{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T09:27:59Z","timestamp":1773998879409,"version":"3.50.1"},"reference-count":16,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100009950","name":"Ministry of Education","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009950","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,8]]},"DOI":"10.1109\/globecom59602.2025.11432543","type":"proceedings-article","created":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T20:04:01Z","timestamp":1773950641000},"page":"3873-3878","source":"Crossref","is-referenced-by-count":0,"title":["Serving Long-Context LLMs at the Mobile Edge: Test-Time Reinforcement Learning-based Model Caching and Inference Offloading"],"prefix":"10.1109","author":[{"given":"Minrui","family":"Xu","sequence":"first","affiliation":[{"name":"Nanyang Technological University,College of Computing and Data Science"}]},{"given":"Dusit","family":"Niyato","sequence":"additional","affiliation":[{"name":"Nanyang Technological University,College of Computing and Data Science"}]},{"given":"Christopher G.","family":"Brinton","sequence":"additional","affiliation":[{"name":"Purdue University,Elmore Family School of Electrical and Computer Engineering"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.005.2400019"},{"key":"ref2","first-page":"1877","article-title":"Language models are few-shot learners","volume":"33","author":"Brown","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref3","article-title":"Sparks of artificial general intelligence: Early experiments with gpt-4","author":"Bubeck","year":"2023"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2024.3465447"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM52122.2024.10621342"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ton.2025.3649068"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3189186"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2023.3323757"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.52202\/068431-1800"},{"key":"ref10","article-title":"Self-consistency improves chain of thought reasoning in language models","author":"Wang","year":"2022"},{"key":"ref11","article-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017"},{"key":"ref12","article-title":"Learning to (learn at test time): Rnns with expressive hidden states","author":"Sun","year":"2024"},{"key":"ref13","article-title":"Are transformers universal approximators of sequence-to-sequence functions?","volume-title":"International Conference on Learning Representations","author":"Yun"},{"key":"ref14","article-title":"Why can large language models generate correct chain-of-thoughts?","author":"Tutunov","year":"2023"},{"key":"ref15","article-title":"A latent space theory for emergent abilities in large language models","author":"Jiang","year":"2023"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01457"}],"event":{"name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","location":"Taipei, Taiwan","start":{"date-parts":[[2025,12,8]]},"end":{"date-parts":[[2025,12,12]]}},"container-title":["GLOBECOM 2025 - 2025 IEEE Global Communications Conference"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11431620\/11431622\/11432543.pdf?arnumber=11432543","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T05:49:46Z","timestamp":1773985786000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11432543\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,8]]},"references-count":16,"URL":"https:\/\/doi.org\/10.1109\/globecom59602.2025.11432543","relation":{},"subject":[],"published":{"date-parts":[[2025,12,8]]}}}