About

Using data and models available for one language for which ample such resources are available (e.g., English) to solve a natural language inference task in another, commonly more low-resource, language.

Benchmarks

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Datasets

Greatest papers with code

Better Fine-Tuning by Reducing Representational Collapse

ICLR 2021 pytorch/fairseq

Although widely adopted, existing approaches for fine-tuning pre-trained language models have been shown to be unstable across hyper-parameter settings, motivating recent work on trust region methods.

ABSTRACTIVE TEXT SUMMARIZATION CROSS-LINGUAL NATURAL LANGUAGE INFERENCE

XNLI: Evaluating Cross-lingual Sentence Representations

EMNLP 2018 facebookresearch/XLM

State-of-the-art natural language processing systems rely on supervision in the form of annotated data to learn competent models.

CROSS-LINGUAL NATURAL LANGUAGE INFERENCE MACHINE TRANSLATION

FarsTail: A Persian Natural Language Inference Dataset

18 Sep 2020dml-qom/FarsTail

This dataset, named FarsTail, includes 10, 367 samples which are provided in both the Persian language as well as the indexed format to be useful for non-Persian researchers.

CROSS-LINGUAL NATURAL LANGUAGE INFERENCE CROSS-LINGUAL TRANSFER

Meemi: A Simple Method for Post-processing and Integrating Cross-lingual Word Embeddings

16 Oct 2019yeraidm/meemi

While monolingual word embeddings encode information about words in the context of a particular language, cross-lingual embeddings define a multilingual space where word embeddings from two or more languages are integrated together.

CROSS-LINGUAL NATURAL LANGUAGE INFERENCE HYPERNYM DISCOVERY WORD EMBEDDINGS