1 code implementation • NeurIPS 2023 • Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik
This reflects an impaired mapping between linguistic binding of entities and modifiers in the prompt and visual binding of the corresponding elements in the generated image.
no code implementations • 1 Mar 2023 • Daniel Glickman, Eran Yahav
The dominant paradigm for machine learning on graphs uses Message Passing Graph Neural Networks (MP-GNNs), in which node representations are updated by aggregating information in their local neighborhood.
Ranked #2 on Link Prediction on PCQM-Contact