{"total":30,"rows":[{"id":"2404.05657","title":"MLP Can Be A Good Transformer Learner","created":"2024-04-08","cited_by_count":17,"area":null},{"id":"2511.19515","title":"Fewer Tokens, Greater Scaling: Self-Adaptive Visual Bases for Efficient and Expansive Representation Learning","created":"2025-11-24","cited_by_count":16,"area":null},{"id":"2407.11717","title":"Turbo: Informativity-Driven Acceleration Plug-In for Vision-Language Large Models","created":"2024-07-16","cited_by_count":13,"area":null},{"id":"2409.11923","title":"Agglomerative Token Clustering","created":"2024-09-18","cited_by_count":13,"area":null},{"id":"2401.14895","title":"MPTQ-ViT: Mixed-Precision Post-Training Quantization for Vision Transformer","created":"2024-01-26","cited_by_count":10,"area":null},{"id":"2501.16811","title":"Not Every Patch is Needed: Towards a More Efficient and Effective Backbone for Video-based Person Re-identification","created":"2025-01-28","cited_by_count":7,"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":"2309.09003","title":"RingMo-lite: A Remote Sensing Multi-task Lightweight Network with CNN-Transformer Hybrid Framework","created":"2023-09-16","cited_by_count":4,"area":null},{"id":"2410.14729","title":"Is Less More? Exploring Token Condensation as Training-free Test-time Adaptation","created":"2024-10-16","cited_by_count":4,"area":null},{"id":"2412.02054","title":"Redundant Queries in DETR-Based 3D Detection Methods: Unnecessary and Prunable","created":"2024-12-03","cited_by_count":4,"area":null},{"id":"2511.06016","title":"One-Shot Knowledge Transfer for Scalable Person Re-Identification","created":"2025-11-08","cited_by_count":4,"area":null},{"id":"2405.20867","title":"Automatic Channel Pruning for Multi-Head Attention","created":"2024-05-31","cited_by_count":3,"area":null},{"id":"2505.22195","title":"S2AFormer: Strip Self-Attention for Efficient Vision Transformer","created":"2025-05-28","cited_by_count":3,"area":null},{"id":"2506.08591","title":"Diversity-Guided MLP Reduction for Efficient Large Vision Transformers","created":"2025-06-10","cited_by_count":3,"area":null},{"id":"2505.03113","title":"Image Recognition with Online Lightweight Vision Transformer: A Survey","created":"2025-05-06","cited_by_count":2,"area":null},{"id":"2603.08100","title":"Adaptive MLP Pruning for Large Vision Transformers","created":"2026-03-09","cited_by_count":2,"area":null},{"id":"2603.26258","title":"ARTA: Adaptive Mixed-Resolution Token Allocation for Efficient Dense Feature Extraction","created":"2026-03-27","cited_by_count":2,"area":null},{"id":"2403.12543","title":"HCPM: Hierarchical Candidates Pruning for Efficient Detector-Free Matching","created":"2024-03-19","cited_by_count":1,"area":null},{"id":"2406.08037","title":"Adaptively Bypassing Vision Transformer Blocks for Efficient Visual Tracking","created":"2024-06-12","cited_by_count":1,"area":null},{"id":"2410.05800","title":"Core Tokensets for Data-efficient Sequential Training of Transformers","created":"2024-10-08","cited_by_count":1,"area":null},{"id":"2512.06288","title":"Theoretical Compression Bounds for Wide Multilayer Perceptrons","created":"2025-12-06","cited_by_count":1,"area":null},{"id":"2607.03784","title":"Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective","created":"2026-07-04","cited_by_count":1,"area":null},{"id":"2310.07664","title":"Accelerating Vision Transformers Based on Heterogeneous Attention Patterns","created":"2023-10-11","cited_by_count":0,"area":null},{"id":"2406.17117","title":"Speeding Up Image Classifiers with Little Companions","created":"2024-06-24","cited_by_count":0,"area":null},{"id":"2507.03268","title":"Dual-frequency Selected Knowledge Distillation with Statistical-based Sample Rectification for PolSAR Image Classification","created":"2025-07-04","cited_by_count":0,"area":null},{"id":"2507.12125","title":"Block-based Symmetric Pruning and Fusion for Efficient Vision Transformers","created":"2025-07-16","cited_by_count":0,"area":null},{"id":"2508.05851","title":"Temporal Cluster Assignment for Efficient Real-Time Video Segmentation","created":"2025-08-07","cited_by_count":0,"area":null},{"id":"2510.05888","title":"BioAutoML-NAS: An End-to-End AutoML Framework for Multimodal Insect Classification via Neural Architecture Search on Large-Scale Biodiversity Data","created":"2025-10-07","cited_by_count":0,"area":null},{"id":"2602.15720","title":"ToaSt: Token Channel Selection and Structured Pruning for Efficient ViT","created":"2026-02-17","cited_by_count":0,"area":null},{"id":"2609.02689","title":"GaLe: memory-efficient Global Approximate and Local Exact features","created":"2026-09-02","cited_by_count":0,"area":null}],"next_cursor":null}