset('chiseng-cheang/TempoSum', 'BBC_future')

# CNN in-distribution test set
dataset = datasets.load_dataset('chiseng-cheang/TempoSum', 'CNN_in-distribution')

# CNN future test set
dataset = datasets.load_dataset('chiseng-cheang/TempoSum', 'CNN_future')

Manual Download

All datasets are also available at: https://drive.google.com/drive/folders/1BdeTFqoea8GD240h78PgXBO68e53ea9E?usp=sharing