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MoEUT: Mixture-of-Experts Universal Transformers.

, , , , и . CoRR, (2024)

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Enik Csordás

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Carina Caroline Csordas

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Róbert Klug

 

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The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization., , и . ICLR, OpenReview.net, (2022)A Generalist Neural Algorithmic Learner., , , , , , , , , и 5 other автор(ы). LoG, том 198 из Proceedings of Machine Learning Research, стр. 2. PMLR, (2022)Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control., и . ICLR (Poster), OpenReview.net, (2019)A Modern Self-Referential Weight Matrix That Learns to Modify Itself., , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 9660-9677. PMLR, (2022)The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of Attention., , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 9639-9659. PMLR, (2022)Practical Computational Power of Linear Transformers and Their Recurrent and Self-Referential Extensions., , и . EMNLP, стр. 9455-9465. Association for Computational Linguistics, (2023)MoEUT: Mixture-of-Experts Universal Transformers., , , , и . CoRR, (2024)Topological Neural Discrete Representation Learning à la Kohonen., , и . CoRR, (2023)Detecting Objects Thrown over Fence in Outdoor Scenes., , и . VISAPP (3), стр. 593-599. SciTePress, (2015)Going Beyond Linear Transformers with Recurrent Fast Weight Programmers., , , и . NeurIPS, стр. 7703-7717. (2021)