activity
20132023
most citedA simple neural network module for relational reasoning

503 citations · 1.3k across the 34 of their papers we have counts for

collaborators
Showing 2022Show all

8 papers · 1 filter

cs.LG2022★ 4 cited

Leave Graphs Alone: Addressing Over-Squashing without Rewiring

Domenico Tortorella, Alessio Micheli

Recent works have investigated the role of graph bottlenecks in preventing long-range information propagation in message-passing graph neural networks, causing the so-called `over-…

cs.AI2022

A Simple, Yet Effective Approach to Finding Biases in Code Generation

Spyridon Mouselinos, Mateusz Malinowski, Henryk Michalewski

Recently, high-performing code generation systems based on large language models have surfaced. They are trained on massive corpora containing much more natural text than actual ex…

cs.CV2022

Compressed Vision for Efficient Video Understanding

Olivia Wiles, Joao Carreira, Iain Barr +2

Experience and reasoning occur across multiple temporal scales: milliseconds, seconds, hours or days. The vast majority of computer vision research, however, still focuses on indiv…

cs.LG2022

Neural Payoff Machines: Predicting Fair and Stable Payoff Allocations Among Team Members

Daphne Cornelisse, Thomas Rood, Mateusz Malinowski +2

In many multi-agent settings, participants can form teams to achieve collective outcomes that may far surpass their individual capabilities. Measuring the relative contributions of…

cs.CV2022★ 7 cited

CLIP-CLOP: CLIP-Guided Collage and Photomontage

Piotr Mirowski, Dylan Banarse, Mateusz Malinowski +2

The unabated mystique of large-scale neural networks, such as the CLIP dual image-and-text encoder, popularized automatically generated art. Increasingly more sophisticated generat…

cs.CV2022★ 18 cited

Transframer: Arbitrary Frame Prediction with Generative Models

Charlie Nash, João Carreira, Jacob Walker +4

We present a general-purpose framework for image modelling and vision tasks based on probabilistic frame prediction. Our approach unifies a broad range of tasks, from image segment…

cs.LG2022★ 1 cited

Measuring CLEVRness: Blackbox testing of Visual Reasoning Models

Spyridon Mouselinos, Henryk Michalewski, Mateusz Malinowski

How can we measure the reasoning capabilities of intelligence systems? Visual question answering provides a convenient framework for testing the model's abilities by interrogating…

cs.LG2022★ 34 cited

General-purpose, long-context autoregressive modeling with Perceiver AR

Curtis Hawthorne, Andrew Jaegle, Cătălina Cangea +12

Real-world data is high-dimensional: a book, image, or musical performance can easily contain hundreds of thousands of elements even after compression. However, the most commonly u…