{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T11:05:20Z","timestamp":1772276720380,"version":"3.50.1"},"reference-count":20,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T00:00:00Z","timestamp":1768089600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T00:00:00Z","timestamp":1768089600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,11]]},"DOI":"10.1109\/sii64115.2026.11404587","type":"proceedings-article","created":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T20:47:13Z","timestamp":1772225233000},"page":"1683-1688","source":"Crossref","is-referenced-by-count":0,"title":["Fast Action Generation via Knowledge Distillation with Flow Matching for Social Navigation"],"prefix":"10.1109","author":[{"given":"Yuki","family":"Tomita","sequence":"first","affiliation":[{"name":"Kyushu University,Graduate School of Information Science and Electrical Engineering,Fukuoka,Japan,819-0395"}]},{"given":"Kohei","family":"Matsumoto","sequence":"additional","affiliation":[{"name":"Kyushu University,Faculty of Information Science and Electrical Engineering,Fukuoka,Japan,819-0395"}]},{"given":"Yuki","family":"Hyodo","sequence":"additional","affiliation":[{"name":"Kyushu University,Graduate School of Information Science and Electrical Engineering,Fukuoka,Japan,819-0395"}]},{"given":"Kazuto","family":"Nakashima","sequence":"additional","affiliation":[{"name":"Kyushu University,Faculty of Information Science and Electrical Engineering,Fukuoka,Japan,819-0395"}]},{"given":"Ryo","family":"Kurazume","sequence":"additional","affiliation":[{"name":"Kyushu University,Faculty of Information Science and Electrical Engineering,Fukuoka,Japan,819-0395"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/icra.2019.8794134"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9340705"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561884"},{"key":"ref4","first-page":"6840","article-title":"Denoising diffusion probabilistic models","author":"Ho","year":"2020","journal-title":"Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref5","article-title":"COLSON: controllable learning-based social navigation via diffusion-based reinforcement learning","author":"Tomita","year":"2025","journal-title":"CoRR"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IROS58592.2024.10802676"},{"key":"ref7","article-title":"Score-based generative modeling through stochastic differential equations","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Song"},{"key":"ref8","article-title":"Planning with diffusion for flexible behavior synthesis","volume-title":"Proceedings of the International Conference on Machine Learnin (ICML)","author":"Janner"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2023.XIX.026"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610665"},{"key":"ref11","first-page":"7787","article-title":"Dippest: Diffusion-based path planner for synthesizing trajectories applied on quadruped robots","volume-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","author":"Xiong"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA55743.2025.11127466"},{"key":"ref13","article-title":"Progressive distillation for fast sampling of diffusion models","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Salimans"},{"key":"ref14","first-page":"32211","article-title":"Consistency models","volume-title":"Proceedings of the International Conference on Machine Learnin (ICML)","author":"Song"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.15607\/rss.2024.xx.071"},{"key":"ref16","article-title":"Flow straight and fast: Learning to generate and transfer data with rectified flow","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Liu"},{"key":"ref17","article-title":"Flow matching for generative modeling","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Lipman"},{"key":"ref18","first-page":"41163","article-title":"Learning a Diffusion Model Policy from Rewards via Q-Score Matching","volume-title":"Proceedings of the International Conference on Machine Learnin (ICML)","author":"Psenka"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19457-3_1"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9341689"}],"event":{"name":"2026 IEEE\/SICE International Symposium on System Integration (SII)","location":"Cancun, Mexico","start":{"date-parts":[[2026,1,11]]},"end":{"date-parts":[[2026,1,14]]}},"container-title":["2026 IEEE\/SICE International Symposium on System Integration (SII)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11404435\/11404394\/11404587.pdf?arnumber=11404587","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T06:45:55Z","timestamp":1772261155000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11404587\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,11]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/sii64115.2026.11404587","relation":{},"subject":[],"published":{"date-parts":[[2026,1,11]]}}}