{"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/open-ended-multi-modal-relational-reason-for","title":"Open-Ended Multi-Modal Relational Reasoning for Video Question Answering","arxiv_id":"2012.00822","date":"2020-12-01","proceeding":null,"authors":["Haozheng Luo","Ruiyang Qin","Chenwei Xu","Guo Ye","Zening Luo"],"abstract":"In this paper, we introduce a robotic agent specifically designed to analyze external environments and address participants' questions. The primary focus of this agent is to assist individuals using language-based interactions within video-based scenes. Our proposed method integrates video recognition technology and natural language processing models within the robotic agent. We investigate the crucial factors affecting human-robot interactions by examining pertinent issues arising between participants and robot agents. Methodologically, our experimental findings reveal a positive relationship between trust and interaction efficiency. Furthermore, our model demonstrates a 2\\% to 3\\% performance enhancement in comparison to other benchmark methods.","url_abs":"https://arxiv.org/abs/2012.00822v4","url_pdf":"https://arxiv.org/pdf/2012.00822v4.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":"open-ended-multi-modal-relational-reason-for","repo_url":"https://github.com/robinzixuan/Video-Question-Answering-HRI","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"relational-reasoning","task_name":"Relational Reasoning"},{"task_slug":"video-question-answering","task_name":"Video Question Answering"},{"task_slug":"video-recognition","task_name":"Video Recognition"},{"task_slug":"visual-question-answering","task_name":"Visual Question Answering (VQA)"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}