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
2006.16990	PriorGAN: Real Data Prior for Generative Adversarial Nets	Generative adversarial networks (GANs) have achieved rapid progress in learning rich data distributions. However, we argue about two main issues in existing techniques. First, the low quality problem where the learned distribution has massive low quality samples. Second, the missing modes problem where the learned dist...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	184,970
1502.08030	Author Name Disambiguation by Using Deep Neural Network	Author name ambiguity decreases the quality and reliability of information retrieved from digital libraries. Existing methods have tried to solve this problem by predefining a feature set based on expert's knowledge for a specific dataset. In this paper, we propose a new approach which uses deep neural network to learn...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	40,638
1201.2050	Adaptive Noise Reduction Scheme for Salt and Pepper	In this paper, a new adaptive noise reduction scheme for images corrupted by impulse noise is presented. The proposed scheme efficiently identifies and reduces salt and pepper noise. MAG (Mean Absolute Gradient) is used to identify pixels which are most likely corrupted by salt and pepper noise that are candidates for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	13,754
1406.5886	Weak Secrecy in the Multi-Way Untrusted Relay Channel with Compute-and-Forward	We investigate the problem of secure communications in a Gaussian multi-way relay channel applying the compute-and-forward scheme using nested lattice codes. All nodes employ half-duplex operation and can exchange confidential messages only via an untrusted relay. The relay is assumed to be honest but curious, i.e., an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,072
2501.12331	Cinepro: Robust Training of Foundation Models for Cancer Detection in Prostate Ultrasound Cineloops	Prostate cancer (PCa) detection using deep learning (DL) models has shown potential for enhancing real-time guidance during biopsies. However, prostate ultrasound images lack pixel-level cancer annotations, introducing label noise. Current approaches often focus on limited regions of interest (ROIs), disregarding anato...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	526,263
1610.03646	Multi 3D Camera Mapping for Predictive and Reflexive Robot Manipulator Trajectory Estimation	With advancing technologies, robotic manipulators and visual environment sensors are becoming cheaper and more widespread. However, robot control can be still a limiting factor for better adaptation of these technologies. Robotic manipulators are performing very well in structured workspaces, but do not adapt well to u...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	62,277
2402.15012	Ar-Spider: Text-to-SQL in Arabic	In Natural Language Processing (NLP), one of the most important tasks is text-to-SQL semantic parsing, which focuses on enabling users to interact with the database in a more natural manner. In recent years, text-to-SQL has made significant progress, but most were English-centric. In this paper, we introduce Ar-Spider ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	431,955
2301.10325	Using Arduino in Physics Experiments:Determining the Speed of Sound in Air	Considering the 21st century skills and the importance of STEM education in fulfilling these skills, it is clear that the course materials should be materials that bring students together with technology and attract their attention, apart from traditional materials. In addition, in terms of the applicability of these m...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	341,766
2011.09019	A Novel RIS-Assisted Modulation Scheme	In this work, in order to achieve higher spectrum efficiency, we propose a reconfigurable intelligent surface (RIS)-assisted multi-user communication uplink system. Different from previous work in which the RIS only optimizes the phase of the incident users's signal, we propose the use of the RIS to create a virtual co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	207,062
2011.04163	Chapter Captor: Text Segmentation in Novels	Books are typically segmented into chapters and sections, representing coherent subnarratives and topics. We investigate the task of predicting chapter boundaries, as a proxy for the general task of segmenting long texts. We build a Project Gutenberg chapter segmentation data set of 9,126 English novels, using a hybrid...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	205,485
2206.05575	MammoFL: Mammographic Breast Density Estimation using Federated Learning	In this study, we automate quantitative mammographic breast density estimation with neural networks and show that this tool is a strong use case for federated learning on multi-institutional datasets. Our dataset included bilateral CC-view and MLO-view mammographic images from two separate institutions. Two U-Nets were...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	302,055
2105.14314	Automatic CT Segmentation from Bounding Box Annotations using Convolutional Neural Networks	Accurate segmentation for medical images is important for clinical diagnosis. Existing automatic segmentation methods are mainly based on fully supervised learning and have an extremely high demand for precise annotations, which are very costly and time-consuming to obtain. To address this problem, we proposed an autom...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	237,623
2403.08103	Contextual Clarity: Generating Sentences with Transformer Models using Context-Reverso Data	In the age of information abundance, the ability to provide users with contextually relevant and concise information is crucial. Keyword in Context (KIC) generation is a task that plays a vital role in and generation applications, such as search engines, personal assistants, and content summarization. In this paper, we...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	437,171
2004.03852	Drone-aided Localization in LoRa IoT Networks	Besides being part of the Internet of Things (IoT), drones can play a relevant role in it as enablers. The 3D mobility of UAVs can be exploited to improve node localization in IoT networks for, e.g., search and rescue or goods localization and tracking. One of the widespread IoT communication technologies is Long Range...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	171,709
2405.03545	Optimizing Hand Region Detection in MediaPipe Holistic Full-Body Pose Estimation to Improve Accuracy and Avoid Downstream Errors	This paper addresses a critical flaw in MediaPipe Holistic's hand Region of Interest (ROI) prediction, which struggles with non-ideal hand orientations, affecting sign language recognition accuracy. We propose a data-driven approach to enhance ROI estimation, leveraging an enriched feature set including additional hand...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	452,222
2407.07924	Solving General Natural-Language-Description Optimization Problems with Large Language Models	Optimization problems seek to find the best solution to an objective under a set of constraints, and have been widely investigated in real-world applications. Modeling and solving optimization problems in a specific domain typically require a combination of domain knowledge, mathematical skills, and programming ability...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	471,951
2406.07869	Unveiling the Power of Wavelets: A Wavelet-based Kolmogorov-Arnold Network for Hyperspectral Image Classification	Hyperspectral image classification is a crucial but challenging task due to the high dimensionality and complex spatial-spectral correlations inherent in hyperspectral data. This paper employs Wavelet-based Kolmogorov-Arnold Network (wav-kan) architecture tailored for efficient modeling of these intricate dependencies....	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	463,249
2403.08829	Mitigating Biases in Collective Decision-Making: Enhancing Performance in the Face of Fake News	Individual and social biases undermine the effectiveness of human advisers by inducing judgment errors which can disadvantage protected groups. In this paper, we study the influence these biases can have in the pervasive problem of fake news by evaluating human participants' capacity to identify false headlines. By foc...	true	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	437,502
cmp-lg/9702011	How much has information technology contributed to linguistics?	Information technology should have much to offer linguistics, not only through the opportunities offered by large-scale data analysis and the stimulus to develop formal computational models, but through the chance to use language in systems for automatic natural language processing. The paper discusses these possibilit...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,698
2502.12478	MSE-Adapter: A Lightweight Plugin Endowing LLMs with the Capability to Perform Multimodal Sentiment Analysis and Emotion Recognition	Current Multimodal Sentiment Analysis (MSA) and Emotion Recognition in Conversations (ERC) methods based on pre-trained language models exhibit two primary limitations: 1) Once trained for MSA and ERC tasks, these pre-trained language models lose their original generalized capabilities. 2) They demand considerable co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	534,886
2406.17890	SigKAN: Signature-Weighted Kolmogorov-Arnold Networks for Time Series	We propose a novel approach that enhances multivariate function approximation using learnable path signatures and Kolmogorov-Arnold networks (KANs). We enhance the learning capabilities of these networks by weighting the values obtained by KANs using learnable path signatures, which capture important geometric features...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	467,777
2409.02826	Automatic facial axes standardization of 3D fetal ultrasound images	Craniofacial anomalies indicate early developmental disturbances and are usually linked to many genetic syndromes. Early diagnosis is critical, yet ultrasound (US) examinations often fail to identify these features. This study presents an AI-driven tool to assist clinicians in standardizing fetal facial axes/planes in ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,841
2111.11980	Scalable Learning for Optimal Load Shedding Under Power Grid Emergency Operations	Effective and timely responses to unexpected contingencies are crucial for enhancing the resilience of power grids. Given the fast, complex process of cascading propagation, corrective actions such as optimal load shedding (OLS) are difficult to attain in large-scale networks due to the computation complexity and commu...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	267,836
2011.01522	Higher-Order Moment-Based Anomaly Detection	The identification of anomalies is a critical component of operating complex, and possibly large-scale and geo-graphically distributed cyber-physical systems. While designing anomaly detectors, it is common to assume Gaussian noise models to maintain tractability; however, this assumption can lead to the actual false a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	204,618
1904.04805	Embodied Neuromorphic Vision with Event-Driven Random Backpropagation	Spike-based communication between biological neurons is sparse and unreliable. This enables the brain to process visual information from the eyes efficiently. Taking inspiration from biology, artificial spiking neural networks coupled with silicon retinas attempt to model these computations. Recent findings in machine ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	127,133
2409.00638	IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching	Stereo matching is a core component in many computer vision and robotics systems. Despite significant advances over the last decade, handling matching ambiguities in ill-posed regions and large disparities remains an open challenge. In this paper, we propose a new deep network architecture, called IGEV++, for stereo ma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,010
2410.09643	Multimodal Physical Activity Forecasting in Free-Living Clinical Settings: Hunting Opportunities for Just-in-Time Interventions	Objective: This research aims to develop a lifestyle intervention system, called MoveSense, that forecasts a patient's activity behavior to allow for early and personalized interventions in real-world clinical environments. Methods: We conducted two clinical studies involving 58 prediabetic veterans and 60 patients wit...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	497,697
2001.04794	A machine learning approach to investigate regulatory control circuits in bacterial metabolic pathways	In this work, a machine learning approach for identifying the multi-omics metabolic regulatory control circuits inside the pathways is described. Therefore, the identification of bacterial metabolic pathways that are more regulated than others in term of their multi-omics follows from the analysis of these circuits . T...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,357
1412.3773	Distinguishing cause from effect using observational data: methods and benchmarks	The discovery of causal relationships from purely observational data is a fundamental problem in science. The most elementary form of such a causal discovery problem is to decide whether X causes Y or, alternatively, Y causes X, given joint observations of two variables X, Y. An example is to decide whether altitude ca...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	38,320
1901.09890	Few-shot Learning with Meta Metric Learners	Few-shot Learning aims to learn classifiers for new classes with only a few training examples per class. Existing meta-learning or metric-learning based few-shot learning approaches are limited in handling diverse domains with various number of labels. The meta-learning approaches train a meta learner to predict weight...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	119,870
2501.15598	Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images	Spatial Transcriptomics (ST) allows a high-resolution measurement of RNA sequence abundance by systematically connecting cell morphology depicted in Hematoxylin and Eosin (H&E) stained histology images to spatially resolved gene expressions. ST is a time-consuming, expensive yet powerful experimental technique that pro...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	527,628
2109.13098	One-Hot Graph Encoder Embedding	In this paper we propose a lightning fast graph embedding method called one-hot graph encoder embedding. It has a linear computational complexity and the capacity to process billions of edges within minutes on standard PC -- making it an ideal candidate for huge graph processing. It is applicable to either adjacency ma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	257,526
2211.03796	Astronomia ex machina: a history, primer, and outlook on neural networks in astronomy	In this review, we explore the historical development and future prospects of artificial intelligence (AI) and deep learning in astronomy. We trace the evolution of connectionism in astronomy through its three waves, from the early use of multilayer perceptrons, to the rise of convolutional and recurrent neural network...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	329,043
2306.11103	Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target Imputation	In prediction of forest parameters with data from remote sensing (RS), regression models have traditionally been trained on a small sample of ground reference data. This paper proposes to impute this sample of true prediction targets with data from an existing RS-based prediction map that we consider as pseudo-targets....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	374,472
2501.14317	Nautilus: Locality-aware Autoencoder for Scalable Mesh Generation	Triangle meshes are fundamental to 3D applications, enabling efficient modification and rasterization while maintaining compatibility with standard rendering pipelines. However, current automatic mesh generation methods typically rely on intermediate representations that lack the continuous surface quality inherent to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	527,079
1106.1933	Lyapunov stochastic stability and control of robust dynamic coalitional games with transferable utilities	This paper considers a dynamic game with transferable utilities (TU), where the characteristic function is a continuous-time bounded mean ergodic process. A central planner interacts continuously over time with the players by choosing the instantaneous allocations subject to budget constraints. Before the game starts, ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	10,801
2303.15365	Impulse excitation diagram as a tool to achieve high energy orbits	The paper presents the application of a new impulse excitation diagram (IED) to help realize high-energy orbits in nonlinear energy harvesting systems. In the case of non-linearity, we can deal with the occurrence of coexisting solutions and the proposed diagram allows for the use of the impulse excitation method in or...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	354,463
2205.15019	Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models	Proteins are macromolecules that mediate a significant fraction of the cellular processes that underlie life. An important task in bioengineering is designing proteins with specific 3D structures and chemical properties which enable targeted functions. To this end, we introduce a generative model of both protein struct...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	299,573
2410.02338	How Much Can RAG Help the Reasoning of LLM?	Retrieval-Augmented Generation (RAG) has gained significant popularity in modern Large Language Models (LLMs) due to its effectiveness in introducing new knowledge and reducing hallucinations. However, the deep understanding of RAG remains limited, how does RAG help the reasoning process and can RAG help improve the re...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	494,234
1801.00431	Ultra-Reliable Cooperative Short-Packet Communications with Wireless Energy Transfer	We analyze a cooperative wireless communication system with finite block length and finite battery energy, under quasi-static Rayleigh fading. Source and relay nodes are powered by a wireless energy transfer (WET) process, while using the harvested energy to feed their circuits, send pilot signals to estimate channels ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,563
1909.03794	Composing Knowledge Graph Embeddings via Word Embeddings	Learning knowledge graph embedding from an existing knowledge graph is very important to knowledge graph completion. For a fact $(h,r,t)$ with the head entity $h$ having a relation $r$ with the tail entity $t$, the current approaches aim to learn low dimensional representations $(\mathbf{h},\mathbf{r},\mathbf{t})$, eac...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	144,604
2201.08237	Simple Gray Coding and LLR Calculation for MDS Modulation Systems	Due to dependence between codeword elements, index modulation (IM) and related modulation techniques struggle to provide simple solutions for practical problems such as Gray coding between information bits and constellation points; and low-complexity log-likelihood ratio (LLR) calculations for channel-encoded informati...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	276,273
2104.14741	Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads	Vision-and-Language (VL) pre-training has shown great potential on many related downstream tasks, such as Visual Question Answering (VQA), one of the most popular problems in the VL field. All of these pre-trained models (such as VisualBERT, ViLBERT, LXMERT and UNITER) are built with Transformer, which extends the clas...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,924
2208.03385	Trust-Aware Control of Automated Vehicles in Car-Following Interactions with Human Drivers	Trust is essential for automated vehicles (AVs) to promote and sustain technology acceptance in human-dominated traffic scenarios. However, computational trust dynamic models describing the interactive relationship between the AVs and surrounding human drivers in traffic rarely exist. This paper aims to fill this gap b...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	311,770
1001.2623	A Steganography Based on CT-CDMA Communication Scheme Using Complete Complementary Codes	It has been shown that complete complementary codes can be applied into some communication systems like approximately synchronized CDMA systems because of its good correlation properties. CT-CDMA is one of the communication systems based on complete complementary codes. In this system, the information data of the multi...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	5,404
1103.2493	A Constrained Evolutionary Gaussian Multiple Access Channel Game	In this paper, we formulate an evolutionary multiple access channel game with continuous-variable actions and coupled rate constraints. We characterize Nash equilibria of the game and show that the pure Nash equilibria are Pareto optimal and also resilient to deviations by coalitions of any size, i.e., they are strong ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	9,587
2003.13388	ML4Chem: A Machine Learning Package for Chemistry and Materials Science	ML4Chem is an open-source machine learning library for chemistry and materials science. It provides an extendable platform to develop and deploy machine learning models and pipelines and is targeted to the non-expert and expert users. ML4Chem follows user-experience design and offers the needed tools to go from data pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	170,195
1702.02012	Tracking using Numerous Anchor points	In this paper, an online adaptive model-free tracker is proposed to track single objects in video sequences to deal with real-world tracking challenges like low-resolution, object deformation, occlusion and motion blur. The novelty lies in the construction of a strong appearance model that captures features from the in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	67,910
2410.22895	Combining psychoanalysis and computer science: an empirical study of the relationship between emotions and the Lacanian discourses	This research explores the interdisciplinary interaction between psychoanalysis and computer science, suggesting a mutually beneficial exchange. Indeed, psychoanalytic concepts can enrich technological applications involving unconscious, elusive aspects of the human factor, such as social media and other interactive di...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	503,815
2305.00408	New sets of Non-Orthogonal Spreading Sequences With Low Correlation and Low PAPR Using Extended Boolean Functions	Extended Boolean functions (EBFs) are one of the most important tools in cryptography and spreading sequence design in communication systems. In this paper, we use EBFs to design new sets of spreading sequences for non-orthogonal multiple access (NOMA), which is an emerging technique capable of supporting massive machi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	361,327
1712.08349	Tracking the Diffusion of Named Entities	Existing studies of how information diffuses across social networks have thus far concentrated on analysing and recovering the spread of deterministic innovations such as URLs, hashtags, and group membership. However investigating how mentions of real-world entities appear and spread has yet to be explored, largely due...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	87,180
2306.02492	RadLing: Towards Efficient Radiology Report Understanding	Most natural language tasks in the radiology domain use language models pre-trained on biomedical corpus. There are few pretrained language models trained specifically for radiology, and fewer still that have been trained in a low data setting and gone on to produce comparable results in fine-tuning tasks. We present R...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	370,920
1609.09546	Dynamic Models of Appraisal Networks Explaining Collective Learning	This paper proposes models of learning process in teams of individuals who collectively execute a sequence of tasks and whose actions are determined by individual skill levels and networks of interpersonal appraisals and influence. The closely-related proposed models have increasing complexity, starting with a centrali...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	false	false	61,738
1807.05696	LineNet: a Zoomable CNN for Crowdsourced High Definition Maps Modeling in Urban Environments	High Definition (HD) maps play an important role in modern traffic scenes. However, the development of HD maps coverage grows slowly because of the cost limitation. To efficiently model HD maps, we proposed a convolutional neural network with a novel prediction layer and a zoom module, called LineNet. It is designed fo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	102,978
1909.07814	CrypTFlow: Secure TensorFlow Inference	We present CrypTFlow, a first of its kind system that converts TensorFlow inference code into Secure Multi-party Computation (MPC) protocols at the push of a button. To do this, we build three components. Our first component, Athos, is an end-to-end compiler from TensorFlow to a variety of semi-honest MPC protocols. Th...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	145,782
2211.04362	Hyperparameter optimization in deep multi-target prediction	As a result of the ever increasing complexity of configuring and fine-tuning machine learning models, the field of automated machine learning (AutoML) has emerged over the past decade. However, software implementations like Auto-WEKA and Auto-sklearn typically focus on classical machine learning (ML) tasks such as clas...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	329,224
1806.03028	Unsupervised Feature Learning Toward a Real-time Vehicle Make and Model Recognition	Vehicle Make and Model Recognition (MMR) systems provide a fully automatic framework to recognize and classify different vehicle models. Several approaches have been proposed to address this challenge, however they can perform in restricted conditions. Here, we formulate the vehicle make and model recognition as a fine...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	99,915
1908.02460	Edge-guided Non-local Fully Convolutional Network for Salient Object Detection	Fully Convolutional Neural Network (FCN) has been widely applied to salient object detection recently by virtue of high-level semantic feature extraction, but existing FCN based methods still suffer from continuous striding and pooling operations leading to loss of spatial structure and blurred edges. To maintain the c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	141,009
2306.08630	High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models	We present a novel method that integrates subspace modeling with an adaptive generative image prior for high-dimensional MR image reconstruction. The subspace model imposes an explicit low-dimensional representation of the high-dimensional images, while the generative image prior serves as a spatial constraint on the "...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	373,473
2403.02618	TinyGC-Net: An Extremely Tiny Network for Calibrating MEMS Gyroscopes	This paper presents a learning-based method for calibrating and denoising microelectromechanical system (MEMS) gyroscopes, which is designed based on a convolutional network, and only contains hundreds of parameters, so the network can be trained on a graphics processing unit (GPU) before being deployed on a microcontr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	434,869
2109.12414	Vehicle Detection and Tracking From Surveillance Cameras in Urban Scenes	Detecting and tracking vehicles in urban scenes is a crucial step in many traffic-related applications as it helps to improve road user safety among other benefits. Various challenges remain unresolved in multi-object tracking (MOT) including target information description, long-term occlusions and fast motion. We prop...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	257,277
1912.09601	Divide and Conquer: an Accurate Machine Learning Algorithm to Process Split Videos on a Parallel Processing Infrastructure	Every day the number of traffic cameras in cities rapidly increase and huge amount of video data are generated. Parallel processing infrastruture, such as Hadoop, and programming models, such as MapReduce, are being used to promptly process that amount of data. The common approach for video processing by using Hadoop M...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	158,114
1011.3189	Warping Peirce Quincuncial Panoramas	The Peirce quincuncial projection is a mapping of the surface of a sphere to the interior of a square. It is a conformal map except for four points on the equator. These points of non-conformality cause significant artifacts in photographic applications. In this paper, we propose an algorithm and user-interface to miti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	8,231
2103.02324	Estimating the Expected Influence Capacities of Nodes in Complex Networks under the Susceptible-Infectious-Recovered (SIR) Model	In recent years, epidemic modeling in complex networks has found many applications, including modeling of information or gossip spread in online social networks, modeling of malware spread in communication networks, and the most recent model of the COVID-19 pandemic. If the information disseminated is accurate, for exa...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	222,923
2411.04308	Improving Bilingual Capabilities of Language Models to Support Diverse Linguistic Practices in Education	Large language models (LLMs) offer promise in generating educational content, providing instructor feedback, and reducing teacher workload on assessments. While prior studies have focused on studying LLM-powered learning analytics, limited research has examined how effective LLMs are in a bilingual context. In this pap...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	506,216
0809.1686	Agent-based Ecological Model Calibration - on the Edge of a New Approach	The purpose of this paper is to present a new approach to ecological model calibration -- an agent-based software. This agent works on three stages: 1- It builds a matrix that synthesizes the inter-variable relationships; 2- It analyses the steady-state sensitivity of different variables to different parameters; 3- It ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	2,323
1902.03081	Size Independent Neural Transfer for RDDL Planning	Neural planners for RDDL MDPs produce deep reactive policies in an offline fashion. These scale well with large domains, but are sample inefficient and time-consuming to train from scratch for each new problem. To mitigate this, recent work has studied neural transfer learning, so that a generic planner trained on othe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	121,011
2312.09744	Bridging the Semantic-Numerical Gap: A Numerical Reasoning Method of Cross-modal Knowledge Graph for Material Property Prediction	Using machine learning (ML) techniques to predict material properties is a crucial research topic. These properties depend on numerical data and semantic factors. Due to the limitations of small-sample datasets, existing methods typically adopt ML algorithms to regress numerical properties or transfer other pre-trained...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	415,864
2202.03199	AI Research Associate for Early-Stage Scientific Discovery	Artificial intelligence (AI) has been increasingly applied in scientific activities for decades; however, it is still far from an insightful and trustworthy collaborator in the scientific process. Most existing AI methods are either too simplistic to be useful in real problems faced by scientists or too domain-speciali...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	279,115
1407.2683	A Real-Time Detecting Algorithm for Tracking Community Structure of Dynamic Networks	In this paper a simple but efficient real-time detecting algorithm is proposed for tracking community structure of dynamic networks. Community structure is intuitively characterized as divisions of network nodes into subgroups, within which nodes are densely connected while between which they are sparsely connected. To...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	34,550
2011.11190	Attentional-GCNN: Adaptive Pedestrian Trajectory Prediction towards Generic Autonomous Vehicle Use Cases	Autonomous vehicle navigation in shared pedestrian environments requires the ability to predict future crowd motion both accurately and with minimal delay. Understanding the uncertainty of the prediction is also crucial. Most existing approaches however can only estimate uncertainty through repeated sampling of generat...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	207,747
2210.17463	Domain Curricula for Code-Switched MT at MixMT 2022	In multilingual colloquial settings, it is a habitual occurrence to compose expressions of text or speech containing tokens or phrases of different languages, a phenomenon popularly known as code-switching or code-mixing (CMX). We present our approach and results for the Code-mixed Machine Translation (MixMT) shared ta...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	327,699
2306.10649	CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification	In the investment industry, it is often essential to carry out fine-grained company similarity quantification for a range of purposes, including market mapping, competitor analysis, and mergers and acquisitions. We propose and publish a knowledge graph, named CompanyKG, to represent and learn diverse company features a...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	374,307
2304.01576	MESAHA-Net: Multi-Encoders based Self-Adaptive Hard Attention Network with Maximum Intensity Projections for Lung Nodule Segmentation in CT Scan	Accurate lung nodule segmentation is crucial for early-stage lung cancer diagnosis, as it can substantially enhance patient survival rates. Computed tomography (CT) images are widely employed for early diagnosis in lung nodule analysis. However, the heterogeneity of lung nodules, size diversity, and the complexity of t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	356,138
1901.10457	Universal Dependency Parsing from Scratch	This paper describes Stanford's system at the CoNLL 2018 UD Shared Task. We introduce a complete neural pipeline system that takes raw text as input, and performs all tasks required by the shared task, ranging from tokenization and sentence segmentation, to POS tagging and dependency parsing. Our single system submissi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	120,025
1803.01462	Optimal Status Updating for an Energy Harvesting Sensor with a Noisy Channel	Consider an energy harvesting sensor continuously monitors a system and sends time-stamped status update to a destination. The destination keeps track of the system status through the received updates. Under the energy causality constraint at the sensor, our objective is to design an optimal online status updating poli...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	91,883
2405.16334	Devil's Advocate: Anticipatory Reflection for LLM Agents	In this work, we introduce a novel approach that equips LLM agents with introspection, enhancing consistency and adaptability in solving complex tasks. Our approach prompts LLM agents to decompose a given task into manageable subtasks (i.e., to make a plan), and to continuously introspect upon the suitability and resul...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	457,363
2112.01167	Multi-scale simulation of COVID-19 epidemics	Over a year after the start of the COVID-19 epidemics, we are still facing the virus and it is hard to correctly predict its future spread over weeks to come, as well as the impacts of potential political interventions. Current epidemic models mainly fall in two approaches: compartmental models, divide the population i...	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	269,395
1912.09670	Adversarial symmetric GANs: bridging adversarial samples and adversarial networks	Generative adversarial networks have achieved remarkable performance on various tasks but suffer from training instability. Despite many training strategies proposed to improve training stability, this issue remains as a challenge. In this paper, we investigate the training instability from the perspective of adversari...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	158,132
2404.03202	OmniGS: Fast Radiance Field Reconstruction using Omnidirectional Gaussian Splatting	Photorealistic reconstruction relying on 3D Gaussian Splatting has shown promising potential in various domains. However, the current 3D Gaussian Splatting system only supports radiance field reconstruction using undistorted perspective images. In this paper, we present OmniGS, a novel omnidirectional Gaussian splattin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,163
2406.01414	CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework	This work presents a novel approach to neural architecture search (NAS) that aims to increase carbon efficiency for the model design process. The proposed framework CE-NAS addresses the key challenge of high carbon cost associated with NAS by exploring the carbon emission variations of energy and energy differences of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	460,303
2210.10763	On the Feasibility of Cross-Task Transfer with Model-Based Reinforcement Learning	Reinforcement Learning (RL) algorithms can solve challenging control problems directly from image observations, but they often require millions of environment interactions to do so. Recently, model-based RL algorithms have greatly improved sample-efficiency by concurrently learning an internal model of the world, and s...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	325,052
2404.12504	Using Capability Maps Tailored to Arm Range of Motion in VR Exergames for Rehabilitation	Many neurological conditions, e.g., a stroke, can cause patients to experience upper limb (UL) motor impairments that hinder their daily activities. For such patients, while rehabilitation therapy is key for regaining autonomy and restoring mobility, its long-term nature entails ongoing time commitment and it is often ...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	447,914
1709.09843	Soft Correspondences in Multimodal Scene Parsing	Exploiting multiple modalities for semantic scene parsing has been shown to improve accuracy over the singlemodality scenario. However multimodal datasets often suffer from problems such as data misalignment and label inconsistencies, where the existing methods assume that corresponding regions in two modalities must h...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	81,691
2309.07235	Autotuning Apache TVM-based Scientific Applications Using Bayesian Optimization	Apache TVM (Tensor Virtual Machine), an open source machine learning compiler framework designed to optimize computations across various hardware platforms, provides an opportunity to improve the performance of dense matrix factorizations such as LU (Lower Upper) decomposition and Cholesky decomposition on GPUs and AI ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	391,708
2406.11836	RetinaGS: Scalable Training for Dense Scene Rendering with Billion-Scale 3D Gaussians	In this work, we explore the possibility of training high-parameter 3D Gaussian splatting (3DGS) models on large-scale, high-resolution datasets. We design a general model parallel training method for 3DGS, named RetinaGS, which uses a proper rendering equation and can be applied to any scene and arbitrary distribution...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	465,090
2309.14687	On The Effects of The Variations In Network Characteristics In Cyber Physical Systems	The popular robotic simulator, Gazebo, lacks the feature of simulating the effects of control latency that would make it a fully-fledged cyber-physical system (CPS) simulator. The CPS that we address to measure is a robotic arm (UR5) controlled remotely with velocity commands. The main goal is to measure Quality of Con...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	394,704
2112.06787	On Stability, Ancillary Services, Operation, and Security of Smart Inverters	This paper presents some recent trends in the research of grid-interactive inverters. Particularly, this paper focuses on stability, ancillary services, operation, and security of single and multiple inverters in the modern power grid. A grid-interactive inverter performs as a controllable interface between the distrib...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	271,302
1906.04115	Robust Multi-Modal Sensor Fusion: An Adversarial Approach	In recent years, multi-modal fusion has attracted a lot of research interest, both in academia, and in industry. Multimodal fusion entails the combination of information from a set of different types of sensors. Exploiting complementary information from different sensors, we show that target detection and classificatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	134,609
1105.0452	Relay-Assisted Multiple Access with Multi-Packet Reception Capability and Simultaneous Transmission and Reception	In this work we examine the operation of a node relaying packets from a number of users to a destination node. We assume multi-packet reception capabilities for the relay and the destination node. The relay node can transmit and receive at the same time, so the problem of self interference arises. The relay does not ha...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,224
1812.01601	Learning 3D Human Dynamics from Video	From an image of a person in action, we can easily guess the 3D motion of the person in the immediate past and future. This is because we have a mental model of 3D human dynamics that we have acquired from observing visual sequences of humans in motion. We present a framework that can similarly learn a representation o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	115,560
2003.13103	Dealer: End-to-End Data Marketplace with Model-based Pricing	Data-driven machine learning (ML) has witnessed great successes across a variety of application domains. Since ML model training are crucially relied on a large amount of data, there is a growing demand for high quality data to be collected for ML model training. However, from data owners' perspective, it is risky for ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	170,109
2111.05226	Leveraging blur information for plenoptic camera calibration	This paper presents a novel calibration algorithm for plenoptic cameras, especially the multi-focus configuration, where several types of micro-lenses are used, using raw images only. Current calibration methods rely on simplified projection models, use features from reconstructed images, or require separated calibrati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	265,731
2502.02773	SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs	High-definition maps (HD maps) are detailed and informative maps capturing lane centerlines and road elements. Although very useful for autonomous driving, HD maps are costly to build and maintain. Furthermore, access to these high-quality maps is usually limited to the firms that build them. On the other hand, standar...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	530,465
2311.03731	A Survey of Large Language Models Attribution	Open-domain generative systems have gained significant attention in the field of conversational AI (e.g., generative search engines). This paper presents a comprehensive review of the attribution mechanisms employed by these systems, particularly large language models. Though attribution or citation improve the factual...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	405,965
2212.04849	Closed pattern mining of interval data and distributional data	We discuss pattern languages for closed pattern mining and learning of interval data and distributional data. We first introduce pattern languages relying on pairs of intersection-based constraints or pairs of inclusion based constraints, or both, applied to intervals. We discuss the encoding of such interval patterns ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	335,596
1910.11871	Towards Online End-to-end Transformer Automatic Speech Recognition	The Transformer self-attention network has recently shown promising performance as an alternative to recurrent neural networks in end-to-end (E2E) automatic speech recognition (ASR) systems. However, Transformer has a drawback in that the entire input sequence is required to compute self-attention. We have proposed a b...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	150,900
1506.05481	Swing-twist decomposition in Clifford algebra	The swing-twist decomposition is a standard routine in motion planning for humanoid limbs. In this paper the decomposition formulas are derived and discussed in terms of Clifford algebra. With the decomposition one can express an arbitrary spinor as a product of a twist-free spinor and a swing-free spinor (or vice-vers...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	44,302
1909.11790	Residual Networks Behave Like Boosting Algorithms	We show that Residual Networks (ResNet) is equivalent to boosting feature representation, without any modification to the underlying ResNet training algorithm. A regret bound based on Online Gradient Boosting theory is proved and suggests that ResNet could achieve Online Gradient Boosting regret bounds through neural n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	146,908
1702.05912	Routes Obey Hierarchy in Complex Networks	Various hypotheses exist about the paths used for communication between the nodes of complex networks. Most studies simply suppose that communication goes via shortest paths, while others have more explicit assumptions about how routing (alternatively navigation or search) works or should work in real networks. However...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	68,499

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