{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T05:44:53Z","timestamp":1782798293197,"version":"3.54.5"},"reference-count":50,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:00:00Z","timestamp":1779062400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:00:00Z","timestamp":1779062400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100003012","name":"Impact Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100003012","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,18]]},"DOI":"10.1109\/infocom59046.2026.11571683","type":"proceedings-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T19:38:15Z","timestamp":1782761895000},"page":"1-10","source":"Crossref","is-referenced-by-count":0,"title":["PPAI: Enabling Personalized LLM Agent Interoperability for Collaborative Edge Intelligence"],"prefix":"10.1109","author":[{"given":"Zile","family":"Wang","sequence":"first","affiliation":[{"name":"The Hong Kong University of Science and Technology,Department of Computer Science and Engineering,Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianli","family":"Liu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology,Department of Computer Science and Engineering,Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaibin","family":"Guo","sequence":"additional","affiliation":[{"name":"Sun Yat-Sen University,School of Software Engineering,China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haodong","family":"Wang","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology,Department of Computer Science and Engineering,Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Lin","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology,Department of Computer Science and Engineering,Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zicong","family":"Hong","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology,Department of Computer Science and Engineering,Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song","family":"Guo","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology,Department of Computer Science and Engineering,Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.acl-long.718"},{"key":"ref2","article-title":"Small language models are the future of agentic ai","author":"Belcak","year":"2025"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3680207.3723493"},{"key":"ref4","article-title":"Klotski: Efficient mixture-of-expert inference via expert-aware multi-batch pipeline","volume-title":"ASPLOS","author":"Fang"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"ref6","article-title":"Lora: Low-rank adaptation of large language models","volume-title":"ICLR","author":"Hu"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2011"},{"key":"ref8","article-title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","volume-title":"NeurIPS","author":"Lewis"},{"key":"ref9","article-title":"Self-rag: Learning to retrieve, generate, and critique through self-reflection","volume-title":"ICLR","author":"Asai"},{"key":"ref10","first-page":"68","article-title":"Incentives build robustness in bittorrent","volume-title":"P2P Econ","volume":"6","author":"Cohen"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45748-8_5"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/1082469.1082470"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.52202\/079017-2120"},{"key":"ref14","article-title":"Kabb: Knowledge-aware bayesian bandits for dynamic expert coordination in multi-agent systems","volume-title":"ICML","author":"Zhang"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1220"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.52202\/079017-1601"},{"key":"ref17","article-title":"Metagpt: Meta programming for a multi-agent collaborative framework","volume-title":"ICLR","author":"Hong"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.52202\/079017-0088"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3690624.3709171"},{"key":"ref20","article-title":"Minirag: Towards extremely simple retrieval-augmented generation","author":"Fan","year":"2025"},{"key":"ref21","article-title":"Gpipe: Efficient training of giant neural networks using pipeline parallelism","volume-title":"NeurIPS","author":"Huang"},{"key":"ref22","first-page":"578","article-title":"{TVM} : An automated {End-to-End} optimizing optimizing compiler for deep learning","volume-title":"OSDI 18","author":"Chen"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM55648.2025.11044533"},{"key":"ref24","article-title":"Optq: Accurate post-training quantization for generative pre-trained transformers","volume-title":"ICLR","author":"Frantar"},{"key":"ref25","article-title":"Minillm: Knowledge distillation of large language models","volume-title":"ICLR","author":"Gu"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.naacl-long.109"},{"key":"ref27","article-title":"Routellm: Learning to route llms from preference data","volume-title":"ICLR","author":"Ong"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.792"},{"key":"ref29","article-title":"Fusing models with complementary expertise","volume-title":"ICLR","author":"Wang"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.52202\/075280-0310"},{"key":"ref31","article-title":"Qwen2.5: A party of foundation models!","author":"Yang","year":"2025"},{"key":"ref32","article-title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning","author":"Guo","year":"2025"},{"key":"ref33","article-title":"Opencodereasoning: Advancing data distillation for competitive coding","author":"Ahmad","year":"2025"},{"key":"ref34","article-title":"Huatuogpt-o1, towards medical complex reasoning with llms","author":"Chen","year":"2024"},{"key":"ref35","article-title":"The llama 3 herd of models","author":"Dubey","year":"2024"},{"key":"ref36","article-title":"Sharegpt","year":"2024"},{"key":"ref37","article-title":"Prototypical networks for few-shot learning","volume-title":"NeurIPS","author":"Snell"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"ref39","article-title":"Tapnet: Neural network augmented with task-adaptive projection for few-shot learning","volume-title":"ICML","author":"Yoon"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.2003.1238221"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/506147.506153"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1017\/9781108591034"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"ref44","article-title":"Agglomerativeclustering","year":"2024"},{"key":"ref45","article-title":"Measuring massive multitask language understanding","volume-title":"ICLR","author":"Hendrycks"},{"key":"ref46","article-title":"Training verifiers to solve math word problems","author":"Cobbe","year":"2021"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.3390\/app11146421"},{"key":"ref48","article-title":"Think you have solved question answering? try arc, the ai2 reasoning challenge","author":"Clark","year":"2018"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-naacl.149"},{"key":"ref50","article-title":"More agents is all you need","volume-title":"TMLR","author":"Li"}],"event":{"name":"IEEE INFOCOM 2026 - IEEE Conference on Computer Communications","location":"Tokyo, Japan","start":{"date-parts":[[2026,5,18]]},"end":{"date-parts":[[2026,5,21]]}},"container-title":["IEEE INFOCOM 2026 - IEEE Conference on Computer Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11571071\/11571169\/11571683.pdf?arnumber=11571683","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T05:16:43Z","timestamp":1782796603000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11571683\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,18]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/infocom59046.2026.11571683","relation":{},"subject":[],"published":{"date-parts":[[2026,5,18]]}}}