On exploring the potential of quantum auto-encoder for learning quantum systems


On extensions of the Jacobson-Morozov theorem to even characteristic


On families of elliptic curves $E_{p,q}:y^2=x^3-pqx$ that intersect the same line $L_{a,b}:y=\frac{a}{b}x$ of rational slope


On feature selection and evaluation of transportation mode prediction strategies


On fits to correlated and auto-correlated data


On generalization bounds for deep networks based on loss surface implicit regularization


On generative models as the basis for digital twins


On generative models of T-cell receptor sequences


On generic $Δ$-modular integer matrices with two rows


On generic singularities of intersections of ellipsoids: the octahedron


On genetic programming representations and fitness functions for interpretable dimensionality reduction


On genuine invariance learning without weight-tying


On harvesting physical predictions from asymptotically safe quantum field theories


On higher order isolas of unstable Stokes waves


On how Cognitive Computing will plan your next Systematic Review


On identifiability and consistency of the nugget in Gaussian spatial process models


On identifying the non-linear dynamics of a hovercraft using an end-to-end deep learning approach


On incorporating variable consumption functions within energy-efficient parallel machine scheduling


On instabilities of deep learning in image reconstruction - Does AI come at a cost?


On invariable generation of alternating groups by elements of prime and prime power order


On iterative methods based on Sherman-Morrison-Woodbury splitting


On large-scale genre classification in symbolically encoded music by automatic identification of repeating patterns


On learning latent dynamics of the AUG plasma state


On learning with shift-invariant structures


On lens space surgeries from the Poincaré homology sphere


On limitations of uniplex networks for modeling multiplex contagion


On locally factorial Fano fourfolds of Picard number two


On long-duration storage, weather uncertainty and limited foresight


On marginal feature attributions of tree-based models


On matching galaxy number densities to reconstruct galaxy evolutionary tracks


On matrix-model approach to simplified Khovanov-Rozansky calculus


On measuring performances of C-SPARQL and CQELS


On measuring two-party partisan bias in unbalanced states


On minimizers and convolutional filters: theoretical connections and applications to genome analysis


On minimizing the training set fill distance in machine learning regression


On mitigating stability-plasticity dilemma in CLIP-guided image morphing via geodesic distillation loss


On model-based time trend adjustments in platform trials with non-concurrent controls


On models for the estimation of the excess mortality hazard in case of insufficiently stratified life tables


On monochromatic arithmetic progressions in binary words associated with pattern sequences


On morphological and functional complexity of proteinoid microspheres


On multifractals: a non-linear study of actigraphy data


On near-group centers and super-modular categories


On near-redundancy and identifiability of parametric hazard regression models under censoring


On noise in swap ASAP repeater chains: exact analytics, distributions and tight approximations


On numerical realizations of Shannon's sampling theorem


On off-line and on-line Bayesian filtering for uncertainty quantification of structural deterioration


On orthogonal projections for dimension reduction and applications in augmented target loss functions for learning problems


On orthogonality and learning recurrent networks with long term dependencies


On partial information retrieval: the unconstrained 100 prisoner problem


On physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling


On possible proxies of AGN light curves cadence selection in future time domain surveys


On power values of pyramidal numbers, II


On predictive inference for intractable models via approximate Bayesian computation


On projection methods for functional time series forecasting


On propensity score matching with a diverging number of matches


On properties and numerical computation of critical points of eigencurves of bivariate matrix pencils


On property (T) for $\operatorname{Aut}(F_n)$ and $\operatorname{SL}_n(\mathbb{Z})$


On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa


On quartics with the maximal number of the maximal tangency lines


On rapid binary mass transfer -- I. Physical model


On realizing differential-algebraic equations by rational dynamical systems


On rectification and enrichment of infinity properads


On reductive subgroups of reductive groups having invariants in almost all representations


On repetitive right application of B-terms


On resampling schemes for particle filters with weakly informative observations


On rigidity of toric varieties arising from bipartite graphs


On sampling determinantal and Pfaffian point processes on a quantum computer


On schemes evinced by generalized additive decompositions and their regularity


On shallow planning under partial observability


On singular Hilbert schemes of points: local structures and tautological sheaves


On social simulation in 4D relativistic spacetime


On solution of conformal mapping for a lower half plane containing a symmetrical noncircular cavity


On solutions of $\sum_{i=1}^n 1/x_i = 1$ in integers of the form $2^a k^b$


On solving the MAX-SAT using sum of squares


On spectral algorithms for community detection in stochastic blockmodel graphs with vertex covariates


On statistic alignment for domain adaptation in structural health monitoring


On statistical zonostrophic instability and the effect of magnetic fields


On symmetrizing the ultraspherical spectral method for self-adjoint problems


On testing pseudorandom generators via statistical tests based on the arcsine law


On tests of the quantum nature of gravitational interactions in presence of non-linear corrections to quantum mechanics


On the (In)Compatibility between Group Fairness and Individual Fairness


On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem


On the (In)security of Peer-to-Peer Decentralized Machine Learning


On the (linear) convergence of Generalized Newton Inexact ADMM


On the 1-Wasserstein Distance between Location-Scale Distributions and the Effect of Differential Privacy


On the Ability and Limitations of Transformers to Recognize Formal Languages


On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory


On the Addams family of discrete frailty distributions for modelling multivariate case I interval-censored data


On the Adversarial Robustness of Camera-based 3D Object Detection


On the Adversarial Robustness of Causal Algorithmic Recourse


On the Adversarial Robustness of Vision Transformers


On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling


On the Age of Information in Single-Server Queues with Aged Updates


On the Algebraic Properties of Flame Graphs


On the Algorithmic Bias of Aligning Large Language Models with RLHF: Preference Collapse and Matching Regularization


On the Ambiguity of Rank-Based Evaluation of Entity Alignment or Link Prediction Methods


On the Analysis of MUD-Files' Interactions, Conflicts, and Configuration Requirements Before Deployment


On the Applicability of Network Coordinate Systems for Fog Computing


On the Applicability of Synthetic Data for Re-Identification


On the Applicability of Zero-Shot Cross-Lingual Transfer Learning for Sentiment Classification in Distant Language Pairs


On the Application of Bayesian Leave-One-Out Cross-Validation to Exoplanet Atmospheric Analysis


On the Application of Egocentric Computer Vision to Industrial Scenarios


On the Approximation Properties of Random ReLU Features


On the Approximation Theory of Linear Variational Subspace Design


On the Assumptions of Synthetic Control Methods


On the Asymptotic Linear Convergence Speed of Anderson Acceleration Applied to ADMM


On the Asymptotic Mean Square Error Optimality of Diffusion Models


On the Automatic Parameter Selection for Permutation Entropy


On the Automation of High Throughput Modeling of Adsorption In Porous Zeolitic Imidazolate Frameworks


On the Average Runtime of an Open Source Binomial Random Variate Generation Algorithm


On the Baltimore Light RailLink into the quantum future


On the Behaviour of Deviant Communities in Online Social Networks


On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting


On the Benefits of 3D Pose and Tracking for Human Action Recognition


On the Benefits of Active Data Collection in Operator Learning


On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization


On the Benefits of Rank in Attention Layers


On the Benefits of Visual Stabilization for Frame- and Event-based Perception


On the Bias of Directed Information Estimators


On the Black-box Explainability of Object Detection Models for Safe and Trustworthy Industrial Applications


On the Blind Spots of Model-Based Evaluation Metrics for Text Generation


On the Bottleneck of Graph Neural Networks and its Practical Implications


On the Byzantine-Resilience of Distillation-Based Federated Learning


On the Ca-strong 1991bg-like type Ia supernova 2016hnk: evidence for a Chandrasekhar-mass explosion


On the Calibration of Epistemic Uncertainty: Principles, Paradoxes and Conflictual Loss


On the Calibration of Massively Multilingual Language Models


On the Calibration of Multiclass Classification with Rejection


On the Challenges of Fuzzing Techniques via Large Language Models


On the Challenges of Using Black-Box APIs for Toxicity Evaluation in Research


On the Challenges of using Reinforcement Learning in Precision Drug Dosing: Delay and Prolongedness of Action Effects


On the Closed Form Expression of Elementary Symmetric Polynomials and the Inverse of Vandermonde Matrix


On the Comparison of Popular End-to-End Models for Large Scale Speech Recognition


On the Compatibility between Neural Networks and Partial Differential Equations for Physics-informed Learning


On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation


On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation


On the Complementary Nature of Knowledge Graph Embedding, Fine Grain Entity Types, and Language Modeling


On the Complexity of Bayesian Generalization


On the Complexity of Opinions and Online Discussions


On the Complexity of Sequential Incentive Design


On the Compositional Generalization of Multimodal LLMs for Medical Imaging


On the Comprehensibility of Multi-structured Financial Documents using LLMs and Pre-processing Tools


On the Computation of the Efficient Frontier in Advanced Sparse Portfolio Optimization


On the Computational Complexity of Private High-dimensional Model Selection


On the Computational Entanglement of Distant Features in Adversarial Machine Learning


On the Computational Power of Transformers and its Implications in Sequence Modeling


On the Concept Trustworthiness in Concept Bottleneck Models


On the Connection Between Adversarial Robustness and Saliency Map Interpretability


On the Connection between Concept Drift and Uncertainty in Industrial Artificial Intelligence


On the Connection between Local Attention and Dynamic Depth-wise Convolution


On the Consistency of Average Embeddings for Item Recommendation


On the Consistency of Video Large Language Models in Temporal Comprehension


On the Contractivity of Plug-and-Play Operators


On the Convergence Rate of Gaussianization with Random Rotations


On the Convergence Theory for Hessian-Free Bilevel Algorithms


On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning


On the Convergence and Stability of Upside-Down Reinforcement Learning, Goal-Conditioned Supervised Learning, and Online Decision Transformers


On the Convergence of Clustered Federated Learning


On the Convergence of Continuous Constrained Optimization for Structure Learning


On the Convergence of Decentralized Federated Learning Under Imperfect Information Sharing


On the Convergence of FedAvg on Non-IID Data


On the Convergence of Federated Learning Algorithms without Data Similarity


On the Convergence of Hermitian Dynamic Mode Decomposition


On the Convergence of Inexact Gradient Descent with Controlled Synchronization Steps


On the Convergence of Locally Adaptive and Scalable Diffusion-Based Sampling Methods for Deep Bayesian Neural Network Posteriors


On the Convergence of Loss and Uncertainty-based Active Learning Algorithms


On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms


On the Convergence of Tsetlin Machines for the XOR Operator


On the Convergence of the SINDy Algorithm


On the Convergence of the Shapley Value in Parametric Bayesian Learning Games


On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator Loss


On the Correctness and Sample Complexity of Inverse Reinforcement Learning


On the Cost of Demographic Parity in Influence Maximization


On the Coupling of Depth and Egomotion Networks for Self-Supervised Structure from Motion


On the Covariance-Hessian Relation in Evolution Strategies


On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World


On the Critical Role of Conventions in Adaptive Human-AI Collaboration


On the Cross-Dataset Generalization of Machine Learning for Network Intrusion Detection


On the Cross-dataset Generalization in License Plate Recognition


On the Cryptomorphism between Davis' Subset Lattices, Atomic Lattices, and Closure Systems under T1 Separation Axiom


On the Decision Boundary of Deep Neural Networks


On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method


On the Design of Deep Priors for Unsupervised Audio Restoration


On the Design of Multi-Dimensional Compactly Supported Parseval Framelets with Directional Characteristics


On the Design of Privacy-Aware Cameras: a Study on Deep Neural Networks


On the Design of Safe Continual RL Methods for Control of Nonlinear Systems


On the Detection of Adaptive Adversarial Attacks in Speaker Verification Systems


On the Detection of Digital Face Manipulation


On the Detection of Image-Scaling Attacks in Machine Learning


On the Detection of Reviewer-Author Collusion Rings From Paper Bidding


On the Difference of BERT-style and CLIP-style Text Encoders


On the Difficulty of Defending Self-Supervised Learning against Model Extraction


On the Difficulty of Designing Processor Arrays for Deep Neural Networks


On the Difficulty of Membership Inference Attacks


On the Difficulty of Translating Free-Order Case-Marking Languages


On the Diminishing Returns of Width for Continual Learning


On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning


On the Distribution of the Information Density of Gaussian Random Vectors: Explicit Formulas and Tight Approximations


On the Divergence of First Order Resonance Widths at Low Eccentricities


On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm


On the Downstream Performance of Compressed Word Embeddings


On the Dynamic Regret of Following the Regularized Leader: Optimism with History Pruning


On the Dynamics of Training Attention Models


On the Effect of (Near) Duplicate Subwords in Language Modelling


On the Effect of Anticipation on Reading Times


On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference


On the Effect of Dropping Layers of Pre-trained Transformer Models


On the Effect of Instrumentation on Test Flakiness


On the Effect of Low-Frequency Terms on Neural-IR Models


On the Effectiveness of Compact Biomedical Transformers


On the Effectiveness of Distillation in Mitigating Backdoors in Pre-trained Encoder


On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities


On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing


On the Effectiveness of Image Rotation for Open Set Domain Adaptation


On the Effectiveness of Incremental Training of Large Language Models


On the Effectiveness of Iterative Learning Control


On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision Transformers


On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning


On the Effectiveness of Log Representation for Log-based Anomaly Detection


On the Effectiveness of Low-rank Approximations for Collaborative Filtering compared to Neural Networks


On the Effectiveness of Machine Learning-based Call Graph Pruning: An Empirical Study


On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping


On the Effectiveness of Offline RL for Dialogue Response Generation


On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning


On the Effectiveness of Parameter-Efficient Fine-Tuning


On the Effectiveness of Supervision in Asymmetric Non-Contrastive Learning


On the Effectiveness of Unlearning in Session-Based Recommendation


On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing


On the Effects of Artificial Data Modification


On the Effects of Batch and Weight Normalization in Generative Adversarial Networks


On the Effects of Irrelevant Variables in Treatment Effect Estimation with Deep Disentanglement


On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks


On the Effects of Regional Spelling Conventions in Retrieval Models


On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering


On the Effects of Small Graph Perturbations in the MaxCut Problem by QAOA


On the Efficacy and High-Performance Implementation of Quaternion Matrix Multiplication


On the Efficacy of 3D Point Cloud Reinforcement Learning


On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study


On the Efficacy of Differentially Private Few-shot Image Classification


On the Efficacy of Eviction Policy for Key-Value Constrained Generative Language Model Inference


On the Efficiency of Energy Markets with Non-Merchant Storage


On the Efficiency of Privacy Attacks in Federated Learning


On the Element-Wise Representation and Reasoning in Zero-Shot Image Recognition: A Systematic Survey


On the Elementary Symmetric Functions of $\{1,1/2,\dots,1/n\}\backslash\{1/i\}$


On the Embedding Collapse when Scaling up Recommendation Models


On the Emergence of Cross-Task Linearity in the Pretraining-Finetuning Paradigm


On the Emergence of Thinking in LLMs I: Searching for the Right Intuition


On the Emergence of a Power Law in the Distribution of COVID-19 Cases


On the Encoder-Decoder Incompatibility in Variational Text Modeling and Beyond


On the Encoding of Gender in Transformer-based ASR Representations


On the End-to-End Solution to Mandarin-English Code-switching Speech Recognition


On the Energy Footprint of Mobile Testing Frameworks


On the Enumeration and Asymptotic Analysis of Fibonacci Compositions


On the Equivalence between Neural Network and Support Vector Machine


On the Equivalence of Decoupled Graph Convolution Network and Label Propagation


On the Equivalence of Graph Convolution and Mixup


On the Error of Random Sampling: Uniformly Distributed Random Points on Parametric Curves


On the Estimation Bias in Double Q-Learning


On the Estimation of Centre of Mass in Periodic Systems


On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators


On the Estimation of Entropy in the FastICA Algorithm


On the Evaluation Metrics for Paraphrase Generation


On the Evaluation of Answer-Agnostic Paragraph-level Multi-Question Generation


On the Evaluation of Commit Message Generation Models: An Experimental Study


On the Evaluation of Generative Adversarial Networks By Discriminative Models


On the Evaluation of Machine Translation for Terminology Consistency


On the Evaluation of NLP-based Models for Software Engineering


On the Evaluation of Neural Code Summarization


On the Evaluation of Neural Code Translation: Taxonomy and Benchmark


On the Evaluation of Procedural Level Generation Systems


On the Eve of True Explainability for OWL Ontologies: Description Logic Proofs with Evee and Evonne (Extended Version)


On the Evolution of A.I. and Machine Learning: Towards a Meta-level Measuring and Understanding Impact, Influence, and Leadership at Premier A.I. Conferences


On the Existence of Steady-State Solutions to the Equations Governing Fluid Flow in Networks


On the Existence of Universal Lottery Tickets


On the Expected Complexity of Maxout Networks


On the Expected Size of Conformal Prediction Sets


On the Exploitability of Instruction Tuning


On the Exploitation of DCT-Traces in the Generative-AI Domain


On the Expressive Power of Deep Polynomial Neural Networks


On the Expressive Power of Geometric Graph Neural Networks


On the Expressive Power of Overlapping Architectures of Deep Learning


On the Expressive Power of Sparse Geometric MPNNs


On the Expressive Power of Spectral Invariant Graph Neural Networks


On the Expressiveness and Length Generalization of Selective State-Space Models on Regular Languages


On the Expressivity Role of LayerNorm in Transformers' Attention


On the External Validity of Average-Case Analyses of Graph Algorithms


On the FRB luminosity function -- II. Event rate density


On the Fair Comparison of Optimization Algorithms in Different Machines


On the Fairness ROAD: Robust Optimization for Adversarial Debiasing


On the Fairness of Time-Critical Influence Maximization in Social Networks


On the Fast Track: Rapid construction of stellar stream paths


On the Feasibility of Creating Iris Periocular Morphed Images


On the Feasibility of Cross-Language Detection of Malicious Packages in npm and PyPI


On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning


On the Feasibility of Using LLMs to Autonomously Execute Multi-host Network Attacks


On the Feasibility of Vision-Language Models for Time-Series Classification


On the Fly Detection of Root Causes from Observed Data with Application to IT Systems


On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization


On the Formation of Min-weight Codewords of Polar/PAC Codes and Its Applications


On the Four Dimensional Holoraumy of the 4D, $\cal N$ = 1 Complex Linear Supermultiplet


On the Fragility of Active Learners for Text Classification


On the Frobenius number of certain numerical semigroups


On the Galois-invariant part of the Weyl group of the Picard lattice of a K3 surface


On the Generality and Persistence of Cosmological Stasis


On the Generalizability and Predictability of Recommender Systems


On the Generalizability of Deep Learning-based Code Completion Across Programming Language Versions


On the Generalizability of Foundation Models for Crop Type Mapping


On the Generalizability of Iterative Patch Selection for Memory-Efficient High-Resolution Image Classification


On the Generalization Ability of Machine-Generated Text Detectors


On the Generalization Effects of Linear Transformations in Data Augmentation


On the Generalization Properties of Diffusion Models


On the Generalization and Causal Explanation in Self-Supervised Learning


On the Generalization of Agricultural Drought Classification from Climate Data


On the Generalization of DIRECTFN for Singular Integrals Over Quadrilateral Patches


On the Generalization of Multi-modal Contrastive Learning


On the Generalization of Representations in Reinforcement Learning


On the Generalization of Training-based ChatGPT Detection Methods


On the Generalization vs Fidelity Paradox in Knowledge Distillation


On the Generation of a Synthetic Event-Based Vision Dataset for Navigation and Landing


On the Generation, Structure, and Symmetries of Minimal Prime Graphs


On the Generative Utility of Cyclic Conditionals


On the Global Convergence of Particle Swarm Optimization Methods


On the Global Optima of Kernelized Adversarial Representation Learning


On the Global Optimality of Direct Policy Search for Nonsmooth $H_\infty$ Output-Feedback Control


On the Granularity of Explanations in Model Agnostic NLP Interpretability


On the Graovac-Ghorbani index for bicyclic graphs with no pendant vertices


On the Graph Laplacian and the Rankability of Data


On the Hallucination in Simultaneous Machine Translation


On the Hardness of Probabilistic Neurosymbolic Learning


On the Identifiability and Estimation of Causal Location-Scale Noise Models


On the Identifiability of Quantized Factors


On the Impact and Utility of Single-Exomoon Modeling for Multi-Moon Systems


On the Impact of Black-box Deployment Strategies for Edge AI on Latency and Model Performance


On the Impact of Bounded Rationality in Strategic Data Gathering


On the Impact of Communities on Semi-supervised Classification Using Graph Neural Networks


On the Impact of Control Signaling in RIS-Empowered Wireless Communications


On the Impact of Entity Linking in Microblog Real-Time Filtering


On the Impact of Feeding Cost Risk in Aquaculture Valuation and Decision Making


On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training


On the Impact of Multi-dimensional Local Differential Privacy on Fairness


On the Impact of Mutual Coupling on RIS-Assisted Channel Estimation


On the Impact of Noise in Differentially Private Text Rewriting


On the Impact of Noises in Crowd-Sourced Data for Speech Translation


On the Impact of Outlier Bias on User Clicks


On the Impact of Security Vulnerabilities in the npm and RubyGems Dependency Networks


On the Impact of Speech Recognition Errors in Passage Retrieval for Spoken Question Answering


On the Impact of Spurious Correlation for Out-of-distribution Detection


On the Impact of Temporal Concept Drift on Model Explanations


On the Impact of the Capacity Drop Phenomenon for Freeway Traffic Flow Control


On the Impacts of Contexts on Repository-Level Code Generation


On the Implementation of a Reinforcement Learning-based Capacity Sharing Algorithm in O-RAN


On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data


On the Importance and Applicability of Pre-Training for Federated Learning


On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks


On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks


On the Importance of Asymmetry for Siamese Representation Learning


On the Importance of Backbone to the Adversarial Robustness of Object Detectors


On the Importance of Building High-quality Training Datasets for Neural Code Search


On the Importance of Capturing a Sufficient Diversity of Perspective for the Classification of micro-PCBs


On the Importance of Data Size in Probing Fine-tuned Models


On the Importance of Denoising when Learning to Compress Images


On the Importance of Difficulty Calibration in Membership Inference Attacks


On the Importance of Distractors for Few-Shot Classification


On the Importance of Embedding Norms in Self-Supervised Learning


On the Importance of Encrypting Deep Features


On the Importance of Environments in Human-Robot Coordination


On the Importance of Exploration for Real Life Learned Algorithms


On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning


On the Importance of Feature Representation for Flood Mapping using Classical Machine Learning Approaches


On the Importance of Firth Bias Reduction in Few-Shot Classification


On the Importance of Gaussianizing Representations


On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning


On the Importance of PWV in Detecting Precipitation


On the Importance of Regularisation & Auxiliary Information in OOD Detection


On the Importance of Sampling in Training GCNs: Tighter Analysis and Variance Reduction


On the Importance of Sign Labeling: The Hamburg Sign Language Notation System Case Study


On the Importance of Word Boundaries in Character-level Neural Machine Translation


On the Importance of Word and Sentence Representation Learning in Implicit Discourse Relation Classification


On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation


On the Impossibility of Global Convergence in Multi-Loss Optimization


On the Improvement of Generalization and Stability of Forward-Only Learning via Neural Polarization


On the Inclusion of Spatial Information for Spatio-Temporal Neural Networks


On the Incorporation of Obstacles in a Fluid Flow Problem Using a Navier-Stokes-Brinkman Penalization Approach


On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies


On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms


On the Inference Calibration of Neural Machine Translation


On the Influence of Context Size and Model Choice in Retrieval-Augmented Generation Systems


On the Influence of Data Resampling for Deep Learning-Based Log Anomaly Detection: Insights and Recommendations


On the Influence of Reading Sequences on Knowledge Gain during Web Search


On the Information Plane of Autoencoders


On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution Data


On the Initialization of Graph Neural Networks


On the Injectivity Radius of the Stiefel Manifold: Numerical investigations and an explicit construction of a cut point at short distance


On the Inter-relationships among Drift rate, Forgetting rate, Bias/variance profile and Error


On the Interaction between Autonomous Mobility on Demand Systems and Power Distribution Networks -- An Optimal Power Flow Approach


On the Interconnections of Calibration, Quantification, and Classifier Accuracy Prediction under Dataset Shift


On the Interplay Between Exposure Misclassification and Informative Cluster Size


On the Interplay Between Fine-tuning and Composition in Transformers


On the Interplay between TLS Certificates and QUIC Performance


On the Interplay of Convolutional Padding and Adversarial Robustness


On the Interplay of Human-AI Alignment,Fairness, and Performance Trade-offs in Medical Imaging


On the Interpolation of Contextualized Term-based Ranking with BM25 for Query-by-Example Retrieval


On the Interpretability and Significance of Bias Metrics in Texts: a PMI-based Approach


On the Interpretability of Attention Networks


On the Interpretability of Part-Prototype Based Classifiers: A Human Centric Analysis


On the Interpretability of Quantum Neural Networks


On the Intersection of Context-Free and Regular Languages


On the Intersection of Signal Processing and Machine Learning: A Use Case-Driven Analysis Approach


On the Language-specificity of Multilingual BERT and the Impact of Fine-tuning


On the Late-Time Evolution of Velocity-Dependent Self-Interacting Dark Matter Halos


On the Learnability of Watermarks for Language Models


On the Learning Dynamics of Attention Networks


On the Learning and Learnability of Quasimetrics


On the Learning with Augmented Class via Forests


On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples


On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games under Noisy Feedback


On the Limitations of Carbon-Aware Temporal and Spatial Workload Shifting in the Cloud


On the Limitations of Continual Learning for Malware Classification


On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation


On the Limitations of Elo: Real-World Games, are Transitive, not Additive


On the Limitations of Fractal Dimension as a Measure of Generalization


On the Limitations of Physics-informed Deep Learning: Illustrations Using First Order Hyperbolic Conservation Law-based Traffic Flow Models


On the Limitations of Stochastic Pre-processing Defenses


On the Limitations of Temperature Scaling for Distributions with Overlaps


On the Limits of Minimal Pairs in Contrastive Evaluation


On the Limits of Pseudo Ground Truth in Visual Camera Re-localisation


On the Linear Speedup of the Push-Pull Method for Decentralized Optimization over Digraphs


On the Lipschitz Constant of Deep Networks and Double Descent


On the Localization of Ultrasound Image Slices within Point Distribution Models


On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning


On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them


On the Loss of Context-awareness in General Instruction Fine-tuning


On the Masking-Friendly Designs for Post-Quantum Cryptography


On the Matrix Form of the Quaternion Fourier Transform and Quaternion Convolution


On the Maximal Independent Sets of $k$-mers with the Edit Distance


On the Maximal Local Disparity of Fairness-Aware Classifiers


On the Maximal Number of Columns of a $Δ$-modular Integer Matrix: Bounds and Computations


On the Maximum Gonality of a Curve over a Finite Field


On the Mechanics of NFT Valuation: AI Ethics and Social Media


On the Mechanistic Interpretability of Neural Networks for Causality in Bio-statistics


On the Memory Mechanism of Tensor-Power Recurrent Models


On the Metrics and Adaptation Methods for Domain Divergences of sEMG-based Gesture Recognition


On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions


On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data


On the Model Update Strategies for Supervised Learning in AIOps Solutions


On the Multi-View Information Bottleneck Representation


On the Multi-modal Vulnerability of Diffusion Models


On the Multi-turn Instruction Following for Conversational Web Agents


On the Multilingual Ability of Decoder-based Pre-trained Language Models: Finding and Controlling Language-Specific Neurons


On the Multilingual Capabilities of Very Large-Scale English Language Models


On the NP-Hardness Approximation Curve for Max-2Lin(2)


On the Necessity of World Knowledge for Mitigating Missing Labels in Extreme Classification


On the Nielsen-Schreier Theorem in Homotopy Type Theory


On the Noise Robustness of In-Context Learning for Text Generation


On the Noise Sensitivity of the Randomized SVD


On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars


On the Noisy Gradient Descent that Generalizes as SGD


On the Nonsmooth Geometry and Neural Approximation of the Optimal Value Function of Infinite-Horizon Pendulum Swing-up


On the Northcott property of Dedekind zeta functions


On the On-Off Problem: An Objective Bayesian Analysis


On the Optimal Deployment of Power Beacons for Massive Wireless Energy Transfer


On the Optimal Fixed-Price Mechanism in Bilateral Trade


On the Optimal Linear Contraction Order of Tree Tensor Networks, and Beyond


On the Optimality of Averaging in Distributed Statistical Learning


On the Optimisation of the GSACA Suffix Array Construction Algorithm


On the Origin of Llamas: Model Tree Heritage Recovery


On the Out-of-Distribution Generalization of Self-Supervised Learning


On the Outsized Importance of Learning Rates in Local Update Methods


On the Over-Memorization During Natural, Robust and Catastrophic Overfitting


On the Overconfidence Problem in Semantic 3D Mapping


On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective


On the Paradox of Learning to Reason from Data


On the Parameter Identifiability of Partially Observed Linear Causal Models


On the Perception Bottleneck of VLMs for Chart Understanding


On the Performance of Cloud-based ARM SVE for Zero-Knowledge Proving Systems


On the Performance of Hybrid Search Strategies for Systematic Literature Reviews in Software Engineering


On the Perils of Cascading Robust Classifiers


On the Periodic Behavior of Neural Network Training with Batch Normalization and Weight Decay


On the Persistence of Higher-Order Interactions in Real-World Hypergraphs


On the Perturbation Function of Ranking and Balance for Weighted Online Bipartite Matching


On the Perturbative Picture and the Chang-Refsdal Lens Approximation for Planetary Microlensing


On the Perturbed States for Transformed Input-robust Reinforcement Learning


On the Pitfalls of Measuring Emergent Communication


On the Pitfalls of Using the Residual Error as Anomaly Score


On the Possibility of Rewarding Structure Learning Agents: Mutual Information on Linguistic Random Sets


On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries


On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and Beyond


On the Power of Deep but Naive Partial Label Learning


On the Power of Edge Independent Graph Models


On the Power of Gradual Network Alignment Using Dual-Perception Similarities


On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages


On the Prandtl-Kolmogorov 1-equation model of turbulence


On the Predictability of Utilizing Rank Percentile to Evaluate Scientific Impact


On the Prediction Instability of Graph Neural Networks


On the Predictive Accuracy of Neural Temporal Point Process Models for Continuous-time Event Data


On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior


On the Preprocessing of Physics-informed Neural Networks: How to Better Utilize Data in Fluid Mechanics


On the Prevalence and Usage of Commit Signing on GitHub: A Longitudinal and Cross-Domain Study


On the Price of Differential Privacy for Hierarchical Clustering


On the Principles of Differentiable Quantum Programming Languages


On the Privacy Effect of Data Enhancement via the Lens of Memorization


On the Privacy Risks of Algorithmic Recourse


On the Privacy Risks of Cell-Based NAS Architectures


On the Privacy of Selection Mechanisms with Gaussian Noise


On the Probability of Necessity and Sufficiency of Explaining Graph Neural Networks: A Lower Bound Optimization Approach


On the Problem of Underranking in Group-Fair Ranking


On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs


On the Proper Treatment of Tokenization in Psycholinguistics


On the Quadratic Convergence of the Cubic Regularization Method under a Local Error Bound Condition


On the Quantum Chromatic Numbers of Small Graphs


On the RTL Implementation of FINN Matrix Vector Compute Unit


On the Ramifications of Human Label Uncertainty


On the Rate of Error Growth in Time for Numerical Solutions of Nonlinear Dispersive Wave Equations


On the Readability of Abstract Set Visualizations


On the Reconstruction Risk of Convolutional Sparse Dictionary Learning


On the Regularity, Planarity and Edge Bounds of Link-irregular Graphs


On the Relation Between Mobile Encounters and Web Traffic Patterns: A Data-driven Study


On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length


On the Relation between Sensitivity and Accuracy in In-context Learning


On the Relation between Syntactic Divergence and Zero-Shot Performance


On the Relationship Between Ground- and Satellite- Based Global Horizontal Irradiance


On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth


On the Relationship Between Relevance and Conflict in Online Social Link Recommendations


On the Relationship Between Variational Inference and Auto-Associative Memory


On the Relationship Between the Value Function and the Efficient Frontier of a Mixed Integer Linear Optimization Problem


On the Relationship between Data Efficiency and Error for Uncertainty Sampling


On the Relationship between Explanation and Recommendation: Learning to Rank Explanations for Improved Performance


On the Relationship between Self-Attention and Convolutional Layers


On the Relationship between Sentence Analogy Identification and Sentence Structure Encoding in Large Language Models


On the Relationship between Skill Neurons and Robustness in Prompt Tuning


On the Relationship between Truth and Political Bias in Language Models


On the Relevance of Cross-project Learning with Nearest Neighbours for Commit Message Generation


On the Relevance of Temporal Features for Medical Ultrasound Video Recognition


On the Reliability of Large Language Models to Misinformed and Demographically-Informed Prompts


On the Reliability of Multiple Systems Estimation for the Quantification of Modern Slavery


On the Representational Capacity of Recurrent Neural Language Models


On the Reproducibility of Learned Sparse Retrieval Adaptations for Long Documents


On the Resilience of Biometric Authentication Systems against Random Inputs


On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents


On the Reuse Bias in Off-Policy Reinforcement Learning


On the Risk of Misinformation Pollution with Large Language Models


On the Risks of Collecting Multidimensional Data Under Local Differential Privacy


On the Road to Online Adaptation for Semantic Image Segmentation


On the Road to Portability: Compressing End-to-End Motion Planner for Autonomous Driving


On the Road with 16 Neurons: Mental Imagery with Bio-inspired Deep Neural Networks


On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving


On the Robustness of Adversarial Training Against Uncertainty Attacks


On the Robustness of Bayesian Neural Networks to Adversarial Attacks


On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot


On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations


On the Robustness of Decision-Focused Learning


On the Robustness of Deep Learning-predicted Contention Models for Network Calculus


On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based Method


On the Robustness of Distributed Machine Learning against Transfer Attacks


On the Robustness of Document-Level Relation Extraction Models to Entity Name Variations


On the Robustness of Editing Large Language Models


On the Robustness of Fully-Spiking Neural Networks in Open-World Scenarios using Forward-Only Learning Algorithms


On the Robustness of GUI Grounding Models Against Image Attacks


On the Robustness of Generative Information Retrieval Models


On the Robustness of Global Feature Effect Explanations


On the Robustness of Graph Neural Diffusion to Topology Perturbations


On the Robustness of Intent Classification and Slot Labeling in Goal-oriented Dialog Systems to Real-world Noise


On the Robustness of Kernel Goodness-of-Fit Tests


On the Robustness of Language Encoders against Grammatical Errors


On the Robustness of Latent Diffusion Models


On the Robustness of Medical Vision-Language Models: Are they Truly Generalizable?


On the Robustness of Neural Collapse and the Neural Collapse of Robustness


On the Robustness of Object Detection Models on Aerial Images


On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion


On the Robustness of Quality Measures for GANs


On the Robustness of Question Rewriting Systems to Questions of Varying Hardness


On the Robustness of Random Forest Against Untargeted Data Poisoning: An Ensemble-Based Approach


On the Robustness of Randomized Ensembles to Adversarial Perturbations


On the Robustness of Reading Comprehension Models to Entity Renaming


On the Robustness of Safe Reinforcement Learning under Observational Perturbations


On the Robustness of Semantic Segmentation Models to Adversarial Attacks


On the Robustness of Topics API to a Re-Identification Attack


On the Robustness of Vision Transformers to Adversarial Examples


On the Robustness of the Successive Projection Algorithm


On the Role of Attention Heads in Large Language Model Safety


On the Role of Collective Sensing and Evolution in Group Formation


On the Role of Conceptualization in Commonsense Knowledge Graph Construction


On the Role of Context in Reading Time Prediction


On the Role of Discrete Tokenization in Visual Representation Learning


On the Role of Entropy-based Loss for Learning Causal Structures with Continuous Optimization


On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks


On the Role of Images for Analyzing Claims in Social Media


On the Role of Label Noise in the Feature Learning Process


On the Role of Negative Precedent in Legal Outcome Prediction


On the Role of Neural Collapse in Meta Learning Models for Few-shot Learning


On the Role of Pre-trained Language Models in Word Ordering: A Case Study with BART


On the Role of Priors in Bayesian Causal Learning


On the Role of Reviewer Expertise in Temporal Review Helpfulness Prediction


On the Role of Sparsity and DAG Constraints for Learning Linear DAGs


On the Role of Summary Content Units in Text Summarization Evaluation


On the Role of Surrogates in Conformal Inference of Individual Causal Effects


On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis


On the Role of Visual Context in Enriching Music Representations


On the Rényi-Ulam Game with Restricted Size Queries


On the SDEs and Scaling Rules for Adaptive Gradient Algorithms


On the Safety of Connected Cruise Control: Analysis and Synthesis with Control Barrier Functions


On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark


On the Salient Limitations of the Methods of Assembly Theory and their Classification of Molecular Biosignatures


On the Sample Complexity of Representation Learning in Multi-task Bandits with Global and Local structure


On the Second-order Convergence Properties of Random Search Methods


On the Secrecy Rate under Statistical QoS Provisioning for RIS-Assisted MISO Wiretap Channel


On the Security Risks of Knowledge Graph Reasoning


On the Semantic Expressiveness of Iso- and Equi-Recursive Types


On the Semantic Overlap of Operators in Stream Processing Engines


On the Semi-Blind Mutually Referenced Equalizers for MIMO Systems


On the Sensitivity and Stability of Model Interpretations in NLP


On the Sentence Embeddings from Pre-trained Language Models


On the Similarities of Embeddings in Contrastive Learning


On the Similarity of Circuits across Languages: a Case Study on the Subject-verb Agreement Task


On the Spectrum of Random Features Maps of High Dimensional Data


On the Spontaneous Emergence of Discrete and Compositional Signals


On the Square Peg Problem and Its Relatives


On the Stability Region of Intermittent Interference Networks


On the Stability of Expressive Positional Encodings for Graphs


On the Stability of Fermionic Non-Isothermal Dark Matter Halos


On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines


On the Stability of General Bayesian Inference


On the Stability of Iterative Retraining of Generative Models on their own Data


On the Stability of a non-hyperbolic nonlinear map with non-bounded set of non-isolated fixed points with applications to Machine Learning


On the Standard Performance Criteria for Applied Control Design: PID, MPC or Machine Learning Controller?


On the State of Social Media Data for Mental Health Research


On the State of the Art in Authorship Attribution and Authorship Verification


On the Statistical Capacity of Deep Generative Models


On the Statistical Relation of Ultra-Reliable Wireless and Location Estimation


On the Steady-State Distributionally Robust Kalman Filter


On the Stepwise Nature of Self-Supervised Learning


On the Strategyproofness of the Geometric Median


On the Strong Convexity of PnP Regularization Using Linear Denoisers


On the Structural Properties of Social Networks and their Measurement-calibrated Synthetic Counterparts


On the Structure of Bad Science Matrices


On the Structure of Game Provenance and its Applications


On the Structures of Representation for the Robustness of Semantic Segmentation to Input Corruption


On the Suboptimality of Thompson Sampling in High Dimensions


On the Suitability of Neural Networks as Building Blocks for The Design of Efficient Learned Indexes


On the Surprising Effectiveness of Attention Transfer for Vision Transformers


On the Surprising Effectiveness of Spectrum Clipping in Learning Stable Linear Dynamics


On the Surprising Efficacy of Distillation as an Alternative to Pre-Training Small Models


On the Surrogate Gap between Contrastive and Supervised Losses


On the Susceptibility of QDI Circuits to Transient Faults


On the Texture Bias for Few-Shot CNN Segmentation


On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers


On the Theoretical Guarantees for Parameter Estimation of Gaussian Random Field Models: A Sparse Precision Matrix Approach


On the Theories Behind Hard Negative Sampling for Recommendation


On the Tool Manipulation Capability of Open-source Large Language Models


On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics


On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks


On the Trade-off between Redundancy and Local Coherence in Summarization


On the Tradeoff between Privacy Preservation and Byzantine-Robustness in Decentralized Learning


On the Transferability of Learning Models for Semantic Segmentation for Remote Sensing Data


On the Transferability of Pre-trained Language Models: A Study from Artificial Datasets


On the Transferability of Visual Features in Generalized Zero-Shot Learning


On the Ubiquity Of Electromagnetic-Duality Rotations in 4D, N = 1 Holoraumy Tensors for On-Shell 4D Supermultiplets


On the Unbounded External Archive and Population Size in Preference-based Evolutionary Multi-objective Optimization Using a Reference Point


On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection


On the Universal Transformation of Data-Driven Models to Control Systems


On the Universal Truthfulness Hyperplane Inside LLMs


On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix


On the Universality of the Double Descent Peak in Ridgeless Regression


On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features


On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation


On the Usability of Next-Generation Authentication: A Study on Eye Movement and Brainwave-based Mechanisms


On the Use of Audio to Improve Dialogue Policies


On the Use of BERT for Automated Essay Scoring: Joint Learning of Multi-Scale Essay Representation


On the Use of Deep Learning Models for Semantic Clone Detection


On the Use of Emojis to Train Emotion Classifiers


On the Use of External Data for Spoken Named Entity Recognition


On the Use of Fine-grained Vulnerable Code Statements for Software Vulnerability Assessment Models


On the Use of Geometric Deep Learning for the Iterative Classification and Down-Selection of Analog Electric Circuits


On the Use of Information Criteria for Subset Selection in Least Squares Regression


On the Use of Large Language Models to Generate Capability Ontologies


On the Use of Random Forest for Two-Sample Testing


On the Use of Sparse Filtering for Covariate Shift Adaptation


On the Use of Two-Way Fixed Effects Models for Policy Evaluation During Pandemics


On the Use of WGANs for Super-Resolution in Dark-Matter Simulations


On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution Detection


On the Usefulness of Embeddings, Clusters and Strings for Text Generator Evaluation


On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers


On the User Behavior Leakage from Recommender System Exposure


On the Utility of 3D Hand Poses for Action Recognition


On the Utility of Equal Batch Sizes for Inference in Stochastic Gradient Descent


On the Utility of Gradient Compression in Distributed Training Systems


On the Utility of Self-supervised Models for Prosody-related Tasks


On the Utility of Speech and Audio Foundation Models for Marmoset Call Analysis


On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes


On the Value of Cross-Modal Misalignment in Multimodal Representation Learning


On the Value of Oversampling for Deep Learning in Software Defect Prediction


On the Value of Wikipedia as a Gateway to the Web


On the Vector Space in Photoplethysmography Imaging


On the Veracity of Local, Model-agnostic Explanations in Audio Classification: Targeted Investigations with Adversarial Examples


On the Viability of Monocular Depth Pre-training for Semantic Segmentation


On the Virasoro fusion and modular kernels at any irrational central charge


On the Voronoi Implicit Interface Method


On the Vulnerability of Backdoor Defenses for Federated Learning


On the Vulnerability of Concept Erasure in Diffusion Models


On the Vulnerability of Text Sanitization


On the Wasserstein Convergence and Straightness of Rectified Flow


On the Weaknesses of Backdoor-based Model Watermarking: An Information-theoretic Perspective


On the Within-Group Fairness of Screening Classifiers


On the accuracy and precision of correlation functions and field-level inference in cosmology


On the accuracy of dark matter halo merger trees and the consequences for semi-analytic models of galaxy formation


On the accuracy of posterior recovery with neural network emulators


On the accurate computation of expected modularity in probabilistic networks


On the achievability of blind source separation for high-dimensional nonlinear source mixtures


On the achievability of efficiency bounds for covariate-adjusted response-adaptive randomization


On the acyclicity of reductions of elliptic curves modulo primes in arithmetic progressions


On the additive image of 0th persistent homology


On the adoption, usage and evolution of Kotlin Features on Android development


On the age distribution of Classical Cepheids in the Galaxy


On the algorithmic construction of deep ReLU networks


On the application of Gaussian graphical models to paired data problems


On the application of Visibility Graphs in the Spectral Domain for Speaker Recognition


On the approximation capability of GNNs in node classification/regression tasks


On the arithmetic and geometry of spaces $L_{m+1,n}$


On the arithmetic of generalized Fekete polynomials


On the arithmetic of multidimensional continued fractions


On the asymptotics of extremal lp-blocks cluster inference


On the asymptotics of the meromorphic 3D-index


On the behavior of Lagrange multipliers in convex and non-convex infeasible interior point methods


On the benchmarking of partitioned real-time systems


On the big quantum cohomology of coadjoint varieties


On the biological plausibility of orthogonal initialisation for solving gradient instability in deep neural networks


On the calibration of compartmental epidemiological models


On the calibration of neural networks for histological slide-level classification


On the calibration of powerset speaker diarization models


On the challenges of detecting MCI using EEG in the wild


On the challenges of learning with inference networks on sparse, high-dimensional data


On the challenges of studying bias in Recommender Systems: A UserKNN case study


On the choice of the low-dimensional domain for global optimization via random embeddings


On the classification of Kahler-Ricci solitons on Gorenstein del Pezzo surfaces


On the cohomology groups of real Lagrangians in Calabi-Yau threefolds


On the combined effect of class imbalance and concept complexity in deep learning


On the complexity and modeling of the electric vehicle sharing problem


On the complexity of meander-like diagrams of knots


On the complexity of the inverse Sturm-Liouville problem


On the computation of Gaussian quadrature rules for Chebyshev sets of linearly independent functions


On the computation of counterfactual explanations -- A survey


On the computation of tensor functions under tensor-tensor multiplications with linear maps


On the computation of the cosine measure in high dimensions


On the computation of the cumulative distribution function of the Normal Inverse Gaussian distribution


On the condition number of the shifted real Ginibre ensemble


On the consistency of hyper-parameter selection in value-based deep reinforcement learning


On the constant terms of certain meromorphic modular forms for Hecke groups


On the constants in Mertens' theorems for primes in arithmetic progressions


On the continuity of Weil-Petersson volumes of the moduli space weighted points on the projective line


On the creation of narrow AI: hierarchy and nonlocality of neural network skills


On the cross-validation bias due to unsupervised pre-processing


On the curvatures of Gaussian random field manifolds


On the decisional Diffie-Hellman problem for class group actions on oriented elliptic curves


On the decomposability of mod 2 cohomological invariants of Weyl groups


On the degeneracies between baryons, massive neutrinos and f(R) gravity in Stage IV cosmic shear analyses


On the descriptive power of LiDAR intensity images for segment-based loop closing in 3-D SLAM


On the design of convolutional neural networks for automatic detection of Alzheimer's disease


On the design of scalable, high-precision spherical-radial Fourier features


On the design-dependent suboptimality of the Lasso


On the detectability and parameterisation of binary stars through spectral energy distributions


On the detectability of transiting planets orbiting white dwarfs using LSST


On the detection of Out-Of-Distribution samples in Multiple Instance Learning


On the detection of synthetic images generated by diffusion models


On the deterministic-shift extended CIR model in a negative interest rate framework


On the development of a practical Bayesian optimisation algorithm for expensive experiments and simulations with changing environmental conditions


On the different regimes of Stochastic Gradient Descent


On the difficulty of learning chaotic dynamics with RNNs


On the discovery of stars, quasars, and galaxies in the Southern Hemisphere with S-PLUS DR2


On the dynamical stability of copper-doped lead apatite


On the dynamics of mortality and the ephemeral nature of mammalian megafauna


On the economics of knowledge creation and sharing


On the effect of normalization layers on Differentially Private training of deep Neural networks


On the effect of the average clustering coefficient on topology-based link prediction in featureless graphs


On the effective transfer of knowledge from English to Hindi Wikipedia


On the effectiveness of Large Language Models in the mechanical design domain


On the effectiveness of adversarial training against common corruptions


On the effectiveness of partial variance reduction in federated learning with heterogeneous data


On the effectiveness of persistent homology


On the eigenmodes of periodic orbits for multiple scattering problems in 2D


On the eigenvalues of Grassmann graphs, Bilinear forms graphs and Hermitian forms graphs


On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks


On the emergence of numerical instabilities in Next Generation Reservoir Computing


On the entropy projection and the robustness of high order entropy stable discontinuous Galerkin schemes for under-resolved flows


On the enumeration of finite $L$-algebras


On the equivalence between graph isomorphism testing and function approximation with GNNs


On the equivalence of Prony and Lanczos methods for Euclidean correlation functions


On the equivalence of direct and indirect data-driven predictive control approaches


On the error control of invariant causal prediction


On the error term in the explicit formula of Riemann-von Mangoldt II


On the estimation of the number of components in multivariate functional principal component analysis


On the estimation of variance parameters in non-standard generalised linear mixed models: Application to penalised smoothing


On the evidence for a common-spectrum process in the search for the nanohertz gravitational-wave background with the Parkes Pulsar Timing Array


On the exact computation of linear frequency principle dynamics and its generalization


On the existence of Monge maps for the Gromov-Wasserstein problem


On the existence of Parseval frames for vector bundles


On the extraction of spectral densities from lattice correlators


On the failure of variational score matching for VAE models


On the finiteness of $k$-vertex-critical $2P_2$-free graphs with forbidden induced squids or bulls


On the frame set of the second-order $B$-spline


On the fundamentality of the radial acceleration relation for late-type galaxy dynamics


On the generalizability of machine-learning-assisted anisotropy mappings for predictive turbulence modelling


On the generation of periodic discrete structures with identical two-point correlation


On the generation of rank 3 simple matroids with an application to Terao's freeness conjecture


On the geometric fixed points of the real topological cyclic homology of $\mathbb{Z}/4$


On the geometry of the Humbert surface of square discriminant


On the good reliability of an interval-based metric to validate prediction uncertainty for machine learning regression tasks


On the graph of the dimension function of the Lagrange and Markov spectra


On the handling of method failure in comparison studies


On the hidden treasure of dialog in video question answering


On the homogeneity of SnIa absolute magnitude in the Pantheon+ sample


On the human-recognizability phenomenon of adversarially trained deep image classifiers


On the identifiability of Bayesian factor analytic models


On the impact of Performance Antipatterns in multi-objective software model refactoring optimization


On the impact of VR assessment on the Quality of Experience of Highly Realistic Digital Humans


On the impact of activation and normalization in obtaining isometric embeddings at initialization


On the impact of outliers in loss reserving


On the impact of predicate complexity in crowdsourced classification tasks


On the importance of 3D stress state in 2D earthquake rupture simulations with off-fault deformation


On the importance of cross-task features for class-incremental learning


On the importance of learning non-local dynamics for stable data-driven climate modeling: A 1D gravity wave-QBO testbed


On the importance of local and global feature learning for automated measurable residual disease detection in flow cytometry data


On the importance of stationarity, strong baselines and benchmarks in transport prediction problems


On the importance of structural identifiability for machine learning with partially observed dynamical systems


On the inadequacy of nominal assortativity for assessing homophily in networks


On the increase in the concentration of primordial black holes in the halos of dwarf galaxies


On the inexact scaled gradient projection method


On the influence of dependent features in classification problems: a game-theoretic perspective


On the influence of over-parameterization in manifold based surrogates and deep neural operators


On the instrumental variable estimation with many weak and invalid instruments


On the integration of Dantzig-Wolfe and Fenchel decompositions via directional normalizations


On the interaction between supervision and self-play in emergent communication


On the interaction of automatic evaluation and task framing in headline style transfer


On the interplay between data structure and loss function in classification problems


On the interpretability and computational reliability of frequency-domain Granger causality


On the interpretation of linear Riemannian tangent space model parameters in M/EEG


On the intersection of local Arthur packets for classical groups and applications


On the inverse Potts functional for single-image super-resolution problems


On the invertibility of a voice privacy system using embedding alignement


On the learning abilities of photonic continuous-variable Born machines


On the limits of agency in agent-based models


On the limits of neural network explainability via descrambling


On the limits of some Bayesian model evaluation statistics


On the linear scaling of entropy vs. energy in human brain activity, the Hagedorn temperature and the Zipf law


On the local homology of Artin groups of finite and affine type


On the local metric property in multivariate extremes


On the local-global principle for isogenies of abelian surfaces


On the locality of local neural operator in learning fluid dynamics


On the logical skills of large language models: evaluations using arbitrarily complex first-order logic problems


On the logistical difficulties and findings of Jopara Sentiment Analysis


On the long-term evolution of razor-thin galactic discs: Balescu-Lenard prediction and perspectives


On the maximum spectral radius of connected graphs with a prescribed order and size


On the minimal modules for exceptional Lie algebras: Jordan blocks and stabilisers


On the mixed-model analysis of covariance in cluster-randomized trials


On the model-based stochastic value gradient for continuous reinforcement learning


On the modularity of elliptic curves over imaginary quadratic fields


On the motion of hairpin filaments in the atmospheric boundary layer


On the multipliers at fixed points of self-maps of the projective plane


On the need to move from a single indicator to a multi-dimensional framework to measure accessibility to urban green


On the non-existence of sympathetic Lie algebras with dimension less than 25


On the non-frame property of Gabor systems with Hermite generators and the frame set conjecture


On the non-global linear stability and spurious fixed points of MPRK schemes with negative RK parameters


On the normalized signal to noise ratio in covariance estimation


On the notion of number in humans and machines


On the number of $k$-mers admitting a given lexicographical minimizer


On the number of small Steiner triple systems with Veblen points


On the number of subproblem iterations per coupling step in partitioned fluid-structure interaction simulations


On the numerical Terao's conjecture and Ziegler pairs for line arrangements


On the numerical evaluation of wall shear stress using the finite element method


On the numerical reliability of nonsmooth autodiff: a MaxPool case study


On the numerical stability of sketched GMRES


On the occupancy fraction of the antiferromagnetic Ising model


On the optimal choice of the illumination function in photoacoustic tomography


On the optimal objective value of random linear programs


On the optimal prediction of extreme events in heavy-tailed time series with applications to solar flare forecasting


On the optimal stopping of Gauss-Markov bridges with random pinning points


On the optimization and pruning for Bayesian deep learning


On the origin of the Hercules group: II. the Trojan quasi-periodic identity on the orbital level


On the orthogonal Grünbaum partition problem in dimension three


On the peak height distribution of non-stationary Gaussian random fields: 1D general covariance and scale space


On the performance of deep learning models for time series classification in streaming


On the performance of machine-learning-assisted Monte Carlo in sampling from simple statistical physics models


On the periodicity of cardiovascular fluid dynamics simulations


On the possibility of engineering social evolution in microfluidic environments


On the potential of BFAST for monitoring burned areas using multi-temporal Landsat-7 images


On the power of conditional independence testing under model-X


On the power of data augmentation for head pose estimation


On the predictability of infectious disease outbreaks


On the progressive hardening of the cosmic-ray proton spectrum in the inner Galaxy


On the quadrature exactness in hyperinterpolation


On the radial distribution of giant exoplanets at Solar System scales


On the randomized Horn problem and the surface tension of hives


On the realistic validation of photometric redshifts, or why Teddy will never be Happy


On the recursive structure of multigrid cycles


On the relationship between a Gamma distributed precision parameter and the associated standard deviation in the context of Bayesian parameter inference


On the relationship between calibrated predictors and unbiased volume estimation


On the relationship between data-enabled predictive control and subspace predictive control


On the reliability of feature attribution methods for speech classification


On the representation and learning of monotone triangular transport maps


On the representation and methodology for wide and short range head pose estimation


On the reproducibility of fully convolutional neural networks for modeling time-space evolving physical systems


On the reusability of samples in active learning


On the rise of fear speech in online social media


On the risk levels of distributionally robust chance constrained problems


On the robustness of high-order upwind summation-by-parts methods for nonlinear conservation laws


On the robustness of the in vivo cyanobacterial circadian clock


On the role of clustering in Personalized PageRank estimation


On the role of feedback in visual processing: a predictive coding perspective


On the role of resonances in polluting white dwarfs by asteroids


On the role of surrogates in the efficient estimation of treatment effects with limited outcome data


On the seeds and the great-grandchildren of a numerical semigroup


On the sensitivity of different ensemble filters to the type of assimilated observation networks


On the sensitivity of pose estimation neural networks: rotation parameterizations, Lipschitz constants, and provable bounds


On the single classical field description of interacting scalar fields


On the size of integer programs with bounded non-vanishing subdeterminants


On the smoothness of nonlinear system identification


On the spin period distribution of millisecond pulsars


On the stability analysis of deep neural network representations of an optimal state-feedback


On the stability analysis of perfectly matched layer for the elastic wave equation in layered media


On the stability of IMEX BDF methods for DDEs and PDDEs


On the stability of gradient descent with second order dynamics for time-varying cost functions


On the stability of isothermal shocks in black hole accretion disks


On the stability of planetary orbits in binary star systems I. The S-type orbits


On the stability of robust dynamical low-rank approximations for hyperbolic problems


On the stability of the infinite Projected Entangled Pair Operator ansatz for driven-dissipative 2D lattices


On the stochastic Magnus expansion and its application to SPDEs


On the sum of fifth powers in arithmetic progression


On the sum of fourth powers in arithmetic progression


On the symmetries in the dynamics of wide two-layer neural networks


On the synchronization of coupled random walks and applications to social systems


On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?


On the thermodynamics-based equilibrium beach profile derived by Jenkins and Inman


On the time complexity analysis of numerical percolation threshold estimation


On the topology of the space of coordination geometries


On the total curvature of minimizing geodesics on convex surfaces


On the transmission of texts: written cultures as complex systems


On the treatment of boundary conditions for bond-based peridynamic models


On the uncertainty of self-supervised monocular depth estimation


On the unification of the graph edit distance and graph matching problems


On the use of Benford's law to detect GAN-generated images


On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation


On the use of Deep Generative Models for Perfect Prognosis Climate Downscaling


On the use of Graphs for Satellite Image Time Series


On the use of Large Language Models in Model-Driven Engineering


On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging


On the use of SRIM for calculating arc-dpa exposure


On the use of Silver Standard Data for Zero-shot Classification Tasks in Information Extraction


On the use of Vision-Language models for Visual Sentiment Analysis: a study on CLIP


On the use of automatically generated synthetic image datasets for benchmarking face recognition


On the use of charged-track information to subtract neutral pileup


On the use of cross-validation for the calibration of the adaptive lasso


On the use of deep learning for phase recovery


On the use of neurosymbolic AI for defending against cyber attacks


On the use of test smells for prediction of flaky tests


On the use of the Gram matrix for multivariate functional principal components analysis


On the use of variability time-scales as an early classifier of radio transients and variables


On the virialization threshold for halo mass functions


On uncertainty estimation in active learning for image segmentation


On unified framework for continuous-time grey models: an integral matching perspective


On unified framework for nonlinear grey system models: an integro-differential equation perspective


On using AI for EEG-based BCI applications: problems, current challenges and future trends


On using SMT-solvers for Modeling and Verifying Dynamic Network Emulators


On using distributed representations of source code for the detection of C security vulnerabilities


On verifiable quantum advantage with peaked circuit sampling


On vertex-girth-regular graphs: (Non-)existence, bounds and enumeration


On volume density and star formation in nearby molecular clouds


On w-Optimization of the Split Covariance Intersection Filter


On weight and variance uncertainty in neural networks for regression tasks


On zero-shot learning in neural state estimation of power distribution systems


On zero-shot recognition of generic objects


On-Chip Laser Power Delivery System for Dielectric Laser Accelerators


On-Chip Verified Quantum Computation with an Ion-Trap Quantum Processing Unit


On-Demand Learning for Deep Image Restoration


On-Demand Sampling: Learning Optimally from Multiple Distributions


On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpedia


On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists


On-Device LLM for Context-Aware Wi-Fi Roaming


On-Device Language Models: A Comprehensive Review


On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation


On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification


On-chip microwave coherent source with in-situ control of the photon number distribution


On-deck seismology: Lessons from InSight for future planetary seismology


On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective


On-device Streaming Discrete Speech Units


On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices


On-orbit model training for satellite imagery with label proportions


On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention


On-the-Fly SfM: What you capture is What you get


On-the-Fly Simulation of Two-Dimensional Fluorescence-Excitation Spectra


On-the-Fly Test-time Adaptation for Medical Image Segmentation


On-the-Fly, Sample-Tailored Optimisation of NMR Experiments


On-the-fly Autonomous Control of Neutron Diffraction via Physics-Informed Bayesian Active Learning


On-the-fly Denoising for Data Augmentation in Natural Language Understanding


On-the-fly Improving Performance of Deep Code Models via Input Denoising


On-the-fly Preference Alignment via Principle-Guided Decoding


On-the-fly Segmentation Approaches for X-ray Diffraction Datasets for Metallic Glasses


On-the-fly Surrogation for Complex Nonlinear Dynamics


On-the-fly Unfolding with Optimal Exploration for Linear Temporal Logic Model Checking of Concurrent Software and Systems


OnSET: Ontology and Semantic Exploration Toolkit


Onboard Ranging-based Relative Localization and Stability for Lightweight Aerial Swarms


Onboard View Planning of a Flying Camera for High Fidelity 3D Reconstruction of a Moving Actor


Onboard dynamic-object detection and tracking for autonomous robot navigation with RGB-D camera


Once Quantization-Aware Training: High Performance Extremely Low-bit Architecture Search


Once Upon a $\textit{Time}$ in $\textit{Graph}$: Relative-Time Pretraining for Complex Temporal Reasoning


Once bitten, twice shy: A modeling framework for incorporating heterogeneous mosquito biting into transmission models


Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer Compression


Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling


Once is Never Enough: Foundations for Sound Statistical Inference in Tor Network Experimentation


Once more Diarization: Improving meeting transcription systems through segment-level speaker reassignment


Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free


Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaption


Onception: Active Learning with Expert Advice for Real World Machine Translation


OncoEnrichR: cancer-dedicated gene set interpretation


OncoNetExplainer: Explainable Predictions of Cancer Types Based on Gene Expression Data


One Adapter for All Programming Languages? Adapter Tuning for Code Search and Summarization


One After Another: Learning Incremental Skills for a Changing World


One Agent To Rule Them All: Towards Multi-agent Conversational AI


One Billion Audio Sounds from GPU-enabled Modular Synthesis


One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles


One Deep Music Representation to Rule Them All? : A comparative analysis of different representation learning strategies


One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation


One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques


One Explanation is Not Enough: Structured Attention Graphs for Image Classification


One Explanation to Rule them All -- Ensemble Consistent Explanations


One Eye is All You Need: Lightweight Ensembles for Gaze Estimation with Single Encoders


One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes


One For All & All For One: Bypassing Hyperparameter Tuning with Model Averaging For Cross-Lingual Transfer


One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment


One Glitch to Rule Them All: Fault Injection Attacks Against AMD's Secure Encrypted Virtualization


One Homography is All You Need: IMM-based Joint Homography and Multiple Object State Estimation


One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing Framework


One Language, Many Gaps: Evaluating Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks


One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples


One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks


One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions


One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs


One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusion


One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NER


One Model is All You Need: ByT5-Sanskrit, a Unified Model for Sanskrit NLP Tasks


One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification


One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations


One Model to Rig Them All: Diverse Skeleton Rigging with UniRig


One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction


One Model, Any Conjunctive Query: Graph Neural Networks for Answering Complex Queries over Knowledge Graphs


One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech


One Net to Rule Them All: Domain Randomization in Quadcopter Racing Across Different Platforms


One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Network


One Network, Many Masks: Towards More Parameter-Efficient Transfer Learning


One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic Networks


One Node One Model: Featuring the Missing-Half for Graph Clustering


One Ontology to Rule Them All: Corner Case Scenarios for Autonomous Driving


One Person, One Model--Learning Compound Router for Sequential Recommendation


One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models


One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion


One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement


One Prompt To Rule Them All: LLMs for Opinion Summary Evaluation


One Prototype Is Enough: Single-Prototype Activation for Interpretable Image Classification


One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search


One Quantizer is Enough: Toward a Lightweight Audio Codec


One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval


One Reference Is Not Enough: Diverse Distillation with Reference Selection for Non-Autoregressive Translation


One Representation per Word - Does it make Sense for Composition?


One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction


One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning


One STEP at a time: Language Agents are Stepwise Planners


One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently


One Self-Configurable Model to Solve Many Abstract Visual Reasoning Problems


One Shot Learning for Deformable Medical Image Registration and Periodic Motion Tracking


One Shot is Enough for Sequential Infrared Small Target Segmentation


One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification


One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning


One Small and One Large for Document-level Event Argument Extraction


One Step Diffusion-based Super-Resolution with Time-Aware Distillation


One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones


One Step is Enough: Multi-Agent Reinforcement Learning based on One-Step Policy Optimization for Order Dispatch on Ride-Sharing Platforms


One Stone, Four Birds: A Comprehensive Solution for QA System Using Supervised Contrastive Learning


One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy


One Strike, You're Out: Detecting Markush Structures in Low Signal-to-Noise Ratio Images


One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP


One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency


One Token Can Help! Learning Scalable and Pluggable Virtual Tokens for Retrieval-Augmented Large Language Models


One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos


One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning


One fish, two fish, but not the whole sea: Alignment reduces language models' conceptual diversity


One flow to correct them all: improving simulations in high-energy physics with a single normalising flow and a switch


One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation


One for All: Simultaneous Metric and Preference Learning over Multiple Users


One for All: Unified Workload Prediction for Dynamic Multi-tenant Edge Cloud Platforms


One for Dozens: Adaptive REcommendation for All Domains with Counterfactual Augmentation


One for Multiple: Physics-informed Synthetic Data Boosts Generalizable Deep Learning for Fast MRI Reconstruction


One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning


One head is better than two: a polynomial restriction for propositional definite Horn forgetting


One hundred optical emission lines of molecular hydrogen from a low-metallicity photodissociation region


One loop QCD corrections to $gg \to t\overline{t}H$ at $\mathcal{O}(ε^2)$


One missing piece in Vision and Language: A Survey on Comics Understanding


One model Packs Thousands of Items with Recurrent Conditional Query Learning


One model to use them all: Training a segmentation model with complementary datasets


One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks


One step closer to unbiased aleatoric uncertainty estimation


One system for learning and remembering episodes and rules


One task to rule them all: A closer look at traffic classification generalizability


One to Rule them All? A First Look at DNS over QUIC


One to many: comparing single gravitational-wave events to astrophysical populations


One-Class Adversarial Nets for Fraud Detection


One-Class Classification by Ensembles of Regression models -- a detailed study


One-Class Graph Neural Networks for Anomaly Detection in Attributed Networks


One-Class Knowledge Distillation for Face Presentation Attack Detection


One-Class Model for Fabric Defect Detection


One-Class Risk Estimation for One-Class Hyperspectral Image Classification


One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget


One-Dimensional Deep Image Prior for Curve Fitting of S-Parameters from Electromagnetic Solvers


One-Layer Transformers are Provably Optimal for In-context Reasoning and Distributional Association Learning in Next-Token Prediction Tasks


One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models


One-Loop Charge-Breaking Minima in the Two-Higgs Doublet Model


One-Phase Batch Update on Sparse Merkle Trees for Rollups


One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks


One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt


One-Shot Affordance Grounding of Deformable Objects in Egocentric Organizing Scenes


One-Shot Collaborative Data Distillation


One-Shot Decision-Making with and without Surrogates


One-Shot Diffusion Mimicker for Handwritten Text Generation


One-Shot Generation of Near-Optimal Topology through Theory-Driven Machine Learning


One-Shot Gesture Recognition for Underwater Diver-To-Robot Communication


One-Shot Imitation Learning with Invariance Matching for Robotic Manipulation


One-Shot Informed Robotic Visual Search in the Wild


One-Shot Labeling for Automatic Relevance Estimation


One-Shot Learning as Instruction Data Prospector for Large Language Models


One-Shot Learning for Pose-Guided Person Image Synthesis in the Wild


One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video


One-Shot Machine Unlearning with Mnemonic Code


One-Shot Medical Video Object Segmentation via Temporal Contrastive Memory Networks


One-Shot Neural Architecture Search via Compressive Sensing


One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking


One-Shot Object Detection with Co-Attention and Co-Excitation


One-Shot Object Detection without Fine-Tuning


One-Shot Open-Set Skeleton-Based Action Recognition


One-Shot Recognition of Manufacturing Defects in Steel Surfaces


One-Shot Relational Learning for Knowledge Graphs


One-Shot Safety Alignment for Large Language Models via Optimal Dualization


One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation


One-Shot Sensitivity-Aware Mixed Sparsity Pruning for Large Language Models


One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity


One-Shot Structure-Aware Stylized Image Synthesis


One-Shot Transfer of Affordance Regions? AffCorrs!


One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer


One-Stage Cascade Refinement Networks for Infrared Small Target Detection


One-Stage Open-Vocabulary Temporal Action Detection Leveraging Temporal Multi-scale and Action Label Features


One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and Its Application to Tumour Segmentation for Breast Cancer


One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning


One-Step Diffusion Distillation through Score Implicit Matching


One-Step Diffusion Model for Image Motion-Deblurring


One-Step Estimation of Differentiable Hilbert-Valued Parameters


One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training


One-Step Image Translation with Text-to-Image Models


One-Step Knowledge Distillation and Fine-Tuning in Using Large Pre-Trained Self-Supervised Learning Models for Speaker Verification


One-Step Offline Distillation of Diffusion-based Models via Koopman Modeling


One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data


One-at-a-time knockoffs: controlled false discovery rate with higher power


One-bit Flip is All You Need: When Bit-flip Attack Meets Model Training


One-bit Supervision for Image Classification


One-bit mmWave MIMO Channel Estimation using Deep Generative Networks


One-class systems seamlessly fit in the forward-forward algorithm


One-element Batch Training by Moving Window


One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation


One-for-More: Continual Diffusion Model for Anomaly Detection


One-half reflected entropy is not a lower bound for entanglement of purification


One-loop Gravitational Bremsstrahlung and Waveforms from a Heavy-Mass Effective Field Theory


One-loop Renormalization Group Equations in Generic Effective Field Theories. Part I: Bosonic Operators


One-particle entanglement for one dimensional spinless fermions after an interaction quantum quench


One-sample log-rank tests with consideration of reference curve sampling variability


One-shot Detail Retouching with Patch Space Neural Transformation Blending


One-shot Distibuted Algorithm for PCA with RBF Kernels


One-shot Face Sketch Synthesis in the Wild via Generative Diffusion Prior and Instruction Tuning


One-shot Federated Learning via Synthetic Distiller-Distillate Communication


One-shot Federated Learning without Server-side Training


One-shot Generative Domain Adaptation in 3D GANs


One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data


One-shot Learning for MIPs with SOS1 Constraints


One-shot Learning for Question-Answering in Gaokao History Challenge


One-shot Learning with Absolute Generalization


One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction


One-shot Transfer Learning for Population Mapping


One-shot Unsupervised Domain Adaptation with Personalized Diffusion Models


One-shot World Models Using a Transformer Trained on a Synthetic Prior


One-shot action recognition in challenging therapy scenarios


One-shot and Partially-Supervised Cell Image Segmentation Using Small Visual Prompt


One-shot screening of potential peptide ligands on HR1 domain in COVID-19 glycosylated spike (S) protein with deep siamese network


One-shot skill assessment in high-stakes domains with limited data via meta learning


One-stage Low-resolution Text Recognition with High-resolution Knowledge Transfer


One-step replica symmetry breaking in the language of tensor networks


One-to-Few Label Assignment for End-to-End Dense Detection


One-to-X analogical reasoning on word embeddings: a case for diachronic armed conflict prediction from news texts


One-to-many Approach for Improving Super-Resolution


One-to-one Mapping between Stimulus and Neural State: Memory and Classification


One2Set: Generating Diverse Keyphrases as a Set


One2set + Large Language Model: Best Partners for Keyphrase Generation


OneBEV: Using One Panoramic Image for Bird's-Eye-View Semantic Mapping


OneBatchPAM: A Fast and Frugal K-Medoids Algorithm


OneBit: Towards Extremely Low-bit Large Language Models


OneChart: Purify the Chart Structural Extraction via One Auxiliary Token


OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction


OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System


OneFlow: Redesign the Distributed Deep Learning Framework from Scratch


OneForecast: A Universal Framework for Global and Regional Weather Forecasting


OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs


OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation


OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System


OneLLM: One Framework to Align All Modalities with Language


OneLabeler: A Flexible System for Building Data Labeling Tools


OneNet: A Channel-Wise 1D Convolutional U-Net


OneNet: A Fine-Tuning Free Framework for Few-Shot Entity Linking via Large Language Model Prompting


OnePose: One-Shot Object Pose Estimation without CAD Models


OneQ: A Compilation Framework for Photonic One-Way Quantum Computation


OneRestore: A Universal Restoration Framework for Composite Degradation


OneRing: A Simple Method for Source-free Open-partial Domain Adaptation


OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting


OneTo3D: One Image to Re-editable Dynamic 3D Model and Video Generation


OneVision: Centralized to Distributed Controller Synthesis with Delay Compensation


Onfocus Detection: Identifying Individual-Camera Eye Contact from Unconstrained Images


OnionEval: An Unified Evaluation of Fact-conflicting Hallucination for Small-Large Language Models


OnionNet-2: A Convolutional Neural Network Model for Predicting Protein-Ligand Binding Affinity based on Residue-Atom Contacting Shells


Online 3D reconstruction and dense tracking in endoscopic videos


Online AUC Optimization for Sparse High-Dimensional Datasets


Online Abstraction with MDP Homomorphisms for Deep Learning


Online Action Recognition for Human Risk Prediction with Anticipated Haptic Alert via Wearables


Online Active Model Selection for Pre-trained Classifiers


Online Adaptable Bug Localization for Rapidly Evolving Software


Online Adaptation for Enhancing Imitation Learning Policies


Online Adaptation for Implicit Object Tracking and Shape Reconstruction in the Wild


Online Adaptation of Language Models with a Memory of Amortized Contexts


Online Adaptive Asymmetric Active Learning with Limited Budgets


Online Adaptive Platoon Control for Connected and Automated Vehicles via Physics Enhanced Residual Learning


Online Adaptive Principal Component Analysis and Its extensions


Online Adaptive Traversability Estimation through Interaction for Unstructured, Densely Vegetated Environments


Online Adversarial Knowledge Distillation for Graph Neural Networks


Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice


Online Analysis of Distributed Dataflows with Timely Dataflow


Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning


Online Anomaly Detection Based On Reservoir Sampling and LOF for IoT devices


Online Anomaly Detection in Surveillance Videos with Asymptotic Bounds on False Alarm Rate


Online Arbitrary Shaped Clustering through Correlated Gaussian Functions


Online Assessment Misconduct Detection using Internet Protocol and Behavioural Classification


Online Assortment and Price Optimization Under Contextual Choice Models


Online Asynchronous Distributed Regression


Online Back-Parsing for AMR-to-Text Generation


Online Batch Selection for Faster Training of Neural Networks


Online Baum-Welch algorithm for Hierarchical Imitation Learning


Online Bayesian changepoint detection for network Poisson processes with community structure


Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model


Online Cascade Learning for Efficient Inference over Streams


Online Causal Inference with Application to Near Real-Time Post-Market Vaccine Safety Surveillance


Online Causation Monitoring of Signal Temporal Logic


Online Change Point Detection in Molecular Dynamics With Optical Random Features


Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning


Online Context Learning for Socially Compliant Navigation


Online Continual Learning Without the Storage Constraint


Online Continual Learning in Keyword Spotting for Low-Resource Devices via Pooling High-Order Temporal Statistics


Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference


Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries


Online Continual Learning under Extreme Memory Constraints


Online Continual Learning via Logit Adjusted Softmax