Limitations of Cross-Lingual Learning from Image Search
Cross-lingual representation learning is an important step in making NLP scale to all the world's languages. Recent work on bilingual lexicon induction suggests that it is possible to learn cross-lingual representations of words based on similarities between images associated with these words. However, that work focused on the translation of selected nouns only. In our work, we investigate whether the meaning of other parts-of-speech, in particular adjectives and verbs, can be learned in the same way. We also experiment with combining the representations learned from visual data with embeddings learned from textual data. Our experiments across five language pairs indicate that previous work does not scale to the problem of learning cross-lingual representations beyond simple nouns.
Code (0)
등록된 구현이 없습니다.
Tasks
Bilingual Lexicon InductionImage RetrievalRepresentation LearningTranslationSimilar Papers 제목 키워드 기반
A Multi-Modal Multilingual Benchmark for Document Image Classification
Document image classification is different from plain-text document classification and consists of classifying a document by understanding the content and structure of documents such as forms, emails, and other such docu…
ClassificationCross-Lingual TransferDocument AIDocument Classification+8Analyzing the Limitations of Cross-lingual Word Embedding Mappings
Recent research in cross-lingual word embeddings has almost exclusively focused on offline methods, which independently train word embeddings in different languages and map them to a shared space through linear transform…
Bilingual Lexicon InductionCross-Lingual Word EmbeddingsWord EmbeddingsSemantic Indexing of Multilingual Corpora and its Application on the History Domain
The increasing amount of multilingual text collections available in different domains makes its automatic processing essential for the development of a given field. However, standard processing techniques based on statis…
RetrievalText RetrievalTranslationUnderstanding Cross-Lingual Alignment -- A Survey
Cross-lingual alignment, the meaningful similarity of representations across languages in multilingual language models, has been an active field of research in recent years. We survey the literature of techniques to impr…
DecoderSurveyFrom Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers
Massively multilingual transformers pretrained with language modeling objectives (e.g., mBERT, XLM-R) have become a de facto default transfer paradigm for zero-shot cross-lingual transfer in NLP, offering unmatched trans…
Cross-Lingual TransferCross-Lingual Word EmbeddingsDependency ParsingLanguage Modeling+7