Cross-lingual paraphrase identification
The paraphrase identification task involves measuring semantic similarity between two short sentences. It is a tricky task, and multilingual paraphrase identification is even more challenging. In this work, we train a bi-encoder model in a contrastive manner to detect hard paraphrases across multiple languages. This approach allows us to use model-produced embeddings for various tasks, such as semantic search. We evaluate our model on downstream tasks and also assess embedding space quality. Our performance is comparable to state-of-the-art cross-encoders, with only a minimal relative drop of 7-10% on the chosen dataset, while keeping decent quality of embeddings.
Code (0)
등록된 구현이 없습니다.
Tasks
Cross-Lingual Paraphrase IdentificationParaphrase IdentificationSemantic SimilaritySemantic Textual SimilaritySimilar Papers 제목 키워드 기반
PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification
Most existing work on adversarial data generation focuses on English. For example, PAWS (Paraphrase Adversaries from Word Scrambling) consists of challenging English paraphrase identification pairs from Wikipedia and Quo…
Paraphrase IdentificationSentenceUnsupervised Paraphrasing without Translation
Paraphrasing exemplifies the ability to abstract semantic content from surface forms. Recent work on automatic paraphrasing is dominated by methods leveraging Machine Translation (MT) as an intermediate step. This contra…
Machine TranslationParaphrase IdentificationTranslationXLA: A Robust Unsupervised Data Augmentation Framework for Cross-Lingual NLP
Transfer learning has yielded state-of-the-art (SoTA) results in many supervised NLP tasks. However, annotated data for every target task in every target language is rare, especially for low-resource languages. We propo…
Cross-Lingual TransferData Augmentationnamed-entity-recognitionNamed Entity Recognition+6Paraphrases as Foreign Languages in Multilingual Neural Machine Translation
Paraphrases, the rewordings of the same semantic meaning, are useful for improving generalization and translation. However, prior works only explore paraphrases at the word or phrase level, not at the sentence or corpus …
Machine TranslationNMTSentenceTAG+2Learning to Represent Bilingual Dictionaries
Bilingual word embeddings have been widely used to capture the similarity of lexical semantics in different human languages. However, many applications, such as cross-lingual semantic search and question answering, can b…
Multi-Task LearningParaphrase IdentificationQuestion AnsweringRetrieval+3