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๐Ÿ•ธ๏ธ Graph Learning

๐ŸŽž๏ธ ECCV2026 ยท 1 paper notes

๐Ÿ“Œ Same area in other venues: ๐Ÿ“ท CVPR2026 (8) ยท ๐Ÿ”ฌ ICLR2026 (118) ยท ๐Ÿ’ฌ ACL2026 (24) ยท ๐Ÿงช ICML2026 (35) ยท ๐Ÿค– AAAI2026 (37) ยท ๐Ÿง  NeurIPS2025 (54)

MG2-RAG: Multi-Granularity Graph for Multimodal Retrieval-Augmented Generation

Addressing the issues of flat vector retrieval overlooking structural dependencies and traditional graph methods discarding visual details through costly MLLM triplet extraction, MG2-RAG integrates lightweight dependency parsing with entity-driven open-vocabulary segmentation into unified multimodal nodes, enabling low-cost, high-fidelity multi-hop retrieval and reasoning via dense similarity aggregation and Personalized PageRank.