**BLOOM** is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of
sources in 46 natural and 13 programming languages (59 in total).

**BRepNet** is a neural network for CAD applications. It is designed to operate directly on B-rep data structures, avoiding the need to approximate the model as meshes or point clouds. BRepNet defines convolutional kernels with respect to oriented coedges in the data structure. In the neighborhood of each coedge, a small collection of faces, edges and coedges can be identified and patterns in the feature vectors from these entities detected by specific learnable parameters.

BRepNet

BRepNet: A topological message passing system for solid models

BLOOM

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

CP with N3 Regularizer and Relation Prediction

Source	BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Year	2000
Data Source	CC BY-SA - https://paperswithcode.com