IEEE

28 M Weights $\times$ TOPs $/ \mathrm{W}/\text{mm}^{2}$ PCM-Based Analog in-Memory Computing Core with 8 $512 \times 512{}$-Weight Layers in 28 nm FD-SOI CMOS

28 M Weights TOPs PCM-Based Analog in-Memory Computing Core with 8 -Weight Layers in 28 nm FD-SOI CMOS Abstract: In-Memory Computing (IMC) hardware accelerators for Deep Neural Networks (DNNs) require ...
IEEE

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models

Abstract: Today’s most advanced vision-language models (VLMs) remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good performance, ...