{"total":36,"rows":[{"id":"2103.13630","title":"A Survey of Quantization Methods for Efficient Neural Network Inference","created":"2021-03-25","cited_by_count":815,"area":null},{"id":"2111.14826","title":"Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation","created":"2021-11-29","cited_by_count":79,"area":null},{"id":"2106.11309","title":"How Do Adam and Training Strategies Help BNNs Optimization?","created":"2021-06-21","cited_by_count":46,"area":null},{"id":"2110.06804","title":"A comprehensive review of Binary Neural Network","created":"2021-10-11","cited_by_count":45,"area":null},{"id":"2211.07091","title":"BiViT: Extremely Compressed Binary Vision Transformer","created":"2022-11-14","cited_by_count":28,"area":null},{"id":"2102.07981","title":"SiMaN: Sign-to-Magnitude Network Binarization","created":"2021-02-16","cited_by_count":18,"area":null},{"id":"2402.00422","title":"Lightweight Pixel Difference Networks for Efficient Visual Representation Learning","created":"2024-02-01","cited_by_count":17,"area":null},{"id":"2210.15976","title":"BEBERT: Efficient and Robust Binary Ensemble BERT","created":"2022-10-28","cited_by_count":14,"area":null},{"id":"2206.09909","title":"Low-Precision Stochastic Gradient Langevin Dynamics","created":"2022-06-20","cited_by_count":12,"area":null},{"id":"2508.15008","title":"Neural Network Quantization for Microcontrollers: A Comprehensive Survey of Methods, Platforms, and Applications","created":"2025-08-20","cited_by_count":7,"area":null},{"id":"2203.14645","title":"REx: Data-Free Residual Quantization Error Expansion","created":"2022-03-28","cited_by_count":6,"area":null},{"id":"2103.02394","title":"Self-Distribution Binary Neural Networks","created":"2021-03-03","cited_by_count":4,"area":null},{"id":"2104.10044","title":"BCNN: Binary Complex Neural Network","created":"2021-03-28","cited_by_count":3,"area":null},{"id":"2110.05850","title":"Improving Binary Neural Networks through Fully Utilizing Latent Weights","created":"2021-10-12","cited_by_count":3,"area":null},{"id":"2110.08562","title":"BNAS v2: Learning Architectures for Binary Networks with Empirical Improvements","created":"2021-10-16","cited_by_count":3,"area":null},{"id":"2110.14357","title":"Binarized ResNet: Enabling Robust Automatic Modulation Classification at the resource-constrained Edge","created":"2021-10-27","cited_by_count":3,"area":null},{"id":"2303.14470","title":"Compacting Binary Neural Networks by Sparse Kernel Selection","created":"2023-03-25","cited_by_count":3,"area":null},{"id":"2106.09925","title":"Realizing Neural Decoder at the Edge with Ensembled BNN","created":"2021-06-18","cited_by_count":2,"area":null},{"id":"2204.01234","title":"Soft Threshold Ternary Networks","created":"2022-04-04","cited_by_count":2,"area":null},{"id":"2205.07433","title":"Binarizing by Classification: Is soft function really necessary?","created":"2022-05-16","cited_by_count":2,"area":null},{"id":"2207.06893","title":"E2FIF: Push the limit of Binarized Deep Imagery Super-resolution using End-to-end Full-precision Information Flow","created":"2022-07-14","cited_by_count":2,"area":null},{"id":"2207.09049","title":"RepBNN: towards a precise Binary Neural Network with Enhanced Feature Map via Repeating","created":"2022-07-19","cited_by_count":2,"area":null},{"id":"2503.11159","title":"Stabilizing Quantization-Aware Training by Implicit-Regularization on Hessian Matrix","created":"2025-03-14","cited_by_count":2,"area":null},{"id":"2506.23717","title":"Towards Efficient and Accurate Spiking Neural Networks via Adaptive Bit Allocation","created":"2025-06-30","cited_by_count":2,"area":null},{"id":"2110.15137","title":"PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations","created":"2021-10-28","cited_by_count":1,"area":null},{"id":"2206.12322","title":"How to train accurate BNNs for embedded systems?","created":"2022-06-24","cited_by_count":1,"area":null},{"id":"2206.13116","title":"Transfer learning for ensembles: reducing computation time and keeping the diversity","created":"2022-06-27","cited_by_count":1,"area":null},{"id":"2504.06591","title":"NAPER: Fault Protection for Real-Time Resource-Constrained Deep Neural Networks","created":"2025-04-09","cited_by_count":1,"area":null},{"id":"2106.15350","title":"LB-CNN: An Open Source Framework for Fast Training of Light Binary Convolutional Neural Networks using Chainer and Cupy","created":"2021-06-25","cited_by_count":0,"area":null},{"id":"2206.03325","title":"Searching Similarity Measure for Binarized Neural Networks","created":"2022-06-05","cited_by_count":0,"area":null},{"id":"2210.00834","title":"Merging Classification Predictions with Sequential Information for Lightweight Visual Place Recognition in Changing Environments","created":"2022-10-03","cited_by_count":0,"area":null},{"id":"2210.02637","title":"IR2Net: Information Restriction and Information Recovery for Accurate Binary Neural Networks","created":"2022-10-06","cited_by_count":0,"area":null},{"id":"2311.15806","title":"PIPE : Parallelized Inference Through Post-Training Quantization Ensembling of Residual Expansions","created":"2023-11-27","cited_by_count":0,"area":null},{"id":"2410.00050","title":"CycleBNN: Cyclic Precision Training in Binary Neural Networks","created":"2024-09-28","cited_by_count":0,"area":null},{"id":"2503.23709","title":"Expanding-and-Shrinking Binary Neural Networks","created":"2025-03-31","cited_by_count":0,"area":null},{"id":"2508.12609","title":"A Self-Ensemble Inspired Approach for Effective Training of Binary-Weight Spiking Neural Networks","created":"2025-08-18","cited_by_count":0,"area":null}],"next_cursor":null}