Title: The LAMBADA dataset: Word prediction requiring a broad discourse context
Abstract: https://arxiv.org/abs/1606.06031
Cloze-style LAMBADA dataset. LAMBADA is a dataset to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative passages sharing the characteristic that human subjects are able to guess their last word if they are exposed to the whole passage, but not if they only see the last sentence preceding the target word. To succeed on LAMBADA, computational models cannot simply rely on local context, but must be able to keep track of information in the broader discourse.
Homepage: https://zenodo.org/record/2630551#.X4Xzn5NKjUI
@misc{
author={Paperno, Denis and Kruszewski, Germán and Lazaridou, Angeliki and Pham, Quan Ngoc and Bernardi, Raffaella and Pezzelle, Sandro and Baroni, Marco and Boleda, Gemma and Fernández, Raquel},
title={The LAMBADA dataset},
DOI={10.5281/zenodo.2630551},
publisher={Zenodo},
year={2016},
month={Aug}
}
lambada_cloze
lambada_openai_cloze_yaml
lambada_standard_cloze_yaml
For adding novel benchmarks/datasets to the library:
- Is the task an existing benchmark in the literature?
- Have you referenced the original paper that introduced the task?
- If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
If other tasks on this dataset are already supported:
- Is the "Main" variant of this task clearly denoted?
- Have you provided a short sentence in a README on what each new variant adds / evaluates?
- Have you noted which, if any, published evaluation setups are matched by this variant?