{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T07:43:38Z","timestamp":1770191018385,"version":"3.49.0"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032141064","type":"print"},{"value":"9783032141071","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-14107-1_1","type":"book-chapter","created":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T19:37:18Z","timestamp":1770147438000},"page":"3-14","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GraphRAG-V: Fast Multi-hop Retrieval via\u00a0Text-Chunk Communities"],"prefix":"10.1007","author":[{"given":"Tengkai","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Venkatesh","family":"Srinivasan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex","family":"Thomo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,2,4]]},"reference":[{"key":"1_CR1","unstructured":"Achiam, J., et\u00a0al.: GPT-4 technical report. arXiv preprint arXiv:2303.08774 (2023)"},{"key":"1_CR2","unstructured":"Akesson, S., Santos, F.A.: Clustered retrieved augmented generation (CRAG). arXiv preprint arXiv:2406.00029 (2024)"},{"key":"1_CR3","unstructured":"Anonymous: Vlouvain: graph-free community detection for large vector collections. In: Proceedings under Double-Blind Review (2025). Preprint to be released post-review"},{"key":"1_CR4","unstructured":"Asai, A., Wu, Z., Wang, Y., Sil, A., Hajishirzi, H.: Self-RAG: learning to retrieve, generate, and critique through self-reflection. In: 12th International Conference on Learning Representations (2023)"},{"issue":"10","key":"1_CR5","doi-asserted-by":"publisher","first-page":"P10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","volume":"2008","author":"VD Blondel","year":"2008","unstructured":"Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech: Theory Exp. 2008(10), P10008 (2008)","journal-title":"J. Stat. Mech: Theory Exp."},{"key":"1_CR6","unstructured":"Brown, T., et al.: Language models are few-shot learners. In: NeurIPS, vol. 33, pp. 1877\u20131901 (2020)"},{"key":"1_CR7","doi-asserted-by":"crossref","unstructured":"Chen, J., Xiao, S., Zhang, P., Luo, K., Lian, D., Liu, Z.: BGE M3-embedding: multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation (2023)","DOI":"10.18653\/v1\/2024.findings-acl.137"},{"key":"1_CR8","unstructured":"Edge, D., et al.: From local to global: a graph rag approach to query-focused summarization. arXiv preprint arXiv:2404.16130 (2024)"},{"key":"1_CR9","unstructured":"Grattafiori, A., et\u00a0al.: The LLaMA 3 herd of models. arXiv preprint arXiv:2407.21783 (2024)"},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Guo, Z., Xia, L., Yu, Y., Ao, T., Huang, C.: LightRAG: simple and fast retrieval-augmented generation (2024)","DOI":"10.18653\/v1\/2025.findings-emnlp.568"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"Guti\u00e9rrez, B.J., Shu, Y., Gu, Y., Yasunaga, M., Su, Y.: HippoRAG: neurobiologically inspired long-term memory for large language models. In: NeurIPS (2024)","DOI":"10.52202\/079017-1902"},{"issue":"2","key":"1_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3703155","volume":"43","author":"L Huang","year":"2025","unstructured":"Huang, L., et al.: A survey on hallucination in large language models: principles, taxonomy, challenges, and open questions. ACM Trans. Inf. Syst. 43(2), 1\u201355 (2025)","journal-title":"ACM Trans. Inf. Syst."},{"key":"1_CR13","doi-asserted-by":"crossref","unstructured":"Huang, Y., Zhang, S., Xiao, X.: KET-RAG: a cost-efficient multi-granular indexing framework for graph-RAG. arXiv preprint arXiv:2502.09304 (2025)","DOI":"10.1145\/3711896.3737012"},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Karpukhin, V., et al.: Dense passage retrieval for open-domain question answering. In: EMNLP (1), pp. 6769\u20136781 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.550"},{"key":"1_CR15","unstructured":"Lewis, P., et al.: Retrieval-augmented generation for knowledge-intensive NLP tasks. In: NeurIPS, vol. 33, pp. 9459\u20139474 (2020)"},{"key":"1_CR16","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1162\/tacl_a_00638","volume":"12","author":"NF Liu","year":"2024","unstructured":"Liu, N.F., et al.: Lost in the middle: how language models use long contexts. Trans. Assoc. Comput. Linguist. 12, 157\u2013173 (2024)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"1_CR17","unstructured":"Ma, S., et al.: Think-on-graph 2.0: deep and faithful large language model reasoning with knowledge-guided retrieval augmented generation. arXiv preprint arXiv:2407.10805 (2024)"},{"issue":"4","key":"1_CR18","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1109\/TPAMI.2018.2889473","volume":"42","author":"YA Malkov","year":"2018","unstructured":"Malkov, Y.A., Yashunin, D.A.: Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE Trans. Pattern Anal. Mach. Intell. 42(4), 824\u2013836 (2018)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1_CR19","doi-asserted-by":"crossref","unstructured":"Mavromatis, C., Karypis, G.: GNN-RAG: graph neural retrieval for large language model reasoning. Preprint arXiv:2405.20139 (2024)","DOI":"10.18653\/v1\/2025.findings-acl.856"},{"issue":"23","key":"1_CR20","doi-asserted-by":"publisher","first-page":"8577","DOI":"10.1073\/pnas.0601602103","volume":"103","author":"ME Newman","year":"2006","unstructured":"Newman, M.E.: Modularity and community structure in networks. PNAS 103(23), 8577\u20138582 (2006)","journal-title":"PNAS"},{"key":"1_CR21","doi-asserted-by":"publisher","first-page":"1316","DOI":"10.1162\/tacl_a_00605","volume":"11","author":"O Ram","year":"2023","unstructured":"Ram, O., et al.: In-context retrieval-augmented language models. Trans. Assoc. Comput. Linguist. 11, 1316\u20131331 (2023)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Sentence-BERT: sentence embeddings using Siamese BERT-networks. arXiv preprint arXiv:1908.10084 (2019)","DOI":"10.18653\/v1\/D19-1410"},{"key":"1_CR23","doi-asserted-by":"crossref","unstructured":"Santhanam, K., Khattab, O., Saad-Falcon, J., Potts, C., Zaharia, M.: ColBERTv2: effective and efficient retrieval via lightweight late interaction. arXiv preprint arXiv:2112.01488 (2021)","DOI":"10.18653\/v1\/2022.naacl-main.272"},{"key":"1_CR24","unstructured":"Shi, W., et al.: REPLUG: retrieval-augmented black-box language models. arXiv preprint arXiv:2301.12652 (2023)"},{"key":"1_CR25","unstructured":"Song, K., Tan, X., Qin, T., Lu, J., Liu, T.Y.: MPNet: masked and permuted pre-training for language understanding. In: NeurIPS, vol. 33, pp. 16857\u201316867 (2020)"},{"key":"1_CR26","unstructured":"Tang, Y., Yang, Y.: Multihop-RAG: benchmarking retrieval-augmented generation for multi-hop queries. arXiv preprint arXiv:2401.15391 (2024)"},{"key":"1_CR27","unstructured":"Team, Q.: Qwen2.5: a party of foundation models (2024). https:\/\/qwenlm.github.io\/blog\/qwen2.5\/"},{"issue":"1","key":"1_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-019-41695-z","volume":"9","author":"VA Traag","year":"2019","unstructured":"Traag, V.A., Waltman, L., Van Eck, N.J.: From Louvain to Leiden: guaranteeing well-connected communities. Sci. Rep. 9(1), 1\u201312 (2019)","journal-title":"Sci. Rep."},{"key":"1_CR29","unstructured":"Wang, S., Fang, Y., Zhou, Y., Liu, X., Ma, Y.: ArchRAG: attributed community-based hierarchical retrieval-augmented generation. arXiv preprint arXiv:2502.09891 (2025)"},{"key":"1_CR30","doi-asserted-by":"crossref","unstructured":"Xiao, S., Liu, Z., Zhang, P., Muennighoff, N.: C-pack: packaged resources to advance general Chinese embedding (2023)","DOI":"10.1145\/3626772.3657878"},{"key":"1_CR31","doi-asserted-by":"crossref","unstructured":"Xiao, S., Liu, Z., Zhang, P., Xing, X.: LM-cocktail: resilient tuning of language models via model merging (2023)","DOI":"10.18653\/v1\/2024.findings-acl.145"},{"key":"1_CR32","unstructured":"Yang, A., et\u00a0al.: Qwen2 technical report. arXiv preprint arXiv:2407.10671 (2024)"},{"key":"1_CR33","unstructured":"Zhang, P., Xiao, S., Liu, Z., Dou, Z., Nie, J.Y.: Retrieve anything to augment large language models (2023)"},{"key":"1_CR34","unstructured":"Zhao, P., et al.: Retrieval-augmented generation for AI-generated content: a survey. preprint arXiv:2402.19473 (2024)"}],"container-title":["Lecture Notes in Computer Science","Social Networks Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-14107-1_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T19:37:22Z","timestamp":1770147442000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-14107-1_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032141064","9783032141071"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-14107-1_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"4 February 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ASONAM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advances in Social Networks Analysis and Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":", ON","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"asonam-12025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/asonam.cpsc.ucalgary.ca\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}