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MambaPSA replaces C2PSA in YOLO26, boosting efficiency with Mamba integration

By PulseAugur Editorial · [2 sources] ·

Researchers have developed MambaPSA, a new component designed to replace the C2PSA block in the YOLO26 object detection framework. This Mamba-based module offers improved efficiency by reducing parameters and FLOPs, leading to a significant increase in CPU inference throughput with minimal impact on accuracy. Further enhancements were achieved by incorporating a bidirectional Vision Mamba (BiViM) module, which resulted in notable accuracy gains on the PASCAL VOC dataset. AI

IMPACT This research demonstrates the potential of state space models like Mamba to improve the efficiency of object detection frameworks without sacrificing accuracy.

RANK_REASON The cluster contains an arXiv paper detailing a new model component for an existing framework.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

MambaPSA replaces C2PSA in YOLO26, boosting efficiency with Mamba integration

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The cluster contains an arXiv paper detailing a new model component for an existing framework.
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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Sheng-Wei Chan, Chia-Min Lin, Hsin-Jui Pan, Ching-Yu Tsai, Chih-Hsiang Yang, Yung-Che Wang, Jen-Shiun Chiang ·

    MambaPSA: A Mamba-based Replacement for C2PSA in YOLO26

    arXiv:2607.12681v1 Announce Type: new Abstract: State space models (SSMs), notably Mamba, have recently emerged as efficient alternatives to self-attention with linear computational complexity. We investigate the integration of Mamba into YOLO26, the latest non-maximum suppressio…

  2. arXiv cs.CV TIER_1 English(EN) · Jen-Shiun Chiang ·

    MambaPSA: A Mamba-based Replacement for C2PSA in YOLO26

    State space models (SSMs), notably Mamba, have recently emerged as efficient alternatives to self-attention with linear computational complexity. We investigate the integration of Mamba into YOLO26, the latest non-maximum suppression (NMS)-free object detection framework, by prop…

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