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
2303.08536	Watch or Listen: Robust Audio-Visual Speech Recognition with Visual Corruption Modeling and Reliability Scoring	This paper deals with Audio-Visual Speech Recognition (AVSR) under multimodal input corruption situations where audio inputs and visual inputs are both corrupted, which is not well addressed in previous research directions. Previous studies have focused on how to complement the corrupted audio inputs with the clean vis...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	351,679
2111.06038	Hybrid Saturation Restoration for LDR Images of HDR Scenes	There are shadow and highlight regions in a low dynamic range (LDR) image which is captured from a high dynamic range (HDR) scene. It is an ill-posed problem to restore the saturated regions of the LDR image. In this paper, the saturated regions of the LDR image are restored by fusing model-based and data-driven approa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	265,968
2002.10537	Video Monitoring Queries	Recent advances in video processing utilizing deep learning primitives achieved breakthroughs in fundamental problems in video analysis such as frame classification and object detection enabling an array of new applications. In this paper we study the problem of interactive declarative query processing on video strea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	165,426
1907.09110	Strategic Voting Under Uncertainty About the Voting Method	Much of the theoretical work on strategic voting makes strong assumptions about what voters know about the voting situation. A strategizing voter is typically assumed to know how other voters will vote and to know the rules of the voting method. A growing body of literature explores strategic voting when there is uncer...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	139,270
2307.07876	Real-time goal recognition using approximations in Euclidean space	While recent work on online goal recognition efficiently infers goals under low observability, comparatively less work focuses on online goal recognition that works in both discrete and continuous domains. Online goal recognition approaches often rely on repeated calls to the planner at each new observation, incurring ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	379,575
2007.10878	DeepNetQoE: Self-adaptive QoE Optimization Framework of Deep Networks	Future advances in deep learning and its impact on the development of artificial intelligence (AI) in all fields depends heavily on data size and computational power. Sacrificing massive computing resources in exchange for better precision rates of the network model is recognized by many researchers. This leads to huge...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	188,405
2102.01807	Building population models for large-scale neural recordings: opportunities and pitfalls	Modern recording technologies now enable simultaneous recording from large numbers of neurons. This has driven the development of new statistical models for analyzing and interpreting neural population activity. Here we provide a broad overview of recent developments in this area. We compare and contrast different appr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	218,223
1511.08899	Applying deep learning to classify pornographic images and videos	It is no secret that pornographic material is now a one-click-away from everyone, including children and minors. General social media networks are striving to isolate adult images and videos from normal ones. Intelligent image analysis methods can help to automatically detect and isolate questionable images in media. U...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	true	49,592
2304.07711	Obstacle-Transformer: A Trajectory Prediction Network Based on Surrounding Trajectories	Recurrent Neural Network, Long Short-Term Memory, and Transformer have made great progress in predicting the trajectories of moving objects. Although the trajectory element with the surrounding scene features has been merged to improve performance, there still exist some problems to be solved. One is that the time seri...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	358,451
2407.20152	Hierarchically Disentangled Recurrent Network for Factorizing System Dynamics of Multi-scale Systems	We present a knowledge-guided machine learning (KGML) framework for modeling multi-scale processes, and study its performance in the context of streamflow forecasting in hydrology. Specifically, we propose a novel hierarchical recurrent neural architecture that factorizes the system dynamics at multiple temporal scales...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	477,061
2305.09795	The Value of Competing Energy Storage in Decarbonized Power Systems	As the world seeks to transition to a sustainable energy future, energy storage technologies are increasingly recognized as critical enablers. However, the macro-energy system assessment of energy storage has often focused on isolated storage technologies and neglected competition between them, thus leaving out which e...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	364,777
1701.03918	Marked Temporal Dynamics Modeling based on Recurrent Neural Network	We are now witnessing the increasing availability of event stream data, i.e., a sequence of events with each event typically being denoted by the time it occurs and its mark information (e.g., event type). A fundamental problem is to model and predict such kind of marked temporal dynamics, i.e., when the next event wil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	66,778
2111.05174	CAESynth: Real-Time Timbre Interpolation and Pitch Control with Conditional Autoencoders	In this paper, we present a novel audio synthesizer, CAESynth, based on a conditional autoencoder. CAESynth synthesizes timbre in real-time by interpolating the reference sounds in their shared latent feature space, while controlling a pitch independently. We show that training a conditional autoencoder based on accura...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,713
2501.01371	CLIP-UP: CLIP-Based Unanswerable Problem Detection for Visual Question Answering	Recent Vision-Language Models (VLMs) have demonstrated remarkable capabilities in visual understanding and reasoning, and in particular on multiple-choice Visual Question Answering (VQA). Still, these models can make distinctly unnatural errors, for example, providing (wrong) answers to unanswerable VQA questions, such...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	522,037
1501.03924	On cyclic codes over $\mathbb{Z}_q+u\mathbb{Z}_q$	Let $R=\mathbb{Z}_q+u\mathbb{Z}_q$, where $q=p^s$ and $u^2=0$. In this paper, some structural properties of cyclic codes over the ring $R$ are considered. A necessary and sufficient condition for cyclic codes over the ring $R$ to be free is obtained and a BCH-type bound on the minimum Hamming distance for them is also ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,305
2112.09279	Robust Upper Bounds for Adversarial Training	Many state-of-the-art adversarial training methods for deep learning leverage upper bounds of the adversarial loss to provide security guarantees against adversarial attacks. Yet, these methods rely on convex relaxations to propagate lower and upper bounds for intermediate layers, which affect the tightness of the boun...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	272,094
2411.13908	Hybrid Physics-ML Modeling for Marine Vehicle Maneuvering Motions in the Presence of Environmental Disturbances	A hybrid physics-machine learning modeling framework is proposed for the surface vehicles' maneuvering motions to address the modeling capability and stability in the presence of environmental disturbances. From a deep learning perspective, the framework is based on a variant version of residual networks with additiona...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	509,968
2312.09877	Distributed Learning of Mixtures of Experts	In modern machine learning problems we deal with datasets that are either distributed by nature or potentially large for which distributing the computations is usually a standard way to proceed, since centralized algorithms are in general ineffective. We propose a distributed learning approach for mixtures of experts (...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	415,915
2112.13353	Novel Hybrid DNN Approaches for Speaker Verification in Emotional and Stressful Talking Environments	In this work, we conducted an empirical comparative study of the performance of text-independent speaker verification in emotional and stressful environments. This work combined deep models with shallow architecture, which resulted in novel hybrid classifiers. Four distinct hybrid models were utilized: deep neural netw...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,219
2107.13743	Malware Classification Using Transfer Learning	With the rapid growth of the number of devices on the Internet, malware poses a threat not only to the affected devices but also their ability to use said devices to launch attacks on the Internet ecosystem. Rapid malware classification is an important tools to combat that threat. One of the successful approaches to cl...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	248,290
2411.16164	Text-to-Image Synthesis: A Decade Survey	When humans read a specific text, they often visualize the corresponding images, and we hope that computers can do the same. Text-to-image synthesis (T2I), which focuses on generating high-quality images from textual descriptions, has become a significant aspect of Artificial Intelligence Generated Content (AIGC) and a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,926
1503.08223	A System View of the Recognition and Interpretation of Observed Human Shape, Pose and Action	There is physiological evidence that our ability to interpret human pose and action from 2D visual imagery (binocular or monocular) engages the circuitry of the motor cortices as well as the visual areas of the brain. This implies that the capability of the motor cortices to solve inverse kinematics is flexible enough ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	41,559
1312.6949	Joint Phase Tracking and Channel Decoding for OFDM Physical-Layer Network Coding	This paper investigates the problem of joint phase tracking and channel decoding in OFDM based Physical-layer Network Coding (PNC) systems. OFDM signaling can obviate the need for tight time synchronization among multiple simultaneous transmissions in the uplink of PNC systems. However, OFDM PNC systems are susceptible...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	29,424
1904.06535	Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes	Previous scene text detection methods have progressed substantially over the past years. However, limited by the receptive field of CNNs and the simple representations like rectangle bounding box or quadrangle adopted to describe text, previous methods may fall short when dealing with more challenging text instances, s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	127,574
2410.15804	Deep Learning and Data Augmentation for Detecting Self-Admitted Technical Debt	Self-Admitted Technical Debt (SATD) refers to circumstances where developers use textual artifacts to explain why the existing implementation is not optimal. Past research in detecting SATD has focused on either identifying SATD (classifying SATD items as SATD or not) or categorizing SATD (labeling instances as SATD th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	500,735
2410.14262	Good Parenting is all you need -- Multi-agentic LLM Hallucination Mitigation	This study explores the ability of Large Language Model (LLM) agents to detect and correct hallucinations in AI-generated content. A primary agent was tasked with creating a blog about a fictional Danish artist named Flipfloppidy, which was then reviewed by another agent for factual inaccuracies. Most LLMs hallucinated...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	499,961
1705.03430	Analysis of Channel-Based User Authentication by Key-Less and Key-Based Approaches	User authentication (UA) supports the receiver in deciding whether a message comes from the claimed transmitter or from an impersonating attacker. In cryptographic approaches messages are signed with either an asymmetric or symmetric key, and a source of randomness is required to generate the key. In physical layer aut...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	73,185
2305.14575	Towards Early Prediction of Human iPSC Reprogramming Success	This paper presents advancements in automated early-stage prediction of the success of reprogramming human induced pluripotent stem cells (iPSCs) as a potential source for regenerative cell therapies.The minuscule success rate of iPSC-reprogramming of around $ 0.01% $ to $ 0.1% $ makes it labor-intensive, time-consumin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	367,101
2210.17012	GotFlow3D: Recurrent Graph Optimal Transport for Learning 3D Flow Motion in Particle Tracking	Flow visualization technologies such as particle tracking velocimetry (PTV) are broadly used in understanding the all-pervasiveness three-dimensional (3D) turbulent flow from nature and industrial processes. Despite the advances in 3D acquisition techniques, the developed motion estimation algorithms in particle tracki...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	327,535
2306.13681	Estimating the Value of Evidence-Based Decision Making	Business/policy decisions are often based on evidence from randomized experiments and observational studies. In this article we propose an empirical framework to estimate the value of evidence-based decision making (EBDM) and the return on the investment in statistical precision.	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	375,360
2411.11479	Value-Spectrum: Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media Contexts	The recent progress in Vision-Language Models (VLMs) has broadened the scope of multimodal applications. However, evaluations often remain limited to functional tasks, neglecting abstract dimensions such as personality traits and human values. To address this gap, we introduce Value-Spectrum, a novel Visual Question An...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	509,068
2307.13977	Formal Verification of Robotic Contact Tasks via Reachability Analysis	Verifying the correct behavior of robots in contact tasks is challenging due to model uncertainties associated with contacts. Standard methods for testing often fall short since all (uncountable many) solutions cannot be obtained. Instead, we propose to formally and efficiently verify robot behaviors in contact tasks u...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	381,767
2305.05355	Turning Privacy-preserving Mechanisms against Federated Learning	Recently, researchers have successfully employed Graph Neural Networks (GNNs) to build enhanced recommender systems due to their capability to learn patterns from the interaction between involved entities. In addition, previous studies have investigated federated learning as the main solution to enable a native privacy...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	363,116
1609.06666	Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks	This paper proposes a computationally efficient approach to detecting objects natively in 3D point clouds using convolutional neural networks (CNNs). In particular, this is achieved by leveraging a feature-centric voting scheme to implement novel convolutional layers which explicitly exploit the sparsity encountered in...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	true	false	false	61,330
2401.05535	Theoretical and Empirical Advances in Forest Pruning	Decades after their inception, regression forests continue to provide state-of-the-art accuracy, outperforming in this respect alternative machine learning models such as regression trees or even neural networks. However, being an ensemble method, the one aspect where regression forests tend to severely underperform re...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	420,822
2208.06616	Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification	Learning time-series representations when only unlabeled data or few labeled samples are available can be a challenging task. Recently, contrastive self-supervised learning has shown great improvement in extracting useful representations from unlabeled data via contrasting different augmented views of data. In this wor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	312,773
2204.05490	Continuous-Time User Preference Modelling for Temporal Sets Prediction	Given a sequence of sets, where each set has a timestamp and contains an arbitrary number of elements, temporal sets prediction aims to predict the elements in the subsequent set. Previous studies for temporal sets prediction mainly focus on the modelling of elements and implicitly represent each user's preference base...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	291,040
2002.00518	Efficiency Analysis of the Simplified Refined Instrumental Variable Method for Continuous-time Systems	In this paper, we derive the asymptotic Cram\'er-Rao lower bound for the continuous-time output error model structure and provide an analysis of the statistical efficiency of the Simplified Refined Instrumental Variable method for Continuous-time systems (SRIVC) based on sampled data.It is shown that the asymptotic Cra...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	162,372
2311.02894	Design and Performance Analysis of a Class of Generalized Predictive Controllers	The design and structure of generalized predictive control (GPC) are not simple and intuitive. The performance analysis does not deeply analyze how the controller parameters affect the system characteristics and the relationship between the tracking error caused by the noise and the selected controller parameters. This...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	405,633
2209.12771	Hamiltonian Monte Carlo for efficient Gaussian sampling: long and random steps	Hamiltonian Monte Carlo (HMC) is a Markov chain algorithm for sampling from a high-dimensional distribution with density $e^{-f(x)}$, given access to the gradient of $f$. A particular case of interest is that of a $d$-dimensional Gaussian distribution with covariance matrix $\Sigma$, in which case $f(x) = x^\top \Sigma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	319,649
2404.01842	Semi-Supervised Domain Adaptation for Wildfire Detection	Recently, both the frequency and intensity of wildfires have increased worldwide, primarily due to climate change. In this paper, we propose a novel protocol for wildfire detection, leveraging semi-supervised Domain Adaptation for object detection, accompanied by a corresponding dataset designed for use by both academi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	443,609
2010.04947	Double Forward Propagation for Memorized Batch Normalization	Batch Normalization (BN) has been a standard component in designing deep neural networks (DNNs). Although the standard BN can significantly accelerate the training of DNNs and improve the generalization performance, it has several underlying limitations which may hamper the performance in both training and inference. I...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	199,933
2403.10663	Not Just Change the Labels, Learn the Features: Watermarking Deep Neural Networks with Multi-View Data	With the increasing prevalence of Machine Learning as a Service (MLaaS) platforms, there is a growing focus on deep neural network (DNN) watermarking techniques. These methods are used to facilitate the verification of ownership for a target DNN model to protect intellectual property. One of the most widely employed wa...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	438,292
2305.18927	Evaluating the feasibility of using Generative Models to generate Chest X-Ray Data	In this paper, we explore the feasibility of using generative models, specifically Progressive Growing GANs (PG-GANs) and Stable Diffusion fine-tuning, to generate synthetic chest X-ray images for medical diagnosis purposes. Due to ethical concerns, obtaining sufficient medical data for machine learning is a challenge,...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	369,302
2212.00186	Multi-Task Imitation Learning for Linear Dynamical Systems	We study representation learning for efficient imitation learning over linear systems. In particular, we consider a setting where learning is split into two phases: (a) a pre-training step where a shared $k$-dimensional representation is learned from $H$ source policies, and (b) a target policy fine-tuning step where t...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	333,963
2306.16906	Numerical Data Imputation for Multimodal Data Sets: A Probabilistic Nearest-Neighbor Kernel Density Approach	Numerical data imputation algorithms replace missing values by estimates to leverage incomplete data sets. Current imputation methods seek to minimize the error between the unobserved ground truth and the imputed values. But this strategy can create artifacts leading to poor imputation in the presence of multimodal or ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	376,526
2311.11278	Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection	Deepfake detection faces a critical generalization hurdle, with performance deteriorating when there is a mismatch between the distributions of training and testing data. A broadly received explanation is the tendency of these detectors to be overfitted to forgery-specific artifacts, rather than learning features that ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,883
2402.02399	FreDF: Learning to Forecast in Frequency Domain	Time series modeling is uniquely challenged by the presence of autocorrelation in both historical and label sequences. Current research predominantly focuses on handling autocorrelation within the historical sequence but often neglects its presence in the label sequence. Specifically, emerging forecast models mainly co...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	426,542
2206.06537	A software toolkit and hardware platform for investigating and comparing robot autonomy algorithms in simulation and reality	We describe a software framework and a hardware platform used in tandem for the design and analysis of robot autonomy algorithms in simulation and reality. The software, which is open source, containerized, and operating system (OS) independent, has three main components: a ROS 2 interface to a C++ vehicle simulation f...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	302,408
2101.06919	Link Prediction and Unlink Prediction on Dynamic Networks	Link prediction on dynamic networks has been extensively studied and widely applied in various applications. However, temporal unlink prediction, which also plays an important role in the evolution of social networks, has not been paid much attention. Accurately predicting the links and unlinks on the future network gr...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	215,886
nlin/0611054	A Model of a Trust-based Recommendation System on a Social Network	In this paper, we present a model of a trust-based recommendation system on a social network. The idea of the model is that agents use their social network to reach information and their trust relationships to filter it. We investigate how the dynamics of trust among agents affect the performance of the system by compa...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	540,796
2204.13091	Attention Consistency on Visual Corruptions for Single-Source Domain Generalization	Generalizing visual recognition models trained on a single distribution to unseen input distributions (i.e. domains) requires making them robust to superfluous correlations in the training set. In this work, we achieve this goal by altering the training images to simulate new domains and imposing consistent visual atte...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,702
2010.00979	BOSS: Bayesian Optimization over String Spaces	This article develops a Bayesian optimization (BO) method which acts directly over raw strings, proposing the first uses of string kernels and genetic algorithms within BO loops. Recent applications of BO over strings have been hindered by the need to map inputs into a smooth and unconstrained latent space. Learning th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	198,462
2208.07744	Secrecy Performance Analysis of RIS-aided Communication System with Randomly Flying Eavesdroppers	In this letter, we analyze the secrecy performance of a reconfigurable intelligent surface (RIS)-aided communication system with spatially random unmanned aerial vehicles (UAVs) acting as eavesdroppers. We consider the scenarios where the base station (BS) is equipped with single and multiple antennas.The signal-to-noi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	313,142
2004.04596	Global Public Health Surveillance using Media Reports: Redesigning GPHIN	Global public health surveillance relies on reporting structures and transmission of trustworthy health reports. But in practice, these processes may not always be fast enough, or are hindered by procedural, technical, or political barriers. GPHIN, the Global Public Health Intelligence Network, was designed in the late...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	171,926
2110.06884	ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers	We describe a Question Answering (QA) dataset that contains complex questions with conditional answers, i.e. the answers are only applicable when certain conditions apply. We call this dataset ConditionalQA. In addition to conditional answers, the dataset also features: (1) long context documents with information that ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	260,775
1811.01090	Value-based Search in Execution Space for Mapping Instructions to Programs	Training models to map natural language instructions to programs given target world supervision only requires searching for good programs at training time. Search is commonly done using beam search in the space of partial programs or program trees, but as the length of the instructions grows finding a good program beco...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	112,265
2401.06183	End to end Hindi to English speech conversion using Bark, mBART and a finetuned XLSR Wav2Vec2	Speech has long been a barrier to effective communication and connection, persisting as a challenge in our increasingly interconnected world. This research paper introduces a transformative solution to this persistent obstacle an end-to-end speech conversion framework tailored for Hindi-to-English translation, culminat...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	421,064
1212.1752	Hybrid Optimized Back propagation Learning Algorithm For Multi-layer Perceptron	Standard neural network based on general back propagation learning using delta method or gradient descent method has some great faults like poor optimization of error-weight objective function, low learning rate, instability .This paper introduces a hybrid supervised back propagation learning algorithm which uses trust...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	20,195
2402.18405	Multi-cell Coordinated Joint Sensing and Communications	This paper proposes block-level precoder (BLP) designs for a multi-input single-output (MISO) system that performs joint sensing and communication across multiple cells and users. The Cramer-Rao-Bound for estimating a target's azimuth angle is determined for coordinated beamforming (CBF) and coordinated multi-point (Co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	433,420
1207.7245	Autofocus Correction of Azimuth Phase Error and Residual Range Cell Migration in Spotlight SAR Polar Format Imagery	Synthetic aperture radar (SAR) images are often blurred by phase perturbations induced by uncompensated sensor motion and /or unknown propagation effects caused by turbulent media. To get refocused images, autofocus proves to be useful post-processing technique applied to estimate and compensate the unknown phase error...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	17,839
1902.00342	Tree-Sliced Variants of Wasserstein Distances	Optimal transport (\OT) theory defines a powerful set of tools to compare probability distributions. \OT~suffers however from a few drawbacks, computational and statistical, which have encouraged the proposal of several regularized variants of OT in the recent literature, one of the most notable being the \textit{slice...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,384
1906.07760	Tumor Saliency Estimation for Breast Ultrasound Images via Breast Anatomy Modeling	Tumor saliency estimation aims to localize tumors by modeling the visual stimuli in medical images. However, it is a challenging task for breast ultrasound due to the complicated anatomic structure of the breast and poor image quality; and existing saliency estimation approaches only model generic visual stimuli, e.g.,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	135,673
2408.10998	Audio Match Cutting: Finding and Creating Matching Audio Transitions in Movies and Videos	A "match cut" is a common video editing technique where a pair of shots that have a similar composition transition fluidly from one to another. Although match cuts are often visual, certain match cuts involve the fluid transition of audio, where sounds from different sources merge into one indistinguishable transition ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	482,112
2303.10895	Leapfrog Diffusion Model for Stochastic Trajectory Prediction	To model the indeterminacy of human behaviors, stochastic trajectory prediction requires a sophisticated multi-modal distribution of future trajectories. Emerging diffusion models have revealed their tremendous representation capacities in numerous generation tasks, showing potential for stochastic trajectory predictio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,624
2105.14370	BAAI-VANJEE Roadside Dataset: Towards the Connected Automated Vehicle Highway technologies in Challenging Environments of China	As the roadside perception plays an increasingly significant role in the Connected Automated Vehicle Highway(CAVH) technologies, there are immediate needs of challenging real-world roadside datasets for bench marking and training various computer vision tasks such as 2D/3D object detection and multi-sensor fusion. In t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	237,644
2411.13281	VideoAutoArena: An Automated Arena for Evaluating Large Multimodal Models in Video Analysis through User Simulation	Large multimodal models (LMMs) with advanced video analysis capabilities have recently garnered significant attention. However, most evaluations rely on traditional methods like multiple-choice questions in benchmarks such as VideoMME and LongVideoBench, which are prone to lack the depth needed to capture the complex d...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	true	509,740
2101.04804	Embedded Computer Vision System Applied to a Four-Legged Line Follower Robot	Robotics can be defined as the connection of perception to action. Taking this further, this project aims to drive a robot using an automated computer vision embedded system, connecting the robot's vision to its behavior. In order to implement a color recognition system on the robot, open source tools are chosen, such ...	false	false	false	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	215,238
2405.04691	Carbon Filter: Real-time Alert Triage Using Large Scale Clustering and Fast Search	"Alert fatigue" is one of the biggest challenges faced by the Security Operations Center (SOC) today, with analysts spending more than half of their time reviewing false alerts. Endpoint detection products raise alerts by pattern matching on event telemetry against behavioral rules that describe potentially malicious b...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	452,642
1509.00714	Dictionary based Approach to Edge Detection	Edge detection is a very essential part of image processing, as quality and accuracy of detection determines the success of further processing. We have developed a new self learning technique for edge detection using dictionary comprised of eigenfilters constructed using features of the input image. The dictionary base...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	46,526
2502.05147	LP-DETR: Layer-wise Progressive Relations for Object Detection	This paper presents LP-DETR (Layer-wise Progressive DETR), a novel approach that enhances DETR-based object detection through multi-scale relation modeling. Our method introduces learnable spatial relationships between object queries through a relation-aware self-attention mechanism, which adaptively learns to balance ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	531,459
cs/0609133	An application-oriented terminology evaluation: the case of back-of-the book indexes	This paper addresses the problem of computational terminology evaluation not per se but in a specific application context. This paper describes the evaluation procedure that has been used to assess the validity of our overall indexing approach and the quality of the IndDoc indexing tool. Even if user-oriented extended ...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	539,723
2306.17395	Real-time Optimization for Wind-to-H2 Driven Critical Infrastructures: High-fidelity Active Constraints and Integer Variables Prediction Enhanced by Feature Space Expansion	This paper focuses on developing a real-time optimal operation model for a new engineering system, wind-to-hydrogen-driven low-carbon critical infrastructure (W2H-LCCI), that utilizes wind power to generate hydrogen through electrolysis and combines it with carbon capture to reduce carbon emissions from the power secto...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	376,684
2306.11714	Meta-Analysis of Transfer Learning for Segmentation of Brain Lesions	A major challenge in stroke research and stroke recovery predictions is the determination of a stroke lesion's extent and its impact on relevant brain systems. Manual segmentation of stroke lesions from 3D magnetic resonance (MR) imaging volumes, the current gold standard, is not only very time-consuming, but its accur...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	374,684
2310.19046	Large Language Models as Evolutionary Optimizers	Evolutionary algorithms (EAs) have achieved remarkable success in tackling complex combinatorial optimization problems. However, EAs often demand carefully-designed operators with the aid of domain expertise to achieve satisfactory performance. In this work, we present the first study on large language models (LLMs) as...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	403,823
2301.04655	ChatGPT is not all you need. A State of the Art Review of large Generative AI models	During the last two years there has been a plethora of large generative models such as ChatGPT or Stable Diffusion that have been published. Concretely, these models are able to perform tasks such as being a general question and answering system or automatically creating artistic images that are revolutionizing several...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	340,135
2103.02843	Pandemic Drugs at Pandemic Speed: Infrastructure for Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers	The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	223,080
2110.02316	Prediction of the Facial Growth Direction is Challenging	Facial dysmorphology or malocclusion is frequently associated with abnormal growth of the face. The ability to predict facial growth (FG) direction would allow clinicians to prepare individualized therapy to increase the chance for successful treatment. Prediction of FG direction is a novel problem in the machine learn...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	259,073
2309.13064	InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning	We present a new financial domain large language model, InvestLM, tuned on LLaMA-65B (Touvron et al., 2023), using a carefully curated instruction dataset related to financial investment. Inspired by less-is-more-for-alignment (Zhou et al., 2023), we manually curate a small yet diverse instruction dataset, covering a w...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	394,039
2307.03440	A review of dynamics design methods for high-speed and high-precision CNC machine tool feed systems	With the development of CNC machine tools toward high speed and high precision, the traditional static design methods can hardly meet the demand. Hence, in this paper, the dynamics matching design methods of existing CNC machine tool feed systems were investigated and analyzed. Further, sub-system coupling mechanisms a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	378,044
1207.4155	Similarity-Driven Cluster Merging Method for Unsupervised Fuzzy Clustering	In this paper, a similarity-driven cluster merging method is proposed for unsuper-vised fuzzy clustering. The cluster merging method is used to resolve the problem of cluster validation. Starting with an overspecified number of clusters in the data, pairs of similar clusters are merged based on the proposed similarity-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	17,580
2404.16375	List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs	Set-of-Mark (SoM) Prompting unleashes the visual grounding capability of GPT-4V, by enabling the model to associate visual objects with tags inserted on the image. These tags, marked with alphanumerics, can be indexed via text tokens for easy reference. Despite the extraordinary performance from GPT-4V, we observe that...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	449,467
2001.06370	Approximating Activation Functions	ReLU is widely seen as the default choice for activation functions in neural networks. However, there are cases where more complicated functions are required. In particular, recurrent neural networks (such as LSTMs) make extensive use of both hyperbolic tangent and sigmoid functions. These functions are expensive to co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	160,787
2206.02391	Automated Circuit Sizing with Multi-objective Optimization based on Differential Evolution and Bayesian Inference	With the ever increasing complexity of specifications, manual sizing for analog circuits recently became very challenging. Especially for innovative, large-scale circuits designs, with tens of design variables, operating conditions and conflicting objectives to be optimized, design engineers spend many weeks, running t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	300,877
1508.02977	A massively parallel multi-level approach to a domain decomposition method for the optical flow estimation with varying illumination	We consider a variational method to solve the optical flow problem with varying illumination. We apply an adaptive control of the regularization parameter which allows us to preserve the edges and fine features of the computed flow. To reduce the complexity of the estimation for high resolution images and the time of c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,957
1711.06815	WAKE: Wavelet Decomposition Coupled with Adaptive Kalman Filtering for Pathological Tremor Extraction	Pathological Hand Tremor (PHT) is among common symptoms of several neurological movement disorders, which can significantly degrade quality of life of affected individuals. Beside pharmaceutical and surgical therapies, mechatronic technologies have been utilized to control PHTs. Most of these technologies function base...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	84,859
2407.02124	Data-Driven Subsynchronous Oscillation Suppression for Renewable Energy Integrated Power Systems Based on Koopman Operator	Recently, subsynchronous oscillations (SSOs) have emerged frequently worldwide, with the high penetration of renewable power generation in modern power systems. The SSO introduced by renewables has become a prominent new stability problem, seriously threatening the stable operation of systems. This paper proposes a dat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	469,596
2306.13154	Communication-Free Distributed Charging Control for Electric Vehicle Group	The disordered charging of electric vehicles (EVs) in residential areas leads to a rapid increase of the peak load, causing transformer overload, but the charging control of EV group can effectively alleviate this phenomenon. However, existing charging control methods need reliable two-way communication infrastructure,...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	375,181
2404.04197	Convex MPC and Thrust Allocation with Deadband for Spacecraft Rendezvous	This paper delves into a rendezvous scenario involving a chaser and a target spacecraft, focusing on the application of Model Predictive Control (MPC) to design a controller capable of guiding the chaser toward the target. The operational principle of spacecraft thrusters, requiring a minimum activation time that leads...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	444,540
2001.07688	Estimating international trade status of countries from global liner shipping networks	Maritime shipping is a backbone of international trade and, thus, the world economy. Cargo-loaded vessels travel from one country's port to another via an underlying port-to-port transport network, contributing to international trade values of countries en route. We hypothesize that ports that involve trans-shipment ac...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	161,101
2302.06247	Continuous-time convolutions model of event sequences	Event sequences often emerge in data mining. Modeling these sequences presents two main challenges: methodological and computational. Methodologically, event sequences are non-uniform and sparse, making traditional models unsuitable. Computationally, the vast amount of data and the significant length of each sequence n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	345,341
2404.09735	Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image Enhancement	Image restoration, which aims to recover high-quality images from their corrupted counterparts, often faces the challenge of being an ill-posed problem that allows multiple solutions for a single input. However, most deep learning based works simply employ l1 loss to train their network in a deterministic way, resultin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	446,811
2401.17738	Harnessing Smartwatch Microphone Sensors for Cough Detection and Classification	This study investigates the potential of using smartwatches with built-in microphone sensors for monitoring coughs and detecting various cough types. We conducted a study involving 32 participants and collected 9 hours of audio data in a controlled manner. Afterward, we processed this data using a structured approach, ...	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	425,305
2410.18727	Breaking Down the Barriers: Investigating Non-Expert User Experiences in Robotic Teleoperation in UK and Japan	Robots are being created each year with the goal of integrating them into our daily lives. As such, there is an interest in research in evaluating the trust of humans toward robots. In addition, teleoperating robotic arms can be challenging for non-experts. To reduce the strain put on the user, we created TELESIM, a mo...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	502,009
1911.05940	Distributional Clustering: A distribution-preserving clustering method	One key use of k-means clustering is to identify cluster prototypes which can serve as representative points for a dataset. However, a drawback of using k-means cluster centers as representative points is that such points distort the distribution of the underlying data. This can be highly disadvantageous in problems wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,415
1612.09027	On Covert Communication with Noise Uncertainty	Prior studies on covert communication with noise uncertainty adopted a worst-case approach from the warden's perspective. That is, the worst-case detection performance of the warden is used to assess covertness, which is overly optimistic. Instead of simply considering the worst limit, in this work, we take the distrib...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	66,141
2302.06083	Universal Agent Mixtures and the Geometry of Intelligence	Inspired by recent progress in multi-agent Reinforcement Learning (RL), in this work we examine the collective intelligent behaviour of theoretical universal agents by introducing a weighted mixture operation. Given a weighted set of agents, their weighted mixture is a new agent whose expected total reward in any envir...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	345,282
2209.06656	Syndrome decoding meets multiple instances	The NP-hard problem of decoding random linear codes is crucial to both coding theory and cryptography. In particular, this problem underpins the security of many code based post-quantum cryptographic schemes. The state-of-art algorithms for solving this problem are the information syndrome decoding algorithm and its ad...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	317,473
2410.24071	Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs	Achieving the no-regret property for Reinforcement Learning (RL) problems in continuous state and action-space environments is one of the major open problems in the field. Existing solutions either work under very specific assumptions or achieve bounds that are vacuous in some regimes. Furthermore, many structural assu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,316
2407.18480	Scalable Graph Compressed Convolutions	Designing effective graph neural networks (GNNs) with message passing has two fundamental challenges, i.e., determining optimal message-passing pathways and designing local aggregators. Previous methods of designing optimal pathways are limited with information loss on the input features. On the other hand, existing lo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	476,387

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