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
1606.02467	Point-wise mutual information-based video segmentation with high temporal consistency	In this paper, we tackle the problem of temporally consistent boundary detection and hierarchical segmentation in videos. While finding the best high-level reasoning of region assignments in videos is the focus of much recent research, temporal consistency in boundary detection has so far only rarely been tackled. We a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	56,966
2407.09548	Towards Temporal Change Explanations from Bi-Temporal Satellite Images	Explaining temporal changes between satellite images taken at different times is important for urban planning and environmental monitoring. However, manual dataset construction for the task is costly, so human-AI collaboration is promissing. Toward the direction, in this paper, we investigate the ability of Large-scale...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	472,636
2201.05972	Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentation	Two major challenges of 3D LiDAR Panoptic Segmentation (PS) are that point clouds of an object are surface-aggregated and thus hard to model the long-range dependency especially for large instances, and that objects are too close to separate each other. Recent literature addresses these problems by time-consuming group...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	275,571
2101.10721	Data sharing games	Data sharing issues pervade online social and economic environments. To foster social progress, it is important to develop models of the interaction between data producers and consumers that can promote the rise of cooperation between the involved parties. We formalize this interaction as a game, the data sharing game,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	217,026
1806.09076	Distributed Edge Caching in Ultra-dense Fog Radio Access Networks: A Mean Field Approach	In this paper, the edge caching problem in ultra-dense fog radio access networks (F-RAN) is investigated. Taking into account time-variant user requests and ultra-dense deployment of fog access points (F-APs), we propose a dynamic distributed edge caching scheme to jointly minimize the request service delay and frontha...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	101,287
2404.08095	Energy-Intensive Industries Providing Ancillary Services: A Real Case of Zinc Galvanizing Process	Energy-intensive industries can adapt to help balance the power grid. By using a real-world case study of a zinc galvanizing process in Denmark, we show how a modest investment in power control of the furnace enables the provision of various ancillary services. We consider two types of services, namely frequency contai...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	446,111
2307.07909	Is Imitation All You Need? Generalized Decision-Making with Dual-Phase Training	We introduce DualMind, a generalist agent designed to tackle various decision-making tasks that addresses challenges posed by current methods, such as overfitting behaviors and dependence on task-specific fine-tuning. DualMind uses a novel "Dual-phase" training strategy that emulates how humans learn to act in the worl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	379,584
2204.03873	Spatial Transformer Network on Skeleton-based Gait Recognition	Skeleton-based gait recognition models usually suffer from the robustness problem, as the Rank-1 accuracy varies from 90\% in normal walking cases to 70\% in walking with coats cases. In this work, we propose a state-of-the-art robust skeleton-based gait recognition model called Gait-TR, which is based on the combinati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	290,462
2007.05901	Shortened Linear Codes over Finite Fields	The puncturing and shortening technique are two important approaches to constructing new linear codes from old ones. In the past 70 years, a lot of progress on the puncturing technique has been made, and many works on punctured linear codes have been done. Many families of linear codes with interesting parameters have ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	186,822
2305.10216	CHMMOTv1 -- Cardiac and Hepatic Multi-Echo (T2*) MRI Images and Clinical Dataset for Iron Overload on Thalassemia Patients	Owing to the invasiveness and low accuracy of other tests, including biopsy and ferritin levels, magnetic resonance imaging (T2 and T2*-MRI) has been considered the standard test for patients with thalassemia (THM). Regarding deep learning networks in medical sciences for improving diagnosis and treatment purposes and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	364,958
1409.5040	Communities and Hierarchical Structures in Dynamic Social Networks: Analysis and Visualization	Detection of community structures in social networks has attracted lots of attention in the domain of sociology and behavioral sciences. Social networks also exhibit dynamic nature as these networks change continuously with the passage of time. Social networks might also present a hierarchical structure led by individu...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	36,130
0905.0192	Fuzzy Mnesors	A fuzzy mnesor space is a semimodule over the positive real numbers. It can be used as theoretical framework for fuzzy sets. Hence we can prove a great number of properties for fuzzy sets without refering to the membership functions.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	3,627
2406.00830	Collaborative Novel Object Discovery and Box-Guided Cross-Modal Alignment for Open-Vocabulary 3D Object Detection	Open-vocabulary 3D Object Detection (OV-3DDet) addresses the detection of objects from an arbitrary list of novel categories in 3D scenes, which remains a very challenging problem. In this work, we propose CoDAv2, a unified framework designed to innovatively tackle both the localization and classification of novel 3D o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	460,043
1411.7855	V-variable image compression	V-variable fractals, where $V$ is a positive integer, are intuitively fractals with at most $V$ different "forms" or "shapes" at all levels of magnification. In this paper we describe how V-variable fractals can be used for the purpose of image compression.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	37,968
2306.11128	CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning	Before taking actions in an environment with more than one intelligent agent, an autonomous agent may benefit from reasoning about the other agents and utilizing a notion of a guarantee or confidence about the behavior of the system. In this article, we propose a novel multi-agent reinforcement learning (MARL) algorith...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	374,483
2204.13874	OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak Supervision	Automatic extraction of product attributes from their textual descriptions is essential for online shopper experience. One inherent challenge of this task is the emerging nature of e-commerce products -- we see new types of products with their unique set of new attributes constantly. Most prior works on this matter min...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	293,974
2407.13303	Mean Teacher based SSL Framework for Indoor Localization Using Wi-Fi RSSI Fingerprinting	Wi-Fi fingerprinting is widely applied for indoor localization due to the widespread availability of Wi-Fi devices. However, traditional methods are not ideal for multi-building and multi-floor environments due to the scalability issues. Therefore, more and more researchers have employed deep learning techniques to ena...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	474,326
1804.08280	PlusEmo2Vec at SemEval-2018 Task 1: Exploiting emotion knowledge from emoji and #hashtags	This paper describes our system that has been submitted to SemEval-2018 Task 1: Affect in Tweets (AIT) to solve five subtasks. We focus on modeling both sentence and word level representations of emotion inside texts through large distantly labeled corpora with emojis and hashtags. We transfer the emotional knowledge b...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	95,734
2304.06469	Analysing Fairness of Privacy-Utility Mobility Models	Preserving the individuals' privacy in sharing spatial-temporal datasets is critical to prevent re-identification attacks based on unique trajectories. Existing privacy techniques tend to propose ideal privacy-utility tradeoffs, however, largely ignore the fairness implications of mobility models and whether such techn...	false	false	false	false	true	false	true	false	false	false	false	false	true	true	false	false	false	false	357,983
2004.04220	Determination of spatial configuration of an underwater swarm with minimum data	The subject is the localization problem of an underwater swarm of autonomous underwater robots (AUV), in the frame of the HARNESS project; by localization, we mean the relative swarm configuration, i.e., the geometrical shape of the group. The result is achieved by using the signals that the robots exchange. The swarm ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	171,812
2101.02047	Unified Learning Approach for Egocentric Hand Gesture Recognition and Fingertip Detection	Head-mounted device-based human-computer interaction often requires egocentric recognition of hand gestures and fingertips detection. In this paper, a unified approach of egocentric hand gesture recognition and fingertip detection is introduced. The proposed algorithm uses a single convolutional neural network to predi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	214,515
1810.02497	Compositional planning in Markov decision processes: Temporal abstraction meets generalized logic composition	In hierarchical planning for Markov decision processes (MDPs), temporal abstraction allows planning with macro-actions that take place at different time scale in form of sequential composition. In this paper, we propose a novel approach to compositional reasoning and hierarchical planning for MDPs under temporal logic ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	109,601
1810.08307	Reduction of Parameter Redundancy in Biaffine Classifiers with Symmetric and Circulant Weight Matrices	Currently, the biaffine classifier has been attracting attention as a method to introduce an attention mechanism into the modeling of binary relations. For instance, in the field of dependency parsing, the Deep Biaffine Parser by Dozat and Manning has achieved state-of-the-art performance as a graph-based dependency pa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	110,791
2411.04833	Finding Control Invariant Sets via Lipschitz Constants of Linear Programs	Control invariant sets play an important role in safety-critical control and find broad application in numerous fields such as obstacle avoidance for mobile robots. However, finding valid control invariant sets of dynamical systems under input limitations is notoriously difficult. We present an approach to safely expan...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	506,436
2203.00146	VaultDB: A Real-World Pilot of Secure Multi-Party Computation within a Clinical Research Network	Electronic health records represent a rich and growing source of clinical data for research. Privacy, regulatory, and institutional concerns limit the speed and ease of sharing this data. VaultDB is a framework for securely computing SQL queries over private data from two or more sources. It evaluates queries using sec...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	282,891
2010.07004	Binarization Methods for Motor-Imagery Brain-Computer Interface Classification	Successful motor-imagery brain-computer interface (MI-BCI) algorithms either extract a large number of handcrafted features and train a classifier, or combine feature extraction and classification within deep convolutional neural networks (CNNs). Both approaches typically result in a set of real-valued weights, that po...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	200,673
2011.00164	Differentially Private ADMM Algorithms for Machine Learning	In this paper, we study efficient differentially private alternating direction methods of multipliers (ADMM) via gradient perturbation for many machine learning problems. For smooth convex loss functions with (non)-smooth regularization, we propose the first differentially private ADMM (DP-ADMM) algorithm with performa...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	true	204,115
1803.01626	Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs	The problem of reinforcement learning in an unknown and discrete Markov Decision Process (MDP) under the average-reward criterion is considered, when the learner interacts with the system in a single stream of observations, starting from an initial state without any reset. We revisit the minimax lower bound for that pr...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	91,920
2401.16702	Multi-granularity Correspondence Learning from Long-term Noisy Videos	Existing video-language studies mainly focus on learning short video clips, leaving long-term temporal dependencies rarely explored due to over-high computational cost of modeling long videos. To address this issue, one feasible solution is learning the correspondence between video clips and captions, which however ine...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,943
1804.02156	OpenSeqSLAM2.0: An Open Source Toolbox for Visual Place Recognition Under Changing Conditions	Visually recognising a traversed route - regardless of whether seen during the day or night, in clear or inclement conditions, or in summer or winter - is an important capability for navigating robots. Since SeqSLAM was introduced in 2012, a large body of work has followed exploring how robotic systems can use the algo...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	94,352
2405.11399	An exact coverage path planning algorithm for UAV-based search and rescue operations	Unmanned aerial vehicles (UAVs) are increasingly utilized in global search and rescue efforts, enhancing operational efficiency. In these missions, a coordinated swarm of UAVs is deployed to efficiently cover expansive areas by capturing and analyzing aerial imagery and footage. Rapid coverage is paramount in these sce...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	455,117
2108.09682	Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification	Unsupervised Domain Adaptive (UDA) object re-identification (Re-ID) aims at adapting a model trained on a labeled source domain to an unlabeled target domain. State-of-the-art object Re-ID approaches adopt clustering algorithms to generate pseudo-labels for the unlabeled target domain. However, the inevitable label noi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	251,687
2206.01570	On Calibration of Graph Neural Networks for Node Classification	Graphs can model real-world, complex systems by representing entities and their interactions in terms of nodes and edges. To better exploit the graph structure, graph neural networks have been developed, which learn entity and edge embeddings for tasks such as node classification and link prediction. These models achie...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	300,522
1911.01167	HARQ-CC Enabled NOMA Designs With Outage Probability Constraints	In this paper, we aim to design an adaptive power allocation scheme to minimize the average transmit power of a hybrid automatic repeat request with chase combining (HARQ-CC) enabled non-orthogonal multiple access (NOMA) system under strict outage constraints of users. Specifically, we assume the base station only know...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	152,033
1010.5742	Stochastic Verification Theorem of Forward-Backward Controlled Systems for Viscosity Solutions	In this paper, we investigate the controlled system described by forward-backward stochastic differential equations with the control contained in drift, diffusion and generator of BSDE. A new verification theorem is derived within the framework of viscosity solutions without involving any derivatives of the value funct...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	8,050
2008.11239	HoloLens 2 Research Mode as a Tool for Computer Vision Research	Mixed reality headsets, such as the Microsoft HoloLens 2, are powerful sensing devices with integrated compute capabilities, which makes it an ideal platform for computer vision research. In this technical report, we present HoloLens 2 Research Mode, an API and a set of tools enabling access to the raw sensor streams. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	193,211
2312.00700	Generative Parameter-Efficient Fine-Tuning	We present Generative Parameter-Efficient Fine-Tuning (GIFT) for adapting pretrained Transformer backbones on downstream tasks. GIFT learns to generate the fine-tuned weights for a layer directly from its pretrained weights. The GIFT network is parameterized in a minimally-simple way by two linear layers (without bias ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	412,143
2308.06594	CoverNav: Cover Following Navigation Planning in Unstructured Outdoor Environment with Deep Reinforcement Learning	Autonomous navigation in offroad environments has been extensively studied in the robotics field. However, navigation in covert situations where an autonomous vehicle needs to remain hidden from outside observers remains an underexplored area. In this paper, we propose a novel Deep Reinforcement Learning (DRL) based al...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	385,196
1510.01315	Stochastic model for phonemes uncovers an author-dependency of their usage	We study rank-frequency relations for phonemes, the minimal units that still relate to linguistic meaning. We show that these relations can be described by the Dirichlet distribution, a direct analogue of the ideal-gas model in statistical mechanics. This description allows us to demonstrate that the rank-frequency rel...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	47,603
2105.04284	Boomerang uniformity of a class of power maps	We consider the boomerang uniformity of an infinite class of (locally-APN) power maps and show that its boomerang uniformity over the finite field $\F_{2^n}$ is $2$ and $4$, when $n \equiv 0 \pmod 4$ and $n \equiv 2 \pmod 4$, respectively. As a consequence, we show that for this class of power maps, the differential un...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	234,458
cs/0109010	Anaphora and Discourse Structure	We argue in this paper that many common adverbial phrases generally taken to signal a discourse relation between syntactically connected units within discourse structure, instead work anaphorically to contribute relational meaning, with only indirect dependence on discourse structure. This allows a simpler discourse st...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,411
2005.02549	Birth-Burst in Evolving Networks	The evolution of complex networks is governed by both growing rules and internal properties. Most evolving network models (e.g. preferential attachment) emphasize on the growing strategy, while neglecting the characteristics of individual nodes. In this study, we analyzed a widely studied network: the evolving protein-...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	175,903
2408.06872	Generative AI Tools in Academic Research: Applications and Implications for Qualitative and Quantitative Research Methodologies	This study examines the impact of Generative Artificial Intelligence (GenAI) on academic research, focusing on its application to qualitative and quantitative data analysis. As GenAI tools evolve rapidly, they offer new possibilities for enhancing research productivity and democratising complex analytical processes. Ho...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	480,375
2305.04039	Refining the Responses of LLMs by Themselves	In this paper, we propose a simple yet efficient approach based on prompt engineering that leverages the large language model itself to optimize its answers without relying on auxiliary models. We introduce an iterative self-evaluating optimization mechanism, with the potential for improved output quality as iterations...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	362,608
2502.13420	Probabilistically Robust Uncertainty Analysis and Optimal Control of Continuous Lyophilization via Polynomial Chaos Theory	Lyophilization, aka freeze drying, is a process commonly used to increase the stability of various drug products in biotherapeutics manufacturing, e.g., mRNA vaccines, allowing for higher storage temperature. While the current trends in the industry are moving towards continuous manufacturing, the majority of industria...	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	535,358
2201.11611	Asymmetric Coded Caching for Multi-Antenna Location-Dependent Content Delivery	Efficient usage of in-device storage and computation capabilities are key solutions to support data-intensive applications such as immersive digital experiences. This paper proposes a location-dependent multi-antenna coded caching -based content delivery scheme tailored specifically for wireless immersive viewing appli...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	277,340
2410.16295	Identification of Mean-Field Dynamics using Transformers	This paper investigates the use of transformer architectures to approximate the mean-field dynamics of interacting particle systems exhibiting collective behavior. Such systems are fundamental in modeling phenomena across physics, biology, and engineering, including gas dynamics, opinion formation, biological networks,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	500,968
2105.07745	Low-Input Accurate Periodic Motion of an Underactuated Mechanism: Mass Distribution and Nonlinear Spring Shaping	This work presents a control-oriented structural design approach for a 2-DOF underactuated mechanical system, with the purpose of generating an optimal oscillatory behavior of the end-effector. To achieve the desired periodic motion, we propose to adjust the dynamic response of the mechanism by selecting its mass distr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	235,543
2406.08876	Heuristics for Influence Maximization with Tiered Influence and Activation thresholds	The information flows among the people while they communicate through social media websites. Due to the dependency on digital media, a person shares important information or regular updates with friends and family. The set of persons on social media forms a social network. Influence Maximization (IM) is a known problem...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	463,670
1808.07456	Stacked Pooling: Improving Crowd Counting by Boosting Scale Invariance	In this work, we explore the cross-scale similarity in crowd counting scenario, in which the regions of different scales often exhibit high visual similarity. This feature is universal both within an image and across different images, indicating the importance of scale invariance of a crowd counting model. Motivated by...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	105,745
1708.00977	Network Community Detection: A Review and Visual Survey	Community structure is an important area of research. It has received a considerable attention from the scientific community. Despite its importance, one of the key problems in locating information about community detection is the diverse spread of related articles across various disciplines. To the best of our knowled...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	78,309
2106.02044	Heterogeneous Noisy Short Signal Camouflage in Multi-Domain Environment Decision-Making	Data transmission between two or more digital devices in industry and government demands secure and agile technology. Digital information distribution often requires deployment of Internet of Things (IoT) devices and Data Fusion techniques which have also gained popularity in both, civilian and military environments, s...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	238,709
1912.13436	30% Reach Increase via Low-complexity Hybrid HD/SD FEC and Nonlinearity-tolerant 4D Modulation	Current optical coherent transponders technology is driving data rates towards 1 Tb/s/{\lambda}and beyond. This trend requires both high-performance coded modulation schemes and efficient implementation of the forward-error-correction (FEC) decoder. A possible solution to this problem is combining advanced multidimensi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	159,079
2102.04883	Introduction to Machine Learning for the Sciences	This is an introductory machine-learning course specifically developed with STEM students in mind. Our goal is to provide the interested reader with the basics to employ machine learning in their own projects and to familiarize themself with the terminology as a foundation for further reading of the relevant literature...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,253
2404.17550	CoCar NextGen: a Multi-Purpose Platform for Connected Autonomous Driving Research	Real world testing is of vital importance to the success of automated driving. While many players in the business design purpose build testing vehicles, we designed and build a modular platform that offers high flexibility for any kind of scenario. CoCar NextGen is equipped with next generation hardware that addresses ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	449,896
2501.13071	Robust Body Composition Analysis by Generating 3D CT Volumes from Limited 2D Slices	Body composition analysis provides valuable insights into aging, disease progression, and overall health conditions. Due to concerns of radiation exposure, two-dimensional (2D) single-slice computed tomography (CT) imaging has been used repeatedly for body composition analysis. However, this approach introduces signifi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	526,544
1911.00760	GRAPHENE: A Precise Biomedical Literature Retrieval Engine with Graph Augmented Deep Learning and External Knowledge Empowerment	Effective biomedical literature retrieval (BLR) plays a central role in precision medicine informatics. In this paper, we propose GRAPHENE, which is a deep learning based framework for precise BLR. GRAPHENE consists of three main different modules 1) graph-augmented document representation learning; 2) query expansion ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	true	151,907
1812.06023	Advanced Super-Resolution using Lossless Pooling Convolutional Networks	In this paper, we present a novel deep learning-based approach for still image super-resolution, that unlike the mainstream models does not rely solely on the input low resolution image for high quality upsampling, and takes advantage of a set of artificially created auxiliary self-replicas of the input image that are ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	116,524
2112.11975	Page Segmentation using Visual Adjacency Analysis	Page segmentation is a web page analysis process that divides a page into cohesive segments, such as sidebars, headers, and footers. Current page segmentation approaches use either the DOM, textual content, or rendering style information of the page. However, these approaches have a number of drawbacks, such as a large...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	272,846
2002.00781	Towards an Operational Definition of Group Network Codes	Group network codes are a generalization of linear codes that have seen several studies over the last decade. When studying network codes, operations performed at internal network nodes called local encoding functions, are of significant interest. While local encoding functions of linear codes are well understood (and ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	162,466
1804.02419	Image Segmentation Using Subspace Representation and Sparse Decomposition	Image foreground extraction is a classical problem in image processing and vision, with a large range of applications. In this dissertation, we focus on the extraction of text and graphics in mixed-content images, and design novel approaches for various aspects of this problem. We first propose a sparse decomposition...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,397
2205.12215	DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages	We introduce DivEMT, the first publicly available post-editing study of Neural Machine Translation (NMT) over a typologically diverse set of target languages. Using a strictly controlled setup, 18 professional translators were instructed to translate or post-edit the same set of English documents into Arabic, Dutch, It...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	298,444
2009.08322	Moving with the Times: Investigating the Alt-Right Network Gab with Temporal Interaction Graphs	Gab is an online social network often associated with the alt-right political movement and users barred from other networks. It presents an interesting opportunity for research because near-complete data is available from day one of the network's creation. In this paper, we investigate the evolution of the user interac...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	196,206
2006.04421	Cyber-Physical Control of Indoor Multi-vehicle Testbed for Cooperative Driving	The system of connected vehicle to vehicle and vehicle to infrastructure can be considered as a wireless cyberphysical system of systems (Wireless CPSoS), which will be provided with the high ability of adaptive control on system of systems, cooperative scenarios to control of a Wireless CPSoS and adaptive wireless net...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	180,687
2409.14755	BranchPoseNet: Characterizing tree branching with a deep learning-based pose estimation approach	This paper presents an automated pipeline for detecting tree whorls in proximally laser scanning data using a pose-estimation deep learning model. Accurate whorl detection provides valuable insights into tree growth patterns, wood quality, and offers potential for use as a biometric marker to track trees throughout the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	490,618
2104.02045	A robust extended Kalman filter for power system dynamic state estimation using PMU measurements	This paper develops a robust extended Kalman filter to estimate the rotor angles and the rotor speeds of synchronous generators of a multimachine power system. Using a batch-mode regression form, the filter processes together predicted state vector and PMU measurements to track the system dynamics faster than the stand...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	228,571
2410.16512	TIPS: Text-Image Pretraining with Spatial Awareness	While image-text representation learning has become very popular in recent years, existing models tend to lack spatial awareness and have limited direct applicability for dense understanding tasks. For this reason, self-supervised image-only pretraining is still the go-to method for many dense vision applications (e.g....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	501,060
1903.10676	SciBERT: A Pretrained Language Model for Scientific Text	Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive. We release SciBERT, a pretrained language model based on BERT (Devlin et al., 2018) to address the lack of high-quality, large-scale labeled scientific data. SciBERT leverages unsupervised pretraining on a large mu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	125,337
2311.10811	A novel post-hoc explanation comparison metric and applications	Explanatory systems make the behavior of machine learning models more transparent, but are often inconsistent. To quantify the differences between explanatory systems, this paper presents the Shreyan Distance, a novel metric based on the weighted difference between ranked feature importance lists produced by such syste...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	408,681
cs/0603053	Automatic generation of simplified weakest preconditions for integrity constraint verification	Given a constraint $c$ assumed to hold on a database $B$ and an update $u$ to be performed on $B$, we address the following question: will $c$ still hold after $u$ is performed? When $B$ is a relational database, we define a confluent terminating rewriting system which, starting from $c$ and $u$, automatically derives ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	539,328
1802.03943	Temporal and volumetric denoising via quantile sparse image prior	This paper introduces an universal and structure-preserving regularization term, called quantile sparse image (QuaSI) prior. The prior is suitable for denoising images from various medical imaging modalities. We demonstrate its effectiveness on volumetric optical coherence tomography (OCT) and computed tomography (CT) ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	90,108
2006.09610	Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network	Noun phrases and relational phrases in Open Knowledge Bases are often not canonical, leading to redundant and ambiguous facts. In this work, we integrate structural information (from which tuple, which sentence) and semantic information (semantic similarity) to do the canonicalization. We represent the two types of inf...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	182,596
1605.06431	Residual Networks Behave Like Ensembles of Relatively Shallow Networks	In this work we propose a novel interpretation of residual networks showing that they can be seen as a collection of many paths of differing length. Moreover, residual networks seem to enable very deep networks by leveraging only the short paths during training. To support this observation, we rewrite residual networks...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	56,136
2311.11194	Testing with Non-identically Distributed Samples	We examine the extent to which sublinear-sample property testing and estimation applies to settings where samples are independently but not identically distributed. Specifically, we consider the following distributional property testing framework: Suppose there is a set of distributions over a discrete support of size ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	408,841
2211.09081	Secure SWIPT in the Multiuser STAR-RIS Aided MISO Rate Splitting Downlink	Recently, simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have emerged as a novel technology that provides 360 coverage and new degrees-of-freedom (DoFs). They are also capable of manipulating signal propagation and simultaneous wireless information and power transfer (SWIPT)....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	330,867
2406.16740	Learning the boundary-to-domain mapping using Lifting Product Fourier Neural Operators for partial differential equations	Neural operators such as the Fourier Neural Operator (FNO) have been shown to provide resolution-independent deep learning models that can learn mappings between function spaces. For example, an initial condition can be mapped to the solution of a partial differential equation (PDE) at a future time-step using a neural...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	467,252
2004.09846	SIBRE: Self Improvement Based REwards for Adaptive Feedback in Reinforcement Learning	We propose a generic reward shaping approach for improving the rate of convergence in reinforcement learning (RL), called Self Improvement Based REwards, or SIBRE. The approach is designed for use in conjunction with any existing RL algorithm, and consists of rewarding improvement over the agent's own past performance....	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	173,475
2411.14365	Formal Simulation and Visualisation of Hybrid Programs	The design and analysis of systems that combine computational behaviour with physical processes' continuous dynamics - such as movement, velocity, and voltage - is a famous, challenging task. Several theoretical results from programming theory emerged in the last decades to tackle the issue; some of which are the basis...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	510,126
1505.04342	Sifting Robotic from Organic Text: A Natural Language Approach for Detecting Automation on Twitter	Twitter, a popular social media outlet, has evolved into a vast source of linguistic data, rich with opinion, sentiment, and discussion. Due to the increasing popularity of Twitter, its perceived potential for exerting social influence has led to the rise of a diverse community of automatons, commonly referred to as bo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	43,174
2409.04743	GRVFL-MV: Graph Random Vector Functional Link Based on Multi-View Learning	The classification performance of the random vector functional link (RVFL), a randomized neural network, has been widely acknowledged. However, due to its shallow learning nature, RVFL often fails to consider all the relevant information available in a dataset. Additionally, it overlooks the geometrical properties of t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	486,489
2303.16386	Quantifying VIO Uncertainty	We compute the uncertainty of XIVO, a monocular visual-inertial odometry system based on the Extended Kalman Filter, in the presence of Gaussian noise, drift, and attribution errors in the feature tracks in addition to Gaussian noise and drift in the IMU. Uncertainty is computed using Monte-Carlo simulations of a suffi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	354,837
2112.14278	Beta-VAE Reproducibility: Challenges and Extensions	$\beta$-VAE is a follow-up technique to variational autoencoders that proposes special weighting of the KL divergence term in the VAE loss to obtain disentangled representations. Unsupervised learning is known to be brittle even on toy datasets and a meaningful, mathematically precise definition of disentanglement rema...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	273,480
1005.0961	Performance Oriented Query Processing In GEO Based Location Search Engines	Geographic location search engines allow users to constrain and order search results in an intuitive manner by focusing a query on a particular geographic region. Geographic search technology, also called location search, has recently received significant interest from major search engine companies. Academic research i...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	6,423
2408.07244	Sign language recognition based on deep learning and low-cost handcrafted descriptors	In recent years, deep learning techniques have been used to develop sign language recognition systems, potentially serving as a communication tool for millions of hearing-impaired individuals worldwide. However, there are inherent challenges in creating such systems. Firstly, it is important to consider as many linguis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	480,507
1308.6487	A New Algorithm of Speckle Filtering using Stochastic Distances	This paper presents a new approach for filter design based on stochastic distances and tests between distributions. A window is defined around each pixel, overlapping samples are compared and only those which pass a goodness-of-fit test are used to compute the filtered value. The technique is applied to intensity SAR d...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	true	26,718
2411.18905	FedRGL: Robust Federated Graph Learning for Label Noise	Federated Graph Learning (FGL) is a distributed machine learning paradigm based on graph neural networks, enabling secure and collaborative modeling of local graph data among clients. However, label noise can degrade the global model's generalization performance. Existing federated label noise learning methods, primari...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	512,047
1906.07492	Chemotaxis Based Virtual Fence for Swarm Robots in Unbounded Environments	This paper presents a novel swarm robotics application of chemotaxis behaviour observed in microorganisms. This approach was used to cause exploration robots to return to a work area around the swarm's nest within a boundless environment. We investigate the performance of our algorithm through extensive simulation stud...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	135,608
2005.09704	Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting	Recently data-driven image inpainting methods have made inspiring progress, impacting fundamental image editing tasks such as object removal and damaged image repairing. These methods are more effective than classic approaches, however, due to memory limitations they can only handle low-resolution inputs, typically sma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	177,983
1706.06279	Short-Term Forecasting of Passenger Demand under On-Demand Ride Services: A Spatio-Temporal Deep Learning Approach	Short-term passenger demand forecasting is of great importance to the on-demand ride service platform, which can incentivize vacant cars moving from over-supply regions to over-demand regions. The spatial dependences, temporal dependences, and exogenous dependences need to be considered simultaneously, however, which m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	75,655
2407.02648	STRIDE: An Open-Source, Low-Cost, and Versatile Bipedal Robot Platform for Research and Education	In this paper, we present STRIDE, a Simple, Terrestrial, Reconfigurable, Intelligent, Dynamic, and Educational bipedal platform. STRIDE aims to propel bipedal robotics research and education by providing a cost-effective implementation with step-by-step instructions for building a bipedal robotic platform while providi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	469,819
1404.1100	A Tutorial on Principal Component Analysis	Principal component analysis (PCA) is a mainstay of modern data analysis - a black box that is widely used but (sometimes) poorly understood. The goal of this paper is to dispel the magic behind this black box. This manuscript focuses on building a solid intuition for how and why principal component analysis works. Thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	32,076
2006.01216	Crowd simulation for crisis management: the outcomes of the last decade	The last few decades, crowd simulation for crisis management is highlighted as an important topic of interest for many scientific fields. As the continues evolution of computational resources increases, along with the capabilities of Artificial Intelligence, the demand for better and more realistic simulation has becom...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	179,706
2408.12890	Multiple Areal Feature Aware Transportation Demand Prediction	A reliable short-term transportation demand prediction supports the authorities in improving the capability of systems by optimizing schedules, adjusting fleet sizes, and generating new transit networks. A handful of research efforts incorporate one or a few areal features while learning spatio-temporal correlation, to...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	482,932
2307.09141	Machine Learning for SAT: Restricted Heuristics and New Graph Representations	Boolean satisfiability (SAT) is a fundamental NP-complete problem with many applications, including automated planning and scheduling. To solve large instances, SAT solvers have to rely on heuristics, e.g., choosing a branching variable in DPLL and CDCL solvers. Such heuristics can be improved with machine learning (ML...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	380,066
2501.17749	Early External Safety Testing of OpenAI's o3-mini: Insights from the Pre-Deployment Evaluation	Large Language Models (LLMs) have become an integral part of our daily lives. However, they impose certain risks, including those that can harm individuals' privacy, perpetuate biases and spread misinformation. These risks highlight the need for robust safety mechanisms, ethical guidelines, and thorough testing to ensu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	528,439
2003.05056	Multi-level Context Gating of Embedded Collective Knowledge for Medical Image Segmentation	Medical image segmentation has been very challenging due to the large variation of anatomy across different cases. Recent advances in deep learning frameworks have exhibited faster and more accurate performance in image segmentation. Among the existing networks, U-Net has been successfully applied on medical image segm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,751
2311.12824	Comparative Analysis of Shear Strength Prediction Models for Reinforced Concrete Slab-Column Connections	This research aims at comparative analysis of shear strength prediction at slab-column connection, unifying machine learning, design codes and Finite Element Analysis. Current design codes (CDCs) of ACI 318-19 (ACI), Eurocode 2 (EC2), Compressive Force Path (CFP) method, Feed Forward Neural Network (FNN) based Artifici...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	409,497
2104.07295	Variational Co-embedding Learning for Attributed Network Clustering	Recent works for attributed network clustering utilize graph convolution to obtain node embeddings and simultaneously perform clustering assignments on the embedding space. It is effective since graph convolution combines the structural and attributive information for node embedding learning. However, a major limitatio...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	230,371
1908.02745	Developing a Simple Model for Sand-Tool Interaction and Autonomously Shaping Sand	Autonomy for robots interacting with sand will enable a wide range of beneficial behaviors, from earth moving for construction and farming vehicles to navigating rough terrain for Mars rovers. The goal of this work is to shape sand into desired forms. Unlike other common autonomous tasks of achieving desired state of a...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	141,082
2108.00648	From LSAT: The Progress and Challenges of Complex Reasoning	Complex reasoning aims to draw a correct inference based on complex rules. As a hallmark of human intelligence, it involves a degree of explicit reading comprehension, interpretation of logical knowledge and complex rule application. In this paper, we take a step forward in complex reasoning by systematically studying ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	248,787

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