Tootfinder

Stereo sound event localization and detection based on PSELDnet pretraining and BiMamba sequence modeling
Wenmiao Gao, Yang Xiao
https://arxiv.org/abs/2506.13455

Stereo sound event localization and detection based on PSELDnet pretraining and BiMamba sequence modeling
Pre-training methods have achieved significant performance improvements in sound event localization and detection (SELD) tasks, but existing Transformer-based models suffer from high computational complexity. In this work, we propose a stereo sound event localization and detection system based on pre-trained PSELDnet and bidirectional Mamba sequence modeling. We replace the Conformer module with a BiMamba module and introduce asymmetric convolutions to more effectively model the spatiotemporal …

Tja, da die #Wildpolulationen die riesigen landwirtschaftlichen Flächen nicht bestäuben können, fährt man #Bienenvölker spazieren.
Nach dem Unfall eines Lkw mit rund 14 Millionen #Honigbienen

Washington: 250 million honeybees escape overturned truck in US
Master bee-keepers are called to the scene after a truck containing 70,000 pounds of active honey bee hives flipped over.

Adapting General-Purpose Embedding Models to Private Datasets Using Keyword-based Retrieval
Yubai Wei, Jiale Han, Yi Yang
https://arxiv.org/abs/2506.00363 …

Adapting General-Purpose Embedding Models to Private Datasets Using Keyword-based Retrieval
Text embedding models play a cornerstone role in AI applications, such as retrieval-augmented generation (RAG). While general-purpose text embedding models demonstrate strong performance on generic retrieval benchmarks, their effectiveness diminishes when applied to private datasets (e.g., company-specific proprietary data), which often contain specialized terminology and lingo. In this work, we introduce BMEmbed, a novel method for adapting general-purpose text embedding models to private data…