{"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/select-additive-learning-improving","title":"Select-Additive Learning: Improving Generalization in Multimodal Sentiment Analysis","arxiv_id":"1609.05244","date":"2016-09-16","proceeding":null,"authors":["Haohan Wang","Aaksha Meghawat","Louis-Philippe Morency","Eric P. Xing"],"abstract":"Multimodal sentiment analysis is drawing an increasing amount of attention\nthese days. It enables mining of opinions in video reviews which are now\navailable aplenty on online platforms. However, multimodal sentiment analysis\nhas only a few high-quality data sets annotated for training machine learning\nalgorithms. These limited resources restrict the generalizability of models,\nwhere, for example, the unique characteristics of a few speakers (e.g., wearing\nglasses) may become a confounding factor for the sentiment classification task.\nIn this paper, we propose a Select-Additive Learning (SAL) procedure that\nimproves the generalizability of trained neural networks for multimodal\nsentiment analysis. In our experiments, we show that our SAL approach improves\nprediction accuracy significantly in all three modalities (verbal, acoustic,\nvisual), as well as in their fusion. Our results show that SAL, even when\ntrained on one dataset, achieves good generalization across two new test\ndatasets.","url_abs":"http://arxiv.org/abs/1609.05244v2","url_pdf":"http://arxiv.org/pdf/1609.05244v2.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":"select-additive-learning-improving","repo_url":"https://github.com/HaohanWang/SelectAdditiveLearning","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"multimodal-sentiment-analysis","task_name":"Multimodal Sentiment Analysis"},{"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=1609.05244","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}