Reservoir Transformers

1. 2021Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Littlecited by 176
2. 2023Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learningcited by 24
3. 2022How does the pre-training objective affect what large language models learn about linguistic properties?cited by 16
4. 2021Efficient and Private Federated Learning with Partially Trainable Networkscited by 13
5. 2022Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Trainingcited by 11
6. 2021What's Hidden in a One-layer Randomly Weighted Transformer?cited by 3
7. 2023Partially Randomizing Transformer Weights for Dialogue Response Diversitycited by 1
8. 2025Perturbative Gradient Training: A novel training paradigm for bridging the gap between deep neural networks and physical reservoir computingcited by 1
9. 2025Frozen in Time: Parameter-Efficient Time Series Transformers via Reservoir-Induced Feature Expansion and Fixed Random Dynamicscited by 1
10. 2026Training-Free Universal Approximation by Prompting Random Transformerscited by 1
11. 2022Physical Deep Learning with Biologically Plausible Training Methodcited by 0
12. 2024Changes by Butterflies: Farsighted Forecasting with Group Reservoir Transformercited by 0

1. 2026Training-Free Universal Approximation by Prompting Random Transformers10 Aug 2026
2. 2026Quantum Reservoir Computing: Recent Advances and Future Directions20 Jul 2026
3. 2025Reservoir Computing inspired Matrix Multiplication-free Language Model29 Dec 2025
4. 2025Echo Flow Networks28 Sep 2025
5. 2025ResFormer: All-Time Reservoir Memory for Long Sequence Classification28 Sep 2025
6. 2025Frozen in Time: Parameter-Efficient Time Series Transformers via Reservoir-Induced Feature Expansion and Fixed Random Dynamics25 Aug 2025
7. 2025Perturbative Gradient Training: A novel training paradigm for bridging the gap between deep neural networks and physical reservoir computing5 Jun 2025
8. 2025Learning Music Audio Representations With Limited Data9 May 2025
9. 2025Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection14 Mar 2025
10. 2024Changes by Butterflies: Farsighted Forecasting with Group Reservoir Transformer14 Feb 2024
11. 2023Partially Randomizing Transformer Weights for Dialogue Response Diversity18 Nov 2023
12. 2023Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning31 Oct 2023

1. 2023Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learningcited by 24

1. 2023Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning31 Oct 2023

1. 2021Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Littlecited by 176
2. 2022How does the pre-training objective affect what large language models learn about linguistic properties?cited by 16
3. 2021Efficient and Private Federated Learning with Partially Trainable Networkscited by 13
4. 2022Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Trainingcited by 11
5. 2021What's Hidden in a One-layer Randomly Weighted Transformer?cited by 3
6. 2023Partially Randomizing Transformer Weights for Dialogue Response Diversitycited by 1
7. 2025Perturbative Gradient Training: A novel training paradigm for bridging the gap between deep neural networks and physical reservoir computingcited by 1
8. 2025Frozen in Time: Parameter-Efficient Time Series Transformers via Reservoir-Induced Feature Expansion and Fixed Random Dynamicscited by 1
9. 2026Training-Free Universal Approximation by Prompting Random Transformerscited by 1
10. 2022Physical Deep Learning with Biologically Plausible Training Methodcited by 0
11. 2024Changes by Butterflies: Farsighted Forecasting with Group Reservoir Transformercited by 0
12. 2025Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detectioncited by 0

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1. 2026Training-Free Universal Approximation by Prompting Random Transformers10 Aug 2026
2. 2026Quantum Reservoir Computing: Recent Advances and Future Directions20 Jul 2026
3. 2025Reservoir Computing inspired Matrix Multiplication-free Language Model29 Dec 2025
4. 2025Echo Flow Networks28 Sep 2025
5. 2025ResFormer: All-Time Reservoir Memory for Long Sequence Classification28 Sep 2025
6. 2025Frozen in Time: Parameter-Efficient Time Series Transformers via Reservoir-Induced Feature Expansion and Fixed Random Dynamics25 Aug 2025
7. 2025Perturbative Gradient Training: A novel training paradigm for bridging the gap between deep neural networks and physical reservoir computing5 Jun 2025
8. 2025Learning Music Audio Representations With Limited Data9 May 2025
9. 2025Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection14 Mar 2025
10. 2024Changes by Butterflies: Farsighted Forecasting with Group Reservoir Transformer14 Feb 2024
11. 2023Partially Randomizing Transformer Weights for Dialogue Response Diversity18 Nov 2023
12. 2022Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training22 Sep 2022

12 newest of 17 · All 17 (JSON)