{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T08:43:01Z","timestamp":1759826581046},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p>Generalization beyond in-domain experience to out-of-distribution data is of paramount significance in the AI domain. Of late, state-of-the-art Visual Question Answering (VQA) models have shown impressive performance on in-domain data, partially due to the language prior bias which, however, hinders the generalization ability in practice. This paper attempts to provide new insights into the influence of language modality on VQA performance from an empirical study perspective. To achieve this, we conducted a series of experiments on six models. The results of these experiments revealed that, 1) apart from prior bias caused by question types, there is a notable influence of postfix-related bias in inducing biases, and 2) training VQA models with word-sequence-related variant questions demonstrated improved performance on the out-of-distribution benchmark, and the LXMERT even achieved a 10-point gain without adopting any debiasing methods. We delved into the underlying reasons behind these experimental results and put forward some simple proposals to reduce the models' dependency on language priors. The experimental results demonstrated the effectiveness of our proposed method in improving performance on the out-of-distribution benchmark, VQA-CPv2.  We hope this study can inspire novel insights for future research on designing bias-reduction approaches.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/457","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:31:30Z","timestamp":1691742690000},"page":"4109-4117","source":"Crossref","is-referenced-by-count":3,"title":["An Empirical Study on the Language Modal in Visual Question Answering"],"prefix":"10.24963","author":[{"given":"Daowan","family":"Peng","sequence":"first","affiliation":[{"name":"Cognitive Computing and Intelligent Information Processing (CCIIP) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology"},{"name":"Joint Laboratory of HUST and Pingan Property & Casualty Research (HPL)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wei","sequence":"additional","affiliation":[{"name":"Cognitive Computing and Intelligent Information Processing (CCIIP) Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology"},{"name":"Joint Laboratory of HUST and Pingan Property & Casualty Research (HPL)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xian-Ling","family":"Mao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Beijing Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanyuan","family":"Fu","sequence":"additional","affiliation":[{"name":"Joint Laboratory of HUST and Pingan Property & Casualty Research (HPL)"},{"name":"Ping An Property&Casualty Insurance Company of China, Ltd"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dangyang","family":"Chen","sequence":"additional","affiliation":[{"name":"Joint Laboratory of HUST and Pingan Property & Casualty Research (HPL)"},{"name":"Ping An Property&Casualty Insurance Company of China, Ltd"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2023","name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","start":{"date-parts":[[2023,8,19]]},"theme":"Artificial Intelligence","location":"Macau, SAR China","end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:48:59Z","timestamp":1691743739000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/457"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/457","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}