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README.md

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 ![teaser](https://cvlab-unibo.github.io/gmnerf/static/images/teaser.svg)
 
-This repository contains the datasets for the paper [Weight Space Representation Learning on Diverse NeRF Architectures](https://arxiv.org/abs/2502.09623). The paper proposes a framework that is capable of processing NeRFs with diverse architectures (MLPs, tri-planes, and hash tables) by training a graph metanetwork to obtain an architecture-agnostic latent space.
+This repository contains the datasets for the paper [Weight Space Representation Learning on Diverse NeRF Architectures](https://arxiv.org/abs/2502.09623), accepted at ICLR 2026. The paper proposes a framework that is capable of processing NeRFs with diverse architectures (MLPs, tri-planes, and hash tables) by training a graph metanetwork to obtain an architecture-agnostic latent space.
 
 ## NeRF weights