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In this paper, we propose EAGLE, a lightweight framework that integrates short-term temporal recency and long-term global structural patterns. EAGLE consists of a time-aware module that aggregates information from a node's most recent neighbors to reflect its immediate preferences, and a structure-aware module that leverages temporal personalized PageRank to capture the influence of globally important nodes. To balance these attributes, EAGLE employs an adaptive weighting mechanism to dynamically adjust their contributions based on data characteristics. Also, EAGLE eliminates the need for complex multi-hop message passing or memory-intensive mechanisms, enabling significant improvements in efficiency. Extensive experiments on seven real-world temporal graphs demonstrate that EAGLE consistently achieves superior performance against state-of-the-art T-GNNs in both effectiveness and efficiency, delivering more than a 50\u00d7 speedup over effective transformer-based T-GNNs.<\/jats:p>","DOI":"10.14778\/3748191.3748203","type":"journal-article","created":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T13:50:16Z","timestamp":1756993816000},"page":"3396-3405","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["When Speed Meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction"],"prefix":"10.14778","volume":"18","author":[{"given":"Haoyang","family":"Li","sequence":"first","affiliation":[{"name":"PolyU"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuming","family":"Xu","sequence":"additional","affiliation":[{"name":"PolyU &amp; SCUT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiming","family":"Li","sequence":"additional","affiliation":[{"name":"HKUST"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanmo","family":"Liu","sequence":"additional","affiliation":[{"name":"HKUST"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darian","family":"Li","sequence":"additional","affiliation":[{"name":"PolyU &amp; GDUT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen Jason","family":"Zhang","sequence":"additional","affiliation":[{"name":"PolyU"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Chen","sequence":"additional","affiliation":[{"name":"HKUST(GZ) &amp; FYTRI"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Li","sequence":"additional","affiliation":[{"name":"PolyU"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,9,4]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/3636218.3636223"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.14778\/3632093.3632108"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271740"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.14778\/3648160.3648173"},{"key":"e_1_2_1_5_1","volume-title":"The Eleventh International Conference on Learning Representations.","author":"Cong Weilin","year":"2023","unstructured":"Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, and Mehrdad Mahdavi. 2023. 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