{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T13:57:00Z","timestamp":1787061420165,"version":"3.56.0"},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["24511103400"],"award-info":[{"award-number":["24511103400"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52405029"],"award-info":[{"award-number":["52405029"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011415","name":"State Key Laboratory of Mechanical System and Vibration","doi-asserted-by":"publisher","award":["MSVZD202608"],"award-info":[{"award-number":["MSVZD202608"]}],"id":[{"id":"10.13039\/501100011415","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1109\/lra.2026.3700379","type":"journal-article","created":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T19:57:26Z","timestamp":1780603046000},"page":"8864-8871","source":"Crossref","is-referenced-by-count":1,"title":["RLRC: Reinforcement Learning-Based Recovery for Compressed Vision-Language-Action Models"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-9418-1686","authenticated-orcid":false,"given":"Yuxuan","family":"Chen","sequence":"first","affiliation":[{"name":"State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9771-3489","authenticated-orcid":false,"given":"Yixin","family":"Han","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6179-9053","authenticated-orcid":false,"given":"Yize","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2565-9883","authenticated-orcid":false,"given":"Xiao","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"2165","article-title":"RT-2: Vision-language-action models transfer web knowledge to robotic control","volume-title":"Proc. 7th Conf. Robot Learn. (CoRL 2023). Proc. Mach. Learn. Res.","volume":"229","author":"Zitkovich","year":"2023"},{"key":"ref2","first-page":"2679","article-title":"OpenVLA: An open-source vision-language-action model","volume-title":"Proc. 8th Conf. Robot Learn. (CoRL 2024). Proc. Mach. Learn. Res.","volume":"270","author":"Kim","year":"2024"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2025.XXI.017"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.15607\/rss.2025.xxi.010"},{"key":"ref5","article-title":"SmolVLA: A vision-language-action model for affordable and efficient robotics","author":"Shukor","year":"2025"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2025.3544909"},{"key":"ref7","article-title":"Quantization-aware imitation-learning for resource-efficient robotic control","author":"Park","year":"2024"},{"key":"ref8","article-title":"VLA-Cache: Efficient vision- language-action manipulation via adaptive token caching","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NeurIPS)","author":"Xu","year":"2025"},{"key":"ref9","article-title":"Think twice, act once: Token-aware compression and action reuse for efficient inference in vision-language-action models","author":"Tan","year":"2025"},{"key":"ref10","article-title":"GR00T N1: An open foundation model for generalist humanoid robots","author":"Bjorck","year":"2025"},{"key":"ref11","article-title":"GPTQ: Accurate post-training quantization for generative pre-trained transformers","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Frantar","year":"2023"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.26"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.52202\/075280-0950"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i10.28960"},{"key":"ref15","article-title":"EfficientVLA: Training-free acceleration and compression for vision-language-action models","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NeurIPS)","author":"Yang","year":"2025"},{"key":"ref16","article-title":"The better you learn, the smarter you prune: Towards efficient vision-language-action models via differentiable token pruning","author":"Jiang","year":"2025"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA55743.2025.11127299"},{"key":"ref18","article-title":"RLinf-VLA: A unified and efficient framework for VLARL training","author":"Zang","year":"2025"},{"key":"ref19","article-title":"What can RL bring to VLA generalization? An empirical study","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NeurIPS)","author":"Liu","year":"2025"},{"key":"ref20","article-title":"A simple and effective pruning approach for large language models","volume-title":"Proc. 12th Int. Conf. Learn. Representations (ICLR)","author":"Sun","year":"2024"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1939"},{"key":"ref22","first-page":"30318","article-title":"LLM.int8(): 8-bit matrix multiplication for transformers at scale","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NeurIPS)","volume":"35","author":"Dettmers","year":"2022"},{"key":"ref23","article-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017"},{"key":"ref24","article-title":"$\\pi$RL: Online rl fine-tuning for flow-based vision-language-action models","author":"Chen","year":"2025"},{"key":"ref25","article-title":"TwinRL-VLA: Digital twin-driven reinforcement learning for real-world robotic manipulation","author":"Xu","year":"2026"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2025.XXI.021"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.15607\/rss.2025.xxi.012"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.15607\/rss.2025.xxi.011"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02096"},{"key":"ref30","article-title":"VLA-OS: Structuring and dissecting planning representations and paradigms in vision-language-action models","volume-title":"Proc. 39th Annu. Conf. Neural Inf. Process. Syst.","author":"Gao","year":"2025"},{"key":"ref31","article-title":"SP-VLA: A joint model scheduling and token pruning approach for VLA model acceleration","volume-title":"Proc. Int. Conf. Learn. Representations (ICLR)","author":"Li","year":"2026"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.52202\/075280-0441"},{"issue":"2730","key":"ref33","first-page":"17","article-title":"$\\pi _{0.5}$: A vision-language-action model with open-world generalization","volume-title":"Proc. 9th Conf. Robot Learn.","volume":"305","author":"Black","year":"2025"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7083369\/11520964\/11551322.pdf?arnumber=11551322","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T04:47:17Z","timestamp":1781585237000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11551322\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":33,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/lra.2026.3700379","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"value":"2377-3766","type":"electronic"},{"value":"2377-3774","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7]]}}}