{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/baselines-and-test-data-for-cross-lingual","title":"Baselines and test data for cross-lingual inference","arxiv_id":"1704.05347","date":"2017-04-18","proceeding":"LREC 2018 5","authors":["Željko Agić","Natalie Schluter"],"abstract":"The recent years have seen a revival of interest in textual entailment,\nsparked by i) the emergence of powerful deep neural network learners for\nnatural language processing and ii) the timely development of large-scale\nevaluation datasets such as SNLI. Recast as natural language inference, the\nproblem now amounts to detecting the relation between pairs of statements: they\neither contradict or entail one another, or they are mutually neutral. Current\nresearch in natural language inference is effectively exclusive to English. In\nthis paper, we propose to advance the research in SNLI-style natural language\ninference toward multilingual evaluation. To that end, we provide test data for\nfour major languages: Arabic, French, Spanish, and Russian. We experiment with\na set of baselines. Our systems are based on cross-lingual word embeddings and\nmachine translation. While our best system scores an average accuracy of just\nover 75%, we focus largely on enabling further research in multilingual\ninference.","url_abs":"http://arxiv.org/abs/1704.05347v2","url_pdf":"http://arxiv.org/pdf/1704.05347v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"baselines-and-test-data-for-cross-lingual","repo_url":"https://bitbucket.org/nlpitu/xnli","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"cross-lingual-word-embeddings","task_name":"Cross-Lingual Word Embeddings"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"natural-language-inference","task_name":"Natural Language Inference"},{"task_slug":"translation","task_name":"Translation"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1704.05347","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}