Efficient Computing

Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense NeurIPS 2023 FedLab: A Flexible Federated Learning Framework JMLR 2023 FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning IJCAI 2023 FemtoDet: An Object Detection Baseline for Energy Versus Performance Tradeoffs ICCV 2023 FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation NeurIPS 2023 Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction ICML 2023 FFCV: Accelerating Training by Removing Data Bottlenecks CVPR 2023 FIANCEE: Faster Inference of Adversarial Networks via Conditional Early Exits CVPR 2023 FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference ACL 2023 FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction AAAI 2023 Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference in Low Resource Settings ACL 2023 FIT: A Metric for Model Sensitivity ICLR 2023 FitMe: Deep Photorealistic 3D Morphable Model Avatars CVPR 2023 Fixed Input Parameterization for Efficient Prompting ACL 2023 FLASH: Automating federated learning using CASH UAI 2023 Flash: Concept Drift Adaptation in Federated Learning ICML 2023 FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU ICML 2023 FlexiViT: One Model for All Patch Sizes CVPR 2023 FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization ICML 2023 FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout NeurIPS 2023 Focus Your Attention (with Adaptive IIR Filters) EMNLP 2023 ForestPrune: Compact Depth-Pruned Tree Ensembles AISTATS 2023 Fourier Transformer: Fast Long Range Modeling by Removing Sequence Redundancy with FFT Operator ACL 2023 Frame Flexible Network CVPR 2023 FRA-RIR: Fast Random Approximation of the Image-source Method Interspeech 2023