mlsanityData to 7 Oct 2026

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

arXiv 1412.3555 ↗First posted 11 Dec 2014cs.NE cs.LGcited by 2,341

Not on the map. Why?

Cited by 28 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism, such as a long short-term memory (LSTM) unit and a recently proposed gated recurrent unit (GRU). We evaluate these recurrent units on the tasks of polyphonic music modeling and speech signal modeling. Our experiments revealed that these advanced recurrent units are indeed better than more traditional recurrent units such as tanh units. Also, we found GRU to be comparable to LSTM.

Key facts. Cited by 2,341 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Dec 2014.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2018: 3; 2019: 0; 2020: 2; 2021: 439; 2022: 405; 2023: 434; 2024: 467; 2025: 386; 2026: 205.

2,341 papers.

Sort:

By area:

  1. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,616
  2. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  3. 2024Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Dualitycited by 1,283
  4. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  5. 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,197
  6. 2023RWKV: Reinventing RNNs for the Transformer Eracited by 814
  7. 2023One Fits All:Power General Time Series Analysis by Pretrained LMcited by 615
  8. 2021Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layerscited by 607
  9. 2022Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionalitycited by 523
  10. 2021SpeechBrain: A General-Purpose Speech Toolkitcited by 404
  11. 2022ProcTHOR: Large-Scale Embodied AI Using Procedural Generationcited by 369
  12. 2021Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecastingcited by 332
38 more
  1. 2021AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecastingcited by 327
  2. 2021How Much Can CLIP Benefit Vision-and-Language Tasks?cited by 321
  3. 2023A Survey on Multimodal Large Language Models for Autonomous Drivingcited by 288
  4. 2023Reward Design with Language Modelscited by 257
  5. 2021Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Modelscited by 251
  6. 2021A Survey on Deep Semi-supervised Learningcited by 250
  7. 2025MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attentioncited by 248
  8. 2021NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Videocited by 241
  9. 2021Multi-Time Attention Networks for Irregularly Sampled Time Seriescited by 234
  10. 2024Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Modelscited by 232
  11. 2023Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedbackcited by 202
  12. 2023Tracking Anything with Decoupled Video Segmentationcited by 197
  13. 2021Quantum advantage in learning from experimentscited by 186
  14. 2024Are Language Models Actually Useful for Time Series Forecasting?cited by 163
  15. 2024Large Language Model-Brained GUI Agents: A Surveycited by 160
  16. 2021Motif-based Graph Self-Supervised Learning for Molecular Property Predictioncited by 159
  17. 2022A Review on Language Models as Knowledge Basescited by 156
  18. 2022FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecastingcited by 147
  19. 2023A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detectioncited by 145
  20. 2021MultiBench: Multiscale Benchmarks for Multimodal Representation Learningcited by 143
  21. 2022TransDreamer: Reinforcement Learning with Transformer World Modelscited by 143
  22. 2023StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Constructioncited by 143
  23. 2021InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referringcited by 140
  24. 2022SeqTR: A Simple yet Universal Network for Visual Groundingcited by 138
  25. 2022Multi-View Transformer for 3D Visual Groundingcited by 138
  26. 2023Meta-Transformer: A Unified Framework for Multimodal Learningcited by 136
  27. 2022Liquid Structural State-Space Modelscited by 134
  28. 2022ROLAND: Graph Learning Framework for Dynamic Graphscited by 131
  29. 2021Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Surveycited by 130
  30. 2022Deep Learning for Time Series Anomaly Detection: A Surveycited by 130
  31. 2023Leapfrog Diffusion Model for Stochastic Trajectory Predictioncited by 129
  32. 2021KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamicscited by 128
  33. 2021DriveGAN: Towards a Controllable High-Quality Neural Simulationcited by 125
  34. 2021Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmarkcited by 124
  35. 2024HGRN2: Gated Linear RNNs with State Expansioncited by 122
  36. 2021Video Super-Resolution Transformercited by 120
  37. 2021AdaRNN: Adaptive Learning and Forecasting of Time Seriescited by 120
  38. 2021CKConv: Continuous Kernel Convolution For Sequential Datacited by 117

50 most cited of 2,341 All 2,341 (JSON)