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Neural algorithmic reasoning is an emerging area of machine learning focusing on building models that can imitate the execution of classic algorithms, such as sorting, shortest paths, etc.
On the shortest spanning subtree of a graph and the traveling salesman problem
J. B. Kruskal · 1956
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Shortest connection networks and some generalizations
R. C. Prim · 1957
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A note on two problems in connexion with graphs
E. W. Dijkstra · 1959
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Graph theory
F. Harary · 1969
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W. Zaremba and I. Sutskever · 2014
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Ł. Kaiser and I. Sutskever · 2015
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Neural arithmetic logic units
A. Trask, F. Hill, S. E. Reed, J. Rae, C. Dyer, and P. Blunsom · 2018
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Unsupervised feature learning via non-parametric instance discrimination
Z. Wu, Y. Xiong, S. X. Yu, and D. Lin · 2018
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Attention, learn to solve routing problems!
W. Kool, H. van Hoof, and M. Welling · 2019
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D. Georgiev and P. Lió · 2020
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Generative language modeling for automated theorem proving
S. Polu and I. Sutskever · 2020
Cited alongside, same era.
Neural execution of graph algorithms
P. Veličković, R. Ying, M. Padovano, R. Hadsell, and C. Blundell · 2020
Cited alongside, same era.
What can neural networks reason about?
K. Xu, J. Li, M. Zhang, S. S. Du, K.-i. Kawarabayashi, and S. Jegelka · 2020
Cited alongside, same era.
Neural execution engines: Learning to execute subroutines
Y. Yan, K. Swersky, D. Koutra, P. Ranganathan, and M. Hashemi · 2020
Cited alongside, same era.
Representation learning via invariant causal mechanisms
J. Mitrovic, B. McWilliams, J. C. Walker, L. H. Buesing, and C. Blundell · 2021
Cited alongside, same era.
Neural algorithmic reasoning
P. Veličković and C. Blundell · 2021
Cited alongside, same era.
Solving quantitative reasoning problems with language models
A. Lewkowycz, A. Andreassen, D. Dohan, E. Dyer, H. Michalewski, V. Ramasesh, A. Slone, C. Anil, I. Schlag, T. Gutman-Solo, et al · 2022
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The CLRS algorithmic reasoning benchmark
P. Veličković, A. P. Badia, D. Budden, R. Pascanu, A. Banino, M. Dashevskiy, R. Hadsell, and C. Blundell · 2022
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Emergent abilities of large language models
J. Wei, Y. Tay, R. Bommasani, C. Raffel, B. Zoph, S. Borgeaud, D. Yogatama, M. Bosma, D. Zhou, D. Metzler, E. H. Chi, T. Hashimoto, O. Vinyals, P. Liang, J. Dean, and W. Fedus · 2022
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Neural algorithmic reasoning with causal regularisation
B. Bevilacqua, K. Nikiforou, B. Ibarz, I. Bica, M. Paganini, C. Blundell, J. Mitrovic, and P. Veličković · 2023
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Relational attention: Generalizing transformers for graph-structured tasks
C. Diao and R. Loynd · 2023
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Benchmarking graph neural networks
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How to transfer algorithmic reasoning knowledge to learn new algorithms?
L.-P. Xhonneux, A.-I. Deac, P. Veličković, and J. Tang · 2021
Cited alongside, same era.
Graph neural networks are dynamic programmers
A. J. Dudzik and P. Veličković · 2022
Cited alongside, same era.
Training compute-optimal large language models
J. Hoffmann, S. Borgeaud, A. Mensch, E. Buchatskaya, T. Cai, E. Rutherford, D. d. L. Casas, L. A. Hendricks, J. Welbl, A. Clark, et al · 2022
Cited alongside, same era.
A generalist neural algorithmic learner
B. Ibarz, V. Kurin, G. Papamakarios, K. Nikiforou, M. Bennani, R. Csordás, A. J. Dudzik, M. Bošnjak, A. Vitvitskyi, Y. Rubanova, et al · 2022
Cited alongside, same era.
A simple framework for contrastive learning of visual representations
T. Chen, S. Kornblith, M. Norouzi, and G. Hinton
Cited in the paper.
Can graph neural networks count substructures?
Z. Chen, L. Chen, S. Villar, and J. Bruna
Cited in the paper.
V. P. Dwivedi, C. K. Joshi, A. T. Luu, T. Laurent, Y. Bengio, and X. Bresson · 2023
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Draft, sketch, and prove: Guiding formal theorem provers with informal proofs
A. Q. Jiang, S. Welleck, J. P. Zhou, T. Lacroix, J. Liu, W. Li, M. Jamnik, G. Lample, and Y. Wu · 2023
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Towards better out-of-distribution generalization of neural algorithmic reasoning tasks
S. Mahdavi, K. Swersky, T. Kipf, M. Hashemi, C. Thrampoulidis, and R. Liao · 2023
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Dual algorithmic reasoning
D. Numeroso, D. Bacciu, and P. Veličković · 2023
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Llama: Open and efficient foundation language models
H. Touvron, T. Lavril, G. Izacard, X. Martinet, M.-A. Lachaux, T. Lacroix, B. Rozière, N. Goyal, E. Hambro, F. Azhar, et al · 2023
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