{"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/adversarial-deep-averaging-networks-for-cross","title":"Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification","arxiv_id":"1606.01614","date":"2016-06-06","proceeding":"TACL 2018 1","authors":["Xilun Chen","Yu Sun","Ben Athiwaratkun","Claire Cardie","Kilian Weinberger"],"abstract":"In recent years great success has been achieved in sentiment classification\nfor English, thanks in part to the availability of copious annotated resources.\nUnfortunately, most languages do not enjoy such an abundance of labeled data.\nTo tackle the sentiment classification problem in low-resource languages\nwithout adequate annotated data, we propose an Adversarial Deep Averaging\nNetwork (ADAN) to transfer the knowledge learned from labeled data on a\nresource-rich source language to low-resource languages where only unlabeled\ndata exists. ADAN has two discriminative branches: a sentiment classifier and\nan adversarial language discriminator. Both branches take input from a shared\nfeature extractor to learn hidden representations that are simultaneously\nindicative for the classification task and invariant across languages.\nExperiments on Chinese and Arabic sentiment classification demonstrate that\nADAN significantly outperforms state-of-the-art systems.","url_abs":"http://arxiv.org/abs/1606.01614v5","url_pdf":"http://arxiv.org/pdf/1606.01614v5.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":"adversarial-deep-averaging-networks-for-cross","repo_url":"https://github.com/ccsasuke/adan","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"adversarial-deep-averaging-networks-for-cross","repo_url":"https://github.com/htanwar922/Language-Adversarial-Network","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"cross-lingual-document-classification","task_name":"Cross-Lingual Document Classification"},{"task_slug":"cross-lingual-sentiment-classification","task_name":"Cross-Lingual Sentiment Classification"},{"task_slug":"cross-lingual-transfer","task_name":"Cross-Lingual Transfer"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":"sentiment-classification","task_name":"Sentiment Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1606.01614","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1606.01614"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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