{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T05:50:09Z","timestamp":1743054609598,"version":"3.40.3"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031442223"},{"type":"electronic","value":"9783031442230"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-44223-0_20","type":"book-chapter","created":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T05:01:41Z","timestamp":1695272501000},"page":"243-255","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Multi-Timestep-Ahead Prediction with\u00a0Mixture of\u00a0Experts for\u00a0Embodied Question Answering"],"prefix":"10.1007","author":[{"given":"Kanata","family":"Suzuki","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuya","family":"Kamiwano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naoya","family":"Chiba","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroki","family":"Mori","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tetsuya","family":"Ogata","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,22]]},"reference":[{"key":"20_CR1","unstructured":"Brohan, A., et al.: Rt-1: robotics transformer for real-world control at scale. arXiv preprint arXiv:2212.06817 (2022)"},{"key":"20_CR2","unstructured":"Brohan, A., et al.: Do as i can, not as i say: grounding language in robotic affordances. In: Proceedings of the Conference on Robot Learning (2022)"},{"key":"20_CR3","doi-asserted-by":"crossref","unstructured":"Chang, A., et al.: Matterport3d: learning from rgb-d data in indoor environments. In: Proceedings of the International Conference on 3D Vision (2017)","DOI":"10.1109\/3DV.2017.00081"},{"key":"20_CR4","doi-asserted-by":"crossref","unstructured":"Das, A., Datta, S., Gkioxari, G., Lee, S., Parikh, D., Batra, D.: Embodied question answering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1\u201310 (2018)","DOI":"10.1109\/CVPR.2018.00008"},{"key":"20_CR5","doi-asserted-by":"crossref","unstructured":"Das, A., Gkioxari, G., Lee, S., Parikh, D., Batra, D.: Neural modular control for embodied question answering. In: Proceedings of the Conference on Robot Learning, pp. 53\u201362 (2018)","DOI":"10.1109\/CVPR.2018.00008"},{"issue":"10","key":"20_CR6","doi-asserted-by":"publisher","first-page":"2201","DOI":"10.1162\/089976601750541778","volume":"13","author":"M Haruno","year":"2001","unstructured":"Haruno, M., Wolpert, D.M., Kawato, M.: Mosaic model for sensorimotor learning and control. Neural Comput. 13(10), 2201\u20132220 (2001)","journal-title":"Neural Comput."},{"key":"20_CR7","unstructured":"Hermann, K.M., et al.: Grounded language learning in simulated 3d world. arXiv preprint arXiv:1706.06551 (2017)"},{"key":"20_CR8","doi-asserted-by":"crossref","unstructured":"Hong, Y., Wang, Z., Wu, Q., Gould, S.: Bridging the gap between learning in discrete and continuous environments for vision-and-language navigation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 15439\u201315449 (2022)","DOI":"10.1109\/CVPR52688.2022.01500"},{"issue":"65","key":"20_CR9","doi-asserted-by":"publisher","first-page":"eaax8177","DOI":"10.1126\/scirobotics.aax8177","volume":"7","author":"H Ito","year":"2022","unstructured":"Ito, H., Yamamoto, K., Mori, H., Ogata, T.: Efficient multitask learning with an embodied predictive model for door opening and entry with whole-body control. Sci. Rob. 7(65), eaax8177 (2022)","journal-title":"Sci. Rob."},{"issue":"1","key":"20_CR10","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1162\/neco.1991.3.1.79","volume":"3","author":"RA Jacobs","year":"1991","unstructured":"Jacobs, R.A., Jordan, M.I., Nowlan, S.J., Hinton, G.E.: Adaptive mixtures of local experts. Neural Comput. 3(1), 79\u201387 (1991)","journal-title":"Neural Comput."},{"key":"20_CR11","doi-asserted-by":"crossref","unstructured":"Johannink, T., et al.: Residual reinforcement learning for robot control. In: Proceedings of the International Conference on Robotics and Automation, pp. 6023\u20136029 (2019)","DOI":"10.1109\/ICRA.2019.8794127"},{"key":"20_CR12","unstructured":"Kurita, S., Cho, K.: Generative language-grounded policy in vision-and-language navigation with bayes\u2019 rule. arXiv preprint arXiv:2009.07783 (2020)"},{"key":"20_CR13","unstructured":"Li, Z., Motoyoshi, T., Sasaki, K., Ogata, T., Sugano, S.: Rethinking self-driving: multi-task knowledge for better generalization and accident explanation ability. arXiv preprint arXiv:1809.11100 (2018)"},{"key":"20_CR14","doi-asserted-by":"crossref","unstructured":"Nguyen, K., Dey, D., Brockett, C., Dolan, B.: Vision-based navigation with language-based assistance via imitation learning with indirect intervention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12527\u201312537 (2019)","DOI":"10.1109\/CVPR.2019.01281"},{"key":"20_CR15","unstructured":"Okawa, Y., Sasaki, T., Iwane, H.: Control approach combining reinforcement learning and model-based control. In: Proceedings of the 12th Asian Control Conference, pp. 1419\u20131424 (2019)"},{"key":"20_CR16","doi-asserted-by":"crossref","unstructured":"Savva, M., et al.: Habitat: a platform for embodied AI research. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9339\u20139347 (2019)","DOI":"10.1109\/ICCV.2019.00943"},{"key":"20_CR17","doi-asserted-by":"crossref","unstructured":"Shen, W.B., Xu, D., Zhu, Y., Guibas, L.J., Fei-Fei, L., Savarese, S.: Situational fusion of visual representation for visual navigation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2881\u20132890 (2019)","DOI":"10.1109\/ICCV.2019.00297"},{"key":"20_CR18","doi-asserted-by":"crossref","unstructured":"Shridhar, M., et al.: Alfred: a benchmark for interpreting grounded instructions for everyday tasks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10740\u201310749 (2020)","DOI":"10.1109\/CVPR42600.2020.01075"},{"key":"20_CR19","unstructured":"Singh, K.P., Weihs, L., Herrasti, A., Choi, J., Kemhavi, A., Mottaghi, R.: Ask4help: learning to leverage an expert for embodied tasks. arXiv preprint arXiv:2211.09960 (2022)"},{"issue":"2","key":"20_CR20","doi-asserted-by":"publisher","first-page":"3475","DOI":"10.1109\/LRA.2021.3063702","volume":"6","author":"K Suzuki","year":"2021","unstructured":"Suzuki, K., Mori, H., Ogata, T.: Compensation for undefined behaviors during robot task execution by switching controllers depending on embedded dynamics in rnn. IEEE Rob. Autom. Lett. 6(2), 3475\u20133482 (2021)","journal-title":"IEEE Rob. Autom. Lett."},{"issue":"4","key":"20_CR21","doi-asserted-by":"publisher","first-page":"10930","DOI":"10.1109\/LRA.2022.3196159","volume":"7","author":"M Toyoda","year":"2022","unstructured":"Toyoda, M., Suzuki, K., Hayashi, Y., Ogata, T.: Bidirectional translation between descriptions and actions with small paired data. IEEE Rob. Autom. Lett. 7(4), 10930\u201310937 (2022)","journal-title":"IEEE Rob. Autom. Lett."},{"issue":"2","key":"20_CR22","doi-asserted-by":"publisher","first-page":"4225","DOI":"10.1109\/LRA.2021.3067862","volume":"6","author":"M Toyoda","year":"2021","unstructured":"Toyoda, M., Suzuki, K., Mori, H., Hayashi, Y., Ogata, T.: Embodying pre-trained word embeddings through robot actions. IEEE Rob. Autom. Lett. 6(2), 4225\u20134232 (2021)","journal-title":"IEEE Rob. Autom. Lett."},{"key":"20_CR23","doi-asserted-by":"crossref","unstructured":"Wang, X., et al.: Reinforced cross-modal matching and self-supervised imitation learning for vision-language navigation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6629\u20136638 (2019)","DOI":"10.1109\/CVPR.2019.00679"},{"key":"20_CR24","doi-asserted-by":"crossref","unstructured":"Wijmans, E., et al.: Embodied question answering in photorealistic environments with point cloud perception. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6652\u20136661 (2019)","DOI":"10.1109\/CVPR.2019.00682"},{"key":"20_CR25","doi-asserted-by":"crossref","unstructured":"Yamashita, Y., Tani, J.: Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment. PLoS Comput. Biol. 4(11), e000220-1\u2013e1000220-18 (2008)","DOI":"10.1371\/journal.pcbi.1000220"},{"key":"20_CR26","doi-asserted-by":"crossref","unstructured":"Yu, L., Chen, X., Gkioxari, G., Bansal, M., Berg, T.L., Batra, D.: Multi-target embodied question answering. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6309\u20136318 (2019)","DOI":"10.1109\/CVPR.2019.00647"},{"key":"20_CR27","doi-asserted-by":"crossref","unstructured":"Zhu, Y., et al.: Self-motivated communication agent for real-world vision-dialog navigation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1594\u20131603 (2021)","DOI":"10.1109\/ICCV48922.2021.00162"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-44223-0_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T06:13:52Z","timestamp":1695276832000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-44223-0_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031442223","9783031442230"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-44223-0_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"22 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Heraklion","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"32","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easyacademia.org","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"947","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"426","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"22","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"45% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"type of other papers accepted  : 9 Abstract","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}