{"total":420,"rows":[{"id":"2209.12951","title":"Liquid Structural State-Space Models","created":"2022-09-26","cited_by_count":136,"area":null},{"id":"2106.02795","title":"Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding","created":"2021-06-05","cited_by_count":93,"area":null},{"id":"2412.06329","title":"Normalizing Flows are Capable Generative Models","created":"2024-12-09","cited_by_count":91,"area":null},{"id":"2301.03028","title":"Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement","created":"2023-01-08","cited_by_count":90,"area":null},{"id":"2410.20672","title":"Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA","created":"2024-10-28","cited_by_count":78,"area":null},{"id":"2307.00457","title":"GenRec: Large Language Model for Generative Recommendation","created":"2023-07-02","cited_by_count":63,"area":null},{"id":"2110.12690","title":"A Dynamical System Perspective for Lipschitz Neural Networks","created":"2021-10-25","cited_by_count":60,"area":null},{"id":"2205.01138","title":"Transformers in Time-series Analysis: A Tutorial","created":"2022-04-28","cited_by_count":46,"area":null},{"id":"2202.07141","title":"Machine Learning in Aerodynamic Shape Optimization","created":"2022-02-15","cited_by_count":39,"area":null},{"id":"2107.06658","title":"A Framework for Machine Learning of Model Error in Dynamical Systems","created":"2021-07-14","cited_by_count":38,"area":null},{"id":"2107.04556","title":"Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid Simulations","created":"2021-07-09","cited_by_count":36,"area":null},{"id":"2107.13782","title":"Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directions","created":"2021-07-29","cited_by_count":35,"area":null},{"id":"2405.03658","title":"A review on data-driven constitutive laws for solids","created":"2024-05-06","cited_by_count":35,"area":null},{"id":"2503.05659","title":"A Survey of Large Language Model Empowered Agents for Recommendation and Search: Towards Next-Generation Information Retrieval","created":"2025-03-07","cited_by_count":33,"area":"agents"},{"id":"2404.04442","title":"Exploring Autonomous Agents through the Lens of Large Language Models: A Review","created":"2024-04-05","cited_by_count":31,"area":"agents"},{"id":"2403.04260","title":"Can Small Language Models be Good Reasoners for Sequential Recommendation?","created":"2024-03-07","cited_by_count":26,"area":"lr"},{"id":"2211.07377","title":"Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing","created":"2022-11-14","cited_by_count":24,"area":null},{"id":"2302.07200","title":"Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey","created":"2023-02-14","cited_by_count":21,"area":"lr"},{"id":"2401.11611","title":"Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks","created":"2024-01-21","cited_by_count":20,"area":null},{"id":"2408.14909","title":"SpikingSSMs: Learning Long Sequences with Sparse and Parallel Spiking State Space Models","created":"2024-08-27","cited_by_count":19,"area":null},{"id":"2503.10898","title":"Trajectory Mamba: Efficient Attention-Mamba Forecasting Model Based on Selective SSM","created":"2025-03-13","cited_by_count":18,"area":"ssm"},{"id":"2501.01073","title":"Graph Generative Pre-trained Transformer","created":"2025-01-02","cited_by_count":17,"area":null},{"id":"2503.13195","title":"Deep Learning Advancements in Anomaly Detection: A Comprehensive Survey","created":"2025-03-17","cited_by_count":17,"area":null},{"id":"2310.15296","title":"DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLM","created":"2023-10-23","cited_by_count":16,"area":"diffusion"},{"id":"2411.02256","title":"Unified Speech Recognition: A Single Model for Auditory, Visual, and Audiovisual Inputs","created":"2024-11-04","cited_by_count":15,"area":null},{"id":"2305.13854","title":"The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey","created":"2023-05-23","cited_by_count":14,"area":null},{"id":"2307.08220","title":"FRANC: A Lightweight Framework for High-Quality Code Generation","created":"2023-07-17","cited_by_count":14,"area":null},{"id":"2412.13845","title":"Do Language Models Understand Time?","created":"2024-12-18","cited_by_count":14,"area":null},{"id":"2506.13498","title":"A Survey on Imitation Learning for Contact-Rich Tasks in Robotics","created":"2025-06-16","cited_by_count":14,"area":"offlinerl"},{"id":"2202.03480","title":"Universal Spam Detection using Transfer Learning of BERT Model","created":"2022-02-07","cited_by_count":13,"area":null},{"id":"2207.00378","title":"Rapid training of quantum recurrent neural networks","created":"2022-07-01","cited_by_count":13,"area":null},{"id":"2302.09893","title":"Efficient Generator of Mathematical Expressions for Symbolic Regression","created":"2023-02-20","cited_by_count":13,"area":null},{"id":"2401.08664","title":"Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges","created":"2023-12-27","cited_by_count":13,"area":null},{"id":"2312.02142","title":"Object Recognition as Next Token Prediction","created":"2023-12-04","cited_by_count":12,"area":null},{"id":"2403.10766","title":"ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference","created":"2024-03-16","cited_by_count":12,"area":null},{"id":"2405.00077","title":"BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations","created":"2024-04-30","cited_by_count":12,"area":null},{"id":"2410.13846","title":"LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation","created":"2024-10-17","cited_by_count":12,"area":"lr"},{"id":"2412.18260","title":"Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study","created":"2024-12-24","cited_by_count":12,"area":null},{"id":"2502.09346","title":"Machine learning for modelling unstructured grid data in computational physics: a review","created":"2025-02-13","cited_by_count":12,"area":null},{"id":"2507.05938","title":"A Wireless Foundation Model for Multi-Task Prediction","created":"2025-07-08","cited_by_count":12,"area":null},{"id":"2406.00016","title":"Exploration of Attention Mechanism-Enhanced Deep Learning Models in the Mining of Medical Textual Data","created":"2024-05-23","cited_by_count":11,"area":null},{"id":"2105.07949","title":"Using Transformers to Provide Teachers with Personalized Feedback on their Classroom Discourse: The TalkMoves Application","created":"2021-04-29","cited_by_count":10,"area":null},{"id":"2307.09483","title":"Forecasting steam mass flow in power plants using the parallel hybrid network","created":"2023-07-18","cited_by_count":10,"area":null},{"id":"2310.20218","title":"A Systematic Review for Transformer-based Long-term Series Forecasting","created":"2023-10-31","cited_by_count":10,"area":null},{"id":"2401.03728","title":"Generalized Lagrangian Neural Networks","created":"2024-01-08","cited_by_count":10,"area":null},{"id":"2408.11965","title":"CT-AGRG: Automated Abnormality-Guided Report Generation from 3D Chest CT Volumes","created":"2024-08-21","cited_by_count":10,"area":null},{"id":"2112.03414","title":"JUSTICE: A Benchmark Dataset for Supreme Court's Judgment Prediction","created":"2021-12-06","cited_by_count":9,"area":null},{"id":"2205.06806","title":"Goal-Guided Neural Cellular Automata: Learning to Control Self-Organising Systems","created":"2022-04-25","cited_by_count":9,"area":null},{"id":"2210.00169","title":"Multi-stage Progressive Compression of Conformer Transducer for On-device Speech Recognition","created":"2022-10-01","cited_by_count":9,"area":"distill"},{"id":"2305.08473","title":"Shared and Private Information Learning in Multimodal Sentiment Analysis with Deep Modal Alignment and Self-supervised Multi-Task Learning","created":"2023-05-15","cited_by_count":9,"area":null},{"id":"2308.12982","title":"A Survey of AI Music Generation Tools and Models","created":"2023-08-24","cited_by_count":9,"area":null},{"id":"2310.19626","title":"Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities","created":"2023-10-30","cited_by_count":9,"area":null},{"id":"2410.14067","title":"Provable Benefits of Complex Parameterizations for Structured State Space Models","created":"2024-10-17","cited_by_count":9,"area":"ssm"},{"id":"2410.17268","title":"SPikE-SSM: A Sparse, Precise, and Efficient Spiking State Space Model for Long Sequences Learning","created":"2024-10-07","cited_by_count":9,"area":null},{"id":"2109.10253","title":"Short-term traffic prediction using physics-aware neural networks","created":"2021-09-21","cited_by_count":8,"area":null},{"id":"2305.15111","title":"Reconstruction, forecasting, and stability of chaotic dynamics from partial data","created":"2023-05-24","cited_by_count":8,"area":null},{"id":"2407.07346","title":"INSIGHT: Universal Neural Simulator for Analog Circuits Harnessing Autoregressive Transformers","created":"2024-07-10","cited_by_count":8,"area":null},{"id":"2510.16670","title":"All You Need is One: Capsule Prompt Tuning with a Single Vector","created":"2025-10-19","cited_by_count":8,"area":null},{"id":"2109.12094","title":"A spatiotemporal machine learning approach to forecasting COVID-19 incidence at the county level in the USA","created":"2021-09-24","cited_by_count":7,"area":null},{"id":"2111.10559","title":"Learning Non-Stationary Time-Series with Dynamic Pattern Extractions","created":"2021-11-20","cited_by_count":7,"area":null},{"id":"2206.08672","title":"A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications","created":"2022-06-17","cited_by_count":7,"area":null},{"id":"2210.12571","title":"A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence","created":"2022-10-22","cited_by_count":7,"area":null},{"id":"2302.10669","title":"UAV Path Planning Employing MPC- Reinforcement Learning Method Considering Collision Avoidance","created":"2023-02-21","cited_by_count":7,"area":null},{"id":"2303.15569","title":"Core-Periphery Principle Guided Redesign of Self-Attention in Transformers","created":"2023-03-27","cited_by_count":7,"area":null},{"id":"2305.05738","title":"DOCTOR: A Multi-Disease Detection Continual Learning Framework Based on Wearable Medical Sensors","created":"2023-05-09","cited_by_count":7,"area":null},{"id":"2410.15143","title":"Budgeted Online Continual Learning by Adaptive Layer Freezing and Frequency-based Sampling","created":"2024-10-19","cited_by_count":7,"area":null},{"id":"2502.19971","title":"Efficient and Universal Neural-Network Decoder for Stabilizer-Based Quantum Error Correction","created":"2025-02-27","cited_by_count":7,"area":null},{"id":"2211.11281","title":"Intelligent Computing: The Latest Advances, Challenges and Future","created":"2022-11-21","cited_by_count":6,"area":null},{"id":"2303.04689","title":"A Privacy Preserving System for Movie Recommendations Using Federated Learning","created":"2023-03-07","cited_by_count":6,"area":null},{"id":"2308.16008","title":"EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planning","created":"2023-08-30","cited_by_count":6,"area":null},{"id":"2309.09643","title":"HiT: Building Mapping with Hierarchical Transformers","created":"2023-09-18","cited_by_count":6,"area":null},{"id":"2311.14407","title":"LLamol: A Dynamic Multi-Conditional Generative Transformer for De Novo Molecular Design","created":"2023-11-24","cited_by_count":6,"area":null},{"id":"2507.02900","title":"Advancing Talking Head Generation: A Comprehensive Survey of Multi-Modal Methodologies, Datasets, Evaluation Metrics, and Loss Functions","created":"2025-06-23","cited_by_count":6,"area":null},{"id":"2301.06730","title":"Bag of States: A Non-sequential Approach to Video-based Engagement Measurement","created":"2023-01-17","cited_by_count":5,"area":null},{"id":"2301.13279","title":"Learning Coordination Policies over Heterogeneous Graphs for Human-Robot Teams via Recurrent Neural Schedule Propagation","created":"2023-01-30","cited_by_count":5,"area":null},{"id":"2310.05216","title":"Probing Large Language Models from A Human Behavioral Perspective","created":"2023-10-08","cited_by_count":5,"area":null},{"id":"2311.16673","title":"Large Language Models Meet Computer Vision: A Brief Survey","created":"2023-11-28","cited_by_count":5,"area":null},{"id":"2401.06633","title":"Ada-Retrieval: An Adaptive Multi-Round Retrieval Paradigm for Sequential Recommendations","created":"2024-01-12","cited_by_count":5,"area":null},{"id":"2404.18398","title":"UMETTS: A Unified Framework for Emotional Text-to-Speech Synthesis with Multimodal Prompts","created":"2024-04-29","cited_by_count":5,"area":null},{"id":"2407.15794","title":"Disentangling spatio-temporal knowledge for weakly supervised object detection and segmentation in surgical video","created":"2024-07-22","cited_by_count":5,"area":null},{"id":"2409.10523","title":"Harnessing Artificial Intelligence for Wildlife Conservation","created":"2024-08-30","cited_by_count":5,"area":null},{"id":"2502.12214","title":"Zero Token-Driven Deep Thinking in LLMs: Unlocking the Full Potential of Existing Parameters via Cyclic Refinement","created":"2025-02-17","cited_by_count":5,"area":"lr"},{"id":"2509.07287","title":"Paladin: Defending LLM-enabled Phishing Emails with a New Trigger-Tag Paradigm","created":"2025-09-08","cited_by_count":5,"area":null},{"id":"2601.12554","title":"Artificial Intelligence in Materials Science and Engineering: Current Landscape, Key Challenges, and Future Trajectorie","created":"2026-01-18","cited_by_count":5,"area":null},{"id":"2604.12648","title":"TimeSAF: Towards LLM-Guided Semantic Asynchronous Fusion for Time Series Forecasting","created":"2026-04-14","cited_by_count":5,"area":null},{"id":"2109.00103","title":"Automatic non-invasive Cough Detection based on Accelerometer and Audio Signals","created":"2021-08-31","cited_by_count":4,"area":null},{"id":"2201.02741","title":"Two-Pass End-to-End ASR Model Compression","created":"2022-01-08","cited_by_count":4,"area":"distill"},{"id":"2202.04497","title":"Recurrent Spectral Network (RSN): shaping the basin of attraction of a discrete map to reach automated classification","created":"2022-02-09","cited_by_count":4,"area":null},{"id":"2203.09103","title":"Knowledge Graph-Enabled Text-Based Automatic Personality Prediction","created":"2022-03-17","cited_by_count":4,"area":null},{"id":"2209.08171","title":"Deep learning for reconstructing protein structures from cryo-EM density maps: recent advances and future directions","created":"2022-09-16","cited_by_count":4,"area":null},{"id":"2309.02012","title":"iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation","created":"2023-09-05","cited_by_count":4,"area":null},{"id":"2309.12132","title":"Automating construction contract review using knowledge graph-enhanced large language models","created":"2023-09-21","cited_by_count":4,"area":null},{"id":"2407.08558","title":"ST-Mamba: Spatial-Temporal Mamba for Traffic Flow Estimation Recovery using Limited Data","created":"2024-07-11","cited_by_count":4,"area":"ssm"},{"id":"2409.15012","title":"Inference-Friendly Models With MixAttention","created":"2024-09-23","cited_by_count":4,"area":"inference"},{"id":"2410.01483","title":"Foldable SuperNets: Scalable Merging of Transformers with Different Initializations and Tasks","created":"2024-10-02","cited_by_count":4,"area":null},{"id":"2410.17363","title":"DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR","created":"2024-10-22","cited_by_count":4,"area":null},{"id":"2411.00109","title":"Prospective Learning: Learning for a Dynamic Future","created":"2024-10-31","cited_by_count":4,"area":null},{"id":"2502.08690","title":"Skrr: Skip and Re-use Text Encoder Layers for Memory Efficient Text-to-Image Generation","created":"2025-02-12","cited_by_count":4,"area":"diffusion"},{"id":"2503.07041","title":"TCM-3CEval: A Triaxial Benchmark for Assessing Responses from Large Language Models in Traditional Chinese Medicine","created":"2025-03-10","cited_by_count":4,"area":null},{"id":"2506.18339","title":"Structured Kolmogorov-Arnold Neural ODEs for Interpretable Learning and Symbolic Discovery of Nonlinear Dynamics","created":"2025-06-23","cited_by_count":4,"area":null}],"next_cursor":"100"}