Fast and robust earthquake source spectra and moment magnitudes from envelope inversion


Fast and robust method for screened Poisson lattice Green's function using asymptotic expansion and Fast Fourier Transform


Fast and robust parameter estimation with uncertainty quantification for the cardiac function


Fast and scalable Gaussian process modeling with applications to astronomical time series


Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction


Fast and simple quantum state estimation


Fast and simple unrooted dynamic forests


Fast and stable MAP-Elites in noisy domains using deep grids


Fast and stable modification of the Gauss-Newton method for low-rank signal estimation


Fast and stable rational approximation of generalized hypergeometric functions


Fast and stable schemes for non-linear osmosis filtering


Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics


Fast approximate simulation of seismic waves with deep learning


Fast automatically differentiable matrix functions and applications in molecular simulations


Fast calculation of p-values for one-sided Kolmogorov-Smirnov type statistics


Fast calibration of two-factor models for energy option pricing


Fast characterization of optically detected magnetic resonance spectra via data clustering


Fast classical simulation of quantum circuits via parametric rewriting in the ZX-calculus


Fast computation of 2-isogenies in dimension 4 and cryptographic applications


Fast computation of elliptic curve isogenies in characteristic two


Fast computation of kernel statistics using genotype value decomposition


Fast computation of matrix function-based centrality measures for layer-coupled multiplex networks


Fast computation of mutual information in the frequency domain with applications to global multimodal image alignment


Fast computation of optimal damping parameters for linear vibrational systems


Fast computation of persistent homology representatives with involuted persistent homology


Fast computation of soft tissue thermal response under deformation based on fast explicit dynamics finite element algorithm for surgical simulation


Fast computation of spherical phase-space functions of quantum many-body states


Fast conformational clustering of extensive molecular dynamics simulation data


Fast covariance parameter estimation of spatial Gaussian process models using neural networks


Fast deep learning correspondence for neuron tracking and identification in C.elegans using synthetic training


Fast determination of coarse grained cell anisotropy and size in epithelial tissue images using Fourier transform


Fast emulation of anisotropies induced in the cosmic microwave background by cosmic strings


Fast emulation of fermionic circuits with matrix product states


Fast erasure decoder for hypergraph product codes


Fast estimation of ion-pairing for screening electrolytes: A cluster can approximate a bulk liquid


Fast evaluation of spherical harmonics with sphericart


Fast exact computation of the $k$ most abundant isotope peaks with layer-ordered heaps


Fast exact simulation of the first passage of a tempered stable subordinator across a non-increasing function


Fast expansion into harmonics on the ball


Fast expansion into harmonics on the disk: a steerable basis with fast radial convolutions


Fast expectation-maximization algorithms for spatial generalized linear mixed models


Fast explicit dynamics finite element algorithm for transient heat transfer


Fast filtering of non-Gaussian models using Amortized Optimal Transport Maps


Fast fitting of neural ordinary differential equations by Bayesian neural gradient matching to infer ecological interactions from time series data


Fast flow-based algorithm for creating density-equalizing map projections


Fast forward feature selection for the nonlinear classification of hyperspectral images


Fast generalised linear models by database sampling and one-step polishing


Fast generation of entanglement between coupled spins using optimization and deep learning methods


Fast generation of isotropic Gaussian random fields on the sphere


Fast generation of simple directed social network graphs with reciprocal edges and high clustering


Fast geostatistical inference under positional uncertainty: Analysing DHS household survey data


Fast global spectral methods for three-dimensional partial differential equations


Fast gradient method for Low-Rank Matrix Estimation


Fast gradient-free activation maximization for neurons in spiking neural networks


Fast gradient-free optimization of excitations in variational quantum eigensolvers


Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch


Fast high-dimensional node generation with variable density


Fast hybrid numerical-asymptotic boundary element methods for high frequency screen and aperture problems based on least-squares collocation


Fast integrators with sensitivity propagation for use in CasADi


Fast inverse transform sampling of non-Gaussian distribution functions in space plasmas


Fast iterative regularization by reusing data


Fast keyed hash/pseudo-random function using SIMD multiply and permute


Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods


Fast learning from label proportions with small bags


Fast light-field 3D microscopy with out-of-distribution detection and adaptation through Conditional Normalizing Flows


Fast likelihood-free inference in the LSS Stage IV era


Fast local linear regression with anchor regularization


Fast mesh denoising with data driven normal filtering using deep variational autoencoders


Fast methods for tracking grain coagulation and ionization. I. Analytic derivation


Fast model inference and training on-board of Satellites


Fast model-based clustering of partial records


Fast modeling of the shear three-point correlation function


Fast multi-source nanophotonic simulations using augmented partial factorization


Fast multiplication of random dense matrices with fixed sparse matrices


Fast networked data selection via distributed smoothed quantile estimation


Fast non-autoregressive inverse folding with discrete diffusion


Fast non-iterative algorithm for 3D point-cloud holography


Fast nonparametric inference of network backbones for weighted graph sparsification


Fast numerical evaluation of dark matter direct detection event rates


Fast off-the-grid sparse recovery with over-parametrized projected gradient descent


Fast offline decoding with local message-passing automata


Fast optical absorption spectra calculations for periodic solid state systems


Fast optimal entrainment of limit-cycle oscillators by strong periodic inputs via phase-amplitude reduction and Floquet theory


Fast or Better? Balancing Accuracy and Cost in Retrieval-Augmented Generation with Flexible User Control


Fast ordered sampling of DNA sequence variants


Fast parameter estimation of Generalized Extreme Value distribution using Neural Networks


Fast polynomial arithmetic in homomorphic encryption with cyclo-multiquadratic fields


Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature


Fast predictions of lattice energies by continuous isometry invariants of crystal structures


Fast production of cosmological emulators in modified gravity: the matter power spectrum


Fast quantum state reconstruction via accelerated non-convex programming


Fast radio bursts as a probe of gravity on cosmological scales


Fast randomized algorithms for low-rank matrix approximations with applications in global comparative analysis of a class of data sets


Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers


Fast reactive flow simulations using analytical Jacobian and dynamic load balancing in OpenFOAM


Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling


Fast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency


Fast resonance decays in nuclear collisions


Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm


Fast sampling with Gaussian scale-mixture priors in high-dimensional regression


Fast scalar quadratic maximum likelihood estimators for the CMB B-mode power spectrum


Fast sequence to graph alignment using the graph wavefront algorithm


Fast simulation for multi-photon, atomic-ensemble quantum model of linear optical systems addressing the curse of dimensionality


Fast simulation of airfoil flow field via deep neural network


Fast simulation of planar Clifford circuits


Fast simulations for intensity mapping experiments


Fast solver for diffusive transport times on dynamic intracellular networks


Fast symplectic integrator for Nesterov-type acceleration method


Fast threshold optimization for multi-label audio tagging using Surrogate gradient learning


Fast transcription of speech in low-resource languages


Fast unified reconstruction algorithm for conventional, phase-contrast and diffraction tomography


Fast variational Bayes for heavy-tailed PLDA applied to i-vectors and x-vectors


Fast yet Safe: Early-Exiting with Risk Control


Fast zone-based algorithms for reachability in pushdown timed automata


Fast(er) Exact Decoding and Global Training for Transition-Based Dependency Parsing via a Minimal Feature Set


Fast, Accurate and Interpretable Time Series Classification Through Randomization


Fast, Compact and Highly Scalable Visual Place Recognition through Sequence-based Matching of Overloaded Representations


Fast, Distribution-free Predictive Inference for Neural Networks with Coverage Guarantees


Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders


Fast, Exact Bootstrap Principal Component Analysis for p>1 million


Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs


Fast, Expressive SE$(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space


Fast, Flexible Models for Discovering Topic Correlation across Weakly-Related Collections


Fast, Modular, and Differentiable Framework for Machine Learning-Enhanced Molecular Simulations


Fast, Precise Myelin Water Quantification using DESS MRI and Kernel Learning


Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression


Fast, Robust, Continuous Monocular Egomotion Computation


Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching


Fast, Secure, Adaptable: LionsOS Design, Implementation and Performance


Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees


Fast, Structured Clinical Documentation via Contextual Autocomplete


Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings


Fast, accurate, and predictive method for atom detection in site-resolved images of microtrap arrays


Fast, accurate, and system-specific variable-resolution modelling of proteins


Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning


Fast, optimal, and dynamic electoral campaign budgeting by a generalized Colonel Blotto game


Fast-Converged Deep Reinforcement Learning for Optimal Dispatch of Large-Scale Power Systems under Transient Security Constraints


Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation


Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature


Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience


Fast-Forward Video Based on Semantic Extraction


Fast-MVSNet: Sparse-to-Dense Multi-View Stereo With Learned Propagation and Gauss-Newton Refinement


Fast-MoCo: Boost Momentum-based Contrastive Learning with Combinatorial Patches


Fast-PGM: Fast Probabilistic Graphical Model Learning and Inference


Fast-Replanning Motion Control for Non-Holonomic Vehicles with Aborting A*


Fast-SNARF: A Fast Deformer for Articulated Neural Fields


Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN


Fast-Track of F-18 Positron paths simulations using GANs


Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesis


Fast-moving pattern interfaces close to a Turing instability in an asymptotic model for the three-dimensional Bénard-Marangoni problem


Fast-update in self-learning algorithm for continuous-time quantum Monte Carlo


Fast-wave slow-wave spectral deferred correction methods applied to the compressible Euler equations


Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass


FastAMI -- a Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics


FastAST: Accelerating Audio Spectrogram Transformer via Token Merging and Cross-Model Knowledge Distillation


FastAdaSP: Multitask-Adapted Efficient Inference for Large Speech Language Model


FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation


FastAudio: A Learnable Audio Front-End for Spoof Speech Detection


FastBCSD: Fast and Efficient Neural Network for Binary Code Similarity Detection


FastBlend: a Powerful Model-Free Toolkit Making Video Stylization Easier


FastCLIP: A Suite of Optimization Techniques to Accelerate CLIP Training with Limited Resources


FastCTF: A Robust Solver for Conduction Transfer Function Coefficients and Thermal Response Factors


FastCache: Fast Caching for Diffusion Transformer Through Learnable Linear Approximation


FastCar: Cache Attentive Replay for Fast Auto-Regressive Video Generation on the Edge


FastCat Catalogues: Interactive Entity-based Exploratory Analysis of Archival Documents


FastClass: A Time-Efficient Approach to Weakly-Supervised Text Classification


FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention


FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social Networks


FastCuRL: Curriculum Reinforcement Learning with Progressive Context Extension for Efficient Training R1-like Reasoning Models


FastDiagP: An Algorithm for Parallelized Direct Diagnosis


FastDrag: Manipulate Anything in One Step


FastDup: a scalable duplicate marking tool using speculation-and-test mechanism


FastEnsemble: scalable ensemble clustering on large networks


FastFT: Accelerating Reinforced Feature Transformation via Advanced Exploration Strategies


FastFace: Fast-converging Scheduler for Large-scale Face Recognition Training with One GPU


FastFace: Tuning Identity Preservation in Distilled Diffusion via Guidance and Attention


FastFiD: Improve Inference Efficiency of Open Domain Question Answering via Sentence Selection


FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours


FastFormers: Highly Efficient Transformer Models for Natural Language Understanding


FastGEMF: Scalable High-Speed Simulation of Stochastic Spreading Processes over Complex Multilayer Networks


FastGL: A GPU-Efficient Framework for Accelerating Sampling-Based GNN Training at Large Scale


FastGPL: a C++ library for fast evaluation of generalized polylogarithms


FastGeodis: Fast Generalised Geodesic Distance Transform


FastGrasp: Efficient Grasp Synthesis with Diffusion


FastHare: Fast Hamiltonian Reduction for Large-scale Quantum Annealing


FastHyMix: Fast and Parameter-free Hyperspectral Image Mixed Noise Removal


FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging


FastImpute: A Baseline for Open-source, Reference-Free Genotype Imputation Methods -- A Case Study in PRS313


FastInst: A Simple Query-Based Model for Real-Time Instance Segmentation


FastIoT -- A framework and holistic approach for rapid development of IIoT systems


FastKASSIM: A Fast Tree Kernel-Based Syntactic Similarity Metric


FastKV: KV Cache Compression for Fast Long-Context Processing with Token-Selective Propagation


FastLLVE: Real-Time Low-Light Video Enhancement with Intensity-Aware Lookup Table


FastLORS: Joint Modeling for eQTL Mapping in R


FastLTS: Non-Autoregressive End-to-End Unconstrained Lip-to-Speech Synthesis


FastLexRank: Efficient Lexical Ranking for Structuring Social Media Posts


FastLloyd: Federated, Accurate, Secure, and Tunable $k$-Means Clustering with Differential Privacy


FastLog: An End-to-End Method to Efficiently Generate and Insert Logging Statements


FastLogAD: Log Anomaly Detection with Mask-Guided Pseudo Anomaly Generation and Discrimination


FastMAC: Stochastic Spectral Sampling of Correspondence Graph


FastMIM: Expediting Masked Image Modeling Pre-training for Vision


FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction Framework


FastMap: Revisiting Dense and Scalable Structure from Motion


FastMapSVM: Classifying Complex Objects Using the FastMap Algorithm and Support-Vector Machines


FastMask: Segment Multi-scale Object Candidates in One Shot


FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models


FastMig: Leveraging FastFreeze to Establish Robust Service Liquidity in Cloud 2.0


FastMoE: A Fast Mixture-of-Expert Training System


FastPCI: Motion-Structure Guided Fast Point Cloud Frame Interpolation


FastPillars: A Deployment-friendly Pillar-based 3D Detector


FastPoints: A State-of-the-Art Point Cloud Renderer for Unity


FastRE: Towards Fast Relation Extraction with Convolutional Encoder and Improved Cascade Binary Tagging Framework


FastRIFE: Optimization of Real-Time Intermediate Flow Estimation for Video Frame Interpolation


FastRPB: a Scalable Relative Positional Encoding for Long Sequence Tasks


FastRemap: A Tool for Quickly Remapping Reads between Genome Assemblies


FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images


FastSTMF: Efficient tropical matrix factorization algorithm for sparse data


FastSal: a Computationally Efficient Network for Visual Saliency Prediction


FastSpec: Scalable Generation and Detection of Spectre Gadgets Using Neural Embeddings


FastTextSpotter: A High-Efficiency Transformer for Multilingual Scene Text Spotting


FastTrack: an open-source software for tracking varying numbers of deformable objects


FastVID: Dynamic Density Pruning for Fast Video Large Language Models


FastVLM: Efficient Vision Encoding for Vision Language Models


FastWARC: Optimizing Large-Scale Web Archive Analytics


FastZIP: Faster and More Secure Zero-Interaction Pairing


FasteNet: A Fast Railway Fastener Detector


Faster Approximation Algorithms for Parameterized Graph Clustering and Edge Labeling


Faster Asynchronous Nonconvex Block Coordinate Descent with Locally Chosen Stepsizes


Faster Base64 Encoding and Decoding Using AVX2 Instructions


Faster Binary Embeddings for Preserving Euclidean Distances


Faster Born probability estimation via gate merging and frame optimisation


Faster Causal Attention Over Large Sequences Through Sparse Flash Attention


Faster Convergence for Transformer Fine-tuning with Line Search Methods


Faster Convergence with Lexicase Selection in Tree-based Automated Machine Learning


Faster DAN: Multi-target Queries with Document Positional Encoding for End-to-end Handwritten Document Recognition


Faster Deep Reinforcement Learning with Slower Online Network


Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference


Faster Exact MPE and Constrained Optimization with Deterministic Finite State Automata


Faster Family-wise Error Control for Neuroimaging with a Parametric Bootstrap


Faster GPU-based convolutional gridding via thread coarsening


Faster Global Minimum Cut with Predictions


Faster Greedy MAP Inference for Determinantal Point Processes


Faster ISNet for Background Bias Mitigation on Deep Neural Networks


Faster Lead Optimization Mapper Algorithm for Large-Scale Relative Free Energy Perturbation


Faster Learned Sparse Retrieval with Block-Max Pruning


Faster Learned Sparse Retrieval with Guided Traversal


Faster Learning of Temporal Action Proposal via Sparse Multilevel Boundary Generator


Faster Local Solvers for Graph Diffusion Equations


Faster MCMC for Gaussian Latent Position Network Models


Faster Matrix Completion Using Randomized SVD


Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking


Faster Meta Update Strategy for Noise-Robust Deep Learning


Faster Minimum Bayes Risk Decoding with Confidence-based Pruning


Faster Neural Network Training with Approximate Tensor Operations


Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization


Faster OreFSDet : A Lightweight and Effective Few-shot Object Detector for Ore Images


Faster Parameter-Efficient Tuning with Token Redundancy Reduction


Faster Positional-Population Counts for AVX2, AVX-512, and ASIMD


Faster Prefix-Sorting Algorithms for Deterministic Finite Automata


Faster Randomized Block Sparse Kaczmarz by Averaging


Faster Repetition-Aware Compressed Suffix Trees based on Block Trees


Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower Bound


Faster Secure Comparisons with Offline Phase for Efficient Private Set Intersection


Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity


Faster Stochastic Algorithms for Minimax Optimization under Polyak--Łojasiewicz Conditions


Faster Training of Neural ODEs Using Gauß-Legendre Quadrature


Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training


Faster VoxelPose: Real-time 3D Human Pose Estimation by Orthographic Projection


Faster and Better Nested Dissection Orders for Customizable Contraction Hierarchies


Faster and Generalized Temporal Triangle Counting, via Degeneracy Ordering


Faster and Lighter LLMs: A Survey on Current Challenges and Way Forward


Faster and More Accurate Measurement through Additive-Error Counters


Faster and Simpler SNN Simulation with Work Queues


Faster calculation of the percolation correlation length on spatial networks


Faster estimation for constrained gamma mixture models using closed-form estimators


Faster estimation of the Knorr-Held Type IV space-time model


Faster hyperspectral image classification based on selective kernel mechanism using deep convolutional networks


Faster independent component analysis by preconditioning with Hessian approximations


Faster maximal clique enumeration in large real-world link streams


Faster multiplication over $\mathbb{F}_2[X]$ using AVX512 instruction set and VPCLMULQDQ instruction


Faster optimal univariate microgaggregation


Faster parameterized algorithm for 3-Hitting Set


Faster than FAST: GPU-Accelerated Frontend for High-Speed VIO


Faster-LTN: a neuro-symbolic, end-to-end object detection architecture


Faster-Than-Native Alternatives for x86 VP2INTERSECT Instructions


Faster-Than-Nyquist Equalization with Convolutional Neural Networks


FasterSeg: Searching for Faster Real-time Semantic Segmentation


FasterVideo: Efficient Online Joint Object Detection And Tracking


Fat-to-Thin Policy Optimization: Offline RL with Sparse Policies


FatNet: High Resolution Kernels for Classification Using Fully Convolutional Optical Neural Networks


FatSegNet : A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI


FateZero: Fusing Attentions for Zero-shot Text-based Video Editing


FathomGPT: A Natural Language Interface for Interactively Exploring Ocean Science Data


FathomNet: A global image database for enabling artificial intelligence in the ocean


Fatigue Assessment using ECG and Actigraphy Sensors


Fatigue detection via sequential testing of biomechanical data using martingale statistic


Fault Detection via Occupation Kernel Principal Component Analysis


Fault Diagnosis across Heterogeneous Domains via Self-Adaptive Temporal-Spatial Attention and Sample Generation


Fault Handling in Large Water Networks with Online Dictionary Learning


Fault Identification Enhancement with Reinforcement Learning (FIERL)


Fault Localisation and Repair for DL Systems: An Empirical Study with LLMs


Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training


Fault Tolerant Neural Control Barrier Functions for Robotic Systems under Sensor Faults and Attacks


Fault slip in hydraulic stimulation of geothermal reservoirs: governing mechanisms and process-structure interaction


Fault tolerant resource estimation of quantum random-access memories


Fault-tolerant hyperbolic Floquet quantum error correcting codes


FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis


FaultFormer: Pretraining Transformers for Adaptable Bearing Fault Classification


FaultNet: A Deep Convolutional Neural Network for bearing fault classification


Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach


Faulty towers: recovering a functioning quantum random access memory in the presence of defective routers


Fawkes: Protecting Privacy against Unauthorized Deep Learning Models


FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning


FeDXL: Provable Federated Learning for Deep X-Risk Optimization


FeNNol: an Efficient and Flexible Library for Building Force-field-enhanced Neural Network Potentials


FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling


FeTaQA: Free-form Table Question Answering


FeaKM: Robust Collaborative Perception under Noisy Pose Conditions


FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis


Fearless Stochasticity in Expectation Propagation


Feasibility Consistent Representation Learning for Safe Reinforcement Learning


Feasibility Study of Multi-Site Split Learning for Privacy-Preserving Medical Systems under Data Imbalance Constraints in COVID-19, X-Ray, and Cholesterol Dataset


Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation


Feasibility of Local Trajectory Planning for Level-2+ Semi-autonomous Driving without Absolute Localization


Feasibility of Modeling Orthogonal Frequency-Division Multiplexing Communication Signals with Unsupervised Generative Adversarial Networks


Feasibility of accelerating incompressible computational fluid dynamics simulations with fault-tolerant quantum computers


Feasible Action Space Reduction for Quantifying Causal Responsibility in Continuous Spatial Interactions


Feasible Action-Space Reduction as a Metric of Causal Responsibility in Multi-Agent Spatial Interactions


Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety


Feasible Path SQP Algorithm for Simulation-based Optimization Surrogated with Differentiable Machine Learning Models


Feasible Recourse Plan via Diverse Interpolation


Feasible Region: an Actuation-Aware Extension of the Support Region


Feasible approximation of matching equilibria for large-scale matching for teams problems


Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models


FeatAug-DETR: Enriching One-to-Many Matching for DETRs with Feature Augmentation


FeatER: An Efficient Network for Human Reconstruction via Feature Map-Based TransformER


FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision


FeatInsight: An Online ML Feature Management System on 4Paradigm Sage-Studio Platform


FeatInv: Spatially resolved mapping from feature space to input space using conditional diffusion models


FeatPCA: A feature subspace based principal component analysis technique for enhancing clustering of single-cell RNA-seq data


FeatSense -- A Feature-based Registration Algorithm with GPU-accelerated TSDF-Mapping Backend for NVIDIA Jetson Boards


FeatUp: A Model-Agnostic Framework for Features at Any Resolution


Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imaging


Feather: A Feature Model Transformation Language


Feather: An Elegant Solution to Effective DNN Sparsification


Featherweight Assisted Vulnerability Discovery


Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields


Feature Adaptation of Pre-Trained Language Models across Languages and Domains with Robust Self-Training


Feature Aggregation and Propagation Network for Camouflaged Object Detection


Feature Aggregation and Refinement Network for 2D AnatomicalLandmark Detection


Feature Alignment and Uniformity for Test Time Adaptation


Feature Alignment: Rethinking Efficient Active Learning via Proxy in the Context of Pre-trained Models


Feature Attribution Explanations for Spiking Neural Networks


Feature Attribution from First Principles


Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation


Feature Boosting, Suppression, and Diversification for Fine-Grained Visual Classification


Feature Characterization for Profile Surface Texture


Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark


Feature Combination Meets Attention: Baidu Soccer Embeddings and Transformer based Temporal Detection


Feature Completion for Occluded Person Re-Identification


Feature Concatenation Multi-view Subspace Clustering


Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize


Feature Decomposition for Reducing Negative Transfer: A Novel Multi-task Learning Method for Recommender System


Feature Distillation Interaction Weighting Network for Lightweight Image Super-Resolution


Feature Distribution Matching for Federated Domain Generalization


Feature Engineering with Regularity Structures


Feature Erasing and Diffusion Network for Occluded Person Re-Identification


Feature Expansion and enhanced Compression for Class Incremental Learning


Feature Expansion for Graph Neural Networks


Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)


Feature Extractor Stacking for Cross-domain Few-shot Learning


Feature Fitted Online Conformal Prediction for Deep Time Series Forecasting Model


Feature Fusion Based on Mutual-Cross-Attention Mechanism for EEG Emotion Recognition


Feature Fusion Revisited: Multimodal CTR Prediction for MMCTR Challenge


Feature Fusion Transferability Aware Transformer for Unsupervised Domain Adaptation


Feature Fusion Vision Transformer for Fine-Grained Visual Categorization


Feature Fusion for Online Mutual Knowledge Distillation


Feature Fusion via Multiresolution Compressive Measurement Matrix Analysis For Spectral Image Classification


Feature Generation and Hypothesis Verification for Reliable Face Anti-Spoofing


Feature Generation for Long-tail Classification


Feature Grouping and Sparse Principal Component Analysis with Truncated Regularization


Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data


Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing


Feature Hedging: Correlated Features Break Narrow Sparse Autoencoders


Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing Tasks


Feature Importance Disparities for Data Bias Investigations


Feature Importance Measurement based on Decision Tree Sampling


Feature Importance Ranking for Deep Learning


Feature Importance and Explainability in Quantum Machine Learning


Feature Importance-Aware Deep Joint Source-Channel Coding for Computationally Efficient and Adjustable Image Transmission


Feature Inference Attack on Model Predictions in Vertical Federated Learning


Feature Interaction Aware Automated Data Representation Transformation


Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection


Feature Interactions Reveal Linguistic Structure in Language Models


Feature Learning and Network Structure from Noisy Node Activity Data


Feature Learning by Multidimensional Scaling and its Applications in Object Recognition


Feature Learning for Accelerometer based Gait Recognition


Feature Learning in Infinite-Width Neural Networks


Feature Lenses: Plug-and-play Neural Modules for Transformation-Invariant Visual Representations


Feature Map Testing for Deep Neural Networks


Feature Map Transform Coding for Energy-Efficient CNN Inference


Feature Mixing for Writer Retrieval and Identification on Papyri Fragments


Feature Necessity & Relevancy in ML Classifier Explanations


Feature Noise Boosts DNN Generalization under Label Noise


Feature Noise Induces Loss Discrepancy Across Groups


Feature Norm Regularized Federated Learning: Transforming Skewed Distributions into Global Insights


Feature Optimization for Atomistic Machine Learning Yields A Data-Driven Construction of the Periodic Table of the Elements


Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective


Feature Perturbation Augmentation for Reliable Evaluation of Importance Estimators in Neural Networks


Feature Programming for Multivariate Time Series Prediction


Feature Proliferation -- the "Cancer" in StyleGAN and its Treatments


Feature Pyramid Network for Multi-task Affective Analysis


Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection


Feature Re-Learning with Data Augmentation for Video Relevance Prediction


Feature Re-calibration based Multiple Instance Learning for Whole Slide Image Classification


Feature Relevance Bounds for Ordinal Regression


Feature Representation Learning for Unsupervised Cross-domain Image Retrieval


Feature Robust Optimal Transport for High-dimensional Data


Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks


Feature Selection for High-Dimensional Neural Network Potentials with the Adaptive Group Lasso


Feature Selection for Recommender Systems with Quantum Computing


Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 Methods


Feature Selection using Stochastic Gates


Feature Separation and Recalibration for Adversarial Robustness


Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformers


Feature Space Particle Inference for Neural Network Ensembles


Feature Space Perturbation: A Panacea to Enhanced Transferability Estimation


Feature Space Saturation during Training


Feature Space Singularity for Out-of-Distribution Detection


Feature Space Targeted Attacks by Statistic Alignment


Feature Splatting for Better Novel View Synthesis with Low Overlap


Feature Staleness Aware Incremental Learning for CTR Prediction


Feature Statistics Mixing Regularization for Generative Adversarial Networks


Feature Statistics with Uncertainty Help Adversarial Robustness


Feature Structure Distillation with Centered Kernel Alignment in BERT Transferring


Feature Stylization and Domain-aware Contrastive Learning for Domain Generalization


Feature Synergy, Redundancy, and Independence in Global Model Explanations using SHAP Vector Decomposition


Feature Visualization in 3D Convolutional Neural Networks


Feature Weighting and Boosting for Few-Shot Segmentation


Feature and Label Embedding Spaces Matter in Addressing Image Classifier Bias


Feature embedding in click-through rate prediction


Feature extraction using Spectral Clustering for Gene Function Prediction using Hierarchical Multi-label Classification


Feature importance to explain multimodal prediction models. A clinical use case


Feature interpretability in BCIs: exploring the role of network lateralization


Feature maps for the Laplacian kernel and its generalizations


Feature point detection in HDR images based on coefficient of variation


Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection


Feature selection as Monte-Carlo Search in Growing Single Rooted Directed Acyclic Graph by Best Leaf Identification


Feature selection in high-dimensional dataset using MapReduce


Feature space approximation for kernel-based supervised learning


Feature transforms for image data augmentation


Feature-Adaptive and Data-Scalable In-Context Learning


Feature-Attending Recurrent Modules for Generalization in Reinforcement Learning


Feature-Balanced Loss for Long-Tailed Visual Recognition


Feature-Based Dual Visual Feature Extraction Model for Compound Multimodal Emotion Recognition


Feature-Based Image Clustering and Segmentation Using Wavelets


Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models


Feature-Based Time-Series Analysis in R using the theft Package


Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis


Feature-Critic Networks for Heterogeneous Domain Generalization


Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels


Feature-Driven End-To-End Test Generation


Feature-Driven Strategies for Trading Wind Power and Hydrogen


Feature-Factory: Automating Software Feature Integration Using Generative AI


Feature-Fused SSD: Fast Detection for Small Objects


Feature-Less End-to-End Nested Term Extraction


Feature-Level Debiased Natural Language Understanding


Feature-Suppressed Contrast for Self-Supervised Food Pre-training


Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations


Feature-based reformulation of entities in triple pattern queries


Feature-level Attentive ICF for Recommendation


Feature-metric Loss for Self-supervised Learning of Depth and Egomotion


Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences


Feature-oriented Deep Learning Framework for Pulmonary Cone-beam CT (CBCT) Enhancement with Multi-task Customized Perceptual Loss


Feature-prompting GBMSeg: One-Shot Reference Guided Training-Free Prompt Engineering for Glomerular Basement Membrane Segmentation


Feature-specific inference for penalized regression using local false discovery rates


Feature-weighted elastic net: using "features of features" for better prediction


Feature2Vec: Distributional semantic modelling of human property knowledge


FeatureBooster: Boosting Feature Descriptors with a Lightweight Neural Network


FeatureNeRF: Learning Generalizable NeRFs by Distilling Foundation Models


FeatureNorm: L2 Feature Normalization for Dynamic Graph Embedding


Features Based Adaptive Augmentation for Graph Contrastive Learning


Features for the 0-1 knapsack problem based on inclusionwise maximal solutions


Features in Extractive Supervised Single-document Summarization: Case of Persian News


Featurizing Koopman Mode Decomposition For Robust Forecasting


Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems


Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning


Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer


Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation


Fed-MUnet: Multi-modal Federated Unet for Brain Tumor Segmentation


Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity


Fed-urlBERT: Client-side Lightweight Federated Transformers for URL Threat Analysis


Fed3DGS: Scalable 3D Gaussian Splatting with Federated Learning


FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection


FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things


FedALA: Adaptive Local Aggregation for Personalized Federated Learning


FedAPM: Federated Learning via ADMM with Partial Model Personalization


FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning


FedAVO: Improving Communication Efficiency in Federated Learning with African Vultures Optimizer


FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors


FedAdapt: Adaptive Offloading for IoT Devices in Federated Learning


FedAdapter: Efficient Federated Learning for Modern NLP


FedApp: a Research Sandbox for Application Orchestration in Federated Clouds using OpenStack


FedAudio: A Federated Learning Benchmark for Audio Tasks


FedBABU: Towards Enhanced Representation for Federated Image Classification


FedBAT: Communication-Efficient Federated Learning via Learnable Binarization


FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems


FedBKD: Distilled Federated Learning to Embrace Gerneralization and Personalization on Non-IID Data


FedBM: Stealing Knowledge from Pre-trained Language Models for Heterogeneous Federated Learning


FedBN: Federated Learning on Non-IID Features via Local Batch Normalization


FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction


FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model


FedBrain-Distill: Communication-Efficient Federated Brain Tumor Classification Using Ensemble Knowledge Distillation on Non-IID Data


FedBug: A Bottom-Up Gradual Unfreezing Framework for Federated Learning


FedCAP: Robust Federated Learning via Customized Aggregation and Personalization


FedCAR: Cross-client Adaptive Re-weighting for Generative Models in Federated Learning


FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization


FedCCRL: Federated Domain Generalization with Cross-Client Representation Learning


FedCIA: Federated Collaborative Information Aggregation for Privacy-Preserving Recommendation


FedCL: Federated Multi-Phase Curriculum Learning to Synchronously Correlate User Heterogeneity


FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy


FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks


FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training


FedCache 2.0: Federated Edge Learning with Knowledge Caching and Dataset Distillation


FedCert: Federated Accuracy Certification


FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks


FedComm: Understanding Communication Protocols for Edge-based Federated Learning


FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices using a Computing Power Aware Scheduler


FedConv: A Learning-on-Model Paradigm for Heterogeneous Federated Clients


FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning


FedCore: Straggler-Free Federated Learning with Distributed Coresets


FedCorr: Multi-Stage Federated Learning for Label Noise Correction


FedCos: A Scene-adaptive Federated Optimization Enhancement for Performance Improvement


FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification


FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning


FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space


FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization


FedDR -- Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization


FedDUAL: A Dual-Strategy with Adaptive Loss and Dynamic Aggregation for Mitigating Data Heterogeneity in Federated Learning


FedDW: Distilling Weights through Consistency Optimization in Heterogeneous Federated Learning


FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment


FedDebug: Systematic Debugging for Federated Learning Applications


FedDefender: Backdoor Attack Defense in Federated Learning


FedDefender: Client-Side Attack-Tolerant Federated Learning


FedDisco: Federated Learning with Discrepancy-Aware Collaboration


FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels


FedE: Embedding Knowledge Graphs in Federated Setting


FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed Settings


FedER: Federated Learning through Experience Replay and Privacy-Preserving Data Synthesis


FedEgo: Privacy-preserving Personalized Federated Graph Learning with Ego-graphs


FedEntropy: Efficient Device Grouping for Federated Learning Using Maximum Entropy Judgment


FedExP: Speeding Up Federated Averaging via Extrapolation


FedFA: Federated Learning with Feature Anchors to Align Features and Classifiers for Heterogeneous Data


FedFOR: Stateless Heterogeneous Federated Learning with First-Order Regularization


FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition


FedFT: Improving Communication Performance for Federated Learning with Frequency Space Transformation


FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising


FedFed: Feature Distillation against Data Heterogeneity in Federated Learning


FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching


FedFisher: Leveraging Fisher Information for One-Shot Federated Learning


FedFly: Towards Migration in Edge-based Distributed Federated Learning


FedForgery: Generalized Face Forgery Detection with Residual Federated Learning


FedFormer: Contextual Federation with Attention in Reinforcement Learning


FedFusion: Manifold Driven Federated Learning for Multi-satellite and Multi-modality Fusion


FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks


FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization


FedGH: Heterogeneous Federated Learning with Generalized Global Header


FedGMark: Certifiably Robust Watermarking for Federated Graph Learning


FedGS: Federated Gradient Scaling for Heterogeneous Medical Image Segmentation


FedGS: Federated Graph-based Sampling with Arbitrary Client Availability


FedGTA: Topology-aware Averaging for Federated Graph Learning


FedGiA: An Efficient Hybrid Algorithm for Federated Learning


FedGrad: Mitigating Backdoor Attacks in Federated Learning Through Local Ultimate Gradients Inspection


FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks


FedHCDR: Federated Cross-Domain Recommendation with Hypergraph Signal Decoupling


FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks


FedHPD: Heterogeneous Federated Reinforcement Learning via Policy Distillation


FedHarmony: Unlearning Scanner Bias with Distributed Data


FedHe: Heterogeneous Models and Communication-Efficient Federated Learning


FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation Completeness


FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data


FedIPR: Ownership Verification for Federated Deep Neural Network Models


FedJudge: Federated Legal Large Language Model


FedKD-hybrid: Federated Hybrid Knowledge Distillation for Lithography Hotspot Detection


FedKL: Tackling Data Heterogeneity in Federated Reinforcement Learning by Penalizing KL Divergence


FedKit: Enabling Cross-Platform Federated Learning for Android and iOS


FedLF: Adaptive Logit Adjustment and Feature Optimization in Federated Long-Tailed Learning


FedLP: Layer-wise Pruning Mechanism for Communication-Computation Efficient Federated Learning


FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentation


FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing


FedLWS: Federated Learning with Adaptive Layer-wise Weight Shrinking


FedLion: Faster Adaptive Federated Optimization with Fewer Communication


FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data


FedMABench: Benchmarking Mobile Agents on Decentralized Heterogeneous User Data


FedMAP: Unlocking Potential in Personalized Federated Learning through Bi-Level MAP Optimization


FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices


FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning


FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data


FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation


FedMRL: Data Heterogeneity Aware Federated Multi-agent Deep Reinforcement Learning for Medical Imaging


FedMSE: Federated learning for IoT network intrusion detection


FedMUA: Exploring the Vulnerabilities of Federated Learning to Malicious Unlearning Attacks


FedMatch: Federated Learning Over Heterogeneous Question Answering Data


FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging


FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation


FedModule: A Modular Federated Learning Framework


FedMood: Federated Learning on Mobile Health Data for Mood Detection


FedNLP: An interpretable NLP System to Decode Federal Reserve Communications


FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning


FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning


FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity


FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning


FedPCL-CDR: A Federated Prototype-based Contrastive Learning Framework for Privacy-Preserving Cross-domain Recommendation


FedPFT: Federated Proxy Fine-Tuning of Foundation Models


FedPH: Privacy-enhanced Heterogeneous Federated Learning


FedPall: Prototype-based Adversarial and Collaborative Learning for Federated Learning with Feature Drift


FedPalm: A General Federated Learning Framework for Closed- and Open-Set Palmprint Verification


FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated Learning


FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning


FedPop: Federated Population-based Hyperparameter Tuning


FedPref: Federated Learning Across Heterogeneous Multi-objective Preferences


FedProc: Prototypical Contrastive Federated Learning on Non-IID data


FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehicles


FedQAS: Privacy-aware machine reading comprehension with federated learning


FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients


FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems


FedRAV: Hierarchically Federated Region-Learning for Traffic Object Classification of Autonomous Vehicles


FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering


FedRIR: Rethinking Information Representation in Federated Learning


FedRKG: A Privacy-preserving Federated Recommendation Framework via Knowledge Graph Enhancement


FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning


FedRSU: Federated Learning for Scene Flow Estimation on Roadside Units


FedReMa: Improving Personalized Federated Learning via Leveraging the Most Relevant Clients


FedRec: Federated Learning of Universal Receivers over Fading Channels


FedRecAttack: Model Poisoning Attack to Federated Recommendation


FedRef: Communication-Efficient Bayesian Fine Tuning with Reference Model


FedSC: Federated Learning with Semantic-Aware Collaboration


FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization


FedSECA: Sign Election and Coordinate-wise Aggregation of Gradients for Byzantine Tolerant Federated Learning


FedSIS: Federated Split Learning with Intermediate Representation Sampling for Privacy-preserving Generalized Face Presentation Attack Detection


FedSKC: Federated Learning with Non-IID Data via Structural Knowledge Collaboration


FedSL: Federated Split Learning on Distributed Sequential Data in Recurrent Neural Networks


FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning


FedSPU: Personalized Federated Learning for Resource-constrained Devices with Stochastic Parameter Update


FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning


FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference


FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs


FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning


FedServing: A Federated Prediction Serving Framework Based on Incentive Mechanism


FedShield-LLM: A Secure and Scalable Federated Fine-Tuned Large Language Model


FedSiKD: Clients Similarity and Knowledge Distillation: Addressing Non-i.i.d. and Constraints in Federated Learning


FedSkel: Efficient Federated Learning on Heterogeneous Systems with Skeleton Gradients Update


FedSkip: Combatting Statistical Heterogeneity with Federated Skip Aggregation


FedSlate:A Federated Deep Reinforcement Learning Recommender System


FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation


FedStale: leveraging stale client updates in federated learning


FedStaleWeight: Buffered Asynchronous Federated Learning with Fair Aggregation via Staleness Reweighting


FedStyle: Style-Based Federated Learning Crowdsourcing Framework for Art Commissions


FedTADBench: Federated Time-Series Anomaly Detection Benchmark


FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning


FedTP: Federated Learning by Transformer Personalization


FedTabDiff: Federated Learning of Diffusion Probabilistic Models for Synthetic Mixed-Type Tabular Data Generation


FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective


FedVLN: Privacy-preserving Federated Vision-and-Language Navigation


FedVSR: Towards Model-Agnostic Federated Learning in Video Super-Resolution


FedVal: Different good or different bad in federated learning


FedX: Unsupervised Federated Learning with Cross Knowledge Distillation


FedZero: Leveraging Renewable Excess Energy in Federated Learning


Federated Accelerated Stochastic Gradient Descent


Federated Active Learning for Target Domain Generalisation


Federated Adaptation for Foundation Model-based Recommendations


Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning


Federated Anomaly Detection for Early-Stage Diagnosis of Autism Spectrum Disorders using Serious Game Data


Federated Bayesian Optimization via Thompson Sampling


Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning


Federated Black-Box Adaptation for Semantic Segmentation


Federated Boosted Decision Trees with Differential Privacy


Federated Causal Discovery from Heterogeneous Data


Federated Causal Inference in Heterogeneous Observational Data


Federated Class-Incremental Learning with New-Class Augmented Self-Distillation


Federated Conformal Predictors for Distributed Uncertainty Quantification


Federated Continual Learning for Text Classification via Selective Inter-client Transfer


Federated Continual Learning with Weighted Inter-client Transfer


Federated Cross Learning for Medical Image Segmentation


Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity


Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks


Federated Deep Reinforcement Learning-based Bitrate Adaptation for Dynamic Adaptive Streaming over HTTP


Federated Deep Unfolding for Sparse Recovery


Federated Domain Generalization for Image Recognition via Cross-Client Style Transfer


Federated Domain Generalization via Prompt Learning and Aggregation


Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better


Federated Edge Learning with Misaligned Over-The-Air Computation


Federated Ensemble-Directed Offline Reinforcement Learning


Federated Fairness Analytics: Quantifying Fairness in Federated Learning


Federated Few-Shot Learning for Mobile NLP


Federated Few-shot Learning for Cough Classification with Edge Devices


Federated Foundation Models on Heterogeneous Time Series


Federated Fuzzy Neural Network with Evolutionary Rule Learning


Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling


Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent


Federated Graph Classification over Non-IID Graphs


Federated Graph Learning with Structure Proxy Alignment


Federated Graph Semantic and Structural Learning


Federated Hybrid Model Pruning through Loss Landscape Exploration


Federated Impression for Learning with Distributed Heterogeneous Data


Federated Incremental Named Entity Recognition


Federated Learning Assisted Edge Caching Scheme Based on Lightweight Architecture DDPM


Federated Learning Based Multilingual Emoji Prediction In Clean and Attack Scenarios


Federated Learning Based on Dynamic Regularization


Federated Learning Beyond the Star: Local D2D Model Consensus with Global Cluster Sampling


Federated Learning Client Pruning for Noisy Labels


Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS


Federated Learning Hyper-Parameter Tuning from a System Perspective


Federated Learning Meets Fairness and Differential Privacy


Federated Learning Meets Multi-objective Optimization


Federated Learning Under Attack: Exposing Vulnerabilities through Data Poisoning Attacks in Computer Networks


Federated Learning With Individualized Privacy Through Client Sampling


Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data


Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach


Federated Learning based on Pruning and Recovery


Federated Learning for COVID-19 Detection with Generative Adversarial Networks in Edge Cloud Computing


Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection


Federated Learning for Malware Detection in IoT Devices


Federated Learning for Misbehaviour Detection with Variational Autoencoders and Gaussian Mixture Models


Federated Learning for Privacy-Preserving Feedforward Control in Multi-Agent Systems


Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms


Federated Learning for Time-Series Healthcare Sensing with Incomplete Modalities


Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients


Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method


Federated Learning in ASR: Not as Easy as You Think


Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data Sources


Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data


Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks


Federated Learning of Dynamic Bayesian Network via Continuous Optimization from Time Series Data


Federated Learning of Generative Image Priors for MRI Reconstruction


Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization


Federated Learning of Large Models at the Edge via Principal Sub-Model Training


Federated Learning of Models Pre-Trained on Different Features with Consensus Graphs


Federated Learning of Socially Appropriate Agent Behaviours in Simulated Home Environments


Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features


Federated Learning on Non-IID Graphs via Structural Knowledge Sharing


Federated Learning on Patient Data for Privacy-Protecting Polycystic Ovary Syndrome Treatment


Federated Learning over 5G, WiFi, and Ethernet: Measurements and Evaluation


Federated Learning under Partially Class-Disjoint Data via Manifold Reshaping


Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis


Federated Learning via Consensus Mechanism on Heterogeneous Data: A New Perspective on Convergence


Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments


Federated Learning via Input-Output Collaborative Distillation


Federated Learning with Bilateral Curation for Partially Class-Disjoint Data


Federated Learning with Convex Global and Local Constraints


Federated Learning with Diffusion Models for Privacy-Sensitive Vision Tasks


Federated Learning with Extremely Noisy Clients via Negative Distillation


Federated Learning with Heterogeneous Data Handling for Robust Vehicular Object Detection


Federated Learning with Intermediate Representation Regularization


Federated Learning with Label-Masking Distillation


Federated Learning with Matched Averaging


Federated Learning with New Knowledge: Fundamentals, Advances, and Futures


Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving ML


Federated Learning with Reduced Information Leakage and Computation


Federated Learning with Reservoir State Analysis for Time Series Anomaly Detection


Federated Learning with Spiking Neural Networks


Federated Learning with Taskonomy for Non-IID Data


Federated Learning with Uncertainty-Based Client Clustering for Fleet-Wide Fault Diagnosis


Federated Learning with Unreliable Clients: Performance Analysis and Mechanism Design


Federated Learning-based Vehicle Trajectory Prediction against Cyberattacks


Federated Low-Rank Adaptation for Foundation Models: A Survey


Federated Modality-specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation


Federated Model Aggregation via Self-Supervised Priors for Highly Imbalanced Medical Image Classification


Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer Interfaces


Federated Multi-Task Learning on Non-IID Data Silos: An Experimental Study


Federated Multi-armed Bandits with Personalization


Federated Multi-organ Segmentation with Inconsistent Labels


Federated Multimodal Learning with Dual Adapters and Selective Pruning for Communication and Computational Efficiency


Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With Supplement


Federated Optimization Algorithms with Random Reshuffling and Gradient Compression


Federated Over-Air Subspace Tracking from Incomplete and Corrupted Data


Federated Prediction-Powered Inference from Decentralized Data


Federated Prompt Learning for Weather Foundation Models on Devices


Federated Recommendation via Hybrid Retrieval Augmented Generation


Federated Recommendation with Additive Personalization


Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning


Federated Reinforcement Learning with Environment Heterogeneity


Federated Representation Learning in the Under-Parameterized Regime


Federated Robustness Propagation: Sharing Robustness in Heterogeneous Federated Learning


Federated Semantic Learning for Privacy-preserving Cross-domain Recommendation


Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning


Federated Semi-Supervised Learning with Prototypical Networks


Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching


Federated Sketching LoRA: On-Device Collaborative Fine-Tuning of Large Language Models


Federated Spectral Graph Transformers Meet Neural Ordinary Differential Equations for Non-IID Graphs


Federated Stain Normalization for Computational Pathology


Federated Statistical Analysis: Non-parametric Testing and Quantile Estimation


Federated Submodel Optimization for Hot and Cold Data Features


Federated Transfer Learning for EEG Signal Classification


Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data


Federated Two Stage Decoupling With Adaptive Personalization Layers


Federated Unlearning Made Practical: Seamless Integration via Negated Pseudo-Gradients


Federated Unlearning with Gradient Descent and Conflict Mitigation


Federated Unsupervised Domain Generalization using Global and Local Alignment of Gradients


Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation


Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients


Federated clustering with GAN-based data synthesis


Federated learning compression designed for lightweight communications


Federated learning framework for collaborative remaining useful life prognostics: an aircraft engine case study


Federated mixed effects logistic regression based on one-time shared summary statistics


Federated nnU-Net for Privacy-Preserving Medical Image Segmentation


Federated singular value decomposition for high dimensional data


Federating Dynamic Models using Early-Exit Architectures for Automatic Speech Recognition on Heterogeneous Clients


Fedivertex: a Graph Dataset based on Decentralized Social Networks for Trustworthy Machine Learning


Feed-Forward Optimization With Delayed Feedback for Neural Networks


Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion


Feedback Control of Real-Time Display Advertising


Feedback Enhanced Motion Planning for Autonomous Vehicles


Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs


Feedback Loops With Language Models Drive In-Context Reward Hacking


Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity Estimation


Feedback from Pixels: Output Regulation via Learning-Based Scene View Synthesis


Feedback-Driven Automated Whole Bug Report Reproduction for Android Apps


Feedback-Free Starbursts at Cosmic Dawn: Observable Predictions for JWST


Feedback-augmented Non-homogeneous Hidden Markov Models for Longitudinal Causal Inference


Feedback-driven object detection and iterative model improvement


Feedback-feedforward Signal Control with Exogenous Demand Estimation in Congested Urban Road Networks


Feedback-guided Data Synthesis for Imbalanced Classification


Feedback-prop: Convolutional Neural Network Inference under Partial Evidence


FeedbackEval: A Benchmark for Evaluating Large Language Models in Feedback-Driven Code Repair Tasks


FeedbackMap: a tool for making sense of open-ended survey responses


Feedforward and feedback influences through distinct frequency bands between two spiking-neuron networks


Feel The Music: Automatically Generating A Dance For An Input Song


Fekete polynomials of principal Dirichlet characters


Felix: A Topology based Framework for Visual Exploration of Cosmic Filaments


Femto-Containers: Lightweight Virtualization and Fault Isolation For Small Software Functions on Low-Power IoT Microcontrollers


FemtoDet: An Object Detection Baseline for Energy Versus Performance Tradeoffs


Femtosecond pulse parameter estimation from photoelectron momenta using machine learning


Femtosecond two-pulse laser approach for spall failure in thin foils


Femtosecond-and-atom-resolved solvation dynamics of a Na$^+$ ion in a helium nanodroplet


Fence Synthesis under the C11 Memory Model


FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques


Fennec: Fine-grained Language Model Evaluation and Correction Extended through Branching and Bridging


Fenrir: Physics-Enhanced Regression for Initial Value Problems


Fermat's Last Theorem and modular curves over real quadratic fields


Fermat's Last Theorem for regular primes


Fermat's Last Theorem over $\mathbb{Q}(\sqrt{2},\sqrt{3})$


Fermi Resonance and the Quantum Mechanical Basis of Global Warming


FermiKit: assembly-based variant calling for Illumina resequencing data


Fermihedral: On the Optimal Compilation for Fermion-to-Qubit Encoding


Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity


Ferret: Faster and Effective Automated Red Teaming with Reward-Based Scoring Technique


Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models


Ferrofluid nucleus phase transitions in an external uniform magnetic field


Fessonia: a Method for Real-Time Estimation of Human Operator Workload Using Behavioural Entropy


FetDTIAlign: A Deep Learning Framework for Affine and Deformable Registration of Fetal Brain dMRI


Fetal ECG Extraction from Maternal ECG using Attention-based CycleGAN


Fetal MRI by robust deep generative prior reconstruction and diffeomorphic registration: application to gestational age prediction


Fetal-BET: Brain Extraction Tool for Fetal MRI


FetalNet: Multi-task Deep Learning Framework for Fetal Ultrasound Biometric Measurements


Fetuses Made Simple: Modeling and Tracking of Fetal Shape and Pose


Few 'Zero Level Set'-Shot Learning of Shape Signed Distance Functions in Feature Space


Few Clean Instances Help Denoising Distant Supervision


Few Labels are all you need: A Weakly Supervised Framework for Appliance Localization in Smart-Meter Series


Few Observation Binary Orbit Solver (FOBOS) from two (or more) astrometric observations


Few Shot Medical Image Segmentation with Cross Attention Transformer


Few Shot Network Compression via Cross Distillation


Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection


Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes


Few hamiltonian cycles in graphs with one or two vertex degrees


Few shot chain-of-thought driven reasoning to prompt LLMs for open ended medical question answering


Few shot clustering for indoor occupancy detection with extremely low-quality images from battery free cameras


Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement


Few-Cost Salient Object Detection with Adversarial-Paced Learning


Few-Max: Few-Shot Domain Adaptation for Unsupervised Contrastive Representation Learning


Few-Sample Named Entity Recognition for Security Vulnerability Reports by Fine-Tuning Pre-Trained Language Models


Few-Sample Traffic Prediction with Graph Networks using Locale as Relational Inductive Biases


Few-Shot Action Localization without Knowing Boundaries


Few-Shot Adaptation for Parsing Contextual Utterances with LLMs


Few-Shot Adaptation of Pre-Trained Networks for Domain Shift


Few-Shot Adversarial Prompt Learning on Vision-Language Models


Few-Shot Anaphora Resolution in Scientific Protocols via Mixtures of In-Context Experts


Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy


Few-Shot Anomaly Detection via Category-Agnostic Registration Learning


Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation


Few-Shot Backdoor Attacks on Visual Object Tracking


Few-Shot Bot: Prompt-Based Learning for Dialogue Systems


Few-Shot Calibration of Set Predictors via Meta-Learned Cross-Validation-Based Conformal Prediction


Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind


Few-Shot Class Incremental Learning via Robust Transformer Approach


Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt


Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks


Few-Shot Class-Incremental Learning from an Open-Set Perspective


Few-Shot Class-Incremental Learning via Entropy-Regularized Data-Free Replay


Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration


Few-Shot Classification of Interactive Activities of Daily Living (InteractADL)


Few-Shot Classification of Skin Lesions from Dermoscopic Images by Meta-Learning Representative Embeddings


Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learning


Few-Shot Continual Learning via Flat-to-Wide Approaches


Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training


Few-Shot Defect Image Generation via Defect-Aware Feature Manipulation


Few-Shot Document-Level Event Argument Extraction


Few-Shot Document-Level Relation Extraction


Few-Shot Domain Adaptation For End-to-End Communication


Few-Shot Domain Adaptation for Low Light RAW Image Enhancement


Few-Shot Domain Adaptation for Named-Entity Recognition via Joint Constrained k-Means and Subspace Selection


Few-Shot Electronic Health Record Coding through Graph Contrastive Learning


Few-Shot Emotion Recognition in Conversation with Sequential Prototypical Networks


Few-Shot Event Detection with Prototypical Amortized Conditional Random Field


Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning


Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation


Few-Shot Forecasting of Time-Series with Heterogeneous Channels


Few-Shot Fruit Segmentation via Transfer Learning


Few-Shot Generalization Across Dialogue Tasks


Few-Shot Generative Conversational Query Rewriting


Few-Shot Graph Learning for Molecular Property Prediction


Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling


Few-Shot Image Classification Benchmarks are Too Far From Reality: Build Back Better with Semantic Task Sampling


Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning


Few-Shot Keyword Spotting With Prototypical Networks


Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa


Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies


Few-Shot Learning by Dimensionality Reduction in Gradient Space


Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport


Few-Shot Learning for Image Classification of Common Flora


Few-Shot Learning for Opinion Summarization


Few-Shot Learning on Graphs via Super-Classes based on Graph Spectral Measures


Few-Shot Learning with Localization in Realistic Settings


Few-Shot Learning with Siamese Networks and Label Tuning


Few-Shot Learning with Visual Distribution Calibration and Cross-Modal Distribution Alignment


Few-Shot Medical Image Segmentation via a Region-enhanced Prototypical Transformer


Few-Shot Microscopy Image Cell Segmentation


Few-Shot Multilingual Open-Domain QA from 5 Examples


Few-Shot Object Detection via Association and DIscrimination


Few-Shot Object Detection via Variational Feature Aggregation


Few-Shot Object Detection with Fully Cross-Transformer


Few-Shot One-Class Classification via Meta-Learning


Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant Setup


Few-Shot Panoptic Segmentation With Foundation Models


Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning


Few-Shot Physically-Aware Articulated Mesh Generation via Hierarchical Deformation


Few-Shot Point Cloud Region Annotation with Human in the Loop


Few-Shot Recognition via Stage-Wise Retrieval-Augmented Finetuning


Few-Shot Representation Learning for Out-Of-Vocabulary Words


Few-Shot Rotation-Invariant Aerial Image Semantic Segmentation


Few-Shot Scene Adaptive Crowd Counting Using Meta-Learning


Few-Shot Segmentation Propagation with Guided Networks


Few-Shot Segmentation with Global and Local Contrastive Learning


Few-Shot Self-Rationalization with Natural Language Prompts


Few-Shot Semantic Parsing for New Predicates


Few-Shot Specific Emitter Identification via Deep Metric Ensemble Learning


Few-Shot Speech Deepfake Detection Adaptation with Gaussian Processes


Few-Shot Table-to-Text Generation with Prototype Memory


Few-Shot Text Classification with Pre-Trained Word Embeddings and a Human in the Loop


Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning


Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision


Few-Shot Transfer Learning for Device-Free Fingerprinting Indoor Localization


Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited triplets


Few-Shot Upsampling for Protest Size Detection


Few-Shot and Continual Learning with Attentive Independent Mechanisms


Few-particle scattering from localized quantum systems in spatially structured bosonic baths


Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning


Few-shot 3D Point Cloud Semantic Segmentation


Few-shot Adaptation Works with UnpredicTable Data


Few-shot Adaptation of Medical Vision-Language Models


Few-shot Backdoor Attacks via Neural Tangent Kernels


Few-shot Class-Incremental Semantic Segmentation via Pseudo-Labeling and Knowledge Distillation


Few-shot Class-incremental Audio Classification Using Adaptively-refined Prototypes


Few-shot Class-incremental Audio Classification Using Dynamically Expanded Classifier with Self-attention Modified Prototypes


Few-shot Class-incremental Audio Classification Using Stochastic Classifier


Few-shot Class-incremental Learning for 3D Point Cloud Objects


Few-shot Classification via Adaptive Attention


Few-shot Defect Image Generation based on Consistency Modeling


Few-shot Diagnosis of Chest x-rays Using an Ensemble of Random Discriminative Subspaces


Few-shot Domain Adaptation by Causal Mechanism Transfer


Few-shot Event Detection: An Empirical Study and a Unified View


Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross Modulation


Few-shot Fine-tuning is All You Need for Source-free Domain Adaptation


Few-shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-Learning


Few-shot Hybrid Domain Adaptation of Image Generators


Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier


Few-shot Image Generation via Adaptation-Aware Kernel Modulation


Few-shot In-context Learning for Knowledge Base Question Answering


Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt


Few-shot Keypoint Detection with Uncertainty Learning for Unseen Species


Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation


Few-shot Knowledge Graph-to-Text Generation with Pretrained Language Models


Few-shot Learner Parameterization by Diffusion Time-steps


Few-shot Learning as Cluster-induced Voronoi Diagrams: A Geometric Approach


Few-shot Learning for Multi-modal Social Media Event Filtering


Few-shot Learning with LSSVM Base Learner and Transductive Modules


Few-shot Learning with Multilingual Language Models


Few-shot Long-Tailed Bird Audio Recognition


Few-shot Multimodal Sentiment Analysis based on Multimodal Probabilistic Fusion Prompts


Few-shot Named Entity Recognition with Self-describing Networks


Few-shot Natural Language Generation for Task-Oriented Dialog


Few-shot News Recommendation via Cross-lingual Transfer


Few-shot Node Classification with Extremely Weak Supervision


Few-shot Novel View Synthesis using Depth Aware 3D Gaussian Splatting


Few-shot Object Counting with Similarity-Aware Feature Enhancement


Few-shot Object Detection in Remote Sensing: Lifting the Curse of Incompletely Annotated Novel Objects


Few-shot Online Anomaly Detection and Segmentation


Few-shot Personalization of LLMs with Mis-aligned Responses


Few-shot Relational Reasoning via Connection Subgraph Pretraining


Few-shot Scene-adaptive Anomaly Detection


Few-shot Semantic Image Synthesis Using StyleGAN Prior


Few-shot Semantic Segmentation with Self-supervision from Pseudo-classes


Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network


Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes


Few-shot Structure-Informed Machinery Part Segmentation with Foundation Models and Graph Neural Networks


Few-shot Text Classification with Distributional Signatures


Few-shot Transfer Learning for Knowledge Base Question Answering: Fusing Supervised Models with In-Context Learning


Few-shot Tuning of Foundation Models for Class-incremental Learning


Few-shot Unsupervised Domain Adaptation for Multi-modal Cardiac Image Segmentation


Few-shot Visual Relationship Co-localization


Few-shot calibration of low-cost air pollution (PM2.5) sensors using meta-learning


Few-shot classification in Named Entity Recognition Task


Few-shot human motion prediction for heterogeneous sensors


Few-shot learning for COVID-19 Chest X-Ray Classification with Imbalanced Data: An Inter vs. Intra Domain Study


Few-shot learning through contextual data augmentation


Few-shot semantic segmentation via mask aggregation


Few-shots Portrait Generation with Style Enhancement and Identity Preservation


FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark


FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding


FewRel 2.0: Towards More Challenging Few-Shot Relation Classification


FewSAR: A Few-shot SAR Image Classification Benchmark


FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks


FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual Framework


Fewer Errors, but More Stereotypes? The Effect of Model Size on Gender Bias


Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies


Fewer-token Neural Speech Codec with Time-invariant Codes


FeynMG: a FeynRules extension for scalar-tensor theories of gravity


Feynman checkers: towards algorithmic quantum theory


Feynman graph generation and calculations in the Hopf algebra of Feynman graphs


Feynman's solution of the quintessential problem in solid state physics


FgC2F-UDiff: Frequency-guided and Coarse-to-fine Unified Diffusion Model for Multi-modality Missing MRI Synthesis


Fi$^2$VTS: Time Series Forecasting Via Capturing Intra- and Inter-Variable Variations in the Frequency Domain


FiCo-ITR: bridging fine-grained and coarse-grained image-text retrieval for comparative performance analysis


FiFAR: A Fraud Detection Dataset for Learning to Defer


FiFTy: Large-scale File Fragment Type Identification using Neural Networks


FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations


FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation


FiLM: Fill-in Language Models for Any-Order Generation


FiNCAT: Financial Numeral Claim Analysis Tool


FiNER: Financial Numeric Entity Recognition for XBRL Tagging


FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems


FiRework: Field Refinement Framework for Efficient Enhancement of Deformable Registration


FiSSA at SemEval-2020 Task 9: Fine-tuned For Feelings


FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification


FiTs: Fine-grained Two-stage Training for Knowledge-aware Question Answering


FibeR-CNN: Expanding Mask R-CNN to Improve Image-Based Fiber Analysis


FibeRed: Fiberwise Dimensionality Reduction of Topologically Complex Data with Vector Bundles


Fiber crosslinking drives the emergence of order in a 3D dynamical network model


Fiber product homotopy method for multiparameter eigenvalue problems


FiberStars: Visual Comparison of Diffusion Tractography Data between Multiple Subjects


Fibonacci Neural Network Approach for Numerical Solutions of Fractional Order Differential Equations


Fibonacci and k-Subsecting Recursive Feature Elimination


Fibration symmetries and cluster synchronization in the Caenorhabditis elegans connectome


Fibro-CoSANet: Pulmonary Fibrosis Prognosis Prediction using a Convolutional Self Attention Network


Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers -- A multi-institutional evaluation


Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning


Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning


Fidelity Aware Multipath Routing for Multipartite State Distribution in Quantum Networks


Fidelity Isn't Accuracy: When Linearly Decodable Functions Fail to Match the Ground Truth


Fidelity and Overlap of Neural Quantum States: Error Bounds on the Monte Carlo Estimator


Fidelity decay and error accumulation in random quantum circuits


Fidelity witnesses for fermionic quantum simulations


Fidelity-Controllable Extreme Image Compression with Generative Adversarial Networks


Fidelity-Enriched Contrastive Search: Reconciling the Faithfulness-Diversity Trade-Off in Text Generation


Fidelity-Guarantee Entanglement Routing in Quantum Networks


Fidelity-preserving Learning-Based Image Compression: Loss Function and Subjective Evaluation Methodology


Fidelius: Protecting User Secrets from Compromised Browsers


Fiducial Tag Localization on a 3D LiDAR Prior Map


Field Assessment of Force Torque Sensors for Planetary Rover Navigation


Field Extraction from Forms with Unlabeled Data


Field Level Neural Network Emulator for Cosmological N-body Simulations


Field Notes on Deploying Research Robots in Public Spaces


Field Report on a Wearable and Versatile Solution for Field Acquisition and Exploration


Field Teams Coordination for Earthquake-Damaged Distribution System Energization


Field moment expansion method for interacting Bosonic systems


Field of Junctions: Extracting Boundary Structure at Low SNR


Field-induced freezing in the unfrustrated Ising antiferromagnet


Field-level Lyman-alpha forest modelling in redshift space via augmented non-local Fluctuating Gunn-Peterson Approximation


Field-wise Learning for Multi-field Categorical Data


Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation


Fields of definition of elliptic $k$-curves and the realizability of all genus 2 Sato--Tate groups over a number field


FieldsX -- An extension package for the xAct tensor computer algebra suite to include fermions, gauge fields and BRST cohomology


Fieldscale: Locality-Aware Field-based Adaptive Rescaling for Thermal Infrared Image


Fietje: An open, efficient LLM for Dutch


Fifth-Force Screening around Extremely Compact Sources


Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks


FigCaps-HF: A Figure-to-Caption Generative Framework and Benchmark with Human Feedback


Fight Detection from Still Images in the Wild


Fight Fire with Fire: Combating Adversarial Patch Attacks using Pattern-randomized Defensive Patches


Fight Hardware with Hardware: System-wide Detection and Mitigation of Side-Channel Attacks using Performance Counters


Fight Perturbations with Perturbations: Defending Adversarial Attacks via Neuron Influence


Fighter Jet Navigation and Combat using Deep Reinforcement Learning with Explainable AI


Fighting Bias with Bias: Promoting Model Robustness by Amplifying Dataset Biases


Fighting Fire with Fire: The Dual Role of LLMs in Crafting and Detecting Elusive Disinformation


Fighting Fires from Space: Leveraging Vision Transformers for Enhanced Wildfire Detection and Characterization


Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks


Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation


Fighting Spurious Correlations in Text Classification via a Causal Learning Perspective


Fighting an Infodemic: COVID-19 Fake News Dataset


Fighting crime with Transformers: Empirical analysis of address parsing methods in payment data


Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms


Fighting the COVID-19 Infodemic with a Holistic BERT Ensemble


Figurative Language in Recognizing Textual Entailment


Figurative-cum-Commonsense Knowledge Infusion for Multimodal Mental Health Meme Classification


Figuratively Speaking: Authorship Attribution via Multi-Task Figurative Language Modeling


Figure and Figure Caption Extraction for Mixed Raster and Vector PDFs: Digitization of Astronomical Literature with OCR Features


FigureQA: An Annotated Figure Dataset for Visual Reasoning


FilFL: Client Filtering for Optimized Client Participation in Federated Learning


Filamentary Dust Polarization and the Morphology of Neutral Hydrogen Structures


Filaments of The Slime Mold Cosmic Web And How They Affect Galaxy Evolution


Filaments of crime: Informing policing via thresholded ridge estimation


Filipino Benchmarks for Measuring Sexist and Homophobic Bias in Multilingual Language Models from Southeast Asia


Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems


Fill the K-Space and Refine the Image: Prompting for Dynamic and Multi-Contrast MRI Reconstruction


Filler Word Detection and Classification: A Dataset and Benchmark


Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach


Filling the Gaps: A Multiple Imputation Approach to Estimating Aging Curves in Baseball


Filling the Image Information Gap for VQA: Prompting Large Language Models to Proactively Ask Questions


Filling the Missings: Spatiotemporal Data Imputation by Conditional Diffusion


Filling the gaps: Gaussian mixture models from noisy, truncated or incomplete samples


Filling time-series gaps using image techniques: Multidimensional context autoencoder approach for building energy data imputation


Filter Grafting for Deep Neural Networks


Filter Like You Test: Data-Driven Data Filtering for CLIP Pretraining


Filter Pruning For CNN With Enhanced Linear Representation Redundancy


Filter Pruning for Efficient CNNs via Knowledge-driven Differential Filter Sampler


Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly Detection


Filter-Pruning of Lightweight Face Detectors Using a Geometric Median Criterion


Filter-adapted spatiotemporal sampling for real-time rendering


Filter-informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis


Filter-then-Generate: Large Language Models with Structure-Text Adapter for Knowledge Graph Completion


Filter2Noise: Interpretable Self-Supervised Single-Image Denoising for Low-Dose CT with Attention-Guided Bilateral Filtering


FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series Forecasting


Filterbank design for end-to-end speech separation


Filtered Corpus Training (FiCT) Shows that Language Models can Generalize from Indirect Evidence


Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction Networks


Filtered-Guided Diffusion: Fast Filter Guidance for Black-Box Diffusion Models


Filtering Dynamical Systems Using Observations of Statistics


Filtering Empty Camera Trap Images in Embedded Systems


Filtering Internal Tides From Wide-Swath Altimeter Data Using Convolutional Neural Networks


Filtering Noisy Dialogue Corpora by Connectivity and Content Relatedness


Filtering and improved Uncertainty Quantification in the dynamic estimation of effective reproduction numbers


Filtering before Iteratively Referring for Knowledge-Grounded Response Selection in Retrieval-Based Chatbots


Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training


Filtration Surfaces for Dynamic Graph Classification


Filtration-Domination in Bifiltered Graphs


Filtrations Indexed by Attracting Levels and their Applications


Fin-Fact: A Benchmark Dataset for Multimodal Financial Fact Checking and Explanation Generation


Fin-R1: A Large Language Model for Financial Reasoning through Reinforcement Learning


FinAI-BERT: A Transformer-Based Model for Sentence-Level Detection of AI Disclosures in Financial Reports


FinBERT-MRC: financial named entity recognition using BERT under the machine reading comprehension paradigm


FinBERT-QA: Financial Question Answering with pre-trained BERT Language Models


FinChat: Corpus and evaluation setup for Finnish chat conversations on everyday topics


FinDABench: Benchmarking Financial Data Analysis Ability of Large Language Models


FinDKG: Dynamic Knowledge Graphs with Large Language Models for Detecting Global Trends in Financial Markets


FinDVer: Explainable Claim Verification over Long and Hybrid-Content Financial Documents


FinDiff: Diffusion Models for Financial Tabular Data Generation


FinEAS: Financial Embedding Analysis of Sentiment


FinEntity: Entity-level Sentiment Classification for Financial Texts


FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models


FinGAT: Financial Graph Attention Networks for Recommending Top-K Profitable Stocks


FinGPT: Open-Source Financial Large Language Models


FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation


FinMamba: Market-Aware Graph Enhanced Multi-Level Mamba for Stock Movement Prediction


FinMaster: A Holistic Benchmark for Mastering Full-Pipeline Financial Workflows with LLMs


FinMultiTime: A Four-Modal Bilingual Dataset for Financial Time-Series Analysis


FinNet: Solving Time-Independent Differential Equations with Finite Difference Neural Network


FinPT: Financial Risk Prediction with Profile Tuning on Pretrained Foundation Models


FinQA: A Dataset of Numerical Reasoning over Financial Data


FinRED: A Dataset for Relation Extraction in Financial Domain


FinReport: Explainable Stock Earnings Forecasting via News Factor Analyzing Model


FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting


FinTagging: An LLM-ready Benchmark for Extracting and Structuring Financial Information


FinTruthQA: A Benchmark Dataset for Evaluating the Quality of Financial Information Disclosure


FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysis


Final Moments II: Observational Properties and Physical Modeling of CSM-Interacting Type II Supernovae


FinanceMath: Knowledge-Intensive Math Reasoning in Finance Domains


FinanceReasoning: Benchmarking Financial Numerical Reasoning More Credible, Comprehensive and Challenging


Financial Data Analysis Using Expert Bayesian Framework For Bankruptcy Prediction


Financial Data Analysis with Robust Federated Logistic Regression


Financial Fine-tuning a Large Time Series Model


Financial Fraud Detection using Jump-Attentive Graph Neural Networks


Financial Fraud Detection with Entropy Computing


Financial Sentiment Analysis: Leveraging Actual and Synthetic Data for Supervised Fine-tuning


Find First, Track Next: Decoupling Identification and Propagation in Referring Video Object Segmentation


Find Rhinos without Finding Rhinos: Active Learning with Multimodal Imagery of South African Rhino Habitats


Find What You Want: Learning Demand-conditioned Object Attribute Space for Demand-driven Navigation


Find it if You Can: End-to-End Adversarial Erasing for Weakly-Supervised Semantic Segmentation


Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban Environments


Find the Cliffhanger: Multi-Modal Trailerness in Soap Operas


Find the Funding: Entity Linking with Incomplete Funding Knowledge Bases


Find the Intention of Instruction: Comprehensive Evaluation of Instruction Understanding for Large Language Models


Find the Lady: Permutation and Re-Synchronization of Deep Neural Networks


FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation


FindTheFlaws: Annotated Errors for Detecting Flawed Reasoning and Scalable Oversight Research


FindView: Precise Target View Localization Task for Look Around Agents


Finding $K$ Contingency List in Power Networks using a New Model of Dependency


Finding A Taxi with Illegal Driver Substitution Activity via Behavior Modelings


Finding A Voice: Evaluating African American Dialect Generation for Chatbot Technology


Finding Archetypal Spaces Using Neural Networks


Finding Better Subword Segmentation for Neural Machine Translation


Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks


Finding Bipartite Components in Hypergraphs


Finding Blind Spots in Evaluator LLMs with Interpretable Checklists


Finding Common Ground: Annotating and Predicting Common Ground in Spoken Conversations


Finding Competence Regions in Domain Generalization


Finding Concept Representations in Neural Networks with Self-Organizing Maps


Finding Convincing Views to Endorse a Claim


Finding Counterfactual Evidences for Node Classification


Finding Counterfactually Optimal Action Sequences in Continuous State Spaces


Finding Crash-Consistency Bugs with Bounded Black-Box Crash Testing


Finding Dataset Shortcuts with Grammar Induction


Finding Densest Subgraphs with Edge-Color Constraints


Finding Deviated Behaviors of the Compressed DNN Models for Image Classifications


Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling


Finding Equilibria in the Traffic Assignment Problem with Primal-Dual Gradient Methods for Stable Dynamics Model and Beckmann Model


Finding Favourite Tuples on Data Streams with Provably Few Comparisons


Finding Friend and Foe in Multi-Agent Games


Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset Augmentation Using Graph Theory


Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation


Finding Fuzziness in Neural Network Models of Language Processing


Finding Galois splitting models to compute local invariants


Finding Generalizable Evidence by Learning to Convince Q&A Models


Finding Geometric Models by Clustering in the Consensus Space


Finding Global Homophily in Graph Neural Networks When Meeting Heterophily


Finding Groups of Cross-Correlated Features in Bi-View Data


Finding Hamiltonian Cycle in Graphs of Bounded Treewidth: Experimental Evaluation


Finding Hamiltonian cycles with graph neural networks


Finding Hidden Swing Voters in the 2022 Italian Elections Twitter Discourse


Finding High-Value Training Data Subset through Differentiable Convex Programming


Finding Influential Cores via Normalized Ricci Flows in Directed and Undirected Hypergraphs with Applications


Finding Influentials in Twitter: A Temporal Influence Ranking Model


Finding Input Characterizations for Output Properties in ReLU Neural Networks


Finding Large Independent Sets in Networks Using Competitive Dynamics