Image Completion via Dual-path Cooperative Filtering


Image Completion with Heterogeneously Filtered Spectral Hints


Image Composition Assessment with Saliency-augmented Multi-pattern Pooling


Image Compressed Sensing Using Non-local Neural Network


Image Compressed Sensing with Multi-scale Dilated Convolutional Neural Network


Image Compression With Learned Lifting-Based DWT and Learned Tree-Based Entropy Models


Image Compression and Decompression Framework Based on Latent Diffusion Model for Breast Mammography


Image Compression for Machine and Human Vision with Spatial-Frequency Adaptation


Image Compression with Encoder-Decoder Matched Semantic Segmentation


Image Content Generation with Causal Reasoning


Image Contrast Enhancement using Fuzzy Technique with Parameter Determination using Metaheuristics


Image Copy-Move Forgery Detection and Localization Scheme: How to Avoid Missed Detection and False Alarm


Image Crowd Counting Using Convolutional Neural Network and Markov Random Field


Image Deblurring by Exploring In-depth Properties of Transformer


Image Deformation Meta-Networks for One-Shot Learning


Image Demoireing in RAW and sRGB Domains


Image Demoiréing Using Dual Camera Fusion on Mobile Phones


Image Denoising and the Generative Accumulation of Photons


Image Denoising with Control over Deep Network Hallucination


Image Deraining with Frequency-Enhanced State Space Model


Image Difference Captioning with Pre-training and Contrastive Learning


Image Distillation for Safe Data Sharing in Histopathology


Image Embedding for Denoising Generative Models


Image Enhancement for Remote Photoplethysmography in a Low-Light Environment


Image Features Influence Reaction Time: A Learned Probabilistic Perceptual Model for Saccade Latency


Image Forgery Localization with State Space Models


Image Formation Model Guided Deep Image Super-Resolution


Image Generation Diversity Issues and How to Tame Them


Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space


Image Generation With Neural Cellular Automatas


Image Generation for Efficient Neural Network Training in Autonomous Drone Racing


Image Hash Minimization for Tamper Detection


Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance


Image Hijacks: Adversarial Images can Control Generative Models at Runtime


Image Inpainting Using AutoEncoder and Guided Selection of Predicted Pixels


Image Inpainting Using Wasserstein Generative Adversarial Imputation Network


Image Inpainting by End-to-End Cascaded Refinement with Mask Awareness


Image Inpainting via Tractable Steering of Diffusion Models


Image Inpainting with External-internal Learning and Monochromic Bottleneck


Image Inpainting with Learnable Bidirectional Attention Maps


Image Inversion: A Survey from GANs to Diffusion and Beyond


Image Labels Are All You Need for Coarse Seagrass Segmentation


Image Masking for Robust Self-Supervised Monocular Depth Estimation


Image Matching Filtering and Refinement by Planes and Beyond


Image Matching across Wide Baselines: From Paper to Practice


Image Matters: A New Dataset and Empirical Study for Multimodal Hyperbole Detection


Image Morphing with Perceptual Constraints and STN Alignment


Image Outlier Detection Without Training using RANSAC


Image Privacy Prediction Using Deep Neural Networks


Image Processing Using Multi-Code GAN Prior


Image Processing and Analysis of Multiple Wavelength Astronomical Data Using Python Tools


Image Processing and Machine Learning for Hyperspectral Unmixing: An Overview and the HySUPP Python Package


Image Processing and Quality Control for Abdominal Magnetic Resonance Imaging in the UK Biobank


Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classification


Image Quality Assessment for Full-Disk Solar Observations with Generative Adversarial Networks


Image Quality Assessment using Contrastive Learning


Image Quality Assessment: From Human to Machine Preference


Image Quality-aware Diagnosis via Meta-knowledge Co-embedding


Image Re-Identification: Where Self-supervision Meets Vision-Language Learning


Image Reconstruction via Deep Image Prior Subspaces


Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases


Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge


Image Restoration Using Deep Regulated Convolutional Networks


Image Restoration by Iterative Denoising and Backward Projections


Image Restoration using Plug-and-Play CNN MAP Denoisers


Image Restoration via Multi-domain Learning


Image Retrieval from Contextual Descriptions


Image Safeguarding: Reasoning with Conditional Vision Language Model and Obfuscating Unsafe Content Counterfactually


Image Segmentation by Iterative Inference from Conditional Score Estimation


Image Segmentation in Foundation Model Era: A Survey


Image Segmentation with Topological Priors


Image Segmentation: Inducing graph-based learning


Image Similarity using An Ensemble of Context-Sensitive Models


Image Smoothing via Unsupervised Learning


Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical Naturalness


Image Super-Resolution as a Defense Against Adversarial Attacks


Image Super-Resolution via Attention based Back Projection Networks


Image Super-Resolution via Deterministic-Stochastic Synthesis and Local Statistical Rectification


Image Super-Resolution with Deep Dictionary


Image Super-Resolution with Text Prompt Diffusion


Image Super-resolution Inspired Electron Density Prediction


Image Super-resolution Via Latent Diffusion: A Sampling-space Mixture Of Experts And Frequency-augmented Decoder Approach


Image Super-resolution via Feature-augmented Random Forest


Image Super-resolution with An Enhanced Group Convolutional Neural Network


Image Synthesis under Limited Data: A Survey and Taxonomy


Image Synthesis with Adversarial Networks: a Comprehensive Survey and Case Studies


Image Textualization: An Automatic Framework for Creating Accurate and Detailed Image Descriptions


Image Translation for Medical Image Generation -- Ischemic Stroke Lesions


Image Translation via Fine-grained Knowledge Transfer


Image Understanding Makes for A Good Tokenizer for Image Generation


Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning


Image Vectorization with Depth: convexified shape layers with depth ordering


Image Velocimetry using Direct Displacement Field estimation with Neural Networks for Fluids


Image Watermarks are Removable Using Controllable Regeneration from Clean Noise


Image and AIS Data Fusion Technique for Maritime Computer Vision Applications


Image and Encoded Text Fusion for Multi-Modal Classification


Image and Video Tokenization with Binary Spherical Quantization


Image classification and retrieval with random depthwise signed convolutional neural networks


Image classification in frequency domain with 2SReLU: a second harmonics superposition activation function


Image deconvolution and PSF reconstruction with STARRED: a wavelet-based two-channel method optimized for light-curve extraction


Image feature extraction and galaxy classification: a novel and efficient approach with automated machine learning


Image features of a splashing drop on a solid surface extracted using a feedforward neural network


Image generation with shortest path diffusion


Image interpretation by iterative bottom-up top-down processing


Image memorability enhances social media virality


Image or Information? Examining the Nature and Impact of Visualization Perceptual Classification


Image prediction of disease progression by style-based manifold extrapolation


Image quality measurements and denoising using Fourier Ring Correlations


Image recognition from raw labels collected without annotators


Image reconstructions using sparse dictionary representations and implicit, non-negative mappings


Image registration of 2D optical thin sections in a 3D porous medium: Application to a Berea sandstone digital rock image


Image scaling by de la Vallée-Poussin filtered interpolation


Image sensing with multilayer, nonlinear optical neural networks


Image steganography based on generative implicit neural representation


Image super-resolution via dynamic network


Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction


Image translation of Ultrasound to Pseudo Anatomical Display by CycleGAN


Image, Text, and Speech Data Augmentation using Multimodal LLMs for Deep Learning: A Survey


Image-Based CLIP-Guided Essence Transfer


Image-Based Correction of Continuous and Discontinuous Non-Planar Axial Distortion in Serial Section Microscopy


Image-Based Detection of Modifications in Gas Pump PCBs with Deep Convolutional Autoencoders


Image-Based Parking Space Occupancy Classification: Dataset and Baseline


Image-Based Place Recognition on Bucolic Environment Across Seasons From Semantic Edge Description


Image-Based Size Analysis of Agglomerated and Partially Sintered Particles via Convolutional Neural Networks


Image-Based Trajectory Tracking through Unknown Environments without Absolute Positioning


Image-Caption Encoding for Improving Zero-Shot Generalization


Image-Editing Specialists: An RLAIF Approach for Diffusion Models


Image-Goal Navigation Using Refined Feature Guidance and Scene Graph Enhancement


Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection


Image-Text Co-Decomposition for Text-Supervised Semantic Segmentation


Image-and-Spatial Transformer Networks for Structure-Guided Image Registration


Image-based Automatic Dial Meter Reading in Unconstrained Scenarios


Image-based Detection of Surface Defects in Concrete during Construction


Image-based Geolocalization by Ground-to-2.5D Map Matching


Image-based Guidance of Autonomous Aircraft for Wildfire Surveillance and Prediction


Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models, Benchmark and Efficient Evaluation


Image-based Proof of Work Algorithm for the Incentivization of Blockchain Archival of Interesting Images


Image-based eeg classification of brain responses to song recordings


Image-embodied Knowledge Representation Learning


Image-free Classifier Injection for Zero-Shot Classification


Image-guided topic modeling for interpretable privacy classification


Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks


Image-level Regression for Uncertainty-aware Retinal Image Segmentation


Image-specific Convolutional Kernel Modulation for Single Image Super-resolution


Image-text Retrieval via Preserving Main Semantics of Vision


Image-text matching for large-scale book collections


Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging


Image-to-Image Retrieval by Learning Similarity between Scene Graphs


Image-to-Image Translation with Low Resolution Conditioning


Image-to-Image Translation-based Data Augmentation for Robust EV Charging Inlet Detection


Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data


Image-to-image Translation via Hierarchical Style Disentanglement


Image-to-image translation for cross-domain disentanglement


Image2Gif: Generating Continuous Realistic Animations with Warping NODEs


Image2PCI -- A Multitask Learning Framework for Estimating Pavement Condition Indices Directly from Images


Image2Points:A 3D Point-based Context Clusters GAN for High-Quality PET Image Reconstruction


Image2Reverb: Cross-Modal Reverb Impulse Response Synthesis


ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness Mining


ImageBox3: No-Server Tile Serving to Traverse Whole Slide Images on the Web


ImageCHD: A 3D Computed Tomography Image Dataset for Classification of Congenital Heart Disease


ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification with Chest X-rays


ImageInWords: Unlocking Hyper-Detailed Image Descriptions


ImageMech: From image to particle spring network for mechanical characterization


ImageNet Pre-training also Transfers Non-Robustness


ImageNet pre-trained models with batch normalization


ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing


ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms


ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches


ImageNet3D: Towards General-Purpose Object-Level 3D Understanding


ImageNetVC: Zero- and Few-Shot Visual Commonsense Evaluation on 1000 ImageNet Categories


ImageNomer: description of a functional connectivity and omics analysis tool and case study identifying a race confound


ImageNot: A contrast with ImageNet preserves model rankings


ImageRAG: Enhancing Ultra High Resolution Remote Sensing Imagery Analysis with ImageRAG


ImageRef-VL: Enabling Contextual Image Referencing in Vision-Language Models


ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation


ImageScope: Unifying Language-Guided Image Retrieval via Large Multimodal Model Collective Reasoning


ImagenHub: Standardizing the evaluation of conditional image generation models


Images Speak Volumes: User-Centric Assessment of Image Generation for Accessible Communication


Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules


Images in Discrete Choice Modeling: Addressing Data Isomorphism in Multi-Modality Inputs


Images in Language Space: Exploring the Suitability of Large Language Models for Vision & Language Tasks


ImagiNet: A Multi-Content Benchmark for Synthetic Image Detection


Imaginary Voice: Face-styled Diffusion Model for Text-to-Speech


Imaginary time propagation code for large-scale two-dimensional eigenvalue problems in magnetic fields


ImaginaryNet: Learning Object Detectors without Real Images and Annotations


Imagination is All You Need! Curved Contrastive Learning for Abstract Sequence Modeling Utilized on Long Short-Term Dialogue Planning


Imagination-Augmented Natural Language Understanding


Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning Representation


Imagine All The Relevance: Scenario-Profiled Indexing with Knowledge Expansion for Dense Retrieval


Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification


Imagine2Servo: Intelligent Visual Servoing with Diffusion-Driven Goal Generation for Robotic Tasks


Imagine2touch: Predictive Tactile Sensing for Robotic Manipulation using Efficient Low-Dimensional Signals


ImagineBench: Evaluating Reinforcement Learning with Large Language Model Rollouts


ImagineNET: Target Speaker Extraction with Intermittent Visual Cue through Embedding Inpainting


Imaging 3D Chemistry at 1 nm Resolution with Fused Multi-Modal Electron Tomography


Imaging Extended Emission-Line Regions of Obscured AGN with the Subaru Hyper Suprime-Cam Survey


Imaging based feedback cooling of a levitated nanoparticle


Imaging foundation model for universal enhancement of non-ideal measurement CT


Imaging moiré deformation and dynamics in twisted bilayer graphene


Imaging rotating and orbiting exoplanets with the solar gravitational lens


Imaging systematics induced by galaxy sub-sample fluctuation: new systematics at second order


Imaging the Photochemistry of the Hydrogen-Bonded Heptazine-Water Complex with Femtosecond Time-Resolved Spectroscopy: A Computational Study


Imagining In-distribution States: How Predictable Robot Behavior Can Enable User Control Over Learned Policies


ImarisWriter: Open Source Software for Storage of Large Images in Blockwise Multi-Resolution Format


Imbalance Problems in Object Detection: A Review


Imbalance-XGBoost: Leveraging Weighted and Focal Losses for Binary Label-Imbalanced Classification with XGBoost


Imbalanced Big Data Oversampling: Taxonomy, Algorithms, Software, Guidelines and Future Directions


Imbalanced Continual Learning with Partitioning Reservoir Sampling


Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness


Imbalanced Graph Classification via Graph-of-Graph Neural Networks


Imbalanced Graph Classification with Multi-scale Oversampling Graph Neural Networks


Imbalanced Graph-Level Anomaly Detection via Counterfactual Augmentation and Feature Learning


Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels


Imbalanced Open Set Domain Adaptation via Moving-threshold Estimation and Gradual Alignment


Imbalanced Semi-supervised Learning with Bias Adaptive Classifier


Imbalanced malware classification: an approach based on dynamic classifier selection


Imbalanced multi-label classification using multi-task learning with extractive summarization


Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning


Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation


ImgTrojan: Jailbreaking Vision-Language Models with ONE Image


ImitAL: Learned Active Learning Strategy on Synthetic Data


ImitAL: Learning Active Learning Strategies from Synthetic Data


Imitating Arbitrary Talking Style for Realistic Audio-DrivenTalking Face Synthesis


Imitating Cost-Constrained Behaviors in Reinforcement Learning


Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations


Imitating Graph-Based Planning with Goal-Conditioned Policies


Imitating Human Behaviour with Diffusion Models


Imitating Latent Policies from Observation


Imitating from auxiliary imperfect demonstrations via Adversarial Density Weighted Regression


Imitation Attacks and Defenses for Black-box Machine Translation Systems


Imitation Learning by Estimating Expertise of Demonstrators


Imitation Learning by Reinforcement Learning


Imitation Learning by State-Only Distribution Matching


Imitation Learning for Autonomous Driving: Insights from Real-World Testing


Imitation Learning for Generalizable Self-driving Policy with Sim-to-real Transfer


Imitation Learning for Intra-Day Power Grid Operation through Topology Actions


Imitation Learning for Neural Morphological String Transduction


Imitation Learning from Observations under Transition Model Disparity


Imitation Learning from Purified Demonstrations


Imitation Learning from Suboptimal Demonstrations via Meta-Learning An Action Ranker


Imitation Learning from a Single Temporally Misaligned Video


Imitation Learning of Neural Spatio-Temporal Point Processes


Imitation Learning of Stabilizing Policies for Nonlinear Systems


Imitation Learning via Differentiable Physics


Imitation Learning with Human Eye Gaze via Multi-Objective Prediction


Imitation Learning with Limited Actions via Diffusion Planners and Deep Koopman Controllers


Imitation Learning with Sinkhorn Distances


Imitation Learning with Stability and Safety Guarantees


Imitation Learning-based Direct Visual Servoing using the Large Projection Formulation


Imitation Learning-based Implicit Semantic-aware Communication Networks: Multi-layer Representation and Collaborative Reasoning


Imitation learning with artificial neural networks for demand response with a heuristic control approach for heat pumps


Imitation of Life: A Search Engine for Biologically Inspired Design


Imitation of human motion achieves natural head movements for humanoid robots in an active-speaker detection task


ImmersePro: End-to-End Stereo Video Synthesis Via Implicit Disparity Learning


Immersive ExaBrick: Visualizing Large AMR Data in the CAVE


Immersive Video Compression using Implicit Neural Representations


Immersive Visualization of Flat Surfaces Using Ray Marching


Immersive and Wearable Thermal Rendering for Augmented Reality


Immiscible Color Flows in Optimal Transport Networks for Image Classification


Immortality through the dark forces: Dark-charge primordial black holes as dark matter candidates


ImmuNetNAS: An Immune-network approach for searching Convolutional Neural Network Architectures


Immunization Strategies in Networks with Missing Data


Immunofluorescence Capillary Imaging Segmentation: Cases Study


Immunogenicity Prediction with Dual Attention Enables Vaccine Target Selection


Immunohistochemistry guided segmentation of benign epithelial cells, in situ lesions, and invasive epithelial cells in breast cancer slides


Immutability and Design Patterns in Ruby


Imp: Highly Capable Large Multimodal Models for Mobile Devices


ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Language


Impact Analysis of Antenna Array Geometry on Performance of Semi-blind Structured Channel Estimation for massive MIMO-OFDM systems


Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications


Impact Craters and the Observability of Ancient Martian Shorelines


Impact Invariant Control with Applications to Bipedal Locomotion


Impact Makes a Sound and Sound Makes an Impact: Sound Guides Representations and Explorations


Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph Node Classifiers


Impact forces of water drops falling on superhydrophobic surfaces


Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation


Impact of Architectural Modifications on Deep Learning Adversarial Robustness


Impact of Artificial Intelligence on Environmental Quality through Technical Change: A Free Dynamic Equilibrium Approach


Impact of COVID19-induced Lockdown on Air Quality in Ireland


Impact of Channel Variation on One-Class Learning for Spoof Detection


Impact of Climate Simulation Resolutions on Future Energy System Reliability Assessment: A Texas Case Study


Impact of Code Language Models on Automated Program Repair


Impact of Comprehensive Data Preprocessing on Predictive Modelling of COVID-19 Mortality


Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control


Impact of Data Bias on Machine Learning for Crystal Compound Synthesizability Predictions


Impact of Data Distribution on Fairness Guarantees in Equitable Deep Learning


Impact of Data Synthesis Strategies for the Classification of Craniosynostosis


Impact of Domain-Adapted Multilingual Neural Machine Translation in the Medical Domain


Impact of Evaluation Methodologies on Code Summarization


Impact of Galactic dust non-Gaussianity on searches for B-modes from inflation


Impact of Galactic non-Gaussian foregrounds on CMB lensing measurements


Impact of Initialization on Intra-subject Pediatric Brain MR Image Registration: A Comparative Analysis between SyN ANTs and Deep Learning-Based Approaches


Impact of Jittering on Raster- and Distance-based Geostatistical Analyses of DHS Data


Impact of Load Demand Dataset Characteristics on Clustering Validation Indices


Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations I: Black Hole-Neutron Star Mergers


Impact of Massive Binary Star and Cosmic Evolution on Gravitational Wave Observations II: Double Compact Object Rates and Properties


Impact of Nanoscopic Impurity Aggregates on Cavitation in Water


Impact of Network Centrality and Income on Slowing Infection Spread after Outbreaks


Impact of Network Topology on Byzantine Resilience in Decentralized Federated Learning


Impact of Non-Standard Unicode Characters on Security and Comprehension in Large Language Models


Impact of Relativistic Effects on the Primordial Non-Gaussianity Signature in the Large-Scale Clustering of Quasars


Impact of SMILES Notational Inconsistencies on Chemical Language Model Performance


Impact of Spatial Filtering on Distortion from Low-Noise Amplifiers in Massive MIMO Base Stations


Impact of Surface Reflections in Maritime Obstacle Detection


Impact of UAV Wobbling on the Air-to-Ground Wireless Channel


Impact of User Privacy and Mobility on Edge Offloading


Impact of Variable Speed on Collective Movement of Animal Groups


Impact of Visual Context on Noisy Multimodal NMT: An Empirical Study for English to Indian Languages


Impact of Wave Packet Separation in Low-Energy Sterile Neutrino Searches


Impact of a Midband Gravitational Wave Experiment On Detectability of Cosmological Stochastic Gravitational Wave Backgrounds


Impact of a block structure on the Lotka-Volterra model


Impact of a rigid sphere onto an elastic membrane


Impact of astrophysical effects on the dark matter mass constraint with 21cm intensity mapping


Impact of climate change on site characteristics of eight major astronomical observatories using high-resolution global climate projections until 2050


Impact of color and mixing proportion of synthetic point clouds on semantic segmentation


Impact of extragalactic point sources on the low-frequency sky spectrum and cosmic dawn global 21-cm measurements


Impact of global structure on diffusive exploration of organelle networks


Impact of half-wave plate systematics on the measurement of CMB $B$-mode polarization


Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography


Impact of lung segmentation on the diagnosis and explanation of COVID-19 in chest X-ray images


Impact of magneto-rotational instability on grain growth in protoplanetary disks: II. Increased grain collisional velocities


Impact of model misspecification in shared frailty survival models


Impact of non-normal error distributions on the benchmarking and ranking of Quantum Machine Learning models


Impact of non-parabolic electronic band structure on the optical and transport properties of photovoltaic materials


Impact of non-stationarity on hybrid ensemble filters: A study with a doubly stochastic advection-diffusion-decay model


Impact of predictor measurement heterogeneity across settings on performance of prediction models: a measurement error perspective


Impact of random and targeted disruptions on information diffusion during outbreaks


Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics


Impact of the 2022 OSTP Memo: A Bibliometric Analysis of U.S. Federally Funded Publications, 2017-2021


Impact of the Euro 2020 championship on the spread of COVID-19


Impact of the Galactic bar on tidal streams within the Galactic disc: The case of the tidal stream of the Hyades


Impact of the Number of Votes on the Reliability and Validity of Subjective Speech Quality Assessment in the Crowdsourcing Approach


Impact of the Query Set on the Evaluation of Expert Finding Systems


Impact of the characteristics of quantum chemical databases on machine learning predictions of tautomerization energies


Impact of tides on non-coplanar orbits of progenitors of high-mass X-ray binaries


Impact of time and note duration tokenizations on deep learning symbolic music modeling


Impact of unreliable devices on stability of quantum computations


Impact of using the ultra-high-energy cosmic ray arrival energies to constrain source associations


Impact, Attention, Influence: Early Assessment of Autonomous Driving Datasets


Impact-Oriented Contextual Scholar Profiling using Self-Citation Graphs


ImpactCite: An XLNet-based method for Citation Impact Analysis


Impacts of Census Differential Privacy for Small-Area Disease Mapping to Monitor Health Inequities


Impacts of Climate Change on Mortality: An extrapolation of temperature effects based on time series data in France


Impacts of electric carsharing on a power sector with variable renewables


Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications


Impacts of magnetic permeability on electromagnetic data collected in settings with steel-cased wells


Impairments are Clustered in Latents of Deep Neural Network-based Speech Quality Models


Impartial Games: A Challenge for Reinforcement Learning


Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay


Impedance and voltage power spectra of a monopole antenna in a warm plasma -- derivation and application to CubeSats


Imperceptible Adversarial Attack via Invertible Neural Networks


Imperceptible Backdoor Attack: From Input Space to Feature Representation


Imperceptible Face Forgery Attack via Adversarial Semantic Mask


Imperceptible and Robust Backdoor Attack in 3D Point Cloud


Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition


Imperfect Segmentation Labels: How Much Do They Matter?


Imperfect also Deserves Reward: Multi-Level and Sequential Reward Modeling for Better Dialog Management


Implant Global and Local Hierarchy Information to Sequence based Code Representation Models


Implantable Adaptive Cells: differentiable architecture search to improve the performance of any trained U-shaped network


Implementation and Analysis of GPU Algorithms for Vecchia Approximation


Implementation and Analysis of Regev's Quantum Factorization Algorithm


Implementation and Empirical Evaluation of a Quantum Machine Learning Pipeline for Local Classification


Implementation and Evaluation of Fast Raft for Hierarchical Consensus


Implementation and Evaluation of a Framework to calculate Impact Measures for Wikipedia Authors


Implementation of Algorithms for Right-Sizing Data Centers


Implementation of Analytical Jacobian and Chemical Explosive Mode Analysis (CEMA) in OpenFOAM


Implementation of DNN Based Data Detector for QPSK Systems


Implementation of Ethereum Accounts and Transactions on Embedded IoT Devices


Implementation of FGPA based Channel Sounder for Large scale antenna systems using RFNoC on USRP Platform


Implementation of IOAM for IPv6 in the Linux Kernel


Implementation of Kalman Filter Approach for Active Noise Control by Using MATLAB: Dynamic Noise Cancellation


Implementation of Linear Model Predictive Control -- Tutorial


Implementation of OpenAPI Wireshark Dissectors to Validate SBI Messages of 5G Core Networks


Implementation of Reference Public Safety Scenarios in ns-3


Implementation of SquashFS Support in U-Boot


Implementation of Stochastic Quasi-Newton's Method in PyTorch


Implementation of a neural network for non-linearities estimation in a tail-sitter aircraft


Implementation of a perception system for autonomous vehicles using a detection-segmentation network in SoC FPGA


Implementation of a two-stroke quantum heat engine with a collisional model


Implementation of an Oracle-Structured Bundle Method for Distributed Optimization


Implementation of an alternative method for assessing competing risks: restricted mean time lost


Implementation of bond weighting method for the Grassmann tensor renormalization group


Implementation of chemistry in the Athena++ code


Implementation of digital MemComputing using standard electronic components


Implementation of high-order, discontinuous Galerkin time stepping for fractional diffusion problems


Implementation of implicit filter for spatial spectra extraction


Implementation of the Feedforward Multichannel Virtual Sensing Active Noise Control (MVANC) by Using MATLAB


Implementation: The conjugacy problem in right-angled Artin groups


Implementations of efficient univariate polynomial matrix algorithms and application to bivariate resultants


Implementing 64-bit Maximally Equidistributed $\mathbb{F}_2$-Linear Generators with Mersenne Prime Period


Implementing Adaptations for Vision AutoRegressive Model


Implementing Approximate Bayesian Inference using Adaptive Quadrature: the aghq Package


Implementing BDI Continual Temporal Planning for Robotic Agents


Implementing Behavior Trees using Three-Valued Logic


Implementing Dependent Types in pi-forall


Implementing Hadamard Matrices in SageMath


Implementing Parallel Quick Sort Algorithm on OTIS Hyper Hexa-Cell (OHHC) Interconnection Network


Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs


Implementing SIAv2 Over Rubin Observatory's Data Butler


Implementing Smart Contracts: The case of NFT-rental with pay-per-like


Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images


Implementing a GPU-based parallel MAX-MIN Ant System


Implementing a Hierarchical Deep Learning Approach for Simulating Multi-Level Auction Data


Implementing a Metropolis sampler on decomposable graphs using a variety of ways to represent the graph


Implementing a Reverse Dictionary, based on word definitions, using a Node-Graph Architecture


Implementing a foveal-pit inspired filter in a Spiking Convolutional Neural Network: a preliminary study


Implementing an intelligent version of the classical sliding-puzzle game for unix terminals using Golang's concurrency primitives


Implementing and Experimenting with Diffusion Models for Text-to-Image Generation


Implementing contextual biasing in GPU decoder for online ASR


Implementing efficient balanced networks with mixed-signal spike-based learning circuits


Implementing measurement error models with mechanistic mathematical models in a likelihood-based framework for estimation, identifiability analysis, and prediction in the life sciences


Implementing scalable matrix-vector products for the exact diagonalization methods in quantum many-body physics


Implementing spectral methods for hidden Markov models with real-valued emissions


Implementing the Diverting Fast Radix Algorithm


Implementing the three-particle quantization condition for $π^+π^+K^+$ and related systems


Implet: A Post-hoc Subsequence Explainer for Time Series Models


ImpliCity: City Modeling from Satellite Images with Deep Implicit Occupancy Fields


ImpliRet: Benchmarking the Implicit Fact Retrieval Challenge


Implication of a galaxy-scale negative feedback by one of the most powerful multi-phase outflows in a hyper-luminous infrared galaxy at the intermediate redshift


Implications of Annotation Artifacts in Edge Probing Test Datasets


Implications of Decentralized Q-learning Resource Allocation in Wireless Networks


Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs


Implications of atmospheric nondetections for Trappist-1 inner planets on atmospheric retention prospects for outer planets


Implications of construction decisions in keyword-based networks: an empirical assessment


Implicit Adaptive Mesh Refinement for Dispersive Tsunami Propagation


Implicit Affordance Acquisition via Causal Action-Effect Modeling in the Video Domain


Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts


Implicit Argument Prediction as Reading Comprehension


Implicit Argument Prediction with Event Knowledge


Implicit Articulated Robot Morphology Modeling with Configuration Space Neural Signed Distance Functions


Implicit Assimilation of Sparse In Situ Data for Dense & Global Storm Surge Forecasting


Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning


Implicit Background Estimation for Semantic Segmentation


Implicit Bias Injection Attacks against Text-to-Image Diffusion Models


Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture


Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks


Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss


Implicit Bias of Linear Equivariant Networks


Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States


Implicit Chain of Thought Reasoning via Knowledge Distillation


Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation


Implicit Communication in Human-Robot Collaborative Transport


Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD


Implicit Contrastive Representation Learning with Guided Stop-gradient


Implicit Conversion of Manifold B-Rep Solids by Neural Halfspace Representation


Implicit Convolutional Kernels for Steerable CNNs


Implicit Cross-Lingual Rewarding for Efficient Multilingual Preference Alignment


Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods


Implicit Diffusion Models for Continuous Super-Resolution


Implicit Discourse Relation Identification for Open-domain Dialogues


Implicit Discriminative Knowledge Learning for Visible-Infrared Person Re-Identification


Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling


Implicit Electric Field Conjugation Through a Single-mode Fiber


Implicit Electric Field Conjugation with the Photonic Lantern Nuller


Implicit Equivariance in Convolutional Networks


Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter


Implicit Feature Decoupling with Depthwise Quantization


Implicit Feedback for Dense Passage Retrieval: A Counterfactual Approach


Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion


Implicit Gaussian process representation of vector fields over arbitrary latent manifolds


Implicit Generative Prior for Bayesian Neural Networks


Implicit Geometric Descriptor-Enabled ANN Framework for a Unified Structure-Property Relationship in Architected Nanofibrous Materials


Implicit Geometry and Interaction Embeddings Improve Few-Shot Molecular Property Prediction


Implicit Graph Neural Diffusion Networks: Convergence, Generalization, and Over-Smoothing


Implicit Grid Convolution for Multi-Scale Image Super-Resolution


Implicit Guidance and Explicit Representation of Semantic Information in Points Cloud: A Survey


Implicit Hari--Zimmermann algorithm for the generalized SVD on the GPUs


Implicit Identity Representation Conditioned Memory Compensation Network for Talking Head video Generation


Implicit Image-to-Image Schrodinger Bridge for Image Restoration


Implicit Inversion turns CLIP into a Decoder


Implicit Language Models are RNNs: Balancing Parallelization and Expressivity


Implicit Location-Caption Alignment via Complementary Masking for Weakly-Supervised Dense Video Captioning


Implicit Manifold Gaussian Process Regression


Implicit Maximum a Posteriori Filtering via Adaptive Optimization


Implicit Memory Transformer for Computationally Efficient Simultaneous Speech Translation


Implicit Model Specialization through DAG-based Decentralized Federated Learning


Implicit Motion-Compensated Network for Unsupervised Video Object Segmentation


Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model


Implicit Multidimensional Projection of Local Subspaces


Implicit Neural Image Field for Biological Microscopy Image Compression


Implicit Neural Networks with Fourier-Feature Inputs for Free-breathing Cardiac MRI Reconstruction


Implicit Neural Representation for Cooperative Low-light Image Enhancement


Implicit Neural Representation in Medical Imaging: A Comparative Survey


Implicit Neural Representations for Registration of Left Ventricle Myocardium During a Cardiac Cycle


Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data


Implicit Neural Representations for Variable Length Human Motion Generation


Implicit Neural Representations of Molecular Vector-Valued Functions


Implicit Neural Representations with Fourier Kolmogorov-Arnold Networks


Implicit Neural Surface Deformation with Explicit Velocity Fields


Implicit Obstacle Map-driven Indoor Navigation Model for Robust Obstacle Avoidance


Implicit Personalization in Language Models: A Systematic Study


Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks


Implicit Posterior Variational Inference for Deep Gaussian Processes


Implicit Premise Generation with Discourse-aware Commonsense Knowledge Models


Implicit Quantile Networks For Emulation in Jet Physics


Implicit Quantile Neural Networks for Jet Simulation and Correction


Implicit Rankings for Verifying Liveness Properties in First-Order Logic


Implicit Reasoning in Transformers is Reasoning through Shortcuts


Implicit Regularization for Group Sparsity


Implicit Regularization for Optimal Sparse Recovery


Implicit Regularization in Deep Learning May Not Be Explainable by Norms


Implicit Regularization in Deep Matrix Factorization


Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks


Implicit Regularization in Tensor Factorization


Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks


Implicit Regularization via Neural Feature Alignment


Implicit Representations of Meaning in Neural Language Models


Implicit SVD for Graph Representation Learning


Implicit Search via Discrete Diffusion: A Study on Chess


Implicit Session Contexts for Next-Item Recommendations


Implicit Shape Model Trees: Recognition of 3-D Indoor Scenes and Prediction of Object Poses for Mobile Robots


Implicit Solvent Approach Based on Generalised Born and Transferable Graph Neural Networks for Molecular Dynamics Simulations


Implicit Sparse Regularization: The Impact of Depth and Early Stopping


Implicit Surface Reconstruction with a Curl-free Radial Basis Function Partition of Unity Method


Implicit Swept Volume SDF: Enabling Continuous Collision-Free Trajectory Generation for Arbitrary Shapes


Implicit Temporal Modeling with Learnable Alignment for Video Recognition


Implicit Temporal Reasoning for Evidence-Based Fact-Checking


Implicit Transformer Network for Screen Content Image Continuous Super-Resolution


Implicit Unlikelihood Training: Improving Neural Text Generation with Reinforcement Learning


Implicit View-Time Interpolation of Stereo Videos using Multi-Plane Disparities and Non-Uniform Coordinates


Implicit Weight Uncertainty in Neural Networks


Implicit and Explicit Attention for Zero-Shot Learning


Implicit and Implicit-Explicit Strong Stability Preserving Runge-Kutta Methods with High Linear Order


Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks


Implicit bulk-surface filtering method for node-based shape optimization and comparison of explicit and implicit filtering techniques


Implicit degree bias in the link prediction task


Implicit differentiation of variational quantum algorithms


Implicit differentiation with second-order derivatives and benchmarks in finite-element-based differentiable physics


Implicit factorized transformer approach to fast prediction of turbulent channel flows


Implicit field learning for unsupervised anomaly detection in medical images


Implicit field supervision for robust non-rigid shape matching


Implicit low-rank Riemannian schemes for the time integration of stiff partial differential equations


Implicit meta-learning may lead language models to trust more reliable sources


Implicit neural representation for change detection


Implicit neural representations for joint decomposition and registration of gene expression images in the marmoset brain


Implicit regularization in AI meets generalized hardness of approximation in optimization -- Sharp results for diagonal linear networks


Implicit regularization of deep residual networks towards neural ODEs


Implicit self-consistent description of electrolyte in plane-wave density-functional theory


Implicit-Explicit Error Indicator based on Approximation Order


Implicit-Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenes


Implicit-explicit Integrated Representations for Multi-view Video Compression


Implicit-explicit multirate infinitesimal GARK methods


ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value Extraction


ImplicitCell: Resolution Cell Modeling of Joint Implicit Volume Reconstruction and Pose Refinement in Freehand 3D Ultrasound


ImplicitQA: Going beyond frames towards Implicit Video Reasoning


ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering


ImplicitTerrain: a Continuous Surface Model for Terrain Data Analysis


Implicitization of Biquadratic Bézier Triangle and Quadrilateral Surfaces


Implicitly Aligning Humans and Autonomous Agents through Shared Task Abstractions


Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits


Implied volatility (also) is path-dependent


Import2vec - Learning Embeddings for Software Libraries


Importance Corrected Neural JKO Sampling


Importance Reweighting for Biquality Learning


Importance Sampling CAMs for Weakly-Supervised Segmentation


Importance Sampling Methods for Bayesian Inference with Partitioned Data


Importance Sampling Policy Evaluation with an Estimated Behavior Policy


Importance Sampling for Nonlinear Models


Importance Sampling for Stochastic Gradient Descent in Deep Neural Networks


Importance Sampling for the Empirical Measure of Weakly Interacting Diffusions


Importance Sampling of Rare Events in Chaotic Systems


Importance Sampling with the Integrated Nested Laplace Approximation


Importance Sparsification for Sinkhorn Algorithm


Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift


Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning


Importance Weighted Adversarial Discriminative Transfer for Anomaly Detection


Importance Weighted Expectation-Maximization for Protein Sequence Design


Importance Weighting Can Help Large Language Models Self-Improve


Importance nested sampling with normalising flows


Importance of Disjoint Sampling in Conventional and Transformer Models for Hyperspectral Image Classification


Importance of Kernel Bandwidth in Quantum Machine Learning


Importance of hyper-parameter optimization during training of physics-informed deep learning networks


Importance of spatial predictor variable selection in machine learning applications -- Moving from data reproduction to spatial prediction


Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks


Importance sampling for option pricing with feedforward neural networks


Importance sampling for partially observed temporal epidemic models


Importance-Aware Semantic Segmentation with Efficient Pyramidal Context Network for Navigational Assistant Systems


Importance-aware Co-teaching for Offline Model-based Optimization


ImportantAug: a data augmentation agent for speech


Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing


Imposing Relation Structure in Language-Model Embeddings Using Contrastive Learning


Impossibility Theorems for Feature Attribution


Impossibility results on stability of phylogenetic consensus methods


Imprecise Markov Models for Scalable and Robust Performance Evaluation of Flexi-Grid Spectrum Allocation Policies


Imprecise Probabilities Meet Partial Observability: Game Semantics for Robust POMDPs


Imprompter: Tricking LLM Agents into Improper Tool Use


Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models


Improvable Gap Balancing for Multi-Task Learning


Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction


Improve Blockchain Performance using Graph Data Structure and Parallel Mining


Improve Cross-Architecture Generalization on Dataset Distillation


Improve Cross-domain Mixed Sampling with Guidance Training for Adaptive Segmentation


Improve Deep Forest with Learnable Layerwise Augmentation Policy Schedule


Improve Language Model and Brain Alignment via Associative Memory


Improve Machine Learning carbon footprint using Nvidia GPU and Mixed Precision training for classification models -- Part I


Improve Machine Learning carbon footprint using Parquet dataset format and Mixed Precision training for regression models -- Part II


Improve Meta-learning for Few-Shot Text Classification with All You Can Acquire from the Tasks


Improve Query Focused Abstractive Summarization by Incorporating Answer Relevance


Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NAS


Improve Representation for Imbalanced Regression through Geometric Constraints


Improve Student's Reasoning Generalizability through Cascading Decomposed CoTs Distillation


Improve Transformer Models with Better Relative Position Embeddings


Improve Vision Language Model Chain-of-thought Reasoning


Improve robustness of DNN for ECG signal classification:a noise-to-signal ratio perspective


Improved (Related-key) Differential-based Neural Distinguishers for SIMON and SIMECK Block Ciphers


Improved 3D Whole Heart Geometry from Sparse CMR Slices


Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks


Improved Aberth-Ehrlich root-finding algorithm and its further application for Binary Microlensing


Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time Detection


Improved Actor Relation Graph based Group Activity Recognition


Improved Adversarial Training Through Adaptive Instance-wise Loss Smoothing


Improved Algorithm and Bounds for Successive Projection


Improved Algorithms for Contextual Dynamic Pricing


Improved Algorithms for Integer Complexity


Improved Algorithms for Neural Active Learning


Improved Analysis of Clipping Algorithms for Non-convex Optimization


Improved Analysis of Highest-Degree Branching for Feedback Vertex Set


Improved Analysis of RANKING for Online Vertex-Weighted Bipartite Matching in the Random Order Model


Improved Anomaly Detection by Using the Attention-Based Isolation Forest


Improved Anomaly Detection through Conditional Latent Space VAE Ensembles


Improved Approximation Ratios of Fixed-Price Mechanisms in Bilateral Trades


Improved Approximation for Fair Correlation Clustering


Improved AutoEncoder with LSTM module and KL divergence


Improved Automated Machine Learning from Transfer Learning


Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition


Improved Bengali Image Captioning via deep convolutional neural network based encoder-decoder model


Improved Benthic Classification using Resolution Scaling and SymmNet Unsupervised Domain Adaptation


Improved Biomedical Word Embeddings in the Transformer Era


Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions


Improved Brain Age Estimation with Slice-based Set Networks


Improved Cauchy-characteristic evolution system for high-precision numerical relativity waveforms


Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer Learning


Improved Classical and Quantum Algorithms for Subset-Sum


Improved Conditional Flow Models for Molecule to Image Synthesis


Improved Confidence Regions in Meta-analysis of Diagnostic Test Accuracy


Improved Constraints on Cosmic Birefringence from the WMAP and Planck Cosmic Microwave Background Polarization Data


Improved Convergence Rate of Stochastic Gradient Langevin Dynamics with Variance Reduction and its Application to Optimization


Improved Cooperation by Exploiting a Common Signal


Improved DIQKD protocols with finite-size analysis


Improved Deep Hashing with Soft Pairwise Similarity for Multi-label Image Retrieval


Improved Deep Point Cloud Geometry Compression


Improved DeepFake Detection Using Whisper Features


Improved Dense Nested Attention Network Based on Transformer for Infrared Small Target Detection


Improved Depth Estimation of Bayesian Neural Networks


Improved Difference Images for Change Detection Classifiers in SAR Imagery Using Deep Learning


Improved Differentially Private Regression via Gradient Boosting


Improved Diffusion-based Generative Model with Better Adversarial Robustness


Improved Direct Voxel Grid Optimization for Radiance Fields Reconstruction


Improved Distribution Matching Distillation for Fast Image Synthesis


Improved Distribution Matching for Dataset Condensation


Improved Effective Dynamics of Loop-Quantum-Gravity Black Hole and Nariai Limit


Improved Estimation of Concentration Under $\ell_p$-Norm Distance Metrics Using Half Spaces


Improved Evaluation and Generation of Grid Layouts using Distance Preservation Quality and Linear Assignment Sorting


Improved Evolutionary Algorithms for Submodular Maximization with Cost Constraints


Improved Extrinsic Calibration of Acoustic Cameras via Batch Optimization


Improved Fault Analysis on SIMECK Ciphers


Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses


Improved Field Size Bounds for Higher Order MDS Codes


Improved Fitness-Dependent Optimizer Algorithm


Improved GUI Grounding via Iterative Narrowing


Improved Galactic Foreground Removal for B-Modes Detection with Clustering Methods


Improved Generalization of Weight Space Networks via Augmentations


Improved Generation of Adversarial Examples Against Safety-aligned LLMs


Improved Generation of Synthetic Imaging Data Using Feature-Aligned Diffusion


Improved Gradient based Adversarial Attacks for Quantized Networks


Improved Group Robustness via Classifier Retraining on Independent Splits


Improved Handling of Repeats and Jumps in Audio-Sheet Image Synchronization


Improved Hard Example Mining Approach for Single Shot Object Detectors


Improved IR-based Bug Localization with Intelligent Relevance Feedback


Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairing


Improved Image Segmentation via Cost Minimization of Multiple Hypotheses


Improved Input Reprogramming for GAN Conditioning


Improved Instruction Ordering in Recipe-Grounded Conversation


Improved Kernel Alignment Regret Bound for Online Kernel Learning


Improved Knowledge Distillation via Full Kernel Matrix Transfer


Improved Knowledge Distillation via Teacher Assistant


Improved Latent Tree Induction with Distant Supervision via Span Constraints


Improved Learned Sparse Retrieval with Corpus-Specific Vocabularies


Improved Learning-augmented Algorithms for k-means and k-medians Clustering


Improved Load Balancing in Large Scale Systems using Attained Service Time Reporting


Improved Logical Error Rate via List Decoding of Quantum Polar Codes


Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming


Improved Lower Bound on the Number of Pseudoline Arrangements


Improved Lower Bounds on the Expected Length of Longest Common Subsequences


Improved Marginal Unbiased Score Expansion (MUSE) via Implicit Differentiation


Improved Master for the LSS: Fast and accurate analysis of the two point power spectra and correlation functions


Improved Max-value Entropy Search for Multi-objective Bayesian Optimization with Constraints


Improved Mixed Dark Matter Halo Model for Ultralight Axions


Improved Mixed-Example Data Augmentation


Improved Mixing and Pressure Loss Formulations for Gas Network Optimization


Improved Moving-Puncture Techniques for Compact Binary Simulations


Improved Multi-Shot Diffusion-Weighted MRI with Zero-Shot Self-Supervised Learning Reconstruction


Improved Multi-label Classification under Temporal Concept Drift: Rethinking Group-Robust Algorithms in a Label-Wise Setting


Improved Network Robustness with Adversary Critic


Improved Neural Machine Translation with a Syntax-Aware Encoder and Decoder


Improved Neural Protoform Reconstruction via Reflex Prediction


Improved Nonlinear Transform Source-Channel Coding to Catalyze Semantic Communications


Improved Off-policy Reinforcement Learning in Biological Sequence Design


Improved Operator Learning by Orthogonal Attention


Improved Orientation Sampling for Indexing Diffraction Patterns of Polycrystalline Materials


Improved Out-of-Scope Intent Classification with Dual Encoding and Threshold-based Re-Classification


Improved Pancreatic Tumor Detection by Utilizing Clinically-Relevant Secondary Features


Improved Paraphrase Generation via Controllable Latent Diffusion


Improved Pathwise Coordinate Descent for Power Penalties


Improved Peel-and-Bound: Methods for Generating Dual Bounds with Multivalued Decision Diagrams


Improved Person Re-Identification Based on Saliency and Semantic Parsing with Deep Neural Network Models


Improved Point Transformation Methods For Self-Supervised Depth Prediction


Improved Policy Optimization for Online Imitation Learning


Improved Pothole Detection Using YOLOv7 and ESRGAN


Improved Probabilistic Image-Text Representations


Improved Protein-ligand Binding Affinity Prediction with Structure-Based Deep Fusion Inference


Improved Quantum Computation using Operator Backpropagation


Improved Regret Bounds for Online Kernel Selection under Bandit Feedback


Improved Regularization and Robustness for Fine-tuning in Neural Networks


Improved Reinforcement Learning Pushing Policies via Heuristic Rules


Improved Relation Extraction with Feature-Rich Compositional Embedding Models


Improved Robust Price Bounds for Multi-Asset Derivatives under Market-Implied Dependence Information


Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output Codes


Improved STEREO simulation with a new gamma ray spectrum of excited gadolinium isotopes using FIFRELIN


Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin


Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning


Improved Sentiment Detection via Label Transfer from Monolingual to Synthetic Code-Switched Text


Improved Soft Duplicate Detection in Search-Based Motion Planning


Improved Stereo Matching with Constant Highway Networks and Reflective Confidence Learning


Improved StyleGAN Embedding: Where are the Good Latents?


Improved Techniques for Learning to Dehaze and Beyond: A Collective Study


Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs


Improved Techniques for Optimization-Based Jailbreaking on Large Language Models


Improved Test-Time Adaptation for Domain Generalization


Improved Topology-Independent Distributed Adaptive Node-Specific Signal Estimation for Wireless Acoustic Sensor Networks


Improved Training Technique for Latent Consistency Models


Improved Transformer for High-Resolution GANs


Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles


Improved Upper Bound on Brun's Constant Under GRH


Improved Upper and Lower Bounds on the Capacity of the Binary Deletion Channel


Improved Utility Analysis of Private CountSketch


Improved Variational Bayesian Phylogenetic Inference using Mixtures


Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows


Improved Vessel Segmentation with Symmetric Rotation-Equivariant U-Net


Improved Visual Fine-tuning with Natural Language Supervision


Improved Visually Prompted Keyword Localisation in Real Low-Resource Settings


Improved Volume-of-Solid formulations for micro-continuum simulation of mineral dissolution at the pore-scale


Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word Representations


Improved Xception with Dual Attention Mechanism and Feature Fusion for Face Forgery Detection


Improved Zero-Shot Classification by Adapting VLMs with Text Descriptions


Improved acoustic-to-articulatory inversion using representations from pretrained self-supervised learning models


Improved algorithms for left factorial residues


Improved anomaly detection by training an autoencoder with skip connections on images corrupted with Stain-shaped noise


Improved approximation algorithms for the EPR Hamiltonian


Improved approximation ratios for the Quantum Max-Cut problem on general, triangle-free and bipartite graphs


Improved architectures and training algorithms for deep operator networks


Improved asymptotic upper bounds for the minimum number of pairwise distinct longest cycles in regular graphs


Improved automated lesion segmentation in whole-body FDG/PET-CT via Test-Time Augmentation


Improved bounds for Serre's open image theorem


Improved bounds for randomized Schatten norm estimation of numerically low-rank matrices


Improved bridge constructs for stochastic differential equations


Improved calculations of mean ionization states with an average-atom model


Improved clinical data imputation via classical and quantum determinantal point processes


Improved computation of fundamental domains for arithmetic Fuchsian groups


Improved computational efficiency and stability when imputing censored covariates: Analytic and numerical approaches


Improved constraints on reionisation from CMB observations: A parameterisation of the kSZ effect


Improved critical drift estimates for the frog model on trees


Improved detection of discarded fish species through BoxAL active learning


Improved distinct bone segmentation in upper-body CT through multi-resolution networks


Improved error bounds for Koopman operator and reconstructed trajectories approximations with kernel-based methods


Improved estimation of the effective reproduction number with heterogeneous transmission rates and reporting delays


Improved estimators in beta prime regression models


Improved finite-size key rates for discrete-modulated continuous variable quantum key distribution under coherent attacks


Improved fluxonium readout through dynamic flux pulsing


Improved inference on risk measures for univariate extremes


Improved information criteria for Bayesian model averaging in lattice field theory


Improved learning theory for kernel distribution regression with two-stage sampling


Improved log-Gaussian approximation for over-dispersed Poisson regression: application to spatial analysis of COVID-19


Improved lower bounds for Queen's Domination via an exactly-solvable relaxation


Improved memory in recurrent neural networks with sequential non-normal dynamics


Improved methods for empirical Bayes multivariate multiple testing and effect size estimation


Improved mirror ball projection for more accurate merging of multiple camera outputs and process monitoring


Improved object recognition using neural networks trained to mimic the brain's statistical properties


Improved particle spray algorithm for modeling globular cluster streams


Improved phase-field models of melting and dissolution in multi-component flows


Improved physics-informed neural network in mitigating gradient related failures


Improved post-Newtonian waveform model for inspiralling precessing-eccentric compact binaries


Improved post-hoc probability calibration for out-of-domain MRI segmentation


Improved prediction of ligand-protein binding affinities by meta-modeling


Improved proteasomal cleavage prediction with positive-unlabeled learning


Improved rates for prediction and identification of partially observed linear dynamical systems


Improved replica bounds for the independence ratio of random regular graphs


Improved reproducibility of diffusion kurtosis imaging using regularized non-linear optimization informed by artificial neural networks


Improved simulation of non-Gaussian temperature and polarization CMB maps


Improved small-sample inference for functions of parameters in the k-sample multinomial problem


Improved techniques for deterministic l2 robustness


Improved training of neural trans-dimensional random field language models with dynamic noise-contrastive estimation


Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients


Improved variants of the Hutch++ algorithm for trace estimation


Improved, Deterministic Smoothing for L_1 Certified Robustness


Improvement Graph Convolution Collaborative Filtering with Weighted addition input


Improvement in Sign Language Translation Using Text CTC Alignment


Improvement of Classification in One-Stage Detector


Improvement of Computational Performance of Evolutionary AutoML in a Heterogeneous Environment


Improvement of Data Analytics Techniques in Reflection High Energy Electron Diffraction to Enable Machine Learning


Improvement of Geant4 Neutron-HP package: Doppler broadening of the neutron elastic scattering kernel and cross sections


Improvement of Geant4 Neutron-HP package: Unresolved Resonance Region description with Probability Tables


Improvement of Geant4 Neutron-HP package: from methodology to evaluated nuclear data library


Improvement of digest2 NEO Classification Code -- utilizing the Astrometry Data Exchange Standard


Improvement over Pinball Loss Support Vector Machine


Improvement-Focused Causal Recourse (ICR)


Improvements & Evaluations on the MLCommons CloudMask Benchmark


Improvements of Discriminative Feature Space Training for Anomalous Sound Detection in Unlabeled Conditions


Improvements on Scalable Stochastic Bayesian Inference Methods for Multivariate Hawkes Process


Improvements to Modern Portfolio Theory based models applied to electricity systems


Improvements to short-term weather prediction with recurrent-convolutional networks


Improvements to the Search for Cosmic Dawn Using the Long Wavelength Array


Improving $(α, f)$-Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distance


Improving $t \bar{t}$ reconstruction in the dilepton channel at future lepton colliders


Improving (Dis)agreement Detection with Inductive Social Relation Information From Comment-Reply Interactions


Improving 2D Human Pose Estimation in Rare Camera Views with Synthetic Data


Improving 3D Medical Image Segmentation at Boundary Regions using Local Self-attention and Global Volume Mixing


Improving 3D Object Detection with Channel-wise Transformer


Improving AI weather prediction models using global mass and energy conservation schemes


Improving AMR Parsing with Sequence-to-Sequence Pre-training


Improving Access to Housing and Supportive Services for Runaway and Homeless Youth: Reducing Vulnerability to Human Trafficking in New York City


Improving Accuracy and Explainability of Online Handwriting Recognition


Improving Accuracy of Permutation DAG Search using Best Order Score Search


Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training


Improving Acne Image Grading with Label Distribution Smoothing


Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech Representations


Improving Across-Dataset Brain Tissue Segmentation Using Transformer


Improving Action Quality Assessment using Weighted Aggregation


Improving Adaptive Density Control for 3D Gaussian Splatting


Improving Address Matching using Siamese Transformer Networks


Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset


Improving Adversarial Robustness by Enforcing Local and Global Compactness


Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples


Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations


Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics


Improving Adversarial Robustness of Masked Autoencoders via Test-time Frequency-domain Prompting


Improving Adversarial Robustness via Channel-wise Activation Suppressing


Improving Adversarial Robustness via Decoupled Visual Representation Masking


Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes


Improving Adversarial Robustness via Mutual Information Estimation


Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints


Improving Adversarial Robustness with Self-Paced Hard-Class Pair Reweighting


Improving Adversarial Transferability on Vision Transformers via Forward Propagation Refinement


Improving Adversarial Transferability via Intermediate-level Perturbation Decay


Improving Adversarial Transferability via Model Alignment


Improving Adversarial Transferability via Neuron Attribution-Based Attacks


Improving Anomalous Sound Detection through Pseudo-anomalous Set Selection and Pseudo-label Utilization under Unlabeled Conditions


Improving Ant Colony Optimization Efficiency for Solving Large TSP Instances


Improving Antibody Humanness Prediction using Patent Data


Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss


Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function


Improving Arithmetic Reasoning Ability of Large Language Models through Relation Tuples, Verification and Dynamic Feedback


Improving Artificial Teachers by Considering How People Learn and Forget


Improving Aspect Sentiment Quad Prediction via Template-Order Data Augmentation


Improving Aspect Term Extraction with Bidirectional Dependency Tree Representation


Improving Aspect-Based Sentiment with End-to-End Semantic Role Labeling Model


Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation


Improving Attribution Methods by Learning Submodular Functions


Improving Audio Captioning Models with Fine-grained Audio Features, Text Embedding Supervision, and LLM Mix-up Augmentation


Improving Audio-Visual Segmentation with Bidirectional Generation


Improving Audio-Visual Speech Recognition by Lip-Subword Correlation Based Visual Pre-training and Cross-Modal Fusion Encoder


Improving Autoencoder Image Interpolation via Dynamic Optimal Transport


Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation


Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model Decoding


Improving Axial-Attention Network Classification via Cross-Channel Weight Sharing


Improving BERT Model Using Contrastive Learning for Biomedical Relation Extraction


Improving BERT Pretraining with Syntactic Supervision


Improving BERT with Syntax-aware Local Attention


Improving Back-Translation with Uncertainty-based Confidence Estimation


Improving Background Based Conversation with Context-aware Knowledge Pre-selection


Improving Bayesian Network Structure Learning in the Presence of Measurement Error


Improving Bayesian radiological profiling of waste drums using Dirichlet priors, Gaussian process priors, and hierarchical modeling


Improving Bi-encoder Document Ranking Models with Two Rankers and Multi-teacher Distillation


Improving Bias Mitigation through Bias Experts in Natural Language Understanding


Improving Bilingual Lexicon Induction with Cross-Encoder Reranking


Improving Biomedical Abstractive Summarisation with Knowledge Aggregation from Citation Papers


Improving Biomedical Entity Linking with Retrieval-enhanced Learning


Improving Biomedical Pretrained Language Models with Knowledge


Improving Bitswap Privacy with Forwarding and Source Obfuscation


Improving Black Hole Accretion Treatment in Hydrodynamical Simulations


Improving Black-box Robustness with In-Context Rewriting


Improving Blind Spot Denoising for Microscopy


Improving Bot Response Contradiction Detection via Utterance Rewriting


Improving Both Domain Robustness and Domain Adaptability in Machine Translation


Improving Broad-Coverage Medical Entity Linking with Semantic Type Prediction and Large-Scale Datasets


Improving CLIP Training with Language Rewrites


Improving COVID-19 Forecasting using eXogenous Variables


Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness


Improving Camouflaged Object Detection with the Uncertainty of Pseudo-edge Labels


Improving Candidate Generation for Low-resource Cross-lingual Entity Linking


Improving Candidate Retrieval with Entity Profile Generation for Wikidata Entity Linking


Improving Capital Efficiency and Impermanent Loss: Multi-Token Proactive Market Maker


Improving Causal Reasoning in Large Language Models: A Survey


Improving Certified Robustness via Statistical Learning with Logical Reasoning


Improving Chest X-Ray Report Generation by Leveraging Warm Starting


Improving Children's Speech Recognition by Fine-tuning Self-supervised Adult Speech Representations


Improving Chinese Spelling Check by Character Pronunciation Prediction: The Effects of Adaptivity and Granularity


Improving Chinese Story Generation via Awareness of Syntactic Dependencies and Semantics


Improving Choral Music Separation through Expressive Synthesized Data from Sampled Instruments


Improving Classification Neural Networks by using Absolute activation function (MNIST/LeNET-5 example)


Improving Clinical Document Understanding on COVID-19 Research with Spark NLP


Improving Clinical Efficiency and Reducing Medical Errors through NLP-enabled diagnosis of Health Conditions from Transcription Reports


Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data


Improving Clinical Outcome Predictions Using Convolution over Medical Entities with Multimodal Learning


Improving Clinician Performance in Classification of EEG Patterns on the Ictal-Interictal-Injury Continuum using Interpretable Machine Learning


Improving Code Example Recommendations on Informal Documentation Using BERT and Query-Aware LSH: A Comparative Study


Improving Code Generation by Training with Natural Language Feedback


Improving Code Search with Hard Negative Sampling Based on Fine-tuning


Improving Code Summarization with Block-wise Abstract Syntax Tree Splitting


Improving Collaborative Metric Learning with Efficient Negative Sampling


Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles


Improving Community-Participated Patrol for Anti-Poaching


Improving Complex Knowledge Base Question Answering via Question-to-Action and Question-to-Question Alignment


Improving Composed Image Retrieval via Contrastive Learning with Scaling Positives and Negatives


Improving Compositional Generalization in Math Word Problem Solving


Improving Compositional Generalization in Semantic Parsing


Improving Compositional Generation with Diffusion Models Using Lift Scores


Improving Compound Activity Classification via Deep Transfer and Representation Learning


Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings


Improving Computed Tomography (CT) Reconstruction via 3D Shape Induction


Improving Concept Alignment in Vision-Language Concept Bottleneck Models


Improving Conditional Coverage via Orthogonal Quantile Regression


Improving Conditional Sequence Generative Adversarial Networks by Stepwise Evaluation


Improving Confidence Estimates for Unfamiliar Examples


Improving Consistency Models with Generator-Induced Flows


Improving Consistency in Large Language Models through Chain of Guidance


Improving Contextualized Topic Models with Negative Sampling


Improving Continual Pre-training Through Seamless Data Packing


Improving Continual Relation Extraction by Distinguishing Analogous Semantics


Improving Contrastive Learning by Visualizing Feature Transformation


Improving Contrastive Learning for Referring Expression Counting


Improving Contrastive Learning of Sentence Embeddings from AI Feedback


Improving Contrastive Learning of Sentence Embeddings with Case-Augmented Positives and Retrieved Negatives


Improving Contrastive Learning with Model Augmentation


Improving Convergence and Generalization Using Parameter Symmetries


Improving Conversational Passage Re-ranking with View Ensemble


Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning


Improving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data Augmentation


Improving Conversational Recommendation Systems via Counterfactual Data Simulation


Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta Information


Improving Cooperation in Language Games with Bayesian Inference and the Cognitive Hierarchy


Improving Coverage and Runtime Complexity for Exact Inference in Non-Projective Transition-Based Dependency Parsers


Improving Cross-Domain Chinese Word Segmentation with Word Embeddings


Improving Cross-Domain Hate Speech Generalizability with Emotion Knowledge


Improving Cross-Lingual Transfer through Subtree-Aware Word Reordering


Improving Cross-Lingual Word Embeddings by Meeting in the Middle


Improving Cross-Modal Alignment in Vision Language Navigation via Syntactic Information


Improving Cross-Modal Retrieval with Set of Diverse Embeddings


Improving Cross-domain Few-shot Classification with Multilayer Perceptron


Improving Cyberbully Detection with User Interaction


Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization


Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay


Improving Data Quality with Training Dynamics of Gradient Boosting Decision Trees


Improving Data-aware and Parameter-aware Robustness for Continual Learning


Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty


Improving Deep Assertion Generation via Fine-Tuning Retrieval-Augmented Pre-trained Language Models


Improving Deep Facial Phenotyping for Ultra-rare Disorder Verification Using Model Ensembles


Improving Deep Image Matting via Local Smoothness Assumption


Improving Deep Learning Interpretability by Saliency Guided Training


Improving Deep Learning Optimization through Constrained Parameter Regularization


Improving Deep Learning for HAR with shallow LSTMs


Improving Deep Localized Level Analysis: How Game Logs Can Help


Improving Deep Metric Learning by Divide and Conquer


Improving Deep Neural Network Random Initialization Through Neuronal Rewiring


Improving Deep Neural Network with Multiple Parametric Exponential Linear Units


Improving Deep Regression with Ordinal Entropy


Improving Deep Regression with Tightness


Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn


Improving Deep Representation Learning via Auxiliary Learnable Target Coding


Improving Demonstration Diversity by Human-Free Fusing for Text-to-SQL


Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale Upsampling


Improving Detail in Pluralistic Image Inpainting with Feature Dequantization


Improving Detection of Person Class Using Dense Pooling


Improving Device-Edge Cooperative Inference of Deep Learning via 2-Step Pruning


Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case Study


Improving Dialog Evaluation with a Multi-reference Adversarial Dataset and Large Scale Pretraining


Improving Dialog Systems for Negotiation with Personality Modeling


Improving Dialogue Management: Quality Datasets vs Models


Improving Differentiable Neural Computers Through Memory Masking, De-allocation, and Link Distribution Sharpness Control


Improving Differentially Private SGD via Randomly Sparsified Gradients


Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing


Improving Diffusion Model Efficiency Through Patching


Improving Diffusion Models for Authentic Virtual Try-on in the Wild


Improving Diffusion Models's Data-Corruption Resistance using Scheduled Pseudo-Huber Loss


Improving Diffusion-Based Generative Models via Approximated Optimal Transport


Improving Diffusion-based Image Translation using Asymmetric Gradient Guidance


Improving Diffusion-based Inverse Algorithms under Few-Step Constraint via Learnable Linear Extrapolation


Improving Discourse Relation Projection to Build Discourse Annotated Corpora


Improving Disease Comorbidity Prediction Based on Human Interactome with Biologically Supervised Graph Embedding


Improving Distantly Supervised Relation Extraction with Self-Ensemble Noise Filtering


Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning


Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance Embeddings


Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning


Improving Diversity with Adversarially Learned Transformations for Domain Generalization


Improving Document Binarization via Adversarial Noise-Texture Augmentation


Improving Document Classification with Multi-Sense Embeddings


Improving Document-Level Sentiment Analysis with User and Product Context


Improving Domain Generalization by Learning without Forgetting: Application in Retail Checkout


Improving Domain Generalization for Sound Classification with Sparse Frequency-Regularized Transformer


Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual Learning


Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial Networks


Improving EO Foundation Models with Confidence Assessment for enhanced Semantic segmentation


Improving Earth-like planet detection in radial velocity using deep learning


Improving Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architectures


Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation


Improving Electron Micrograph Signal-to-Noise with an Atrous Convolutional Encoder-Decoder


Improving Embedded Knowledge Graph Multi-hop Question Answering by introducing Relational Chain Reasoning


Improving Empathetic Dialogue Generation by Dynamically Infusing Commonsense Knowledge


Improving End-to-End Contextual Speech Recognition with Fine-Grained Contextual Knowledge Selection


Improving End-to-End SLU performance with Prosodic Attention and Distillation


Improving End-to-End Sequential Recommendations with Intent-aware Diversification


Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task


Improving Energy Conserving Descent for Machine Learning: Theory and Practice


Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation


Improving Entity Linking by Modeling Latent Relations between Mentions


Improving Entity Linking through Semantic Reinforced Entity Embeddings


Improving Environment Robustness of Deep Reinforcement Learning Approaches for Autonomous Racing Using Bayesian Optimization-based Curriculum Learning


Improving Equivariance in State-of-the-Art Supervised Depth and Normal Predictors


Improving Equivariant Model Training via Constraint Relaxation


Improving Estimation of the Koopman Operator with Kolmogorov-Smirnov Indicator Functions


Improving Event Representation via Simultaneous Weakly Supervised Contrastive Learning and Clustering


Improving Exoplanet Detection Power: Multivariate Gaussian Process Models for Stellar Activity


Improving Experience Replay through Modeling of Similar Transitions' Sets


Improving Expert Predictions with Conformal Prediction


Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings


Improving Explainability of Sentence-level Metrics via Edit-level Attribution for Grammatical Error Correction


Improving Explainability of Softmax Classifiers Using a Prototype-Based Joint Embedding Method


Improving Explicit Spatial Relationships in Text-to-Image Generation through an Automatically Derived Dataset


Improving Exploration in Soft-Actor-Critic with Normalizing Flows Policies


Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction


Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization


Improving Expressivity of Graph Neural Networks using Localization


Improving External Communication of Automated Vehicles Using Bayesian Optimization


Improving Facade Parsing with Vision Transformers and Line Integration


Improving Face Recognition with Large Age Gaps by Learning to Distinguish Children


Improving Factual Accuracy of Neural Table-to-Text Output by Addressing Input Problems in ToTTo


Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation


Improving Factual Consistency for Knowledge-Grounded Dialogue Systems via Knowledge Enhancement and Alignment


Improving Factual Consistency in Summarization with Compression-Based Post-Editing


Improving Factual Error Correction by Learning to Inject Factual Errors


Improving Factual Error Correction for Abstractive Summarization via Data Distillation and Conditional-generation Cloze


Improving Factuality and Reasoning in Language Models through Multiagent Debate


Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators


Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality


Improving Fair Predictions Using Variational Inference In Causal Models


Improving Fairness in AI Models on Electronic Health Records: The Case for Federated Learning Methods


Improving Fairness in Deepfake Detection


Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage


Improving Fairness in Information Exposure by Adding Links


Improving Fairness of Automated Chest X-ray Diagnosis by Contrastive Learning


Improving Fairness using Vision-Language Driven Image Augmentation


Improving Fast Adversarial Training with Prior-Guided Knowledge


Improving Feature-based Visual Localization by Geometry-Aided Matching


Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data


Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs using Confidence-Augmented Reinforcement Learning


Improving Few-Shot Learning for Talking Face System with TTS Data Augmentation


Improving Few-Shot Learning through Multi-task Representation Learning Theory


Improving Few-Shot Learning with Auxiliary Self-Supervised Pretext Tasks


Improving Few-shot Image Generation by Structural Discrimination and Textural Modulation


Improving Fine-Grained Control via Aggregation of Multiple Diffusion Models


Improving Fine-Grained Visual Recognition in Low Data Regimes via Self-Boosting Attention Mechanism


Improving Fine-grained Entity Typing with Entity Linking


Improving Fine-tuning of Self-supervised Models with Contrastive Initialization


Improving Forecasts for Heterogeneous Time Series by "Averaging", with Application to Food Demand Forecast


Improving Forward Compatibility in Class Incremental Learning by Increasing Representation Rank and Feature Richness


Improving Front-end Performance through Modular Rendering and Adaptive Hydration (MRAH) in React Applications


Improving Fuzzing Using Software Complexity Metrics


Improving GAN Training via Binarized Representation Entropy (BRE) Regularization


Improving GAN Training with Probability Ratio Clipping and Sample Reweighting


Improving GANs for Long-Tailed Data through Group Spectral Regularization


Improving GBDT Performance on Imbalanced Datasets: An Empirical Study of Class-Balanced Loss Functions


Improving GFlowNets for Text-to-Image Diffusion Alignment


Improving GNSS Positioning using Neural Network-based Corrections


Improving Galaxy Clustering Measurements with Deep Learning: analysis of the DECaLS DR7 data


Improving Galileo OSNMA Time To First Authenticated Fix


Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors


Improving Generalizability of Fake News Detection Methods using Propensity Score Matching


Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output Codes


Improving Generalization Ability for 3D Object Detection by Learning Sparsity-invariant Features


Improving Generalization Ability of Countermeasures for New Mismatch Scenario by Combining Multiple Advanced Regularization Terms


Improving Generalization Bounds for VC Classes Using the Hypergeometric Tail Inversion


Improving Generalization and Stability of Generative Adversarial Networks


Improving Generalization by Controlling Label-Noise Information in Neural Network Weights


Improving Generalization for AI-Synthesized Voice Detection


Improving Generalization for Multimodal Fake News Detection


Improving Generalization in Meta-Learning via Meta-Gradient Augmentation


Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics Mixture


Improving Generalization in Meta-learning via Task Augmentation


Improving Generalization of Batch Whitening by Convolutional Unit Optimization


Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution


Improving Generalization of Medical Image Registration Foundation Model


Improving Generalization of Metric Learning via Listwise Self-distillation


Improving Generalization of Neural Vehicle Routing Problem Solvers Through the Lens of Model Architecture


Improving Generalization of Synthetically Trained Sonar Image Descriptors for Underwater Place Recognition


Improving Generalization of Universal Adversarial Perturbation via Dynamic Maximin Optimization


Improving Generalization on the ProcGen Benchmark with Simple Architectural Changes and Scale


Improving Generalization with Domain Convex Game


Improving Generation and Evaluation of Visual Stories via Semantic Consistency


Improving Generative Adversarial Networks with Local Coordinate Coding


Improving Generative Inverse Design of Rectangular Patch Antennas with Test Time Optimization


Improving Generative Model-based Unfolding with Schrödinger Bridges


Improving Gloss-free Sign Language Translation by Reducing Representation Density


Improving Gradient Computation for Differentiable Physics Simulation with Contacts


Improving Gradient-guided Nested Sampling for Posterior Inference


Improving Grammar-based Sequence-to-Sequence Modeling with Decomposition and Constraints


Improving Grammatical Error Correction via Contextual Data Augmentation


Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning


Improving Graph Generation by Restricting Graph Bandwidth


Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting


Improving Graph Neural Networks at Scale: Combining Approximate PageRank and CoreRank


Improving Graph Neural Networks by Learning Continuous Edge Directions


Improving Graph Property Prediction with Generalized Readout Functions


Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings


Improving Grip Stability Using Passive Compliant Microspine Arrays for Soft Robots in Unstructured Terrain


Improving Grounded Natural Language Understanding through Human-Robot Dialog


Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference


Improving Group Robustness on Spurious Correlation via Evidential Alignment


Improving Hamiltonian encodings with the Gray code


Improving Hate Speech Classification with Cross-Taxonomy Dataset Integration


Improving Head Pose Estimation with a Combined Loss and Bounding Box Margin Adjustment


Improving Health Question Answering with Reliable and Time-Aware Evidence Retrieval


Improving Heterogeneous Graph Learning with Weighted Mixed-Curvature Product Manifold


Improving Heterogeneous Model Reuse by Density Estimation


Improving How Agents Cooperate: Attention Schemas in Artificial Neural Networks


Improving Hyper-Relational Knowledge Graph Completion


Improving Hypernymy Detection with an Integrated Path-based and Distributional Method


Improving Hypernymy Extraction with Distributional Semantic Classes


Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models


Improving Hyperparameter Optimization with Checkpointed Model Weights


Improving Image Captioning with Better Use of Captions


Improving Image Clustering through Sample Ranking and Its Application to remote--sensing images


Improving Image Restoration through Removing Degradations in Textual Representations


Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment


Improving In-Context Learning with Prediction Feedback for Sentiment Analysis


Improving In-Context Learning with Reasoning Distillation


Improving In-Context Learning with Small Language Model Ensembles


Improving In-context Learning of Multilingual Generative Language Models with Cross-lingual Alignment


Improving Indoor Localization Accuracy by Using an Efficient Implicit Neural Map Representation


Improving Inductive Link Prediction Using Hyper-Relational Facts


Improving Information Cascade Modeling by Social Topology and Dual Role User Dependency


Improving Information Extraction on Business Documents with Specific Pre-Training Tasks


Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation


Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path


Improving Interpersonal Communication by Simulating Audiences with Language Models


Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training


Improving Interpretability via Explicit Word Interaction Graph Layer


Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models


Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder


Improving Java Deserialization Gadget Chain Mining via Overriding-Guided Object Generation


Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment


Improving Knot Prediction in Wood Logs with Longitudinal Feature Propagation


Improving Knowledge Distillation via Transferring Learning Ability


Improving Knowledge Graph Embedding Using Simple Constraints


Improving Knowledge Graph Entity Alignment with Graph Augmentation


Improving Knowledge Tracing via Pre-training Question Embeddings


Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering


Improving Knowledge-aware Recommendation with Multi-level Interactive Contrastive Learning


Improving Korean NLP Tasks with Linguistically Informed Subword Tokenization and Sub-character Decomposition


Improving LIME Robustness with Smarter Locality Sampling


Improving LLM Reasoning with Multi-Agent Tree-of-Thought Validator Agent


Improving LLM Safety Alignment with Dual-Objective Optimization


Improving LLM Unlearning Robustness via Random Perturbations


Improving LLM-as-a-Judge Inference with the Judgment Distribution


Improving LLM-based Global Optimization with Search Space Partitioning


Improving LLM-powered Recommendations with Personalized Information


Improving LSHADE by means of a pre-screening mechanism


Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfinding


Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback


Improving Language Transfer Capability of Decoder-only Architecture in Multilingual Neural Machine Translation


Improving Language Understanding from Screenshots


Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering


Improving Large Language Models in Event Relation Logical Prediction


Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing Constraint


Improving Large Models with Small models: Lower Costs and Better Performance


Improving Lemmatization of Non-Standard Languages with Joint Learning


Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning


Improving Levenberg-Marquardt Algorithm for Neural Networks


Improving Lexically Constrained Neural Machine Translation with Source-Conditioned Masked Span Prediction


Improving Line Search Methods for Large Scale Neural Network Training


Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes


Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-Tuning


Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions


Improving Localization for Semi-Supervised Object Detection


Improving Log-Cumulant Based Estimation of Roughness Information in SAR imagery


Improving Long-Horizon Imitation Through Instruction Prediction


Improving Long-Text Alignment for Text-to-Image Diffusion Models


Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative Learning


Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding


Improving Low-Resource Cross-lingual Parsing with Expected Statistic Regularization


Improving Low-Resource Knowledge Tracing Tasks by Supervised Pre-training and Importance Mechanism Fine-tuning


Improving Low-Resource Retrieval Effectiveness using Zero-Shot Linguistic Similarity Transfer


Improving Lyrics Alignment through Joint Pitch Detection


Improving MATLAB's isprime performance without arbitrary-precision arithmetic


Improving MMD-GAN Training with Repulsive Loss Function


Improving Machine Reading Comprehension with General Reading Strategies


Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model


Improving Machine Translation with Large Language Models: A Preliminary Study with Cooperative Decoding


Improving Malware Detection Accuracy by Extracting Icon Information


Improving Maritime Traffic Emission Estimations on Missing Data with CRBMs


Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation


Improving Matrix-vector Multiplication via Lossless Grammar-Compressed Matrices


Improving Medical Dialogue Generation with Abstract Meaning Representations


Improving Medical Multi-modal Contrastive Learning with Expert Annotations


Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modeling


Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models


Improving Medical Report Generation with Adapter Tuning and Knowledge Enhancement in Vision-Language Foundation Models


Improving Memory Efficiency for Training KANs via Meta Learning


Improving Merge Sort and Quick Sort Performance by Utilizing Alphadev's Sorting Networks as Base Cases


Improving Meta-Learning Generalization with Activation-Based Early-Stopping


Improving Metric Dimensionality Reduction with Distributed Topology


Improving Micro-video Recommendation via Contrastive Multiple Interests


Improving Minimax Group Fairness in Sequential Recommendation


Improving Minimum Bayes Risk Decoding with Multi-Prompt


Improving Misaligned Multi-modality Image Fusion with One-stage Progressive Dense Registration


Improving Mitosis Detection Via UNet-based Adversarial Domain Homogenizer


Improving Model Chain Approaches for Probabilistic Solar Energy Forecasting through Post-processing and Machine Learning