{"total":66,"rows":[{"id":"2112.10508","title":"Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP","created":"2021-12-20","cited_by_count":132,"area":null},{"id":"2311.04823","title":"Hierarchically Gated Recurrent Neural Network for Sequence Modeling","created":"2023-11-08","cited_by_count":102,"area":null},{"id":"2211.09761","title":"Efficient Transformers with Dynamic Token Pooling","created":"2022-11-17","cited_by_count":76,"area":null},{"id":"2507.07955","title":"Dynamic Chunking for End-to-End Hierarchical Sequence Modeling","created":"2025-07-10","cited_by_count":72,"area":null},{"id":"2304.06632","title":"AI-Generated Content (AIGC): A Survey","created":"2023-03-26","cited_by_count":59,"area":null},{"id":"2102.09532","title":"Clockwork Variational Autoencoders","created":"2021-02-18","cited_by_count":42,"area":null},{"id":"2203.05483","title":"projUNN: efficient method for training deep networks with unitary matrices","created":"2022-03-10","cited_by_count":27,"area":null},{"id":"2111.02592","title":"Conformal prediction for text infilling and part-of-speech prediction","created":"2021-11-04","cited_by_count":22,"area":null},{"id":"2110.15949","title":"Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains","created":"2021-10-29","cited_by_count":18,"area":null},{"id":"2103.10972","title":"Learning Task Decomposition with Ordered Memory Policy Network","created":"2021-03-19","cited_by_count":15,"area":null},{"id":"2203.09303","title":"MSPred: Video Prediction at Multiple Spatio-Temporal Scales with Hierarchical Recurrent Networks","created":"2022-03-17","cited_by_count":13,"area":null},{"id":"2205.14794","title":"Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning","created":"2022-05-30","cited_by_count":13,"area":null},{"id":"2102.09794","title":"Hierarchical Recurrent Neural Networks for Conditional Melody Generation with Long-term Structure","created":"2021-02-19","cited_by_count":12,"area":null},{"id":"2102.11218","title":"Neural Pharmacodynamic State Space Modeling","created":"2021-02-22","cited_by_count":12,"area":null},{"id":"2309.05812","title":"Interpretable learning of effective dynamics for multiscale systems","created":"2023-09-11","cited_by_count":11,"area":null},{"id":"2110.11236","title":"Variational Predictive Routing with Nested Subjective Timescales","created":"2021-10-21","cited_by_count":9,"area":null},{"id":"2307.00337","title":"Recursive Algorithmic Reasoning","created":"2023-07-01","cited_by_count":9,"area":null},{"id":"2206.11396","title":"Multi-Horizon Representations with Hierarchical Forward Models for Reinforcement Learning","created":"2022-06-22","cited_by_count":7,"area":null},{"id":"2312.14880","title":"SutraNets: Sub-series Autoregressive Networks for Long-Sequence, Probabilistic Forecasting","created":"2023-12-22","cited_by_count":7,"area":null},{"id":"2103.02339","title":"Deep Recurrent Encoder: A scalable end-to-end network to model brain signals","created":"2021-03-03","cited_by_count":6,"area":null},{"id":"2208.03523","title":"Generalizing Downsampling from Regular Data to Graphs","created":"2022-08-06","cited_by_count":6,"area":null},{"id":"2407.07239","title":"RotRNN: Modelling Long Sequences with Rotations","created":"2024-07-09","cited_by_count":6,"area":null},{"id":"2106.06033","title":"Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties","created":"2021-06-10","cited_by_count":4,"area":null},{"id":"2111.03282","title":"Recurrent Neural Networks for Learning Long-term Temporal Dependencies with Reanalysis of Time Scale Representation","created":"2021-11-05","cited_by_count":4,"area":null},{"id":"2106.01001","title":"Warming up recurrent neural networks to maximise reachable multistability greatly improves learning","created":"2021-06-02","cited_by_count":3,"area":null},{"id":"2306.01070","title":"Hierarchical Attention Encoder Decoder","created":"2023-06-01","cited_by_count":3,"area":null},{"id":"2106.02562","title":"Recurrent Neural Networks with Mixed Hierarchical Structures for Natural Language Processing","created":"2021-06-04","cited_by_count":2,"area":null},{"id":"2106.06621","title":"Piecewise-constant Neural ODEs","created":"2021-06-11","cited_by_count":2,"area":null},{"id":"2201.03709","title":"Pavlovian Signalling with General Value Functions in Agent-Agent Temporal Decision Making","created":"2022-01-11","cited_by_count":2,"area":null},{"id":"2203.09498","title":"The Frost Hollow Experiments: Pavlovian Signalling as a Path to Coordination and Communication Between Agents","created":"2022-03-17","cited_by_count":2,"area":null},{"id":"2209.01728","title":"Features Fusion Framework for Multimodal Irregular Time-series Events","created":"2022-09-05","cited_by_count":2,"area":null},{"id":"2306.10164","title":"MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series Prediction","created":"2023-06-16","cited_by_count":2,"area":null},{"id":"2408.09453","title":"Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling","created":"2024-08-18","cited_by_count":2,"area":null},{"id":"2410.03892","title":"Towards Cost Sensitive Decision Making","created":"2024-10-04","cited_by_count":2,"area":null},{"id":"2508.12121","title":"Time-Scale Coupling Between States and Parameters in Recurrent Neural Networks","created":"2025-08-16","cited_by_count":2,"area":null},{"id":"2512.23824","title":"MS-SSM: A Multi-Scale State Space Model for Efficient Sequence Modeling","created":"2025-12-29","cited_by_count":2,"area":null},{"id":"2604.01577","title":"Exploration of Fast-Slow Latent Recurrence for Train-Short, Test-Long Generalization","created":"2026-04-02","cited_by_count":2,"area":null},{"id":"2201.05464","title":"Bayesian sense of time in biological and artificial brains","created":"2022-01-14","cited_by_count":1,"area":null},{"id":"2311.14549","title":"FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification","created":"2023-11-24","cited_by_count":1,"area":null},{"id":"2409.12924","title":"Wavelet GPT: Wavelet Inspired Large Language Models","created":"2024-09-04","cited_by_count":1,"area":null},{"id":"2409.18013","title":"Spatiotemporal Graph Learning with Direct Volumetric Information Passing and Feature Enhancement","created":"2024-09-26","cited_by_count":1,"area":null},{"id":"2604.08661","title":"Geometry-Induced Long-Range Correlations in Recurrent Neural Network Quantum States","created":"2026-04-09","cited_by_count":1,"area":null},{"id":"2605.12049","title":"Scaling Laws and Tradeoffs in Recurrent Networks of Expressive Neurons","created":"2026-05-12","cited_by_count":1,"area":null},{"id":"2607.02087","title":"SUNTA: Hierarchical Video Prediction with Surprise-based Chunking","created":"2026-07-02","cited_by_count":1,"area":null},{"id":"2607.28989","title":"SILVA Networks as Structured Implicit Layers and Vector Attractors via Dynamic Interaction Fields","created":"2026-07-31","cited_by_count":1,"area":null},{"id":"2104.13853","title":"Learning deep autoregressive models for hierarchical data","created":"2021-04-28","cited_by_count":0,"area":null},{"id":"2106.04148","title":"RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting","created":"2021-06-08","cited_by_count":0,"area":null},{"id":"2201.08919","title":"Recurrent Neural Networks with Mixed Hierarchical Structures and EM Algorithm for Natural Language Processing","created":"2022-01-21","cited_by_count":0,"area":null},{"id":"2205.04034","title":"AI Based Digital Twin Model for Cattle Caring","created":"2022-05-09","cited_by_count":0,"area":null},{"id":"2206.02042","title":"Developing hierarchical anticipations via neural network-based event segmentation","created":"2022-06-04","cited_by_count":0,"area":null},{"id":"2206.04806","title":"Syntactic Inductive Biases for Deep Learning Methods","created":"2022-06-08","cited_by_count":0,"area":null},{"id":"2211.02561","title":"An Improved Time Feedforward Connections Recurrent Neural Networks","created":"2022-11-03","cited_by_count":0,"area":null},{"id":"2211.09001","title":"Multi-Timescale Modeling of Human Behavior","created":"2022-11-16","cited_by_count":0,"area":null},{"id":"2306.14476","title":"STEF-DHNet: Spatiotemporal External Factors Based Deep Hybrid Network for Enhanced Long-Term Taxi Demand Prediction","created":"2023-06-26","cited_by_count":0,"area":null},{"id":"2311.02123","title":"RigLSTM: Recurrent Independent Grid LSTM for Generalizable Sequence Learning","created":"2023-11-03","cited_by_count":0,"area":null},{"id":"2404.08011","title":"An inclusive review on deep learning techniques and their scope in handwriting recognition","created":"2024-04-10","cited_by_count":0,"area":null},{"id":"2506.00588","title":"Temporal Chunking Enhances Recognition of Implicit Sequential Patterns","created":"2025-05-31","cited_by_count":0,"area":null},{"id":"2508.07969","title":"Understanding Syntactic Generalization in Structure-inducing Language Models","created":"2025-08-11","cited_by_count":0,"area":null},{"id":"2512.05790","title":"Learnability Window in Gated Recurrent Neural Networks","created":"2025-12-05","cited_by_count":0,"area":null},{"id":"2602.09209","title":"Wearable environmental sensing to forecast how legged systems will interact with upcoming terrain","created":"2026-02-09","cited_by_count":0,"area":null},{"id":"2602.19531","title":"A Statistical Approach for Modeling Irregular Multivariate Time Series with Missing Observations","created":"2026-02-23","cited_by_count":0,"area":null},{"id":"2603.02226","title":"Efficient Sparse Selective-Update RNNs for Long-Range Sequence Modeling","created":"2026-02-11","cited_by_count":0,"area":null},{"id":"2606.00732","title":"SHARP: Sleep-based Hierarchical Accelerated Replay for Long Range Non-Stationary Temporal Pattern Recognition","created":"2026-05-30","cited_by_count":0,"area":null},{"id":"2609.38426","title":"LoopVL: Recurrent Visual Intelligence","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.07505","title":"MARS: Multi-resolution Adaptive Routing for Sequential Recommendation","created":"2026-10-05","cited_by_count":0,"area":null},{"id":"2610.14030","title":"Rotate the Loop: Blockwise Conformality for Looped Transformers","created":"2026-09-30","cited_by_count":0,"area":null}],"next_cursor":null}