{"total":40,"rows":[{"id":"2102.04906","title":"Dynamic Neural Networks: A Survey","created":"2021-02-09","cited_by_count":408,"area":null},{"id":"2111.07624","title":"Attention Mechanisms in Computer Vision: A Survey","created":"2021-11-15","cited_by_count":232,"area":null},{"id":"2102.04170","title":"Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck Approach","created":"2021-02-08","cited_by_count":110,"area":null},{"id":"2103.13258","title":"Dynamic Slimmable Network","created":"2021-03-24","cited_by_count":83,"area":null},{"id":"2102.05775","title":"AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition","created":"2021-02-10","cited_by_count":48,"area":null},{"id":"2105.05165","title":"AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition","created":"2021-05-11","cited_by_count":36,"area":null},{"id":"2108.10394","title":"Dynamic Network Quantization for Efficient Video Inference","created":"2021-08-23","cited_by_count":36,"area":null},{"id":"2402.18447","title":"Prompt-Driven Dynamic Object-Centric Learning for Single Domain Generalization","created":"2024-02-28","cited_by_count":24,"area":null},{"id":"2205.03055","title":"Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism","created":"2022-05-06","cited_by_count":20,"area":null},{"id":"2209.01425","title":"Dynamic Spatio-Temporal Specialization Learning for Fine-Grained Action Recognition","created":"2022-09-03","cited_by_count":17,"area":null},{"id":"2306.04451","title":"Referring Expression Comprehension Using Language Adaptive Inference","created":"2023-06-06","cited_by_count":15,"area":null},{"id":"2310.09163","title":"Jointly-Learned Exit and Inference for a Dynamic Neural Network : JEI-DNN","created":"2023-10-13","cited_by_count":15,"area":null},{"id":"2105.03014","title":"BasisNet: Two-stage Model Synthesis for Efficient Inference","created":"2021-05-07","cited_by_count":7,"area":null},{"id":"2109.10060","title":"DS-Net++: Dynamic Weight Slicing for Efficient Inference in CNNs and Transformers","created":"2021-09-21","cited_by_count":6,"area":null},{"id":"2312.10193","title":"Adaptive Computation Modules: Granular Conditional Computation For Efficient Inference","created":"2023-12-15","cited_by_count":6,"area":null},{"id":"2112.00492","title":"Human-Object Interaction Detection via Weak Supervision","created":"2021-12-01","cited_by_count":5,"area":null},{"id":"2205.06404","title":"Fast Conditional Network Compression Using Bayesian HyperNetworks","created":"2022-05-13","cited_by_count":5,"area":null},{"id":"2501.07451","title":"A Survey on Dynamic Neural Networks: from Computer Vision to Multi-modal Sensor Fusion","created":"2025-01-13","cited_by_count":5,"area":null},{"id":"2207.06242","title":"SlimSeg: Slimmable Semantic Segmentation with Boundary Supervision","created":"2022-07-13","cited_by_count":4,"area":null},{"id":"2304.00280","title":"Progressive Channel-Shrinking Network","created":"2023-04-01","cited_by_count":4,"area":null},{"id":"2407.04274","title":"Fine-grained Dynamic Network for Generic Event Boundary Detection","created":"2024-07-05","cited_by_count":4,"area":null},{"id":"2506.21080","title":"EgoAdapt: Adaptive Multisensory Distillation and Policy Learning for Efficient Egocentric Perception","created":"2025-06-26","cited_by_count":4,"area":null},{"id":"2305.17305","title":"DynaShare: Task and Instance Conditioned Parameter Sharing for Multi-Task Learning","created":"2023-05-26","cited_by_count":3,"area":null},{"id":"2406.08804","title":"DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation","created":"2024-06-13","cited_by_count":3,"area":null},{"id":"2409.17016","title":"CNN Mixture-of-Depths","created":"2024-09-25","cited_by_count":3,"area":null},{"id":"2501.02837","title":"Forward Once for All: Structural Parameterized Adaptation for Efficient Cloud-coordinated On-device Recommendation","created":"2025-01-06","cited_by_count":3,"area":null},{"id":"2503.06945","title":"Dynamic Cross-Modal Feature Interaction Network for Hyperspectral and LiDAR Data Classification","created":"2025-03-10","cited_by_count":3,"area":null},{"id":"2307.00198","title":"Filter Pruning for Efficient CNNs via Knowledge-driven Differential Filter Sampler","created":"2023-07-01","cited_by_count":2,"area":null},{"id":"2507.07954","title":"Input Conditioned Layer Dropping in Speech Foundation Models","created":"2025-07-10","cited_by_count":2,"area":null},{"id":"2207.01127","title":"DecisioNet: A Binary-Tree Structured Neural Network","created":"2022-07-03","cited_by_count":1,"area":null},{"id":"2202.05343","title":"Towards Disentangling Information Paths with Coded ResNeXt","created":"2022-02-10","cited_by_count":0,"area":null},{"id":"2206.08427","title":"SATBench: Benchmarking the speed-accuracy tradeoff in object recognition by humans and dynamic neural networks","created":"2022-06-16","cited_by_count":0,"area":null},{"id":"2209.03534","title":"CWP: Instance complexity weighted channel-wise soft masks for network pruning","created":"2022-09-08","cited_by_count":0,"area":null},{"id":"2210.07932","title":"Neural Routing in Meta Learning","created":"2022-10-14","cited_by_count":0,"area":null},{"id":"2301.09164","title":"Unifying Synergies between Self-supervised Learning and Dynamic Computation","created":"2023-01-22","cited_by_count":0,"area":null},{"id":"2305.08021","title":"TIPS: Topologically Important Path Sampling for Anytime Neural Networks","created":"2023-05-13","cited_by_count":0,"area":null},{"id":"2309.01824","title":"On the fly Deep Neural Network Optimization Control for Low-Power Computer Vision","created":"2023-09-04","cited_by_count":0,"area":null},{"id":"2504.08613","title":"Enhancing knowledge retention for continual learning with domain-specific adapters and features gating","created":"2025-04-11","cited_by_count":0,"area":null},{"id":"2601.16117","title":"Distillation-based Layer Dropping (DLD): Effective End-to-end Framework for Dynamic Speech Networks","created":"2026-01-22","cited_by_count":0,"area":null},{"id":"2603.17275","title":"DANCE: Dynamic 3D CNN Pruning: Joint Frame, Channel, and Feature Adaptation for Energy Efficiency on the Edge","created":"2026-03-18","cited_by_count":0,"area":null}],"next_cursor":null}