{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T17:33:58Z","timestamp":1783791238971,"version":"3.55.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>The proliferation of edge devices has generated an unprecedented volume of time series data across different domains, motivating a variety of well-customized methods. Recently, Large Language Models (LLMs) have emerged as a new paradigm for time series analytics by leveraging the shared sequential nature of textual data and time series. However, a fundamental cross-modality gap between time series and LLMs exists, as LLMs are pre-trained on textual corpora and are not inherently optimized for time series. Many recent proposals are designed to address this issue. In this survey, we provide an up-to-date overview of LLMs-based cross-modality modeling for time series analytics. We first introduce a taxonomy that classifies existing approaches into four groups based on the type of textual data employed for time series modeling. We then summarize key cross-modality strategies, e.g., alignment and fusion, and discuss their applications across a range of downstream tasks. Furthermore, we conduct experiments on multimodal datasets from different application domains to investigate effective combinations of textual data and cross-modality strategies for enhancing time series analytics. Finally, we suggest several promising directions for future research. This survey is designed for a range of professionals, researchers, and practitioners interested in LLM-based time series modeling.<\/jats:p>","DOI":"10.24963\/ijcai.2025\/1173","type":"proceedings-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:10:40Z","timestamp":1758269440000},"page":"10564-10572","source":"Crossref","is-referenced-by-count":7,"title":["Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era"],"prefix":"10.24963","author":[{"given":"Chenxi","family":"Liu","sequence":"first","affiliation":[{"name":"S-Lab, Nanyang Technological University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaowen","family":"Zhou","sequence":"additional","affiliation":[{"name":"S-Lab, Nanyang Technological University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianxiong","family":"Xu","sequence":"additional","affiliation":[{"name":"S-Lab, Nanyang Technological University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"Miao","sequence":"additional","affiliation":[{"name":"Aalborg University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Long","sequence":"additional","affiliation":[{"name":"S-Lab, Nanyang Technological University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyue","family":"Li","sequence":"additional","affiliation":[{"name":"Technical University of Munich"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Zhao","sequence":"additional","affiliation":[{"name":"SenseTime Research"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-Fourth International Joint Conference on Artificial Intelligence {IJCAI-25}","theme":"Artificial Intelligence","location":"Montreal, Canada","acronym":"IJCAI-2025","number":"34","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2025,8,16]]},"end":{"date-parts":[[2025,8,22]]}},"container-title":["Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T11:36:21Z","timestamp":1758627381000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2025\/1173"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2025\/1173","relation":{},"subject":[],"published":{"date-parts":[[2025,9]]}}}