Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
1906.04818	Medium-Term Load Forecasting Using Support Vector Regression, Feature Selection, and Symbiotic Organism Search Optimization	An accurate load forecasting has always been one of the main indispensable parts in the operation and planning of power systems. Among different time horizons of forecasting, while short-term load forecasting (STLF) and long-term load forecasting (LTLF) have respectively got benefits of accurate predictors and probabil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	134,845
2204.07770	UniGDD: A Unified Generative Framework for Goal-Oriented Document-Grounded Dialogue	The goal-oriented document-grounded dialogue aims at responding to the user query based on the dialogue context and supporting document. Existing studies tackle this problem by decomposing it into two sub-tasks: knowledge identification and response generation. However, such pipeline methods would unavoidably suffer fr...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	291,840
2206.00845	Hyperspherical Consistency Regularization	Recent advances in contrastive learning have enlightened diverse applications across various semi-supervised fields. Jointly training supervised learning and unsupervised learning with a shared feature encoder becomes a common scheme. Though it benefits from taking advantage of both feature-dependent information from s...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	300,279
2402.12406	Teacher as a Lenient Expert: Teacher-Agnostic Data-Free Knowledge Distillation	Data-free knowledge distillation (DFKD) aims to distill pretrained knowledge to a student model with the help of a generator without using original data. In such data-free scenarios, achieving stable performance of DFKD is essential due to the unavailability of validation data. Unfortunately, this paper has discovered ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	430,838
2406.02464	Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments	Estimating the conditional average treatment effect (CATE) from observational data is relevant for many applications such as personalized medicine. Here, we focus on the widespread setting where the observational data come from multiple environments, such as different hospitals, physicians, or countries. Furthermore, w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	460,777
2302.03026	Sampling-Based Accuracy Testing of Posterior Estimators for General Inference	Parameter inference, i.e. inferring the posterior distribution of the parameters of a statistical model given some data, is a central problem to many scientific disciplines. Generative models can be used as an alternative to Markov Chain Monte Carlo methods for conducting posterior inference, both in likelihood-based a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	344,199
1608.05094	Tolerant Compressed Sensing With Partially Coherent Sensing Matrices	Most of compressed sensing (CS) theory to date is focused on incoherent sensing, that is, columns from the sensing matrix are highly uncorrelated. However, sensing systems with naturally occurring correlations arise in many applications, such as signal detection, motion detection and radar. Moreover, in these applicati...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	59,919
2211.12660	The Impact of Generative AI on the Future of Visual Content Marketing	In today's world of marketing, it is necessary to have visually appealing content. Visual material has become an essential area of focus for every company as a result of the widespread availability of gadgets for mass communication and extended visual advancements. Similarly, artificial intelligence is also gaining gro...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	332,187
2411.12939	Stabilization of Switched Affine Systems With Dwell-Time Constraint	This paper addresses the problem of stabilization of switched affine systems under dwell-time constraint, giving guarantees on the bound of the quadratic cost associated with the proposed state switching control law. Specifically, two switching rules are presented relying on the solution of differential Lyapunov inequa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	509,603
2109.14591	Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration	An increasingly common use case for machine learning models is augmenting the abilities of human decision makers. For classification tasks where neither the human or model are perfectly accurate, a key step in obtaining high performance is combining their individual predictions in a manner that leverages their relative...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	258,006
2212.02469	One-shot Implicit Animatable Avatars with Model-based Priors	Existing neural rendering methods for creating human avatars typically either require dense input signals such as video or multi-view images, or leverage a learned prior from large-scale specific 3D human datasets such that reconstruction can be performed with sparse-view inputs. Most of these methods fail to achieve r...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	334,796
2212.05409	Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages	Building Natural Language Understanding (NLU) capabilities for Indic languages, which have a collective speaker base of more than one billion speakers is absolutely crucial. In this work, we aim to improve the NLU capabilities of Indic languages by making contributions along 3 important axes (i) monolingual corpora (ii...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	335,782
2008.06902	Modeling "Equitable and Sustainable Well-being" (BES) using Bayesian Networks: A Case Study of the Italian regions	Measurement of well-being has been a highly debated topic since the end of the last century. While some specific aspects are still open issues, a multidimensional approach as well as the construction of shared and well-rooted systems of indicators are now accepted as the main route to measure this complex phenomenon. A...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	191,929
cs/9603104	Active Learning with Statistical Models	For many types of machine learning algorithms, one can compute the statistically `optimal' way to select training data. In this paper, we review how optimal data selection techniques have been used with feedforward neural networks. We then show how the same principles may be used to select data for two alternative, sta...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	540,333
1402.6016	Incremental Redundancy, Fountain Codes and Advanced Topics	This document is written in order to establish a common base ground on which the majority of the relevant research about linear fountain codes can be analyzed and compared. As far as I am concerned, there is no unified approach that outlines and compares most of the published linear fountain codes in a single and self-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	31,139
2002.09284	On The Reasons Behind Decisions	Recent work has shown that some common machine learning classifiers can be compiled into Boolean circuits that have the same input-output behavior. We present a theory for unveiling the reasons behind the decisions made by Boolean classifiers and study some of its theoretical and practical implications. We define notio...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	165,024
1803.03169	An Enabling Waveform for 5G - QAM-FBMC: Initial Analysis	In this paper, we identified the challenges and requirements for the waveform design of the fifth generation mobile communication networks (5G) and compared Orthogonal frequency-division multiplexing (OFDM) based waveforms with Filter Bank Multicarrier (FBMC) based ones. Recently it has been shown that Quadrature-Ampli...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	92,199
2312.01947	Maximising Quantum-Computing Expressive Power through Randomised Circuits	In the noisy intermediate-scale quantum era, variational quantum algorithms (VQAs) have emerged as a promising avenue to obtain quantum advantage. However, the success of VQAs depends on the expressive power of parameterised quantum circuits, which is constrained by the limited gate number and the presence of barren pl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	412,639
2212.02168	Video Games as a Corpus: Sentiment Analysis using Fallout New Vegas Dialog	We present a method for extracting a multilingual sentiment annotated dialog data set from Fallout New Vegas. The game developers have preannotated every line of dialog in the game in one of the 8 different sentiments: \textit{anger, disgust, fear, happy, neutral, pained, sad } and \textit{surprised}. The game has been...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	334,705
2410.05441	Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox	We consider Thompson Sampling (TS) for linear combinatorial semi-bandits and subgaussian rewards. We propose the first known TS whose finite-time regret does not scale exponentially with the dimension of the problem. We further show the "mismatched sampling paradox": A learner who knows the rewards distributions and sa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	495,733
2302.12156	Personalized Decentralized Federated Learning with Knowledge Distillation	Personalization in federated learning (FL) functions as a coordinator for clients with high variance in data or behavior. Ensuring the convergence of these clients' models relies on how closely users collaborate with those with similar patterns or preferences. However, it is generally challenging to quantify similarity...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	347,455
2310.09462	A Framework for Empowering Reinforcement Learning Agents with Causal Analysis: Enhancing Automated Cryptocurrency Trading	Despite advances in artificial intelligence-enhanced trading methods, developing a profitable automated trading system remains challenging in the rapidly evolving cryptocurrency market. This research focuses on developing a reinforcement learning (RL) framework to tackle the complexities of trading five prominent altco...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	399,782
2403.07918	On the Societal Impact of Open Foundation Models	Foundation models are powerful technologies: how they are released publicly directly shapes their societal impact. In this position paper, we focus on open foundation models, defined here as those with broadly available model weights (e.g. Llama 2, Stable Diffusion XL). We identify five distinctive properties (e.g. gre...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	437,090
2311.00564	Online Student-$t$ Processes with an Overall-local Scale Structure for Modelling Non-stationary Data	Time-dependent data often exhibit characteristics, such as non-stationarity and heavy-tailed errors, that would be inappropriate to model with the typical assumptions used in popular models. Thus, more flexible approaches are required to be able to accommodate such issues. To this end, we propose a Bayesian mixture of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,696
2006.08580	Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality	We study the distribution and uncertainty of nonconvex optimization for noisy tensor completion -- the problem of estimating a low-rank tensor given incomplete and corrupted observations of its entries. Focusing on a two-stage estimation algorithm proposed by Cai et al. (2019), we characterize the distribution of this ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	182,235
1909.05962	SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation	Deep learning has largely reduced the need for manual feature selection in image segmentation. Nevertheless, network architecture optimization and hyperparameter tuning are mostly manual and time consuming. Although there are increasing research efforts on network architecture search in computer vision, most works conc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	145,250
2306.14177	Enhancing Mapless Trajectory Prediction through Knowledge Distillation	Scene information plays a crucial role in trajectory forecasting systems for autonomous driving by providing semantic clues and constraints on potential future paths of traffic agents. Prevalent trajectory prediction techniques often take high-definition maps (HD maps) as part of the inputs to provide scene knowledge. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	375,581
2305.19244	Testing for the Markov Property in Time Series via Deep Conditional Generative Learning	The Markov property is widely imposed in analysis of time series data. Correspondingly, testing the Markov property, and relatedly, inferring the order of a Markov model, are of paramount importance. In this article, we propose a nonparametric test for the Markov property in high-dimensional time series via deep condit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	369,438
2406.08344	Blind Image Deblurring with FFT-ReLU Sparsity Prior	Blind image deblurring is the process of recovering a sharp image from a blurred one without prior knowledge about the blur kernel. It is a small data problem, since the key challenge lies in estimating the unknown degrees of blur from a single image or limited data, instead of learning from large datasets. The solutio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	463,445
1412.1723	Communication complexity and the reality of the wave-function	In this review, we discuss a relation between quantum communication complexity and a long-standing debate in quantum foundation concerning the interpretation of the quantum state. Is the quantum state a physical element of reality as originally interpreted by Schrodinger? Or is it an abstract mathematical object contai...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	38,130
2408.10623	TextMastero: Mastering High-Quality Scene Text Editing in Diverse Languages and Styles	Scene text editing aims to modify texts on images while maintaining the style of newly generated text similar to the original. Given an image, a target area, and target text, the task produces an output image with the target text in the selected area, replacing the original. This task has been studied extensively, with...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	481,946
2404.09556	nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation	The release of nnU-Net marked a paradigm shift in 3D medical image segmentation, demonstrating that a properly configured U-Net architecture could still achieve state-of-the-art results. Despite this, the pursuit of novel architectures, and the respective claims of superior performance over the U-Net baseline, continue...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	446,732
2402.06707	Multi-class real-time crash risk forecasting using convolutional neural network: Istanbul case study	The performance of an artificial neural network (ANN) in forecasting crash risk is shown in this paper. To begin, some traffic and weather data are acquired as raw data. This data is then analyzed, and relevant characteristics are chosen to utilize as input data based on additional tree and Pearson correlation. Further...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	428,410
1206.3231	CORL: A Continuous-state Offset-dynamics Reinforcement Learner	Continuous state spaces and stochastic, switching dynamics characterize a number of rich, realworld domains, such as robot navigation across varying terrain. We describe a reinforcementlearning algorithm for learning in these domains and prove for certain environments the algorithm is probably approximately correct wit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	16,490
2010.14931	TurboKV: Scaling Up The Performance of Distributed Key-Value Stores With In-Switch Coordination	The power and flexibility of software-defined networks lead to a programmable network infrastructure in which in-network computation can help accelerating the performance of applications. This can be achieved by offloading some computational tasks to the network. However, what kind of computational tasks should be dele...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	203,623
2312.15172	Pre-trained Trojan Attacks for Visual Recognition	Pre-trained vision models (PVMs) have become a dominant component due to their exceptional performance when fine-tuned for downstream tasks. However, the presence of backdoors within PVMs poses significant threats. Unfortunately, existing studies primarily focus on backdooring PVMs for the classification task, neglecti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,902
1906.06007	Convolutional Neural Network based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis	Massive multiple-input multiple-output (MIMO) is a promising technology to increase link capacity and energy efficiency. However, these benefits are based on available channel state information (CSI) at the base station (BS). Therefore, user equipment (UE) needs to keep on feeding CSI back to the BS, thereby consuming ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	135,183
2204.13414	Improving the Robustness of Federated Learning for Severely Imbalanced Datasets	With the ever increasing data deluge and the success of deep neural networks, the research of distributed deep learning has become pronounced. Two common approaches to achieve this distributed learning is synchronous and asynchronous weight update. In this manuscript, we have explored very simplistic synchronous weight...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	293,812
2307.00863	Thompson Sampling under Bernoulli Rewards with Local Differential Privacy	This paper investigates the problem of regret minimization for multi-armed bandit (MAB) problems with local differential privacy (LDP) guarantee. Given a fixed privacy budget $\epsilon$, we consider three privatizing mechanisms under Bernoulli scenario: linear, quadratic and exponential mechanisms. Under each mechanism...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	377,157
1802.04086	The Complex Event Recognition Group	The Complex Event Recognition (CER) group is a research team, affiliated with the National Centre of Scientific Research "Demokritos" in Greece. The CER group works towards advanced and efficient methods for the recognition of complex events in a multitude of large, heterogeneous and interdependent data streams. Its re...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	90,141
2412.01792	CTRL-D: Controllable Dynamic 3D Scene Editing with Personalized 2D Diffusion	Recent advances in 3D representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have greatly improved realistic scene modeling and novel-view synthesis. However, achieving controllable and consistent editing in dynamic 3D scenes remains a significant challenge. Previous work is largely constrained by i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	513,264
2306.11689	Statistical Tests for Replacing Human Decision Makers with Algorithms	This paper proposes a statistical framework of using artificial intelligence to improve human decision making. The performance of each human decision maker is benchmarked against that of machine predictions. We replace the diagnoses made by a subset of the decision makers with the recommendation from the machine learni...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	374,673
2408.15221	LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet	Recent large language model (LLM) defenses have greatly improved models' ability to refuse harmful queries, even when adversarially attacked. However, LLM defenses are primarily evaluated against automated adversarial attacks in a single turn of conversation, an insufficient threat model for real-world malicious use. W...	false	false	false	false	false	false	true	false	true	false	false	false	true	true	false	false	false	false	483,843
2501.19267	Transformer-Based Financial Fraud Detection with Cloud-Optimized Real-Time Streaming	As the financial industry becomes more interconnected and reliant on digital systems, fraud detection systems must evolve to meet growing threats. Cloud-enabled Transformer models present a transformative opportunity to address these challenges. By leveraging the scalability, flexibility, and advanced AI capabilities o...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	529,087
2012.03636	Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent	In the vanishing learning rate regime, stochastic gradient descent (SGD) is now relatively well understood. In this work, we propose to study the basic properties of SGD and its variants in the non-vanishing learning rate regime. The focus is on deriving exactly solvable results and discussing their implications. The m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	210,190
2302.09000	Train What You Know -- Precise Pick-and-Place with Transporter Networks	Precise pick-and-place is essential in robotic applications. To this end, we define a novel exact training method and an iterative inference method that improve pick-and-place precision with Transporter Networks. We conduct a large scale experiment on 8 simulated tasks. A systematic analysis shows, that the proposed mo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	346,261
cs/9811029	A Human - machine interface for teleoperation of arm manipulators in a complex environment	This paper discusses the feasibility of using configuration space (C-space) as a means of visualization and control in operator-guided real-time motion of a robot arm manipulator. The motivation is to improve performance of the human operator in tasks involving the manipulator motion in an environment with obstacles. U...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	540,442
2005.13363	GSTO: Gated Scale-Transfer Operation for Multi-Scale Feature Learning in Pixel Labeling	Existing CNN-based methods for pixel labeling heavily depend on multi-scale features to meet the requirements of both semantic comprehension and detail preservation. State-of-the-art pixel labeling neural networks widely exploit conventional scale-transfer operations, i.e., up-sampling and down-sampling to learn multi-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	178,996
1906.11231	On the Common Randomness Capacity of a Special Class of Two-way Channels	In this paper, we would like to study the common randomness (CR) capacity of intertwined two-way channels, namely those whose marginal channel transition probabilities depends also on the signal they transmit. We bring a few special settings and provide constructive schemes with which the two nodes can agree upon a com...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	136,615
1104.0888	Settling the feasibility of interference alignment for the MIMO interference channel: the symmetric square case	Determining the feasibility conditions for vector space interference alignment in the K-user MIMO interference channel with constant channel coefficients has attracted much recent attention yet remains unsolved. The main result of this paper is restricted to the symmetric square case where all transmitters and receiver...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,879
1706.08915	The Fog of War: A Machine Learning Approach to Forecasting Weather on Mars	For over a decade, scientists at NASA's Jet Propulsion Laboratory (JPL) have been recording measurements from the Martian surface as a part of the Mars Exploration Rovers mission. One quantity of interest has been the opacity of Mars's atmosphere for its importance in day-to-day estimations of the amount of power avail...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	76,067
1705.09619	Learning Lyapunov (Potential) Functions from Counterexamples and Demonstrations	We present a technique for learning control Lyapunov (potential) functions, which are used in turn to synthesize controllers for nonlinear dynamical systems. The learning framework uses a demonstrator that implements a black-box, untrusted strategy presumed to solve the problem of interest, a learner that poses finitel...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	74,236
2501.17770	Generative Unordered Flow for Set-Structured Data Generation	Flow-based generative models have demonstrated promising performance across a broad spectrum of data modalities (e.g., image and text). However, there are few works exploring their extension to unordered data (e.g., spatial point set), which is not trivial because previous models are mostly designed for vector data tha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	528,446
2308.04365	SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation Modeling	Causal inference is a crucial goal of science, enabling researchers to arrive at meaningful conclusions regarding the predictions of hypothetical interventions using observational data. Path models, Structural Equation Models (SEMs), and, more generally, Directed Acyclic Graphs (DAGs), provide a means to unambiguously ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	384,382
2109.06627	Scalable Font Reconstruction with Dual Latent Manifolds	We propose a deep generative model that performs typography analysis and font reconstruction by learning disentangled manifolds of both font style and character shape. Our approach enables us to massively scale up the number of character types we can effectively model compared to previous methods. Specifically, we infe...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	255,217
2412.03812	Pinco: Position-induced Consistent Adapter for Diffusion Transformer in Foreground-conditioned Inpainting	Foreground-conditioned inpainting aims to seamlessly fill the background region of an image by utilizing the provided foreground subject and a text description. While existing T2I-based image inpainting methods can be applied to this task, they suffer from issues of subject shape expansion, distortion, or impaired abil...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,116
1706.09364	Online Adaptation of Convolutional Neural Networks for Video Object Segmentation	We tackle the task of semi-supervised video object segmentation, i.e. segmenting the pixels belonging to an object in the video using the ground truth pixel mask for the first frame. We build on the recently introduced one-shot video object segmentation (OSVOS) approach which uses a pretrained network and fine-tunes it...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,126
1404.6935	Homophily and the Speed of Social Mobilization: The Effect of Acquired and Ascribed Traits	Large-scale mobilization of individuals across social networks is becoming increasingly prevalent in society. However, little is known about what affects the speed of social mobilization. Here we use a framed field experiment to identify and measure properties of individuals and their relationships that predict mobiliz...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	32,646
2310.15966	Constructing and Machine Learning Calabi-Yau Five-folds	We construct all possible complete intersection Calabi-Yau five-folds in a product of four or less complex projective spaces, with up to four constraints. We obtain $27068$ spaces, which are not related by permutations of rows and columns of the configuration matrix, and determine the Euler number for all of them. Excl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	402,521
2305.09602	Urban-StyleGAN: Learning to Generate and Manipulate Images of Urban Scenes	A promise of Generative Adversarial Networks (GANs) is to provide cheap photorealistic data for training and validating AI models in autonomous driving. Despite their huge success, their performance on complex images featuring multiple objects is understudied. While some frameworks produce high-quality street scenes wi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	364,699
2405.03056	Convolutional Learning on Directed Acyclic Graphs	We develop a novel convolutional architecture tailored for learning from data defined over directed acyclic graphs (DAGs). DAGs can be used to model causal relationships among variables, but their nilpotent adjacency matrices pose unique challenges towards developing DAG signal processing and machine learning tools. To...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	452,029
2502.07790	Can Generative AI be Egalitarian?	The recent explosion of "foundation" generative AI models has been built upon the extensive extraction of value from online sources, often without corresponding reciprocation. This pattern mirrors and intensifies the extractive practices of surveillance capitalism, while the potential for enormous profit has challenged...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	532,758
1911.09450	Few Shot Network Compression via Cross Distillation	Model compression has been widely adopted to obtain light-weighted deep neural networks. Most prevalent methods, however, require fine-tuning with sufficient training data to ensure accuracy, which could be challenged by privacy and security issues. As a compromise between privacy and performance, in this paper we inve...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	154,525
2002.05378	Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning	We design efficient distance approximation algorithms for several classes of structured high-dimensional distributions. Specifically, we show algorithms for the following problems: - Given sample access to two Bayesian networks $P_1$ and $P_2$ over known directed acyclic graphs $G_1$ and $G_2$ having $n$ nodes and bo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	163,878
2411.01380	Signer-Optimal Multiple-Time Post-Quantum Hash-Based Signature for Heterogeneous IoT Systems	Heterogeneous Internet of Things (IoTs) harboring resource-limited devices like wearable sensors are essential for next-generation networks. Ensuring the authentication and integrity of security-sensitive telemetry in these applications is vital. Digital signatures provide scalable authentication with non-repudiation a...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	505,042
2412.01807	Occam's LGS: A Simple Approach for Language Gaussian Splatting	TL;DR: Gaussian Splatting is a widely adopted approach for 3D scene representation that offers efficient, high-quality 3D reconstruction and rendering. A major reason for the success of 3DGS is its simplicity of representing a scene with a set of Gaussians, which makes it easy to interpret and adapt. To enhance scene u...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,271
2307.12101	Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes	Object detection via inaccurate bounding boxes supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low annotation quality (\eg tiny objects). The previous works usually utilize multiple instance learning (MIL), which highly depends on category in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,136
2006.05087	Isotropic SGD: a Practical Approach to Bayesian Posterior Sampling	In this work we define a unified mathematical framework to deepen our understanding of the role of stochastic gradient (SG) noise on the behavior of Markov chain Monte Carlo sampling (SGMCMC) algorithms. Our formulation unlocks the design of a novel, practical approach to posterior sampling, which makes the SG noise ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	180,934
1710.07312	FPGA-based ORB Feature Extraction for Real-Time Visual SLAM	Simultaneous Localization And Mapping (SLAM) is the problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. How to enable SLAM robustly and durably on mobile, or even IoT grade devices, is the main challenge faced by the industry today. Th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	82,910
1908.02338	Modelling Segmented Cardiotocography Time-Series Signals Using One-Dimensional Convolutional Neural Networks for the Early Detection of Abnormal Birth Outcomes	Gynaecologists and obstetricians visually interpret cardiotocography (CTG) traces using the International Federation of Gynaecology and Obstetrics (FIGO) guidelines to assess the wellbeing of the foetus during antenatal care. This approach has raised concerns among professionals with regards to inter- and intra-variabi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	140,973
2205.11168	Logarithmic regret bounds for continuous-time average-reward Markov decision processes	We consider reinforcement learning for continuous-time Markov decision processes (MDPs) in the infinite-horizon, average-reward setting. In contrast to discrete-time MDPs, a continuous-time process moves to a state and stays there for a random holding time after an action is taken. With unknown transition probabilities...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	298,030
2502.09274	FLARES: Fast and Accurate LiDAR Multi-Range Semantic Segmentation	3D scene understanding is a critical yet challenging task in autonomous driving, primarily due to the irregularity and sparsity of LiDAR data, as well as the computational demands of processing large-scale point clouds. Recent methods leverage the range-view representation to improve processing efficiency. To mitigate ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	533,386
2501.04217	Continual Self-supervised Learning Considering Medical Domain Knowledge in Chest CT Images	We propose a novel continual self-supervised learning method (CSSL) considering medical domain knowledge in chest CT images. Our approach addresses the challenge of sequential learning by effectively capturing the relationship between previously learned knowledge and new information at different stages. By incorporatin...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	523,136
1805.12022	On $q$-ratio CMSV for sparse recovery	Sparse recovery aims to reconstruct an unknown spare or approximately sparse signal from significantly few noisy incoherent linear measurements. As a kind of computable incoherence measure of the measurement matrix, $q$-ratio constrained minimal singular values (CMSV) was proposed in Zhou and Yu \cite{zhou2018sparse} t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	99,074
2410.14393	Debug Smarter, Not Harder: AI Agents for Error Resolution in Computational Notebooks	Computational notebooks became indispensable tools for research-related development, offering unprecedented interactivity and flexibility in the development process. However, these benefits come at the cost of reproducibility and an increased potential for bugs. With the rise of code-fluent Large Language Models empowe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	500,010
1611.10088	On Binary de Bruijn Sequences from LFSRs with Arbitrary Characteristic Polynomials	We propose a construction of de Bruijn sequences by the cycle joining method from linear feedback shift registers (LFSRs) with arbitrary characteristic polynomial $f(x)$. We study in detail the cycle structure of the set $\Omega(f(x))$ that contains all sequences produced by a specific LFSR on distinct inputs and provi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	64,771
2407.01916	Sequential Manipulation Against Rank Aggregation: Theory and Algorithm	Rank aggregation with pairwise comparisons is widely encountered in sociology, politics, economics, psychology, sports, etc . Given the enormous social impact and the consequent incentives, the potential adversary has a strong motivation to manipulate the ranking list. However, the ideal attack opportunity and the exce...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	469,509
2001.03384	Decentralized Optimization of Vehicle Route Planning -- A Cross-City Comparative Study	New mobility concepts are at the forefront of research and innovation in smart cities. The introduction of connected and autonomous vehicles enables new possibilities in vehicle routing. Specifically, knowing the origin and destination of each agent in the network can allow for real-time routing of the vehicles to opti...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	false	false	true	159,964
1910.05672	Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images	Diagnosing different retinal diseases from Spectral Domain Optical Coherence Tomography (SD-OCT) images is a challenging task. Different automated approaches such as image processing, machine learning and deep learning algorithms have been used for early detection and diagnosis of retinal diseases. Unfortunately, these...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	149,138
1308.1292	Science Fiction as a Worldwide Phenomenon: A Study of International Creation, Consumption and Dissemination	This paper examines the international nature of science fiction. The focus of this research is to determine whether science fiction is primarily English speaking and Western or global; being created and consumed by people in non-Western, non-English speaking countries? Science fiction's international presence was found...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	true	26,296
2212.09252	Mind the Knowledge Gap: A Survey of Knowledge-enhanced Dialogue Systems	Many dialogue systems (DSs) lack characteristics humans have, such as emotion perception, factuality, and informativeness. Enhancing DSs with knowledge alleviates this problem, but, as many ways of doing so exist, keeping track of all proposed methods is difficult. Here, we present the first survey of knowledge-enhance...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	337,044
2410.11347	Periodic autocorrelation of sequences	The autocorrelation of a sequence is a useful criterion, among all, of resistance to cryptographic attacks. The behavior of the autocorrelations of random Boolean functions (studied by Florian Caullery, Eric F\'erard and Fran\c{c}ois Rodier [4]) shows that they are concentrated around a point. We show that the same is ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	498,515
2409.06183	EDADepth: Enhanced Data Augmentation for Monocular Depth Estimation	Due to their text-to-image synthesis feature, diffusion models have recently seen a rise in visual perception tasks, such as depth estimation. The lack of good-quality datasets makes the extraction of a fine-grain semantic context challenging for the diffusion models. The semantic context with fewer details further wor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,028
1503.08513	Hiding Symbols and Functions: New Metrics and Constructions for Information-Theoretic Security	We present information-theoretic definitions and results for analyzing symmetric-key encryption schemes beyond the perfect secrecy regime, i.e. when perfect secrecy is not attained. We adopt two lines of analysis, one based on lossless source coding, and another akin to rate-distortion theory. We start by presenting a ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,598
2309.00386	Satisfiability Checking of Multi-Variable TPTL with Unilateral Intervals Is PSPACE-Complete	We investigate the decidability of the ${0,\infty}$ fragment of Timed Propositional Temporal Logic (TPTL). We show that the satisfiability checking of TPTL$^{0,\infty}$ is PSPACE-complete. Moreover, even its 1-variable fragment (1-TPTL$^{0,\infty}$) is strictly more expressive than Metric Interval Temporal Logic (MITL)...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	389,297
2310.03614	Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally	Deep Neural Networks (DNNs) have been the driving force behind many of the recent advances in machine learning. However, research has shown that DNNs are vulnerable to adversarial examples -- input samples that have been perturbed to force DNN-based models to make errors. As a result, Adversarial Machine Learning (AdvM...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	397,348
2410.06317	Learning in complex action spaces without policy gradients	Conventional wisdom suggests that policy gradient methods are better suited to complex action spaces than action-value methods. However, foundational studies have shown equivalences between these paradigms in small and finite action spaces (O'Donoghue et al., 2017; Schulman et al., 2017a). This raises the question of w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	496,142
2209.08283	Detecting Generated Scientific Papers using an Ensemble of Transformer Models	The paper describes neural models developed for the DAGPap22 shared task hosted at the Third Workshop on Scholarly Document Processing. This shared task targets the automatic detection of generated scientific papers. Our work focuses on comparing different transformer-based models as well as using additional datasets a...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	318,063
1611.04845	An Evaluation of Information Sharing Parking Guidance Policies Using a Bayesian Approach	Real-time parking occupancy information is critical for a parking management system to facilitate drivers to park more efficiently. Recent advances in connected and automated vehicle technologies enable sensor-equipped cars (probe cars) to detect and broadcast available parking spaces when driving through parking lots....	false	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	63,910
2409.15915	Planning in the Dark: LLM-Symbolic Planning Pipeline without Experts	Large Language Models (LLMs) have shown promise in solving natural language-described planning tasks, but their direct use often leads to inconsistent reasoning and hallucination. While hybrid LLM-symbolic planning pipelines have emerged as a more robust alternative, they typically require extensive expert intervention...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	491,127
2103.11056	ConDA: Continual Unsupervised Domain Adaptation	Domain Adaptation (DA) techniques are important for overcoming the domain shift between the source domain used for training and the target domain where testing takes place. However, current DA methods assume that the entire target domain is available during adaptation, which may not hold in practice. This paper conside...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	225,648
2406.09900	GEB-1.3B: Open Lightweight Large Language Model	Recently developed large language models (LLMs) such as ChatGPT, Claude, and Llama have demonstrated impressive abilities, and even surpass human-level performance in several tasks. Despite their success, the resource-intensive demands of these models, requiring significant computational power for both training and inf...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	464,133
1908.11852	New stable method to solve heat conduction problems in extremely large systems	We present a new explicit and stable numerical algorithm to solve the homogeneous heat equation. We illustrate the performance of the new method in the cases of two 2D systems with highly inhomogeneous random parameters. Spatial discretization of these problems results in huge and stiff ordinary differential equation s...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	143,492
1404.7109	Security Thresholds of Multicarrier Continuous-Variable Quantum Key Distribution	We prove the secret key rate formulas and derive security threshold parameters of multicarrier continuous-variable quantum key distribution (CVQKD). In a multicarrier CVQKD scenario, the Gaussian input quantum states of the legal parties are granulated into Gaussian subcarrier CVs (continuous-variables). The multicarri...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	32,664
2207.05703	Tell Me the Evidence? Dual Visual-Linguistic Interaction for Answer Grounding	Answer grounding aims to reveal the visual evidence for visual question answering (VQA), which entails highlighting relevant positions in the image when answering questions about images. Previous attempts typically tackle this problem using pretrained object detectors, but without the flexibility for objects not in the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	307,633
2304.01804	Bridging the Gap between Model Explanations in Partially Annotated Multi-label Classification	Due to the expensive costs of collecting labels in multi-label classification datasets, partially annotated multi-label classification has become an emerging field in computer vision. One baseline approach to this task is to assume unobserved labels as negative labels, but this assumption induces label noise as a form ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,211
2312.11923	IPAD: Iterative, Parallel, and Diffusion-based Network for Scene Text Recognition	Nowadays, scene text recognition has attracted more and more attention due to its diverse applications. Most state-of-the-art methods adopt an encoder-decoder framework with the attention mechanism, autoregressively generating text from left to right. Despite the convincing performance, this sequential decoding strateg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	416,779
2210.03428	Missing Modality meets Meta Sampling (M3S): An Efficient Universal Approach for Multimodal Sentiment Analysis with Missing Modality	Multimodal sentiment analysis (MSA) is an important way of observing mental activities with the help of data captured from multiple modalities. However, due to the recording or transmission error, some modalities may include incomplete data. Most existing works that address missing modalities usually assume a particula...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	322,030
2110.05442	Neural Algorithmic Reasoners are Implicit Planners	Implicit planning has emerged as an elegant technique for combining learned models of the world with end-to-end model-free reinforcement learning. We study the class of implicit planners inspired by value iteration, an algorithm that is guaranteed to yield perfect policies in fully-specified tabular environments. We fi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	260,281
1508.03671	Fuzzy Longest Common Subsequence Matching With FCM Using R	Capturing the interdependencies between real valued time series can be achieved by finding common similar patterns. The abstraction of time series makes the process of finding similarities closer to the way as humans do. Therefore, the abstraction by means of a symbolic levels and finding the common patterns attracts r...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	46,025

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