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
2407.16242	Asymptotic Capacity of 1-Bit MIMO Fading Channels	In this work, we investigate the capacity of multi-antenna fading channels with 1-bit quantized output per receive antenna. Specifically, leveraging Bayesian statistical tools, we analyze the asymptotic regime with a large number of receive antennas. In the coherent case, where the channel state information (CSI) is kn...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	475,521
2410.22830	Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing Images	Recent advancements in diffusion models have significantly improved performance in super-resolution (SR) tasks. However, previous research often overlooks the fundamental differences between SR and general image generation. General image generation involves creating images from scratch, while SR focuses specifically on...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	503,789
2110.12503	Deep Neural Networks on EEG Signals to Predict Auditory Attention Score Using Gramian Angular Difference Field	Auditory attention is a selective type of hearing in which people focus their attention intentionally on a specific source of a sound or spoken words whilst ignoring or inhibiting other auditory stimuli. In some sense, the auditory attention score of an individual shows the focus the person can have in auditory tasks. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,865
2102.05379	Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions	Generative flows and diffusion models have been predominantly trained on ordinal data, for example natural images. This paper introduces two extensions of flows and diffusion for categorical data such as language or image segmentation: Argmax Flows and Multinomial Diffusion. Argmax Flows are defined by a composition of...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	219,420
2211.10124	Global quantitative robustness of regression feed-forward neural networks	Neural networks are an indispensable model class for many complex learning tasks. Despite the popularity and importance of neural networks and many different established techniques from literature for stabilization and robustification of the training, the classical concepts from robust statistics have rarely been consi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,217
2211.08975	Region Embedding with Intra and Inter-View Contrastive Learning	Unsupervised region representation learning aims to extract dense and effective features from unlabeled urban data. While some efforts have been made for solving this problem based on multiple views, existing methods are still insufficient in extracting representations in a view and/or incorporating representations fro...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	330,827
2207.12283	MedML: Fusing Medical Knowledge and Machine Learning Models for Early Pediatric COVID-19 Hospitalization and Severity Prediction	The COVID-19 pandemic has caused devastating economic and social disruption, straining the resources of healthcare institutions worldwide. This has led to a nationwide call for models to predict hospitalization and severe illness in patients with COVID-19 to inform distribution of limited healthcare resources. We respo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	309,964
2308.03072	Customizing Textile and Tactile Skins for Interactive Industrial Robots	Tactile skins made from textiles enhance robot-human interaction by localizing contact points and measuring contact forces. This paper presents a solution for rapidly fabricating, calibrating, and deploying these skins on industrial robot arms. The novel automated skin calibration procedure maps skin locations to robot...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	383,887
2411.18391	GeneQuery: A General QA-based Framework for Spatial Gene Expression Predictions from Histology Images	Gene expression profiling provides profound insights into molecular mechanisms, but its time-consuming and costly nature often presents significant challenges. In contrast, whole-slide hematoxylin and eosin (H&E) stained histological images are readily accessible and allow for detailed examinations of tissue structure ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	511,854
1909.10000	Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud	Clustering big data often requires tremendous computational resources where cloud computing is undoubtedly one of the promising solutions. However, the computation cost in the cloud can be unexpectedly high if it cannot be managed properly. The long tail phenomenon has been observed widely in the big data clustering ar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	146,424
2106.14275	Learning without Forgetting for 3D Point Cloud Objects	When we fine-tune a well-trained deep learning model for a new set of classes, the network learns new concepts but gradually forgets the knowledge of old training. In some real-life applications, we may be interested in learning new classes without forgetting the capability of previous experience. Such learning without...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	243,349
0704.2353	Scaling Laws of Cognitive Networks	We consider a cognitive network consisting of n random pairs of cognitive transmitters and receivers communicating simultaneously in the presence of multiple primary users. Of interest is how the maximum throughput achieved by the cognitive users scales with n. Furthermore, how far these users must be from a primary us...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	56
2112.08614	KAT: A Knowledge Augmented Transformer for Vision-and-Language	The primary focus of recent work with largescale transformers has been on optimizing the amount of information packed into the model's parameters. In this work, we ask a different question: Can multimodal transformers leverage explicit knowledge in their reasoning? Existing, primarily unimodal, methods have explored ap...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,862
1206.4668	Approximate Principal Direction Trees	We introduce a new spatial data structure for high dimensional data called the \emph{approximate principal direction tree} (APD tree) that adapts to the intrinsic dimension of the data. Our algorithm ensures vector-quantization accuracy similar to that of computationally-expensive PCA trees with similar time-complexity...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	16,719
2404.00172	Universal Bovine Identification via Depth Data and Deep Metric Learning	This paper proposes and evaluates, for the first time, a top-down (dorsal view), depth-only deep learning system for accurately identifying individual cattle and provides associated code, datasets, and training weights for immediate reproducibility. An increase in herd size skews the cow-to-human ratio at the farm and ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	442,789
2306.01736	DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model	Observing the close relationship among panoptic, semantic and instance segmentation tasks, we propose to train a universal multi-dataset multi-task segmentation model: DaTaSeg.We use a shared representation (mask proposals with class predictions) for all tasks. To tackle task discrepancy, we adopt different merge opera...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	370,570
2106.14888	Social influence under uncertainty in interaction with peers, robots and computers	Taking advice from others requires confidence in their competence. This is important for interaction with peers, but also for collaboration with social robots and artificial agents. Nonetheless, we do not always have access to information about others' competence or performance. In these uncertain environments, do our ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	243,551
2211.07828	Adaptation Approaches for Nearest Neighbor Language Models	Semi-parametric Nearest Neighbor Language Models ($k$NN-LMs) have produced impressive gains over purely parametric LMs, by leveraging large-scale neighborhood retrieval over external memory datastores. However, there has been little investigation into adapting such models for new domains. This work attempts to fill tha...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	330,381
2305.14607	An Equivalent Circuit Approach to Distributed Optimization	Distributed optimization is an essential paradigm to solve large-scale optimization problems in modern applications where big-data and high-dimensionality creates a computational bottleneck. Distributed optimization algorithms that exhibit fast convergence allow us to fully utilize computing resources and effectively s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	367,129
2009.08427	Discovering Dynamic Salient Regions for Spatio-Temporal Graph Neural Networks	Graph Neural Networks are perfectly suited to capture latent interactions between various entities in the spatio-temporal domain (e.g. videos). However, when an explicit structure is not available, it is not obvious what atomic elements should be represented as nodes. Current works generally use pre-trained object dete...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	196,236
2203.00907	Split Semantic Detection in Sandplay Images	Sandplay image, as an important psychoanalysis carrier, is a visual scene constructed by the client selecting and placing sand objects (e.g., sand, river, human figures, animals, vegetation, buildings, etc.). As the projection of the client's inner world, it contains high-level semantic information reflecting the clien...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	283,175
2408.06878	PBIR-NIE: Glossy Object Capture under Non-Distant Lighting	Glossy objects present a significant challenge for 3D reconstruction from multi-view input images under natural lighting. In this paper, we introduce PBIR-NIE, an inverse rendering framework designed to holistically capture the geometry, material attributes, and surrounding illumination of such objects. We propose a no...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	480,379
2204.05839	The MIT Supercloud Workload Classification Challenge	High-Performance Computing (HPC) centers and cloud providers support an increasingly diverse set of applications on heterogenous hardware. As Artificial Intelligence (AI) and Machine Learning (ML) workloads have become an increasingly larger share of the compute workloads, new approaches to optimized resource usage, al...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	291,162
2409.14485	Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding	Long video understanding poses a significant challenge for current Multi-modal Large Language Models (MLLMs). Notably, the MLLMs are constrained by their limited context lengths and the substantial costs while processing long videos. Although several existing methods attempt to reduce visual tokens, their strategies en...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	490,486
2407.06460	MUSE: Machine Unlearning Six-Way Evaluation for Language Models	Language models (LMs) are trained on vast amounts of text data, which may include private and copyrighted content. Data owners may request the removal of their data from a trained model due to privacy or copyright concerns. However, exactly unlearning only these datapoints (i.e., retraining with the data removed) is in...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	471,399
2304.04299	The Effect of Flagella Stiffness on the Locomotion of a Multi-Flagellated Robot at Low Reynolds Environment	Microorganisms such as algae and bacteria move in a viscous environment with extremely low Reynolds ($Re$), where the viscous drag dominates the inertial forces. They have adapted to this environment by developing specialized features such as whole-body deformations and flexible structures such as flagella (with variou...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	357,167
2309.15847	Disinformation Detection: An Evolving Challenge in the Age of LLMs	The advent of generative Large Language Models (LLMs) such as ChatGPT has catalyzed transformative advancements across multiple domains. However, alongside these advancements, they have also introduced potential threats. One critical concern is the misuse of LLMs by disinformation spreaders, leveraging these models to ...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	395,140
2311.06396	A comprehensive analysis of concept drift locality in data streams	Adapting to drifting data streams is a significant challenge in online learning. Concept drift must be detected for effective model adaptation to evolving data properties. Concept drift can impact the data distribution entirely or partially, which makes it difficult for drift detectors to accurately identify the concep...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	406,923
2010.05039	Pinched Hysteresis Loops In Nonlinear Resonators	This paper shows that pinched hysteresis can be observed in simple nonlinear resonance circuits containing a single diode that behaves as a voltage-controlled switch. Mathematical models are derived and numerically validated for both series and parallel resonator circuits. The lobe area of the pinched loop is found to ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	199,969
2303.10875	Hardware-Aware Graph Neural Network Automated Design for Edge Computing Platforms	Graph neural networks (GNNs) have emerged as a popular strategy for handling non-Euclidean data due to their state-of-the-art performance. However, most of the current GNN model designs mainly focus on task accuracy, lacking in considering hardware resources limitation and real-time requirements of edge application sce...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	352,614
2407.06372	Non-Robust Features are Not Always Useful in One-Class Classification	The robustness of machine learning models has been questioned by the existence of adversarial examples. We examine the threat of adversarial examples in practical applications that require lightweight models for one-class classification. Building on Ilyas et al. (2019), we investigate the vulnerability of lightweight o...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	471,376
2208.03618	An Unsupervised Learning Approach for Spectrum Allocation in Terahertz Communication Systems	We propose a new spectrum allocation strategy, aided by unsupervised learning, for multiuser terahertz communication systems. In this strategy, adaptive sub-band bandwidth is considered such that the spectrum of interest can be divided into sub-bands with unequal bandwidths. This strategy reduces the variation in molec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	311,843
2408.00365	Multimodal Fusion and Coherence Modeling for Video Topic Segmentation	The video topic segmentation (VTS) task segments videos into intelligible, non-overlapping topics, facilitating efficient comprehension of video content and quick access to specific content. VTS is also critical to various downstream video understanding tasks. Traditional VTS methods using shallow features or unsupervi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	477,813
1802.07601	Coupling non-conforming discretizations of PDEs by spectral approximation of the Lagrange multiplier space	This work focuses on the development of a non-conforming domain decomposition method for the approximation of PDEs based on weakly imposed transmission conditions: the continuity of the global solution is enforced by a discrete number of Lagrange multipliers defined over the interfaces of adjacent subdomains. The metho...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	90,930
1904.12465	Asymmetric Impurity Functions, Class Weighting, and Optimal Splits for Binary Classification Trees	We investigate how asymmetrizing an impurity function affects the choice of optimal node splits when growing a decision tree for binary classification. In particular, we relax the usual axioms of an impurity function and show how skewing an impurity function biases the optimal splits to isolate points of a particular c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	129,120
1707.00724	Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning	In the field of reinforcement learning there has been recent progress towards safety and high-confidence bounds on policy performance. However, to our knowledge, no practical methods exist for determining high-confidence policy performance bounds in the inverse reinforcement learning setting---where the true reward fun...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	76,400
2107.05276	Geographical Knowledge-driven Representation Learning for Remote Sensing Images	The proliferation of remote sensing satellites has resulted in a massive amount of remote sensing images. However, due to human and material resource constraints, the vast majority of remote sensing images remain unlabeled. As a result, it cannot be applied to currently available deep learning methods. To fully utilize...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	245,730
2311.08544	JOSA: Joint surface-based registration and atlas construction of brain geometry and function	Surface-based cortical registration is an important topic in medical image analysis and facilitates many downstream applications. Current approaches for cortical registration are mainly driven by geometric features, such as sulcal depth and curvature, and often assume that registration of folding patterns leads to alig...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	407,766
1503.01578	Scalable Iterative Algorithm for Robust Subspace Clustering	Subspace clustering (SC) is a popular method for dimensionality reduction of high-dimensional data, where it generalizes Principal Component Analysis (PCA). Recently, several methods have been proposed to enhance the robustness of PCA and SC, while most of them are computationally very expensive, in particular, for hig...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	40,849
2308.00923	A Novel Lockable Spring-loaded Prismatic Spine to Support Agile Quadrupedal Locomotion	This paper introduces a way to systematically investigate the effect of compliant prismatic spines in quadrupedal robot locomotion. We develop a novel spring-loaded lockable spine module, together with a new Spinal Compliance-Integrated Quadruped (SCIQ) platform for both empirical and numerical research. Individual spi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	383,075
1411.3302	Using Gaussian Measures for Efficient Constraint Based Clustering	In this paper we present a novel iterative multiphase clustering technique for efficiently clustering high dimensional data points. For this purpose we implement clustering feature (CF) tree on a real data set and a Gaussian density distribution constraint on the resultant CF tree. The post processing by the applicatio...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	37,487
1804.07781	Pathologies of Neural Models Make Interpretations Difficult	One way to interpret neural model predictions is to highlight the most important input features---for example, a heatmap visualization over the words in an input sentence. In existing interpretation methods for NLP, a word's importance is determined by either input perturbation---measuring the decrease in model confide...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	95,595
2006.15685	Recursive Analytic Solution of Nonlinear Optimal Regulators	The paper develops an optimal regulator for a general class of multi-input affine nonlinear systems minimizing a nonlinear cost functional with infinite horizon. The cost functional is general enough to enforce saturation limits on the control input if desired. An efficient algorithm utilizing tensor algebra is employe...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	184,588
2005.10199	Line Failure Localization of Power Networks Part I: Non-cut Outages	Transmission line failures in power systems propagate non-locally, making the control of the resulting outages extremely difficult. In this work, we establish a mathematical theory that characterizes the patterns of line failure propagation and localization in terms of network graph structure. It provides a novel persp...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	178,114
2305.15328	Visual Programming for Text-to-Image Generation and Evaluation	As large language models have demonstrated impressive performance in many domains, recent works have adopted language models (LMs) as controllers of visual modules for vision-and-language tasks. While existing work focuses on equipping LMs with visual understanding, we propose two novel interpretable/explainable visual...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	367,568
2412.20868	Machine Learning of Slow Collective Variables and Enhanced Sampling via Spatial Techniques	Understanding the long-time dynamics of complex physical processes depends on our ability to recognize patterns. To simplify the description of these processes, we often introduce a set of reaction coordinates, customarily referred to as collective variables (CVs). The quality of these CVs heavily impacts our comprehen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	521,384
1510.06168	Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Recurrent Neural Network	Bidirectional Long Short-Term Memory Recurrent Neural Network (BLSTM-RNN) has been shown to be very effective for tagging sequential data, e.g. speech utterances or handwritten documents. While word embedding has been demoed as a powerful representation for characterizing the statistical properties of natural language....	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	48,093
2403.00252	EUROPA: A Legal Multilingual Keyphrase Generation Dataset	Keyphrase generation has primarily been explored within the context of academic research articles, with a particular focus on scientific domains and the English language. In this work, we present EUROPA, a dataset for multilingual keyphrase generation in the legal domain. It is derived from legal judgments from the Cou...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	433,912
2404.11224	Analytical results for uncertainty propagation through trained machine learning regression models	Machine learning (ML) models are increasingly being used in metrology applications. However, for ML models to be credible in a metrology context they should be accompanied by principled uncertainty quantification. This paper addresses the challenge of uncertainty propagation through trained/fixed machine learning (ML) ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	447,427
1209.5467	Minimizing inter-subject variability in fNIRS based Brain Computer Interfaces via multiple-kernel support vector learning	Brain signal variability in the measurements obtained from different subjects during different sessions significantly deteriorates the accuracy of most brain-computer interface (BCI) systems. Moreover these variabilities, also known as inter-subject or inter-session variabilities, require lengthy calibration sessions b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	18,733
1707.00409	Deep Ranking Model by Large Adaptive Margin Learning for Person Re-identification	Person re-identification aims to match images of the same person across disjoint camera views, which is a challenging problem in video surveillance. The major challenge of this task lies in how to preserve the similarity of the same person against large variations caused by complex backgrounds, mutual occlusions and di...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,347
2203.10793	Phase-Aware Spoof Speech Detection Based on Res2Net with Phase Network	The spoof speech detection (SSD) is the essential countermeasure for automatic speaker verification systems. Although SSD with magnitude features in the frequency domain has shown promising results, the phase information also can be important to capture the artefacts of certain types of spoofing attacks. Thus, both mag...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	286,688
2001.00170	Residual Block-based Multi-Label Classification and Localization Network with Integral Regression for Vertebrae Labeling	Accurate identification and localization of the vertebrae in CT scans is a critical and standard preprocessing step for clinical spinal diagnosis and treatment. Existing methods are mainly based on the integration of multiple neural networks, and most of them use the Gaussian heat map to locate the vertebrae's centroid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	159,152
2406.08075	Balancing Molecular Information and Empirical Data in the Prediction of Physico-Chemical Properties	Predicting the physico-chemical properties of pure substances and mixtures is a central task in thermodynamics. Established prediction methods range from fully physics-based ab-initio calculations, which are only feasible for very simple systems, over descriptor-based methods that use some information on the molecules ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	463,340
2005.02990	PeTra: A Sparsely Supervised Memory Model for People Tracking	We propose PeTra, a memory-augmented neural network designed to track entities in its memory slots. PeTra is trained using sparse annotation from the GAP pronoun resolution dataset and outperforms a prior memory model on the task while using a simpler architecture. We empirically compare key modeling choices, finding t...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	176,031
2407.20080	UniTTA: Unified Benchmark and Versatile Framework Towards Realistic Test-Time Adaptation	Test-Time Adaptation (TTA) aims to adapt pre-trained models to the target domain during testing. In reality, this adaptability can be influenced by multiple factors. Researchers have identified various challenging scenarios and developed diverse methods to address these challenges, such as dealing with continual domain...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	477,038
1601.01504	Generalized Hamming weights for almost affine codes	We define generalized Hamming weights for almost affine codes. We show how various aspects and applications of generalized Hamming weights for linear codes, such as Wei duality, generalized Kung's bound, profiles, connection to wire-tap channels of type II, apply to the larger class of almost affine codes in general. I...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	50,756
2012.00257	Confluence: A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection	Confluence is a novel non-Intersection over Union (IoU) alternative to Non-Maxima Suppression (NMS) in bounding box post-processing in object detection. It overcomes the inherent limitations of IoU-based NMS variants to provide a more stable, consistent predictor of bounding box clustering by using a normalized Manhatt...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	209,074
1803.01562	Local Distance Metric Learning for Nearest Neighbor Algorithm	Distance metric learning is a successful way to enhance the performance of the nearest neighbor classifier. In most cases, however, the distribution of data does not obey a regular form and may change in different parts of the feature space. Regarding that, this paper proposes a novel local distance metric learning met...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	91,908
2010.09467	ARENA: A Data-driven Radio Access Networks Analysis of Football Events	Mass events represent one of the most challenging scenarios for mobile networks because, although their date and time are usually known in advance, the actual demand for resources is difficult to predict due to its dependency on many different factors. Based on data provided by a major European carrier during mass even...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	201,549
2111.05508	Training Generative Adversarial Networks with Adaptive Composite Gradient	The wide applications of Generative adversarial networks benefit from the successful training methods, guaranteeing that an object function converges to the local minima. Nevertheless, designing an efficient and competitive training method is still a challenging task due to the cyclic behaviors of some gradient-based w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	265,815
1605.00448	Follow Spam Detection based on Cascaded Social Information	In the last decade we have witnessed the explosive growth of online social networking services (SNSs) such as Facebook, Twitter, RenRen and LinkedIn. While SNSs provide diverse benefits for example, forstering interpersonal relationships, community formations and news propagation, they also attracted uninvited nuiance....	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	55,344
1204.1581	A new approach of designing Multi-Agent Systems	Agent technology is a software paradigm that permits to implement large and complex distributed applications. In order to assist analyzing, conception and development or implementation phases of multi-agent systems, we've tried to present a practical application of a generic and scalable method of a MAS with a componen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	15,327
2410.05451	SecAlign: Defending Against Prompt Injection with Preference Optimization	Large language models (LLMs) are becoming increasingly prevalent in modern software systems, interfacing between the user and the Internet to assist with tasks that require advanced language understanding. To accomplish these tasks, the LLM often uses external data sources such as user documents, web retrieval, results...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	495,741
2401.13324	Information That Matters: Exploring Information Needs of People Affected by Algorithmic Decisions	Every AI system that makes decisions about people has a group of stakeholders that are personally affected by these decisions. However, explanations of AI systems rarely address the information needs of this stakeholder group, who often are AI novices. This creates a gap between conveyed information and information tha...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	423,691
2207.02978	Extending Logical Neural Networks using First-Order Theories	Logical Neural Networks (LNNs) are a type of architecture which combine a neural network's abilities to learn and systems of formal logic's abilities to perform symbolic reasoning. LLNs provide programmers the ability to implicitly modify the underlying structure of the neural network via logical formulae. In this pape...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	306,677
1910.10817	Passive Radar at the Roadside Unit to Configure Millimeter Wave Vehicle-to-Infrastructure Links	Millimeter wave (mmWave) vehicular channels are highly dynamic, and the communication link needs to be reconfigured frequently. In this work, we propose to use a passive radar receiver at the roadside unit to reduce the training overhead of establishing an mmWave communication link. Specifically, the passive radar will...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	150,589
1209.1048	Performance Analysis Of Neuro Genetic Algorithm Applied On Detecting Proportion Of Components In Manhole Gas Mixture	The article presents performance analysis of a real valued neuro genetic algorithm applied for the detection of proportion of the gases found in manhole gas mixture. The neural network (NN) trained using genetic algorithm (GA) leads to concept of neuro genetic algorithm, which is used for implementing an intelligent se...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	18,409
2411.11896	HeartBERT: A Self-Supervised ECG Embedding Model for Efficient and Effective Medical Signal Analysis	The HeartBert model is introduced with three primary objectives: reducing the need for labeled data, minimizing computational resources, and simultaneously improving performance in machine learning systems that analyze Electrocardiogram (ECG) signals. Inspired by Bidirectional Encoder Representations from Transformers ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	509,216
2411.11070	Joint Precoding and AP Selection for Energy Efficient RIS-aided Cell-Free Massive MIMO Using Multi-agent Reinforcement Learning	Cell-free (CF) massive multiple-input multiple-output (mMIMO) and reconfigurable intelligent surface (RIS) are two advanced transceiver technologies for realizing future sixth-generation (6G) networks. In this paper, we investigate the joint precoding and access point (AP) selection for energy efficient RIS-aided CF mM...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	508,908
2307.00504	On efficient computation in active inference	Despite being recognized as neurobiologically plausible, active inference faces difficulties when employed to simulate intelligent behaviour in complex environments due to its computational cost and the difficulty of specifying an appropriate target distribution for the agent. This paper introduces two solutions that w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	377,033
2406.08331	Genetic Column Generation for Computing Lower Bounds for Adversarial Classification	Recent theoretical results on adversarial multi-class classification showed a similarity to the multi-marginal formulation of Wasserstein-barycenter in optimal transport. Unfortunately, both problems suffer from the curse of dimension, making it hard to exploit the nice linear program structure of the problems for nume...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	463,437
2009.09467	Addressing reward bias in Adversarial Imitation Learning with neutral reward functions	Generative Adversarial Imitation Learning suffers from the fundamental problem of reward bias stemming from the choice of reward functions used in the algorithm. Different types of biases also affect different types of environments - which are broadly divided into survival and task-based environments. We provide a theo...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	196,591
1811.04968	PennyLane: Automatic differentiation of hybrid quantum-classical computations	PennyLane is a Python 3 software framework for differentiable programming of quantum computers. The library provides a unified architecture for near-term quantum computing devices, supporting both qubit and continuous-variable paradigms. PennyLane's core feature is the ability to compute gradients of variational quantu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	113,209
1506.05690	Using network science and text analytics to produce surveys in a scientific topic	The use of science to understand its own structure is becoming popular, but understanding the organization of knowledge areas is still limited because some patterns are only discoverable with proper computational treatment of large-scale datasets. In this paper, we introduce a network-based methodology combined with te...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	44,327
1905.05605	Encrypted Speech Recognition using Deep Polynomial Networks	The cloud-based speech recognition/API provides developers or enterprises an easy way to create speech-enabled features in their applications. However, sending audios about personal or company internal information to the cloud, raises concerns about the privacy and security issues. The recognition results generated in ...	false	false	true	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	130,768
2310.09279	Control of Vehicle Platoons with Collision Avoidance Using Noncooperative Differential Games	This paper considers a differential game approach to the predecessor-following vehicle platoon control problem without and with collision avoidance. In this approach, each vehicle tries to minimize the performance index (PI) of its control objective, which is reaching consensual velocity with the predecessor vehicle wh...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	399,721
2402.07472	Cartesian atomic cluster expansion for machine learning interatomic potentials	Machine learning interatomic potentials are revolutionizing large-scale, accurate atomistic modelling in material science and chemistry. Many potentials use atomic cluster expansion or equivariant message passing frameworks. Such frameworks typically use spherical harmonics as angular basis functions, and then use Cleb...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	428,737
1711.10212	Multi-stream 3D FCN with Multi-scale Deep Supervision for Multi-modality Isointense Infant Brain MR Image Segmentation	We present a method to address the challenging problem of segmentation of multi-modality isointense infant brain MR images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Our method is based on context-guided, multi-stream fully convolutional networks (FCN), which after training, can directly m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,549
2501.02438	Efficient Deployment of Large Language Models on Resource-constrained Devices	Deploying Large Language Models (LLMs) on resource-constrained (or weak) devices presents significant challenges due to limited resources and heterogeneous data distribution. To address the data concern, it is necessary to fine-tune LLMs using on-device private data for various downstream tasks. While Federated Learnin...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	522,484
2409.06216	SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization	NLP datasets may still contain annotation errors, even when they are manually annotated. Researchers have attempted to develop methods to automatically reduce the adverse effect of errors in datasets. However, existing methods are time-consuming because they require many trained models to detect errors. This paper prop...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	487,045
1908.11355	Human-grounded Evaluations of Explanation Methods for Text Classification	Due to the black-box nature of deep learning models, methods for explaining the models' results are crucial to gain trust from humans and support collaboration between AIs and humans. In this paper, we consider several model-agnostic and model-specific explanation methods for CNNs for text classification and conduct th...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	143,361
2204.08211	How to Attain Communication-Efficient DNN Training? Convert, Compress, Correct	This paper introduces CO3 -- an algorithm for communication-efficient federated Deep Neural Network (DNN) training. CO3 takes its name from three processing applied which reduce the communication load when transmitting the local DNN gradients from the remote users to the Parameter Server. Namely: (i) gradient quantizat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	292,009
2409.05370	KARGEN: Knowledge-enhanced Automated Radiology Report Generation Using Large Language Models	Harnessing the robust capabilities of Large Language Models (LLMs) for narrative generation, logical reasoning, and common-sense knowledge integration, this study delves into utilizing LLMs to enhance automated radiology report generation (R2Gen). Despite the wealth of knowledge within LLMs, efficiently triggering rele...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	486,746
2005.11014	Intent Mining from past conversations for conversational agent	Conversational systems are of primary interest in the AI community. Chatbots are increasingly being deployed to provide round-the-clock support and to increase customer engagement. Many of the commercial bot building frameworks follow a standard approach that requires one to build and train an intent model to recognize...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	178,350
2108.06215	Sentiment Analysis of the COVID-related r/Depression Posts	Reddit.com is a popular social media platform among young people. Reddit users share their stories to seek support from other users, especially during the Covid-19 pandemic. Messages posted on Reddit and their content have provided researchers with opportunity to analyze public concerns. In this study, we analyzed sent...	false	false	false	true	false	true	true	false	true	false	false	false	false	false	false	false	false	false	250,537
2205.04713	Serving and Optimizing Machine Learning Workflows on Heterogeneous Infrastructures	With the advent of ubiquitous deployment of smart devices and the Internet of Things, data sources for machine learning inference have increasingly moved to the edge of the network. Existing machine learning inference platforms typically assume a homogeneous infrastructure and do not take into account the more complex ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	true	295,727
2405.16430	GAMEOPT+: Improving Fuel Efficiency in Unregulated Heterogeneous Traffic Intersections via Optimal Multi-agent Cooperative Control	Better fuel efficiency leads to better financial security as well as a cleaner environment. We propose a novel approach for improving fuel efficiency in unstructured and unregulated traffic environments. Existing intelligent transportation solutions for improving fuel efficiency, however, apply only to traffic intersec...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	457,418
2303.06074	Susceptibility to Influence of Large Language Models	Two studies tested the hypothesis that a Large Language Model (LLM) can be used to model psychological change following exposure to influential input. The first study tested a generic mode of influence - the Illusory Truth Effect (ITE) - where earlier exposure to a statement (through, for example, rating its interest) ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	350,689
2110.05668	NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks	Most existing neural architecture search (NAS) benchmarks and algorithms prioritize well-studied tasks, e.g. image classification on CIFAR or ImageNet. This makes the performance of NAS approaches in more diverse areas poorly understood. In this paper, we present NAS-Bench-360, a benchmark suite to evaluate methods on ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	260,346
2112.12901	A machine learning analysis of the relationship between some underlying medical conditions and COVID-19 susceptibility	For the past couple years, the Coronavirus, commonly known as COVID-19, has significantly affected the daily lives of all citizens residing in the United States by imposing several, fatal health risks that cannot go unnoticed. In response to the growing fear and danger COVID-19 inflicts upon societies in the USA, sever...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,076
2204.13923	Maxmin Participatory Budgeting	Participatory Budgeting (PB) is a popular voting method by which a limited budget is divided among a set of projects, based on the preferences of voters over the projects. PB is broadly categorised as divisible PB (if the projects are fractionally implementable) and indivisible PB (if the projects are atomic). Egalitar...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	293,996
2411.13797	Hugging Rain Man: A Novel Facial Action Units Dataset for Analyzing Atypical Facial Expressions in Children with Autism Spectrum Disorder	Children with Autism Spectrum Disorder (ASD) often exhibit atypical facial expressions. However, the specific objective facial features that underlie this subjective perception remain unclear. In this paper, we introduce a novel dataset, Hugging Rain Man (HRM), which includes facial action units (AUs) manually annotate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,923
2412.02025	PKRD-CoT: A Unified Chain-of-thought Prompting for Multi-Modal Large Language Models in Autonomous Driving	There is growing interest in leveraging the capabilities of robust Multi-Modal Large Language Models (MLLMs) directly within autonomous driving contexts. However, the high costs and complexity of designing and training end-to-end autonomous driving models make them challenging for many enterprises and research entities...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	513,346
1601.06103	Bayesian Learning without Recall	We analyze a model of learning and belief formation in networks in which agents follow Bayes rule yet they do not recall their history of past observations and cannot reason about how other agents' beliefs are formed. They do so by making rational inferences about their observations which include a sequence of independ...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	51,224
cs/0411020	Dynamic Modelling and Adaptive Traction Control for Mobile Robots	Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used ki...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	538,393
2204.07288	Characterizing the Efficiency vs. Accuracy Trade-off for Long-Context NLP Models	With many real-world applications of Natural Language Processing (NLP) comprising of long texts, there has been a rise in NLP benchmarks that measure the accuracy of models that can handle longer input sequences. However, these benchmarks do not consider the trade-offs between accuracy, speed, and power consumption as ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	291,637
2003.01797	Discover Your Social Identity from What You Tweet: a Content Based Approach	An identity denotes the role an individual or a group plays in highly differentiated contemporary societies. In this paper, our goal is to classify Twitter users based on their role identities. We first collect a coarse-grained public figure dataset automatically, then manually label a more fine-grained identity datase...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	166,759
2410.12197	Potential-Based Intrinsic Motivation: Preserving Optimality With Complex, Non-Markovian Shaping Rewards	Recently there has been a proliferation of intrinsic motivation (IM) reward-shaping methods to learn in complex and sparse-reward environments. These methods can often inadvertently change the set of optimal policies in an environment, leading to suboptimal behavior. Previous work on mitigating the risks of reward shap...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,901
2411.11904	GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding	Remote sensing (RS) visual grounding aims to use natural language expression to locate specific objects (in the form of the bounding box or segmentation mask) in RS images, enhancing human interaction with intelligent RS interpretation systems. Early research in this area was primarily based on horizontal bounding boxe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,219

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