189 citations · 201 across the 3 of their papers we have counts for
11 papers
UltRAG: a Universal Simple Scalable Recipe for Knowledge Graph RAG
Dobrik Georgiev, Kheeran Naidu, Alberto Cattaneo +3
Large language models (LLMs) frequently generate confident yet factually incorrect content when used for language generation (a phenomenon often known as hallucination). Retrieval…
Temporal Graph Networks for Deep Learning on Dynamic Graphs
Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca +3
Graph Neural Networks (GNNs) have recently become increasingly popular due to their ability to learn complex systems of relations or interactions arising in a broad spectrum of pro…
SIGN: Scalable Inception Graph Neural Networks
Fabrizio Frasca, Emanuele Rossi, Davide Eynard +3
Graph representation learning has recently been applied to a broad spectrum of problems ranging from computer graphics and chemistry to high energy physics and social media. The po…
ncRNA Classification with Graph Convolutional Networks
Emanuele Rossi, Federico Monti, Michael Bronstein +1
Non-coding RNA (ncRNA) are RNA sequences which don't code for a gene but instead carry important biological functions. The task of ncRNA classification consists in classifying a gi…
Fake News Detection on Social Media using Geometric Deep Learning
Federico Monti, Fabrizio Frasca, Davide Eynard +2
Social media are nowadays one of the main news sources for millions of people around the globe due to their low cost, easy access and rapid dissemination. This however comes at the…
Using Attribution to Decode Dataset Bias in Neural Network Models for Chemistry
Kevin McCloskey, Ankur Taly, Federico Monti +2
Deep neural networks have achieved state of the art accuracy at classifying molecules with respect to whether they bind to specific protein targets. A key breakthrough would occur…