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GraphRAG×Modeli Segment Anything×
FushaMësimi i thellëMësimi i thellë
FamiljaMachine learningMachine learning
Viti i origjinës20232023
KrijuesiYunfan GaoAlexander Kirillov
LlojiSystem architectureNeural network architecture
Burimi themeluesGao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., & Wang, M. (2023). Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv:2312.10997. link ↗Kirillov, A., Mintun, E., Darrell, T., & Girshick, R. (2023). Segment Anything. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 4015-4026). DOI ↗
Emërtime të tjeraGraph RAG, Knowledge Graph RAGSAM, Segment Anything
Të lidhura44
PërmbledhjaGraphRAG is a retrieval-augmented generation approach that augments large language models with knowledge graphs to improve answer quality and factuality. Rather than retrieving flat text passages, GraphRAG constructs and queries structured knowledge graphs extracted from documents, providing rich contextual information to the language model.Segment Anything Model (SAM) is a foundation model introduced by Kirillov et al. in 2023 that can segment any object in an image given various forms of prompts. SAM is trained on a massive dataset of diverse images and learns to segment objects based on minimal user input such as points, boxes, or text descriptions.
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ScholarGateKrahasoni metodat: GraphRAG · Segment Anything Model. Marrë më 2026-06-15 nga https://scholargate.app/sq/compare