Nexdata, a leading global provider of high-quality AI training data, today announced its participation as a Business ...

Microsoft's Phi-4-reasoning-vision-15B uses careful data curation and selective reasoning to compete with models trained on five times more data, reshaping the small AI playbook.

This efficiency makes it viable for enterprises to move beyond generic off-the-shelf solutions and develop specialized models that are deeply aligned with their specific data domains ...

Discover the groundbreaking concepts behind "Attention Is All You Need," the 2017 Google paper that introduced the ...

Citation O. Taran, S. Bonev, and S. Voloshynovskiy, "Clonability of anti-counterfeiting printable graphical codes: a machine learning approach," in Proc. IEEE International Conference on Acoustics, ...

This paper introduces a refined graph encoder embedding method, enhancing the original graph encoder embedding through linear transformation, self-training, and hidden community recovery within ...

Hi, thanks for sharing this great work! I noticed that there are two versions of the checkpoints provided: dinov3 and vitl. Could you please clarify whether the image encoder (e.g., DINOv3 or ViT-L) ...

The developed model modified Schrödinger bridge-type diffusion models to add noise to real data through the encoder and reconstructed samples through the decoder. It uses two objective functions, the ...

Why was a new multilingual encoder needed? XLM-RoBERTa (XLM-R) has dominated multilingual NLP for more than 5 years, an unusually long reign in AI research. While encoder-only models like BERT and ...

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...

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