Reasoning-Modulated Representations
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Abstract (arXiv)
Neural networks leverage robust internal representations in order to generalise. Learning them is difficult, and often requires a large training set that covers the data distribution densely. We study a common setting where our task is not purely opaque. Indeed, very often we may have access to information about the underlying system (e.g. that observations must obey certain laws of physics) that any "tabula rasa" neural network would need to re-learn from scratch, penalising performance. We incorporate this information into a pre-trained reasoning module, and investigate its role in shaping the discovered representations in diverse self-supervised learning settings from pixels. Our approach paves the way for a new class of representation learning, grounded in algorithmic priors.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 46 of its 61 references that are in the map. First posted on arXiv 19 Jul 2021.
Builds on
46 of 61 references.
References · 46
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Citing papers per year: 2022: 4; 2023: 3; 2024: 4; 2025: 1; 2026: 1.
13 papers.
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- 2022The CLRS Algorithmic Reasoning Benchmarkcited by 106
- 2022A Generalist Neural Algorithmic Learnercited by 59
- 2022Graph Neural Networks are Dynamic Programmerscited by 55
- 2022Learning Symmetric Embeddings for Equivariant World Modelscited by 54
- 2023Neural Algorithmic Reasoning with Causal Regularisationcited by 31
- 2023Dual Algorithmic Reasoningcited by 21
- 2024Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systemscited by 13
- 2024On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methodscited by 11
- 2023Parallel Algorithms Align with Neural Executioncited by 6
- 2024Recurrent Aggregators in Neural Algorithmic Reasoningcited by 6
- 2026IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Videocited by 4
- 2024Open-Book Neural Algorithmic Reasoningcited by 3
1 more
- 2026IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video17 Mar 2026
- 2025Leveraging Classical Algorithms for Graph Neural Networks24 Oct 2025
- 2024Open-Book Neural Algorithmic Reasoning30 Dec 2024
- 2024Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems2 Oct 2024
- 2024Recurrent Aggregators in Neural Algorithmic Reasoning11 Sep 2024
- 2024On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods7 Mar 2024
- 2023Parallel Algorithms Align with Neural Execution8 Jul 2023
- 2023Neural Algorithmic Reasoning with Causal Regularisation20 Feb 2023
- 2023Dual Algorithmic Reasoning9 Feb 2023
- 2022A Generalist Neural Algorithmic Learner22 Sep 2022
- 2022The CLRS Algorithmic Reasoning Benchmark31 May 2022
- 2022Learning Symmetric Embeddings for Equivariant World Models24 Apr 2022
1 more
- 2022Graph Neural Networks are Dynamic Programmers29 Mar 2022
- 2023Neural Algorithmic Reasoning with Causal Regularisationcited by 31
- 2023Neural Algorithmic Reasoning with Causal Regularisation20 Feb 2023
- 2022Learning Symmetric Embeddings for Equivariant World Modelscited by 54
- 2022Learning Symmetric Embeddings for Equivariant World Models24 Apr 2022
- 2022The CLRS Algorithmic Reasoning Benchmarkcited by 106
- 2022A Generalist Neural Algorithmic Learnercited by 59
- 2022Graph Neural Networks are Dynamic Programmerscited by 55
- 2023Dual Algorithmic Reasoningcited by 21
- 2024Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systemscited by 13
- 2024On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methodscited by 11
- 2023Parallel Algorithms Align with Neural Executioncited by 6
- 2024Recurrent Aggregators in Neural Algorithmic Reasoningcited by 6
- 2026IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Videocited by 4
- 2024Open-Book Neural Algorithmic Reasoningcited by 3
- 2025Leveraging Classical Algorithms for Graph Neural Networkscited by 0
- 2026IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video17 Mar 2026
- 2025Leveraging Classical Algorithms for Graph Neural Networks24 Oct 2025
- 2024Open-Book Neural Algorithmic Reasoning30 Dec 2024
- 2024Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems2 Oct 2024
- 2024Recurrent Aggregators in Neural Algorithmic Reasoning11 Sep 2024
- 2024On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods7 Mar 2024
- 2023Parallel Algorithms Align with Neural Execution8 Jul 2023
- 2023Dual Algorithmic Reasoning9 Feb 2023
- 2022A Generalist Neural Algorithmic Learner22 Sep 2022
- 2022The CLRS Algorithmic Reasoning Benchmark31 May 2022
- 2022Graph Neural Networks are Dynamic Programmers29 Mar 2022