most citedTransformers meet Neural Algorithmic Reasoners

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20241 cited

Amplifying human performance in combinatorial competitive programming

Petar Veličković, Alex Vitvitskyi, Larisa Markeeva +4

Recent years have seen a significant surge in complex AI systems for competitive programming, capable of performing at admirable levels against human competitors. While steady prog…

cs.CL20243 cited

Transformers meet Neural Algorithmic Reasoners

Wilfried Bounsi, Borja Ibarz, Andrew Dudzik +5

Transformers have revolutionized machine learning with their simple yet effective architecture. Pre-training Transformers on massive text datasets from the Internet has led to unma…

cs.LG2024

The CLRS-Text Algorithmic Reasoning Language Benchmark

Larisa Markeeva, Sean McLeish, Borja Ibarz +7

Eliciting reasoning capabilities from language models (LMs) is a critical direction on the path towards building intelligent systems. Most recent studies dedicated to reasoning foc…

cs.RO2023

TT-SDF2PC: Registration of Point Cloud and Compressed SDF Directly in the Memory-Efficient Tensor Train Domain

Alexey I. Boyko, Anastasiia Kornilova, Rahim Tariverdizadeh +4

This paper addresses the following research question: ``can one compress a detailed 3D representation and use it directly for point cloud registration?''. Map compression of the sc…

cs.CV2023

Laser: Latent Set Representations for 3D Generative Modeling

Pol Moreno, Adam R. Kosiorek, Heiko Strathmann +6

NeRF provides unparalleled fidelity of novel view synthesis: rendering a 3D scene from an arbitrary viewpoint. NeRF requires training on a large number of views that fully cover a…