Papers › A simple neural network module for relational reasoning
A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G. T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, Timothy Lillicrap
Relational reasoning is a central component of generally intelligent behavior, but has proven difficult for neural networks to learn. In this paper we describe how to use Relation Networks (RNs) as a simple plug-and-play module to solve problems that fundamentally hinge on relational reasoning. We tested RN-augmented networks on three tasks: visual question answering using a challenging dataset called CLEVR, on which we achieve state-of-the-art, super-human performance; text-based question answering using the bAbI suite of tasks; and complex reasoning about dynamic physical systems. Then, using a curated dataset called Sort-of-CLEVR we show that powerful convolutional networks do not have a general capacity to solve relational questions, but can gain this capacity when augmented with RNs. Our work shows how a deep learning architecture equipped with an RN module can implicitly discover and learn to reason about entities and their relations.
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Image Retrieval with Multi-Modal Query | Fashion200k | Relationship | Recall@1 | 13 | #5 of 8 | Archive leaderboard | report |
| Image Retrieval with Multi-Modal Query | Fashion200k | Relationship | Recall@10 | 40.5 | #5 of 8 | Archive leaderboard | report |
| Image Retrieval with Multi-Modal Query | Fashion200k | Relationship | Recall@50 | 62.4 | #5 of 8 | Archive leaderboard | report |
| Visual Question Answering (VQA) | CLEVR | CNN + LSTM + RN | Accuracy | 95.50 | #14 of 15 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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