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Add revision for 2026.acl-long.244 #9041

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2 changes: 2 additions & 0 deletions data/xml/2026.acl.xml
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<pages>5385-5394</pages>
<abstract>In recent years, CLIP-based text-video retrieval methods have developed rapidly, with research focusing on constructing diverse features and achieving effective interactions. However, the asymmetry of cross-modal information poses a challenge to accurately establishing retrieval relationships. To overcome this challenge, we propose a novel video retrieval framework, termed the Dual-Pathway and Dual-View model (DPDV), which consists of the Dual-Pathway Partitioning Module (DPPM) for constructing features at an appropriate granularity and the Dual-View Interaction Module (DVIM) for performing effective feature interactions. For DPPM, we simulate a human macro-level cognitive perspective by partitioning visual features into two categories based on their relevance to the text query and supplementing less relevant features with additional textual information. For DVIM, we simulate a human alignment strategy from macro to micro levels, focusing on local visual features while comprehensively modeling fine-grained interactions. We evaluate DPDV on five benchmark datasets, achieving leading retrieval performance.</abstract>
<url hash="0efa54b1">2026.acl-long.244</url>
<revision id="1" href="2026.acl-long.244v1" hash="bb8814fc"/>
<revision id="2" href="2026.acl-long.244v2" hash="0efa54b1" date="2026-07-07">This revision replaces an incorrectly uploaded PDF with the correct camera-ready version for this publication.</revision>
<attachment hash="57599c0f" type="checklist">2026.acl-long.244.checklist.pdf</attachment>
<bibkey>xie-etal-2026-dpdv</bibkey>
<doi>10.18653/v1/2026.acl-long.244</doi>
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