{"total":78,"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":"2305.10657","title":"PTQD: Accurate Post-Training Quantization for Diffusion Models","created":"2023-05-18","cited_by_count":170,"area":"diffusion"},{"id":"2210.06707","title":"Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer","created":"2022-10-13","cited_by_count":108,"area":null},{"id":"2104.00903","title":"Network Quantization with Element-wise Gradient Scaling","created":"2021-04-02","cited_by_count":87,"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":"2310.03270","title":"EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models","created":"2023-10-05","cited_by_count":78,"area":"diffusion"},{"id":"2311.16503","title":"TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models","created":"2023-11-27","cited_by_count":69,"area":"diffusion"},{"id":"2205.07877","title":"A Comprehensive Survey on Model Quantization for Deep Neural Networks in Image Classification","created":"2022-05-14","cited_by_count":65,"area":null},{"id":"2103.12369","title":"ReCU: Reviving the Dead Weights in Binary Neural Networks","created":"2021-03-23","cited_by_count":52,"area":null},{"id":"2205.13016","title":"BiT: Robustly Binarized Multi-distilled Transformer","created":"2022-05-25","cited_by_count":52,"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":"2103.07156","title":"Learnable Companding Quantization for Accurate Low-bit Neural Networks","created":"2021-03-12","cited_by_count":42,"area":null},{"id":"2111.02625","title":"Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples","created":"2021-11-04","cited_by_count":40,"area":null},{"id":"2108.10394","title":"Dynamic Network Quantization for Efficient Video Inference","created":"2021-08-23","cited_by_count":36,"area":null},{"id":"2102.11289","title":"Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference","created":"2021-02-22","cited_by_count":31,"area":null},{"id":"2106.06091","title":"DECORE: Deep Compression with Reinforcement Learning","created":"2021-06-11","cited_by_count":29,"area":null},{"id":"2102.04782","title":"Distribution Adaptive INT8 Quantization for Training CNNs","created":"2021-02-09","cited_by_count":28,"area":null},{"id":"2211.07091","title":"BiViT: Extremely Compressed Binary Vision Transformer","created":"2022-11-14","cited_by_count":28,"area":null},{"id":"2207.10345","title":"CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution","created":"2022-07-21","cited_by_count":27,"area":null},{"id":"2105.03536","title":"Pareto-Optimal Quantized ResNet Is Mostly 4-bit","created":"2021-05-07","cited_by_count":26,"area":null},{"id":"2111.12273","title":"Sharpness-aware Quantization for Deep Neural Networks","created":"2021-11-24","cited_by_count":25,"area":null},{"id":"2404.00928","title":"Instance-Aware Group Quantization for Vision Transformers","created":"2024-04-01","cited_by_count":25,"area":null},{"id":"2304.00253","title":"Q-DETR: An Efficient Low-Bit Quantized Detection Transformer","created":"2023-04-01","cited_by_count":24,"area":null},{"id":"2210.16103","title":"Collaborative Multi-Teacher Knowledge Distillation for Learning Low Bit-width Deep Neural Networks","created":"2022-10-27","cited_by_count":23,"area":"distill"},{"id":"2101.09868","title":"CPT: Efficient Deep Neural Network Training via Cyclic Precision","created":"2021-01-25","cited_by_count":19,"area":null},{"id":"2102.06841","title":"Collaborative Intelligence: Challenges and Opportunities","created":"2021-02-13","cited_by_count":19,"area":null},{"id":"2103.16701","title":"Charged particle tracking via edge-classifying interaction networks","created":"2021-03-30","cited_by_count":19,"area":null},{"id":"2108.06983","title":"Distance-aware Quantization","created":"2021-08-16","cited_by_count":19,"area":null},{"id":"2303.11906","title":"Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective","created":"2023-03-21","cited_by_count":17,"area":null},{"id":"2112.06126","title":"Neural Network Quantization for Efficient Inference: A Survey","created":"2021-12-08","cited_by_count":14,"area":null},{"id":"2304.14271","title":"A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services","created":"2023-04-13","cited_by_count":14,"area":null},{"id":"2505.15304","title":"Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control","created":"2025-05-21","cited_by_count":12,"area":"vla"},{"id":"2309.13220","title":"Poster: Self-Supervised Quantization-Aware Knowledge Distillation","created":"2023-09-22","cited_by_count":11,"area":"distill"},{"id":"2309.15467","title":"Enabling Resource-efficient AIoT System with Cross-level Optimization: A survey","created":"2023-09-27","cited_by_count":8,"area":null},{"id":"2404.01690","title":"RefQSR: Reference-based Quantization for Image Super-Resolution Networks","created":"2024-04-02","cited_by_count":8,"area":null},{"id":"2305.12901","title":"TSPTQ-ViT: Two-scaled post-training quantization for vision transformer","created":"2023-05-22","cited_by_count":7,"area":null},{"id":"2409.17634","title":"P4Q: Learning to Prompt for Quantization in Visual-language Models","created":"2024-09-26","cited_by_count":7,"area":"mllm"},{"id":"2101.04935","title":"Single-path Bit Sharing for Automatic Loss-aware Model Compression","created":"2021-01-13","cited_by_count":6,"area":null},{"id":"2104.08323","title":"Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators","created":"2021-04-16","cited_by_count":6,"area":null},{"id":"2501.00124","title":"PQD: Post-training Quantization for Efficient Diffusion Models","created":"2024-12-30","cited_by_count":6,"area":"diffusion"},{"id":"2103.01435","title":"Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths","created":"2021-03-02","cited_by_count":5,"area":null},{"id":"2307.13337","title":"Overcoming Distribution Mismatch in Quantizing Image Super-Resolution Networks","created":"2023-07-25","cited_by_count":5,"area":null},{"id":"2407.19547","title":"Temporal Feature Matters: A Framework for Diffusion Model Quantization","created":"2024-07-28","cited_by_count":5,"area":"diffusion"},{"id":"2409.14330","title":"Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity Clues","created":"2024-09-22","cited_by_count":5,"area":null},{"id":"2101.11748","title":"Rethinking Floating Point Overheads for Mixed Precision DNN Accelerators","created":"2021-01-27","cited_by_count":4,"area":null},{"id":"2103.05363","title":"MWQ: Multiscale Wavelet Quantized Neural Networks","created":"2021-03-09","cited_by_count":4,"area":null},{"id":"2310.03661","title":"Robustness-Guided Image Synthesis for Data-Free Quantization","created":"2023-10-05","cited_by_count":4,"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":"2212.02634","title":"QFT: Post-training quantization via fast joint finetuning of all degrees of freedom","created":"2022-12-05","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":"2307.04816","title":"Q-YOLO: Efficient Inference for Real-time Object Detection","created":"2023-07-01","cited_by_count":3,"area":null},{"id":"2405.17776","title":"The Binary Quantized Neural Network for Dense Prediction via Specially Designed Upsampling and Attention","created":"2024-05-28","cited_by_count":3,"area":null},{"id":"2412.06661","title":"Efficiency Meets Fidelity: A Novel Quantization Framework for Stable Diffusion","created":"2024-12-09","cited_by_count":3,"area":"diffusion"},{"id":"2108.13465","title":"Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision","created":"2021-08-30","cited_by_count":2,"area":null},{"id":"2203.07713","title":"LDP: Learnable Dynamic Precision for Efficient Deep Neural Network Training and Inference","created":"2022-03-15","cited_by_count":2,"area":null},{"id":"2203.12091","title":"FxP-QNet: A Post-Training Quantizer for the Design of Mixed Low-Precision DNNs with Dynamic Fixed-Point Representation","created":"2022-03-22","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":"2207.07931","title":"Learnable Mixed-precision and Dimension Reduction Co-design for Low-storage Activation","created":"2022-07-16","cited_by_count":2,"area":null},{"id":"2405.06038","title":"From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks","created":"2024-05-09","cited_by_count":2,"area":null},{"id":"2509.20854","title":"Punching Above Precision: Small Quantized Model Distillation with Learnable Regularizer","created":"2025-09-25","cited_by_count":2,"area":"distill"},{"id":"2301.06193","title":"RedBit: An End-to-End Flexible Framework for Evaluating the Accuracy of Quantized CNNs","created":"2023-01-15","cited_by_count":1,"area":null},{"id":"2507.04456","title":"BiVM: Accurate Binarized Neural Network for Efficient Video Matting","created":"2025-07-06","cited_by_count":1,"area":null},{"id":"2509.03850","title":"Data-Augmented Quantization-Aware Knowledge Distillation","created":"2025-09-04","cited_by_count":1,"area":"distill"},{"id":"2103.11704","title":"n-hot: Efficient bit-level sparsity for powers-of-two neural network quantization","created":"2021-03-22","cited_by_count":0,"area":null},{"id":"2106.09886","title":"Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration","created":"2021-06-18","cited_by_count":0,"area":null},{"id":"2108.01224","title":"Rapid Elastic Architecture Search under Specialized Classes and Resource Constraints","created":"2021-08-03","cited_by_count":0,"area":null},{"id":"2202.12422","title":"Standard Deviation-Based Quantization for Deep Neural Networks","created":"2022-02-24","cited_by_count":0,"area":null},{"id":"2312.13575","title":"ARBiBench: Benchmarking Adversarial Robustness of Binarized Neural Networks","created":"2023-12-21","cited_by_count":0,"area":null},{"id":"2403.11106","title":"Self-Supervised Quantization-Aware Knowledge Distillation","created":"2024-03-17","cited_by_count":0,"area":"distill"},{"id":"2405.10802","title":"Reduced storage direct tensor ring decomposition for convolutional neural networks compression","created":"2024-05-17","cited_by_count":0,"area":null},{"id":"2407.12075","title":"Tiled Bit Networks: Sub-Bit Neural Network Compression Through Reuse of Learnable Binary Vectors","created":"2024-07-16","cited_by_count":0,"area":null},{"id":"2506.16776","title":"PQCAD-DM: Progressive Quantization and Calibration-Assisted Distillation for Extremely Efficient Diffusion Model","created":"2025-06-20","cited_by_count":0,"area":"diffusion"},{"id":"2507.02222","title":"High-Fidelity Differential-information Driven Binary Vision Transformer","created":"2025-07-03","cited_by_count":0,"area":null},{"id":"2508.07142","title":"Why Does Stochastic Gradient Descent Slow Down in Low-Precision Training?","created":"2025-08-10","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},{"id":"2509.07025","title":"1 bit is all we need: binary normalized neural networks","created":"2025-09-07","cited_by_count":0,"area":null},{"id":"2510.04044","title":"Quantization Range Estimation for Convolutional Neural Networks","created":"2025-10-05","cited_by_count":0,"area":null},{"id":"2610.04100","title":"Progressive Multi-Ancestor Bit-Depth Distillation","created":"2026-10-02","cited_by_count":0,"area":null}],"next_cursor":null}