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
2103.15819	Augmenting Automated Game Testing with Deep Reinforcement Learning	General game testing relies on the use of human play testers, play test scripting, and prior knowledge of areas of interest to produce relevant test data. Using deep reinforcement learning (DRL), we introduce a self-learning mechanism to the game testing framework. With DRL, the framework is capable of exploring and/or...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	227,349
2307.15593	Robust Distortion-free Watermarks for Language Models	We propose a methodology for planting watermarks in text from an autoregressive language model that are robust to perturbations without changing the distribution over text up to a certain maximum generation budget. We generate watermarked text by mapping a sequence of random numbers -- which we compute using a randomiz...	false	false	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	382,314
2001.03248	Online Estimation and Adaptation for Random Access with Successive Interference Cancellation	This paper proposes an adaptive transmission algorithm for slotted random access systems supporting the successive interference cancellation (SIC) at the access point (AP). When multiple users transmit packets simultaneously in a slot, owing to the SIC technique, the AP is able to decode them through SIC resolve proced...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	159,920
2211.02363	Neural RELAGGS	Multi-relational databases are the basis of most consolidated data collections in science and industry today. Most learning and mining algorithms, however, require data to be represented in a propositional form. While there is a variety of specialized machine learning algorithms that can operate directly on multi-relat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	328,558
1803.02551	Extracting Domain Invariant Features by Unsupervised Learning for Robust Automatic Speech Recognition	The performance of automatic speech recognition (ASR) systems can be significantly compromised by previously unseen conditions, which is typically due to a mismatch between training and testing distributions. In this paper, we address robustness by studying domain invariant features, such that domain information become...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	92,085
2204.04904	The Compact Genetic Algorithm Struggles on Cliff Functions	The compact genetic algorithm (cGA) is an non-elitist estimation of distribution algorithm which has shown to be able to deal with difficult multimodal fitness landscapes that are hard to solve by elitist algorithms. In this paper, we investigate the cGA on the CLIFF function for which it has been shown recently that n...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	290,836
1401.4489	An Analysis of Random Projections in Cancelable Biometrics	With increasing concerns about security, the need for highly secure physical biometrics-based authentication systems utilizing \emph{cancelable biometric} technologies is on the rise. Because the problem of cancelable template generation deals with the trade-off between template security and matching performance, many ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	30,075
2209.05098	SELTO: Sample-Efficient Learned Topology Optimization	Recent developments in Deep Learning (DL) suggest a vast potential for Topology Optimization (TO). However, while there are some promising attempts, the subfield still lacks a firm footing regarding basic methods and datasets. We aim to address both points. First, we explore physics-based preprocessing and equivariant ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	316,992
2410.11226	MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning	Current generative models for drug discovery primarily use molecular docking as an oracle to guide the generation of active compounds. However, such models are often not useful in practice because even compounds with high docking scores do not consistently show experimental activity. More accurate methods for activity ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,448
1607.07906	Approximation and Parameterized Complexity of Minimax Approval Voting	We present three results on the complexity of Minimax Approval Voting. First, we study Minimax Approval Voting parameterized by the Hamming distance $d$ from the solution to the votes. We show Minimax Approval Voting admits no algorithm running in time $\mathcal{O}^\star(2^{o(d\log d)})$, unless the Exponential Time Hy...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	59,087
2310.02743	Reward Model Ensembles Help Mitigate Overoptimization	Reinforcement learning from human feedback (RLHF) is a standard approach for fine-tuning large language models to follow instructions. As part of this process, learned reward models are used to approximately model human preferences. However, as imperfect representations of the "true" reward, these learned reward models...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	396,979
1304.7548	Adaptive Reduced-Rank RLS Algorithms based on Joint Iterative Optimization of Filters for Space-Time Interference Suppression	This paper presents novel adaptive reduced-rank filtering algorithms based on joint iterative optimization of adaptive filters. The novel scheme consists of a joint iterative optimization of a bank of full-rank adaptive filters that constitute the projection matrix and an adaptive reduced-rank filter that operates at t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	24,272
2305.16700	Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making	We argue that explanations for "algorithmic decision-making" (ADM) systems can profit by adopting practices that are already used in the learning sciences. We shortly introduce the importance of explaining ADM systems, give a brief overview of approaches drawing from other disciplines to improve explanations, and prese...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	368,215
2407.18898	A Flexible and Scalable Approach for Collecting Wildlife Advertisements on the Web	Wildlife traffickers are increasingly carrying out their activities in cyberspace. As they advertise and sell wildlife products in online marketplaces, they leave digital traces of their activity. This creates a new opportunity: by analyzing these traces, we can obtain insights into how trafficking networks work as wel...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	476,553
2011.06659	A comprehensive mathematical model of a low-friction servopneumatic actuator	This paper presents a comprehensive mathematical model of a servopneumatic system, aimed at its consolidation in literature. The work exploits system's friction forces, temperature and pressure evolution, heat transfer, leakage between chambers and environment, equilibrium of cylinder forces, resistance of the pipes, m...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	206,297
2401.16094	Federated unsupervised random forest for privacy-preserving patient stratification	In the realm of precision medicine, effective patient stratification and disease subtyping demand innovative methodologies tailored for multi-omics data. Clustering techniques applied to multi-omics data have become instrumental in identifying distinct subgroups of patients, enabling a finer-grained understanding of di...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	424,701
2212.02277	R2FD2: Fast and Robust Matching of Multimodal Remote Sensing Image via Repeatable Feature Detector and Rotation-invariant Feature Descriptor	Automatically identifying feature correspondences between multimodal images is facing enormous challenges because of the significant differences both in radiation and geometry. To address these problems, we propose a novel feature matching method (named R2FD2) that is robust to radiation and rotation differences. Our R...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,747
2307.02037	Reverse Diffusion Monte Carlo	We propose a Monte Carlo sampler from the reverse diffusion process. Unlike the practice of diffusion models, where the intermediary updates -- the score functions -- are learned with a neural network, we transform the score matching problem into a mean estimation one. By estimating the means of the regularized posteri...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	377,562
2501.00436	Intuitive Analysis of the Quantization-based Optimization: From Stochastic and Quantum Mechanical Perspective	In this paper, we present an intuitive analysis of the optimization technique based on the quantization of an objective function. Quantization of an objective function is an effective optimization methodology that decreases the measure of a level set containing several saddle points and local minima and finds the optim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	521,665
2007.12158	Signal Enhancement for Magnetic Navigation Challenge Problem	Harnessing the magnetic field of the Earth for navigation has shown promise as a viable alternative to other navigation systems. A magnetic navigation system collects its own magnetic field data using a magnetometer and uses magnetic anomaly maps to determine the current location. The greatest challenge with magnetic n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	188,749
2311.00241	1DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Tracking	Recently, heatmap regression methods based on 1D landmark representations have shown prominent performance on locating facial landmarks. However, previous methods ignored to make deep explorations on the good potentials of 1D landmark representations for sequential and structural modeling of multiple landmarks to track...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	404,562
2405.09697	Weakly Supervised Bayesian Shape Modeling from Unsegmented Medical Images	Anatomical shape analysis plays a pivotal role in clinical research and hypothesis testing, where the relationship between form and function is paramount. Correspondence-based statistical shape modeling (SSM) facilitates population-level morphometrics but requires a cumbersome, potentially bias-inducing construction pi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	454,497
2204.11565	Value of Optimal Trip and Charging Scheduling of Commercial Electric Vehicle Fleets with Vehicle-to-Grid in Future Low Inertia Systems	The electrification of transport is seen as an important step in the global decarbonisation agenda. With such a large expected load on the power system from electric vehicles (EVs), it is important to coordinate charging in order to balance the supply and demand for electricity. Bidirectional charging, enabled through ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	293,196
1802.01237	Face Destylization	Numerous style transfer methods which produce artistic styles of portraits have been proposed to date. However, the inverse problem of converting the stylized portraits back into realistic faces is yet to be investigated thoroughly. Reverting an artistic portrait to its original photo-realistic face image has potential...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,567
2206.13980	Label-enhanced Prototypical Network with Contrastive Learning for Multi-label Few-shot Aspect Category Detection	Multi-label aspect category detection allows a given review sentence to contain multiple aspect categories, which is shown to be more practical in sentiment analysis and attracting increasing attention. As annotating large amounts of data is time-consuming and labor-intensive, data scarcity occurs frequently in real-wo...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	305,143
2212.00622	Vertical Federated Learning: A Structured Literature Review	Federated Learning (FL) has emerged as a promising distributed learning paradigm with an added advantage of data privacy. With the growing interest in having collaboration among data owners, FL has gained significant attention of organizations. The idea of FL is to enable collaborating participants train machine learni...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	334,130
2104.05457	Higher-order percolation processes on multiplex hypergraphs	Higher order interactions are increasingly recognised as a fundamental aspect of complex systems ranging from the brain to social contact networks. Hypergraph as well as simplicial complexes capture the higher-order interactions of complex systems and allow to investigate the relation between their higher-order structu...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	229,735
2112.03624	Time-Equivariant Contrastive Video Representation Learning	We introduce a novel self-supervised contrastive learning method to learn representations from unlabelled videos. Existing approaches ignore the specifics of input distortions, e.g., by learning invariance to temporal transformations. Instead, we argue that video representation should preserve video dynamics and reflec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	270,280
1808.10862	Open Source Dataset and Machine Learning Techniques for Automatic Recognition of Historical Graffiti	Machine learning techniques are presented for automatic recognition of the historical letters (XI-XVIII centuries) carved on the stoned walls of St.Sophia cathedral in Kyiv (Ukraine). A new image dataset of these carved Glagolitic and Cyrillic letters (CGCL) was assembled and pre-processed for recognition and predictio...	false	false	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	106,459
2104.13464	Deep Two-Stage High-Resolution Image Inpainting	In recent years, the field of image inpainting has developed rapidly, learning based approaches show impressive results in the task of filling missing parts in an image. But most deep methods are strongly tied to the resolution of the images on which they were trained. A slight resolution increase leads to serious arti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,508
2403.03929	Extreme Precipitation Nowcasting using Transformer-based Generative Models	This paper presents an innovative approach to extreme precipitation nowcasting by employing Transformer-based generative models, namely NowcastingGPT with Extreme Value Loss (EVL) regularization. Leveraging a comprehensive dataset from the Royal Netherlands Meteorological Institute (KNMI), our study focuses on predicti...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	435,395
1907.02096	A comprehensive evaluation of full-reference image quality assessment algorithms on KADID-10k	Significant progress has been made in the past decade for full-reference image quality assessment (FR-IQA). However, new large scale image quality databases have been released for evaluating image quality assessment algorithms. In this study, our goal is to give a comprehensive evaluation of state-of-the-art FR-IQA met...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	137,521
2403.06243	BlazeBVD: Make Scale-Time Equalization Great Again for Blind Video Deflickering	Developing blind video deflickering (BVD) algorithms to enhance video temporal consistency, is gaining importance amid the flourish of image processing and video generation. However, the intricate nature of video data complicates the training of deep learning methods, leading to high resource consumption and instabilit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,363
2407.14218	Multi-robot maze exploration using an efficient cost-utility method	In the field of modern robotics, robots are proving to be useful in tackling high-risk situations, such as navigating hazardous environments like burning buildings, earthquake-stricken areas, or patrolling crime-ridden streets, as well as exploring uncharted caves. These scenarios share similarities with maze explorati...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	474,699
1908.09419	Deep Closed-Form Subspace Clustering	We propose Deep Closed-Form Subspace Clustering (DCFSC), a new embarrassingly simple model for subspace clustering with learning non-linear mapping. Compared with the previous deep subspace clustering (DSC) techniques, our DCFSC does not have any parameters at all for the self-expressive layer. Instead, DCFSC utilizes ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	142,841
2405.17615	Listenable Maps for Zero-Shot Audio Classifiers	Interpreting the decisions of deep learning models, including audio classifiers, is crucial for ensuring the transparency and trustworthiness of this technology. In this paper, we introduce LMAC-ZS (Listenable Maps for Audio Classifiers in the Zero-Shot context), which, to the best of our knowledge, is the first decode...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	458,026
2010.05185	Constructing a Visual Relationship Authenticity Dataset	A visual relationship denotes a relationship between two objects in an image, which can be represented as a triplet of (subject; predicate; object). Visual relationship detection is crucial for scene understanding in images. Existing visual relationship detection datasets only contain true relationships that correctly ...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	200,020
1810.03201	Optimal Policies for Status Update Generation in a Wireless System with Heterogeneous Traffic	A large body of applications that involve monitoring, decision making, and forecasting require timely status updates for their efficient operation. Age of Information (AoI) is a newly proposed metric that effectively captures this requirement. Recent research on the subject has derived AoI optimal policies for the gene...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	109,759
2402.06251	Single Channel EEG Based Insomnia Identification Without Sleep Stage Annotations	This paper proposes a new approach to identifying patients with insomnia using a single EEG channel, without the need for sleep stage annotation. Data preprocessing, feature extraction, feature selection, and classification techniques are used to automatically detect insomnia based on features extracted from spectral a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	428,232
1805.12549	Channel Gating Neural Networks	This paper introduces channel gating, a dynamic, fine-grained, and hardware-efficient pruning scheme to reduce the computation cost for convolutional neural networks (CNNs). Channel gating identifies regions in the features that contribute less to the classification result, and skips the computation on a subset of the ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	99,203
2410.12475	Aegis:An Advanced LLM-Based Multi-Agent for Intelligent Functional Safety Engineering	Functional safety is a critical aspect of automotive engineering, encompassing all phases of a vehicle's lifecycle, including design, development, production, operation, and decommissioning. This domain involves highly knowledge-intensive tasks. This paper introduces Aegis: An Advanced LLM-Based Multi-Agent for Intelli...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	499,049
2012.07023	InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees	Building deep learning models on source code has found many successful software engineering applications, such as code search, code comment generation, bug detection, code migration, and so on. Current learning techniques, however, have a major drawback that these models are mostly trained on datasets labeled for parti...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	211,316
2103.14797	Unsupervised Self-Training for Sentiment Analysis of Code-Switched Data	Sentiment analysis is an important task in understanding social media content like customer reviews, Twitter and Facebook feeds etc. In multilingual communities around the world, a large amount of social media text is characterized by the presence of Code-Switching. Thus, it has become important to build models that ca...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	226,972
2501.13925	GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing	Recent advances in large multimodal models (LMMs) have recognized fine-grained grounding as an imperative factor of visual understanding and dialogue. However, the benefits of such representation in LMMs are limited to the natural image domain, and these models perform poorly for remote sensing (RS). The distinct overh...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	526,881
2110.15866	Towards Comparative Physical Interpretation of Spatial Variability Aware Neural Networks: A Summary of Results	Given Spatial Variability Aware Neural Networks (SVANNs), the goal is to investigate mathematical (or computational) models for comparative physical interpretation towards their transparency (e.g., simulatibility, decomposability and algorithmic transparency). This problem is important due to important use-cases such a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	264,029
1204.0199	Delay-aware BS Discontinuous Transmission Control and User Scheduling for Energy Harvesting Downlink Coordinated MIMO Systems	In this paper, we propose a two-timescale delay-optimal base station Discontinuous Transmission (BS-DTX) control and user scheduling for downlink coordinated MIMO systems with energy harvesting capability. To reduce the complexity and signaling overhead in practical systems, the BS-DTX control is adaptive to both the e...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	15,233
2408.06397	Distributed Stackelberg Strategies in State-based Potential Games for Autonomous Decentralized Learning Manufacturing Systems	This article describes a novel game structure for autonomously optimizing decentralized manufacturing systems with multi-objective optimization challenges, namely Distributed Stackelberg Strategies in State-Based Potential Games (DS2-SbPG). DS2-SbPG integrates potential games and Stackelberg games, which improves the c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	true	480,196
2312.02416	Towards Fast and Stable Federated Learning: Confronting Heterogeneity via Knowledge Anchor	Federated learning encounters a critical challenge of data heterogeneity, adversely affecting the performance and convergence of the federated model. Various approaches have been proposed to address this issue, yet their effectiveness is still limited. Recent studies have revealed that the federated model suffers sever...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	412,854
1909.07616	Coherence Statistics of Structured Random Ensembles and Support Detection Bounds for OMP	A structured random matrix ensemble that maintains constant modulus entries and unit-norm columns, often called a random phase-rotated (RPR) matrix, is considered in this paper. We analyze the coherence statistics of RPR measurement matrices and apply them to acquire probabilistic performance guarantees of orthogonal m...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	145,724
1905.07464	A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels	Preventable adverse drug reactions as a result of medical errors present a growing concern in modern medicine. As drug-drug interactions (DDIs) may cause adverse reactions, being able to extracting DDIs from drug labels into machine-readable form is an important effort in effectively deploying drug safety information. ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	131,238
2203.10886	ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding	Recently, learned image compression techniques have achieved remarkable performance, even surpassing the best manually designed lossy image coders. They are promising to be large-scale adopted. For the sake of practicality, a thorough investigation of the architecture design of learned image compression, regarding both...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,720
2205.11242	Fusing Multiscale Texture and Residual Descriptors for Multilevel 2D Barcode Rebroadcasting Detection	Nowadays, 2D barcodes have been widely used for advertisement, mobile payment, and product authentication. However, in applications related to product authentication, an authentic 2D barcode can be illegally copied and attached to a counterfeited product in such a way to bypass the authentication scheme. In this paper,...	false	false	false	false	true	false	false	false	false	false	false	true	true	false	false	false	false	false	298,065
1602.00214	Dimensionality Reduction via Regression in Hyperspectral Imagery	This paper introduces a new unsupervised method for dimensionality reduction via regression (DRR). The algorithm belongs to the family of invertible transforms that generalize Principal Component Analysis (PCA) by using curvilinear instead of linear features. DRR identifies the nonlinear features through multivariate r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	51,544
1109.4173	Energy-Efficient Full Diversity Collaborative Unitary Space-Time Block Code Design via Unique Factorization of Signals	In this paper, a novel concept called a \textit{uniquely factorable constellation pair} (UFCP) is proposed for the systematic design of a noncoherent full diversity collaborative unitary space-time block code by normalizing two Alamouti codes for a wireless communication system having two transmitter antennas and a sin...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,236
1406.6170	Distributed Storage Systems based on Equidistant Subspace Codes	Distributed storage systems based on equidistant constant dimension codes are presented. These equidistant codes are based on the Pl\"{u}cker embedding, which is essential in the repair and the reconstruction algorithms. These systems posses several useful properties such as high failure resilience, minimum bandwidth, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,096
2102.08127	Learning curves of generic features maps for realistic datasets with a teacher-student model	Teacher-student models provide a framework in which the typical-case performance of high-dimensional supervised learning can be described in closed form. The assumptions of Gaussian i.i.d. input data underlying the canonical teacher-student model may, however, be perceived as too restrictive to capture the behaviour of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	220,354
2412.05547	KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models	Large language models with retrieval-augmented generation encounter a pivotal challenge in intricate retrieval tasks, e.g., multi-hop question answering, which requires the model to navigate across multiple documents and generate comprehensive responses based on fragmented information. To tackle this challenge, we intr...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	514,865
2403.07567	Triples-to-isiXhosa (T2X): Addressing the Challenges of Low-Resource Agglutinative Data-to-Text Generation	Most data-to-text datasets are for English, so the difficulties of modelling data-to-text for low-resource languages are largely unexplored. In this paper we tackle data-to-text for isiXhosa, which is low-resource and agglutinative. We introduce Triples-to-isiXhosa (T2X), a new dataset based on a subset of WebNLG, whic...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	436,941
2210.07277	The Hidden Uniform Cluster Prior in Self-Supervised Learning	A successful paradigm in representation learning is to perform self-supervised pretraining using tasks based on mini-batch statistics (e.g., SimCLR, VICReg, SwAV, MSN). We show that in the formulation of all these methods is an overlooked prior to learn features that enable uniform clustering of the data. While this pr...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	323,636
1106.1652	Distributed Storage Codes through Hadamard Designs	In distributed storage systems that employ erasure coding, the issue of minimizing the total {\it repair bandwidth} required to exactly regenerate a storage node after a failure arises. This repair bandwidth depends on the structure of the storage code and the repair strategies used to restore the lost data. Minimizing...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	10,771
2011.05279	A review of neural network algorithms and their applications in supercritical extraction	Neural network realizes multi-parameter optimization and control by simulating certain mechanisms of the human brain. It can be used in many fields such as signal processing, intelligent driving, optimal combination, vehicle abnormality detection, and chemical process optimization control. Supercritical extraction is a...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	205,855
2306.05245	Matching Latent Encoding for Audio-Text based Keyword Spotting	Using audio and text embeddings jointly for Keyword Spotting (KWS) has shown high-quality results, but the key challenge of how to semantically align two embeddings for multi-word keywords of different sequence lengths remains largely unsolved. In this paper, we propose an audio-text-based end-to-end model architecture...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,110
2410.05167	Presto! Distilling Steps and Layers for Accelerating Music Generation	Despite advances in diffusion-based text-to-music (TTM) methods, efficient, high-quality generation remains a challenge. We introduce Presto!, an approach to inference acceleration for score-based diffusion transformers via reducing both sampling steps and cost per step. To reduce steps, we develop a new score-based di...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	495,600
2312.01314	NLEBench+NorGLM: A Comprehensive Empirical Analysis and Benchmark Dataset for Generative Language Models in Norwegian	Norwegian, spoken by only 5 million population, is under-representative within the most impressive breakthroughs in NLP tasks. To the best of our knowledge, there has not yet been a comprehensive evaluation of the existing language models (LMs) on Norwegian generation tasks during the article writing process. To fill t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	412,405
2008.07764	New Quality Metrics for Dynamic Graph Drawing	In this paper, we present new quality metrics for dynamic graph drawings. Namely, we present a new framework for change faithfulness metrics for dynamic graph drawings, which compare the ground truth change in dynamic graphs and the geometric change in drawings. More specifically, we present two specific instances, clu...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	192,218
2105.10241	Predictive control barrier functions: Enhanced safety mechanisms for learning-based control	While learning-based control techniques often outperform classical controller designs, safety requirements limit the acceptance of such methods in many applications. Recent developments address this issue through so-called predictive safety filters, which assess if a proposed learning-based control input can lead to co...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	236,327
1008.2565	Multigraph Sampling of Online Social Networks	State-of-the-art techniques for probability sampling of users of online social networks (OSNs) are based on random walks on a single social relation (typically friendship). While powerful, these methods rely on the social graph being fully connected. Furthermore, the mixing time of the sampling process strongly depends...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	7,282
2112.13350	Novel Dual-Channel Long Short-Term Memory Compressed Capsule Networks for Emotion Recognition	Recent analysis on speech emotion recognition has made considerable advances with the use of MFCCs spectrogram features and the implementation of neural network approaches such as convolutional neural networks (CNNs). Capsule networks (CapsNet) have gained gratitude as alternatives to CNNs with their larger capacities ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,217
1408.5574	Supervised Hashing Using Graph Cuts and Boosted Decision Trees	Embedding image features into a binary Hamming space can improve both the speed and accuracy of large-scale query-by-example image retrieval systems. Supervised hashing aims to map the original features to compact binary codes in a manner which preserves the label-based similarities of the original data. Most existing ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	35,564
1103.6067	Short proofs of the Quantum Substate Theorem	The Quantum Substate Theorem due to Jain, Radhakrishnan, and Sen (2002) gives us a powerful operational interpretation of relative entropy, in fact, of the observational divergence of two quantum states, a quantity that is related to their relative entropy. Informally, the theorem states that if the observational diver...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	9,821
2411.08894	Temporal Patterns of Multiple Long-Term Conditions in Individuals with Intellectual Disability Living in Wales: An Unsupervised Clustering Approach to Disease Trajectories	Identifying and understanding the co-occurrence of multiple long-term conditions (MLTC) in individuals with intellectual disabilities (ID) is vital for effective healthcare management. These individuals often face earlier onset and higher prevalence of MLTCs, yet specific co-occurrence patterns remain unexplored. This ...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	508,056
1112.4906	Passive and Driven Trends in the Evolution of Complexity	The nature and source of evolutionary trends in complexity is difficult to assess from the fossil record, and the driven vs. passive nature of such trends has been debated for decades. There are also questions about how effectively artificial life software can evolve increasing levels of complexity. We extend our previ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	13,549
2502.01248	Computational modelling of cancer nanomedicine: Integrating hyperthermia treatment into a multiphase porous-media tumour model	Heat-based cancer treatment, so-called hyperthermia, can be used to destroy tumour cells directly or to make them more susceptible to chemotherapy or radiation therapy. To apply heat locally, iron oxide nanoparticles are injected into the bloodstream and accumulate at the tumour site, where they generate heat when expo...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	529,770
2408.06450	Evaluating Language Models for Efficient Code Generation	We introduce Differential Performance Evaluation (DPE), a framework designed to reliably evaluate Large Language Models (LLMs) for efficient code generation. Traditional coding benchmarks often fail to provide reliable insights into code efficiency, due to their reliance on simplistic test inputs and the absence of eff...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	480,209
1907.05056	Kolmogorov complexity in the USSR (1975--1982): isolation and its end	These reminiscences are about the "dark ages" of algorithmic information theory in the USSR. After a great interest in this topic in 1960s and the beginning of 1970s the number of people working in this area in the USSR decreased significantly. At that time L.A. Levin published a bunch of papers that were seminal for t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	138,268
1901.11417	Geometric fluid approximation for general continuous-time Markov chains	Fluid approximations have seen great success in approximating the macro-scale behaviour of Markov systems with a large number of discrete states. However, these methods rely on the continuous-time Markov chain (CTMC) having a particular population structure which suggests a natural continuous state-space endowed with a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	120,247
1506.06825	DeepStereo: Learning to Predict New Views from the World's Imagery	Deep networks have recently enjoyed enormous success when applied to recognition and classification problems in computer vision, but their use in graphics problems has been limited. In this work, we present a novel deep architecture that performs new view synthesis directly from pixels, trained from a large number of p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	44,449
2402.14449	On decentralized computation of the leader's strategy in bi-level games	Motivated by the omnipresence of hierarchical structures in many real-world applications, this study delves into the intricate realm of bi-level games, with a specific focus on exploring local Stackelberg equilibria as a solution concept. While existing literature offers various methods tailored to specific game struct...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	431,690
1905.03899	Integrating Artificial Intelligence into Weapon Systems	The integration of Artificial Intelligence (AI) into weapon systems is one of the most consequential tactical and strategic decisions in the history of warfare. Current AI development is a remarkable combination of accelerating capability, hidden decision mechanisms, and decreasing costs. Implementation of these system...	false	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	130,317
1902.06818	Data augmentation for low resource sentiment analysis using generative adversarial networks	Sentiment analysis is a task that may suffer from a lack of data in certain cases, as the datasets are often generated and annotated by humans. In cases where data is inadequate for training discriminative models, generate models may aid training via data augmentation. Generative Adversarial Networks (GANs) are one suc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	121,845
1912.11283	An Analisys of Application Logs with Splunk : developing an App for the synthetic analysis of data and security incidents	The present work aims to enhance the application logs of an hypothetical infrastructure platform, and to build an App that displays the synthetic data about performance, anomalies and security incidents synthesized in the form of a Dashboard. The reference architecture, with multiple applications and multiple HW distri...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	158,532
2311.17165	(Ir)rationality in AI: State of the Art, Research Challenges and Open Questions	The concept of rationality is central to the field of artificial intelligence. Whether we are seeking to simulate human reasoning, or the goal is to achieve bounded optimality, we generally seek to make artificial agents as rational as possible. Despite the centrality of the concept within AI, there is no unified defin...	true	false	false	false	true	false	true	false	false	false	false	false	false	true	true	false	false	false	411,200
2011.02563	Fault-Tolerant Individual Pitch Control of Floating Offshore Wind Turbines via Subspace Predictive Repetitive Control	Individual Pitch Control (IPC) is an effective and widely-used strategy to mitigate blade loads in wind turbines. However, conventional IPC fails to cope with blade and actuator faults, and this situation may lead to an emergency shutdown and increased maintenance costs. In this paper, a Fault-Tolerant Individual Pitch...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	204,957
2401.15288	STAC: Leveraging Spatio-Temporal Data Associations For Efficient Cross-Camera Streaming and Analytics	We propose an efficient cross-cameras surveillance system called,STAC, that leverages spatio-temporal associations between multiple cameras to provide real-time analytics and inference under constrained network environments. STAC is built using the proposed omni-scale feature learning people reidentification (reid) alg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	424,388
2406.00976	Generative Pre-trained Speech Language Model with Efficient Hierarchical Transformer	While recent advancements in speech language models have achieved significant progress, they face remarkable challenges in modeling the long acoustic sequences of neural audio codecs. In this paper, we introduce \textbf{G}enerative \textbf{P}re-trained \textbf{S}peech \textbf{T}ransformer (GPST), a hierarchical transfo...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	460,108
2310.17878	A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time	We address the problem of designing a sublinear-time spectral clustering oracle for graphs that exhibit strong clusterability. Such graphs contain $k$ latent clusters, each characterized by a large inner conductance (at least $\varphi$) and a small outer conductance (at most $\varepsilon$). Our aim is to preprocess the...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	403,325
2201.12965	Inverse design of photonic devices with strict foundry fabrication constraints	We introduce a new method for inverse design of nanophotonic devices which guarantees that resulting designs satisfy strict length scale constraints - including minimum width and spacing constraints required by commercial semiconductor foundries. The method adopts several concepts from machine learning to transform the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	277,848
2306.10475	SpreadDetect: Detection of spreading change in a network over time	Change-point analysis has been successfully applied to the detect changes in multivariate data streams over time. In many applications, when data are observed over a graph/network, change does not occur simultaneously but instead spread from an initial source coordinate to the neighbouring coordinates over time. We pro...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	374,246
1711.10688	Facial Dynamics Interpreter Network: What are the Important Relations between Local Dynamics for Facial Trait Estimation?	Human face analysis is an important task in computer vision. According to cognitive-psychological studies, facial dynamics could provide crucial cues for face analysis. The motion of a facial local region in facial expression is related to the motion of other facial local regions. In this paper, a novel deep learning a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,647
2203.00115	The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields	Both a good understanding of geometrical concepts and a broad familiarity with objects lead to our excellent perception of moving objects. The human ability to detect and segment moving objects works in the presence of multiple objects, complex background geometry, motion of the observer and even camouflage. How humans...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	282,873
1905.08501	PDH : Probabilistic deep hashing based on MAP estimation of Hamming distance	With the growth of image on the web, research on hashing which enables high-speed image retrieval has been actively studied. In recent years, various hashing methods based on deep neural networks have been proposed and achieved higher precision than the other hashing methods. In these methods, multiple losses for hash ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	131,483
1302.5729	Sparse Signal Estimation by Maximally Sparse Convex Optimization	This paper addresses the problem of sparsity penalized least squares for applications in sparse signal processing, e.g. sparse deconvolution. This paper aims to induce sparsity more strongly than L1 norm regularization, while avoiding non-convex optimization. For this purpose, this paper describes the design and use of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	22,319
2306.16854	On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth	We examine the assumption that the hidden-state vectors of recurrent neural networks (RNNs) tend to form clusters of semantically similar vectors, which we dub the clustering hypothesis. While this hypothesis has been assumed in the analysis of RNNs in recent years, its validity has not been studied thoroughly on moder...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	376,509
2202.01619	On Manifold Hypothesis: Hypersurface Submanifold Embedding Using Osculating Hyperspheres	Consider a set of $n$ data points in the Euclidean space $\mathbb{R}^d$. This set is called dataset in machine learning and data science. Manifold hypothesis states that the dataset lies on a low-dimensional submanifold with high probability. All dimensionality reduction and manifold learning methods have the assumptio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,531
2010.09925	Hierarchical Paired Channel Fusion Network for Street Scene Change Detection	Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging task in the computer vision community. The intuitive way to solve the SSCD task is to fuse the extracted image feature pairs, and then directl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	201,707
2004.13688	Variational Integrator Graph Networks for Learning Energy Conserving Dynamical Systems	Recent advances show that neural networks embedded with physics-informed priors significantly outperform vanilla neural networks in learning and predicting the long term dynamics of complex physical systems from noisy data. Despite this success, there has only been a limited study on how to optimally combine physics pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	174,634
cs/0006005	Novelty Detection for Robot Neotaxis	The ability of a robot to detect and respond to changes in its environment is potentially very useful, as it draws attention to new and potentially important features. We describe an algorithm for learning to filter out previously experienced stimuli to allow further concentration on novel features. The algorithm uses ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	537,119
2406.05119	Compositional Curvature Bounds for Deep Neural Networks	A key challenge that threatens the widespread use of neural networks in safety-critical applications is their vulnerability to adversarial attacks. In this paper, we study the second-order behavior of continuously differentiable deep neural networks, focusing on robustness against adversarial perturbations. First, we p...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	461,999
2309.11691	RAI4IoE: Responsible AI for Enabling the Internet of Energy	This paper plans to develop an Equitable and Responsible AI framework with enabling techniques and algorithms for the Internet of Energy (IoE), in short, RAI4IoE. The energy sector is going through substantial changes fueled by two key drivers: building a zero-carbon energy sector and the digital transformation of the ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	393,502
2212.09947	Future Sight: Dynamic Story Generation with Large Pretrained Language Models	Recent advances in deep learning research, such as transformers, have bolstered the ability for automated agents to generate creative texts similar to those that a human would write. By default, transformer decoders can only generate new text with respect to previously generated text. The output distribution of candida...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	337,266

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