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
2203.00238	Uncertainty categories in medical image segmentation: a study of source-related diversity	Measuring uncertainties in the output of a deep learning method is useful in several ways, such as in assisting with interpretation of the outputs, helping build confidence with end users, and for improving the training and performance of the networks. Several different methods have been proposed to estimate uncertaint...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	282,926
2303.08028	EdgeServe: A Streaming System for Decentralized Model Serving	The relevant features for a machine learning task may arrive as one or more continuous streams of data. Serving machine learning models over streams of data creates a number of interesting systems challenges in managing data routing, time-synchronization, and rate control. This paper presents EdgeServe, a distributed s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	true	351,477
2009.10794	Investigating Machine Learning Methods for Language and Dialect Identification of Cuneiform Texts	Identification of the languages written using cuneiform symbols is a difficult task due to the lack of resources and the problem of tokenization. The Cuneiform Language Identification task in VarDial 2019 addresses the problem of identifying seven languages and dialects written in cuneiform; Sumerian and six dialects o...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	196,983
2004.04907	Socioeconomic correlations of urban patterns inferred from aerial images: interpreting activation maps of Convolutional Neural Networks	Urbanisation is a great challenge for modern societies, promising better access to economic opportunities while widening socioeconomic inequalities. Accurately tracking how this process unfolds has been challenging for traditional data collection methods, while remote sensing information offers an alternative to gather...	false	false	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	172,022
2408.05697	Evaluating BM3D and NBNet: A Comprehensive Study of Image Denoising Across Multiple Datasets	This paper investigates image denoising, comparing traditional non-learning-based techniques, represented by Block-Matching 3D (BM3D), with modern learning-based methods, exemplified by NBNet. We assess these approaches across diverse datasets, including CURE-OR, CURE-TSR, SSID+, Set-12, and Chest-Xray, each presenting...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	479,894
2403.05102	Enhancing Texture Generation with High-Fidelity Using Advanced Texture Priors	The recent advancements in 2D generation technology have sparked a widespread discussion on using 2D priors for 3D shape and texture content generation. However, these methods often overlook the subsequent user operations, such as texture aliasing and blurring that occur when the user acquires the 3D model and simplifi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	435,869
2409.09302	Heterogeneous Roles against Assignment Based Policies in Two vs Two Target Defense Game	In this paper, we consider a target defense game in which the attacker team seeks to reach a high-value target while the defender team seeks to prevent that by capturing them away from the target. To address the curse of dimensionality, a popular approach to solve such team-vs-team game is to decompose it into a set of...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	488,260
2103.05465	PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency	Removing outlier correspondences is one of the critical steps for successful feature-based point cloud registration. Despite the increasing popularity of introducing deep learning methods in this field, spatial consistency, which is essentially established by a Euclidean transformation between point clouds, has receive...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	223,989
1904.09764	Deep Anchored Convolutional Neural Networks	Convolutional Neural Networks (CNNs) have been proven to be extremely successful at solving computer vision tasks. State-of-the-art methods favor such deep network architectures for its accuracy performance, with the cost of having massive number of parameters and high weights redundancy. Previous works have studied ho...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	128,476
2502.11234	MaskFlow: Discrete Flows For Flexible and Efficient Long Video Generation	Generating long, high-quality videos remains a challenge due to the complex interplay of spatial and temporal dynamics and hardware limitations. In this work, we introduce \textbf{MaskFlow}, a unified video generation framework that combines discrete representations with flow-matching to enable efficient generation of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	534,262
1212.4940	Fourier Domain Beamforming for Medical Ultrasound	Sonography techniques use multiple transducer elements for tissue visualization. Signals detected at each element are sampled prior to digital beamforming. The required sampling rates are up to 4 times the Nyquist rate of the signal and result in considerable amount of data, that needs to be stored and processed. A dev...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	20,501
2203.02997	Smoothing with the Best Rectangle Window is Optimal for All Tapered Rectangle Windows	We investigate the optimal selection of weight windows for the problem of weighted least squares. We show that weight windows should be symmetric around its center, which is also its peak. We consider the class of tapered rectangle window weights, which are nonincreasing away from the center. We show that the best rect...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,932
1102.3181	Spatially Coupled Quasi-Cyclic Quantum LDPC Codes	We face the following dilemma for designing low-density parity-check codes (LDPC) for quantum error correction. 1) The row weights of parity-check should be large: The minimum distances are bounded above by the minimum row weights of parity-check matrices of constituent classical codes. Small minimum distance tends to ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,218
1908.06566	Adversarial Defense by Suppressing High-frequency Components	Recent works show that deep neural networks trained on image classification dataset bias towards textures. Those models are easily fooled by applying small high-frequency perturbations to clean images. In this paper, we learn robust image classification models by removing high-frequency components. Specifically, we dev...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	142,049
2302.08091	Do We Still Need Clinical Language Models?	Although recent advances in scaling large language models (LLMs) have resulted in improvements on many NLP tasks, it remains unclear whether these models trained primarily with general web text are the right tool in highly specialized, safety critical domains such as clinical text. Recent results have suggested that LL...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	345,938
2012.00802	Adversarial Robustness Across Representation Spaces	Adversarial robustness corresponds to the susceptibility of deep neural networks to imperceptible perturbations made at test time. In the context of image tasks, many algorithms have been proposed to make neural networks robust to adversarial perturbations made to the input pixels. These perturbations are typically mea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	209,239
1509.05281	Network analysis of named entity co-occurrences in written texts	The use of methods borrowed from statistics and physics to analyze written texts has allowed the discovery of unprecedent patterns of human behavior and cognition by establishing links between models features and language structure. While current models have been useful to unveil patterns via analysis of syntactical an...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	47,027
1307.3696	Where in the Internet is congestion?	Understanding the distribution of congestion in the Internet is a long-standing problem. Using data from the SamKnows US broadband access network measurement study, commissioned by the FCC, we explore patterns of congestion distribution in DSL and cable Internet service provider (ISP) networks. Using correlation-based ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	25,823
1102.0674	Effective Mechanism for Social Recommendation of News	Recommendation systems represent an important tool for news distribution on the Internet. In this work we modify a recently proposed social recommendation model in order to deal with no explicit ratings of users on news. The model consists of a network of users which continually adapts in order to achieve an efficient ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	9,012
2111.07525	Automatic Analysis of Linguistic Features in Journal Articles of Different Academic Impacts with Feature Engineering Techniques	English research articles (RAs) are an essential genre in academia, so the attempts to employ NLP to assist the development of academic writing ability have received considerable attention in the last two decades. However, there has been no study employing feature engineering techniques to investigate the linguistic fe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	266,404
2403.12194	The POLAR Traverse Dataset: A Dataset of Stereo Camera Images Simulating Traverses across Lunar Polar Terrain under Extreme Lighting Conditions	We present the POLAR Traverse Dataset: a dataset of high-fidelity stereo pair images of lunar-like terrain under polar lighting conditions designed to simulate a straight-line traverse. Images from individual traverses with different camera heights and pitches were recorded at 1 m intervals by moving a suspended stereo...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	439,068
2203.01488	PetsGAN: Rethinking Priors for Single Image Generation	Single image generation (SIG), described as generating diverse samples that have similar visual content with the given single image, is first introduced by SinGAN which builds a pyramid of GANs to progressively learn the internal patch distribution of the single image. It also shows great potentials in a wide range of ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	283,392
2202.00441	Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction	Memory footprint is one of the main limiting factors for large neural network training. In backpropagation, one needs to store the input to each operation in the computational graph. Every modern neural network model has quite a few pointwise nonlinearities in its architecture, and such operation induces additional mem...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	278,137
1808.02350	YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud	Object detection and classification in 3D is a key task in Automated Driving (AD). LiDAR sensors are employed to provide the 3D point cloud reconstruction of the surrounding environment, while the task of 3D object bounding box detection in real time remains a strong algorithmic challenge. In this paper, we build on th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,755
2304.12858	Unpaired Image Translation to Mitigate Domain Shift in Liquid Argon Time Projection Chamber Detector Responses	Deep learning algorithms often are trained and deployed on different datasets. Any systematic difference between the training and a test dataset may degrade the algorithm performance--what is known as the domain shift problem. This issue is prevalent in many scientific domains where algorithms are trained on simulated ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	360,372
2310.16109	Complex Image Generation SwinTransformer Network for Audio Denoising	Achieving high-performance audio denoising is still a challenging task in real-world applications. Existing time-frequency methods often ignore the quality of generated frequency domain images. This paper converts the audio denoising problem into an image generation task. We first develop a complex image generation Swi...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	402,576
2402.08898	UniEnc-CASSNAT: An Encoder-only Non-autoregressive ASR for Speech SSL Models	Non-autoregressive automatic speech recognition (NASR) models have gained attention due to their parallelism and fast inference. The encoder-based NASR, e.g. connectionist temporal classification (CTC), can be initialized from the speech foundation models (SFM) but does not account for any dependencies among intermedia...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	429,283
1602.00095	Walsh Sampling with Incomplete Noisy Signals	With the advent of massive data outputs at a regular rate, admittedly, signal processing technology plays an increasingly key role. Nowadays, signals are not merely restricted to physical sources, they have been extended to digital sources as well. Under the general assumption of discrete statistical signal sources, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,524
2406.08575	Using Quality Attribute Scenarios for ML Model Test Case Generation	Testing of machine learning (ML) models is a known challenge identified by researchers and practitioners alike. Unfortunately, current practice for ML model testing prioritizes testing for model performance, while often neglecting the requirements and constraints of the ML-enabled system that integrates the model. This...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	463,539
2204.05862	Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback	We apply preference modeling and reinforcement learning from human feedback (RLHF) to finetune language models to act as helpful and harmless assistants. We find this alignment training improves performance on almost all NLP evaluations, and is fully compatible with training for specialized skills such as python coding...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	291,168
2405.01012	Correcting Biased Centered Kernel Alignment Measures in Biological and Artificial Neural Networks	Centred Kernel Alignment (CKA) has recently emerged as a popular metric to compare activations from biological and artificial neural networks (ANNs) in order to quantify the alignment between internal representations derived from stimuli sets (e.g. images, text, video) that are presented to both systems. In this paper ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	451,182
2309.00544	Modular, Multi-Robot Integration of Laboratories: An Autonomous Solid-State Workflow for Powder X-Ray Diffraction	Automation can transform productivity in research activities that use liquid handling, such as organic synthesis, but it has made less impact in materials laboratories, which require sample preparation steps and a range of solid-state characterization techniques. For example, powder X-ray diffraction (PXRD) is a key me...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	389,336
2407.08990	Dynamic neural network with memristive CIM and CAM for 2D and 3D vision	The brain is dynamic, associative and efficient. It reconfigures by associating the inputs with past experiences, with fused memory and processing. In contrast, AI models are static, unable to associate inputs with past experiences, and run on digital computers with physically separated memory and processing. We propos...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	true	472,398
2205.15879	Simplex Neural Population Learning: Any-Mixture Bayes-Optimality in Symmetric Zero-sum Games	Learning to play optimally against any mixture over a diverse set of strategies is of important practical interests in competitive games. In this paper, we propose simplex-NeuPL that satisfies two desiderata simultaneously: i) learning a population of strategically diverse basis policies, represented by a single condit...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	299,904
2212.08686	Evaluating Step-by-Step Reasoning through Symbolic Verification	Pre-trained language models (LMs) have shown remarkable reasoning performance using explanations or chain-of-thoughts (CoT)) for in-context learning. On the other hand, these reasoning tasks are usually presumed to be more approachable for symbolic programming. To understand the mechanism of reasoning of LMs, we curate...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	336,837
2105.10736	How They Tweet? An Insightful Analysis of Twitter Handles of Saudi Arabia	The emergence of social network site has attracted many users across the world to share their feeling, news, achievements and personal thoughts over several platforms. The recent crisis due to worldwide lockdown amid COVID 19 has shown how these online social platforms have grown stronger and turned up as the major sou...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	236,486
1612.02174	EMC Regulations and Spectral Constraints for Multicarrier Modulation in PLC	This paper considers Electromagnetic Compatibility (EMC) aspects in the context of Power Line Communication (PLC) systems. It offers a complete overview of both narrow band PLC and broad band PLC EMC norms. How to interpret and translate such norms and measurement procedures into typical constraints used by designers o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	65,197
2008.01566	On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations	With the prevalence of publicly available source code repositories to train deep neural network models, neural program models can do well in source code analysis tasks such as predicting method names in given programs that cannot be easily done by traditional program analysis techniques. Although such neural program mo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	190,375
0801.4287	Movie Recommendation Systems Using An Artificial Immune System	We apply the Artificial Immune System (AIS) technology to the Collaborative Filtering (CF) technology when we build the movie recommendation system. Two different affinity measure algorithms of AIS, Kendall tau and Weighted Kappa, are used to calculate the correlation coefficients for this movie recommendation system. ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	1,223
1412.2817	Diffusion Estimation Over Cooperative Multi-Agent Networks With Missing Data	In many fields, and especially in the medical and social sciences and in recommender systems, data are gathered through clinical studies or targeted surveys. Participants are generally reluctant to respond to all questions in a survey or they may lack information to respond adequately to some questions. The data collec...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	38,237
0905.0044	ADMiRA: Atomic Decomposition for Minimum Rank Approximation	We address the inverse problem that arises in compressed sensing of a low-rank matrix. Our approach is to pose the inverse problem as an approximation problem with a specified target rank of the solution. A simple search over the target rank then provides the minimum rank solution satisfying a prescribed data approxima...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,625
2208.10834	Real-Time Sonar Fusion for Layered Navigation Controller	Navigation in varied and dynamic indoor environments remains a complex task for autonomous mobile platforms. Especially when conditions worsen, typical sensor modalities may fail to operate optimally and subsequently provide inapt input for safe navigation control. In this study, we present an approach for the navigati...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	314,221
2004.10397	A Framework for Evaluating Gradient Leakage Attacks in Federated Learning	Federated learning (FL) is an emerging distributed machine learning framework for collaborative model training with a network of clients (edge devices). FL offers default client privacy by allowing clients to keep their sensitive data on local devices and to only share local training parameter updates with the federate...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	173,625
2410.19300	Golden Ratio-Based Sufficient Dimension Reduction	Many machine learning applications deal with high dimensional data. To make computations feasible and learning more efficient, it is often desirable to reduce the dimensionality of the input variables by finding linear combinations of the predictors that can retain as much original information as possible in the relati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	502,253
1610.06995	Modeling and Analysis of Uplink Non-Orthogonal Multiple Access (NOMA) in Large-Scale Cellular Networks Using Poisson Cluster Processes	Non-orthogonal multiple access (NOMA) serves multiple users by superposing their distinct message signals. The desired message signal is decoded at the receiver by applying successive interference cancellation (SIC). Using the theory of Poisson cluster process (PCP), we provide a framework to analyze multi-cell uplink ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	62,726
1711.01351	Uplink Performance Analysis of a Drone Cell in a Random Field of Ground Interferers	Aerial base stations are a promising technology to increase the capabilities of the existing communication networks. However, the existing analytical frameworks do not sufficiently characterize the impact of ground interferers on the aerial base stations. In order to address this issue, we model the effect of interfere...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	83,866
2006.09289	Isometric Autoencoders	High dimensional data is often assumed to be concentrated on or near a low-dimensional manifold. Autoencoders (AE) is a popular technique to learn representations of such data by pushing it through a neural network with a low dimension bottleneck while minimizing a reconstruction error. Using high capacity AE often lea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,506
2302.05294	MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope	Explaining the predictions of deep neural nets has been a topic of great interest in the computer vision literature. While several gradient-based interpretation schemes have been proposed to reveal the influential variables in a neural net's prediction, standard gradient-based interpretation frameworks have been common...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	344,994
1801.06172	Contextual and Position-Aware Factorization Machines for Sentiment Classification	While existing machine learning models have achieved great success for sentiment classification, they typically do not explicitly capture sentiment-oriented word interaction, which can lead to poor results for fine-grained analysis at the snippet level (a phrase or sentence). Factorization Machine provides a possible a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	88,567
1710.04200	Joint Image Filtering with Deep Convolutional Networks	Joint image filters leverage the guidance image as a prior and transfer the structural details from the guidance image to the target image for suppressing noise or enhancing spatial resolution. Existing methods either rely on various explicit filter constructions or hand-designed objective functions, thereby making it ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	82,446
2108.09986	Indoor Path Planning for an Unmanned Aerial Vehicle via Curriculum Learning	In this study, reinforcement learning was applied to learning two-dimensional path planning including obstacle avoidance by unmanned aerial vehicle (UAV) in an indoor environment. The task assigned to the UAV was to reach the goal position in the shortest amount of time without colliding with any obstacles. Reinforceme...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	251,762
2007.03006	Announcing CzEng 2.0 Parallel Corpus with over 2 Gigawords	We present a new release of the Czech-English parallel corpus CzEng 2.0 consisting of over 2 billion words (2 "gigawords") in each language. The corpus contains document-level information and is filtered with several techniques to lower the amount of noise. In addition to the data in the previous version of CzEng, it c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	185,915
2311.12502	Framework for continuous transition to Agile Systems Engineering in the Automotive Industry	The increasing pressure within VUCA (volatility, uncertainty, complexity and ambiguity) driven environments causes traditional, plan-driven Systems Engineering approaches to no longer suffice. Agility is then changing from a "nice-to-have" to a "must-have" capability for successful system developing organisations. The ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	409,362
2012.05858	SPAA: Stealthy Projector-based Adversarial Attacks on Deep Image Classifiers	Light-based adversarial attacks use spatial augmented reality (SAR) techniques to fool image classifiers by altering the physical light condition with a controllable light source, e.g., a projector. Compared with physical attacks that place hand-crafted adversarial objects, projector-based ones obviate modifying the ph...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	210,913
2501.09776	Multi-Head Self-Attending Neural Tucker Factorization	Quality-of-service (QoS) data exhibit dynamic temporal patterns that are crucial for accurately predicting missing values. These patterns arise from the evolving interactions between users and services, making it essential to capture the temporal dynamics inherent in such data for improved prediction performance. As th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	525,270
2211.14053	Re^2TAL: Rewiring Pretrained Video Backbones for Reversible Temporal Action Localization	Temporal action localization (TAL) requires long-form reasoning to predict actions of various durations and complex content. Given limited GPU memory, training TAL end to end (i.e., from videos to predictions) on long videos is a significant challenge. Most methods can only train on pre-extracted features without optim...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	332,703
2008.06982	A Self-supervised GAN for Unsupervised Few-shot Object Recognition	This paper addresses unsupervised few-shot object recognition, where all training images are unlabeled, and test images are divided into queries and a few labeled support images per object class of interest. The training and test images do not share object classes. We extend the vanilla GAN with two loss functions, bot...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,958
2102.11855	Deep Unitary Convolutional Neural Networks	Deep neural networks can suffer from the exploding and vanishing activation problem, in which the networks fail to train properly because the neural signals either amplify or attenuate across the layers and become saturated. While other normalization methods aim to fix the stated problem, most of them have inference sp...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	221,538
1810.05683	Long-Duration Autonomy for Small Rotorcraft UAS including Recharging	Many unmanned aerial vehicle surveillance and monitoring applications require observations at precise locations over long periods of time, ideally days or weeks at a time (e.g. ecosystem monitoring), which has been impractical due to limited endurance and the requirement of humans in the loop for operation. To overcome...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	110,282
2109.04145	PIMNet: A Parallel, Iterative and Mimicking Network for Scene Text Recognition	Nowadays, scene text recognition has attracted more and more attention due to its various applications. Most state-of-the-art methods adopt an encoder-decoder framework with attention mechanism, which generates text autoregressively from left to right. Despite the convincing performance, the speed is limited because of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	254,295
2408.03172	Leveraging Parameter Efficient Training Methods for Low Resource Text Classification: A Case Study in Marathi	With the surge in digital content in low-resource languages, there is an escalating demand for advanced Natural Language Processing (NLP) techniques tailored to these languages. BERT (Bidirectional Encoder Representations from Transformers), serving as the foundational framework for numerous NLP architectures and langu...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	478,921
2310.05072	Performance Analysis of RIS-Aided Double Spatial Scattering Modulation for mmWave MIMO Systems	In this paper, we investigate a practical structure of reconfigurable intelligent surface (RIS)-based double spatial scattering modulation (DSSM) for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. A suboptimal detector is proposed, in which the beam direction is first demodulated according to t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	397,968
2005.07064	Multi-agent Communication meets Natural Language: Synergies between Functional and Structural Language Learning	We present a method for combining multi-agent communication and traditional data-driven approaches to natural language learning, with an end goal of teaching agents to communicate with humans in natural language. Our starting point is a language model that has been trained on generic, not task-specific language data. W...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	177,182
2306.07646	Enhanced Multimodal Representation Learning with Cross-modal KD	This paper explores the tasks of leveraging auxiliary modalities which are only available at training to enhance multimodal representation learning through cross-modal Knowledge Distillation (KD). The widely adopted mutual information maximization-based objective leads to a short-cut solution of the weak teacher, i.e.,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	373,096
2305.17695	k-NNN: Nearest Neighbors of Neighbors for Anomaly Detection	Anomaly detection aims at identifying images that deviate significantly from the norm. We focus on algorithms that embed the normal training examples in space and when given a test image, detect anomalies based on the features distance to the k-nearest training neighbors. We propose a new operator that takes into accou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,708
2303.02901	$\alpha$-divergence Improves the Entropy Production Estimation via Machine Learning	Recent years have seen a surge of interest in the algorithmic estimation of stochastic entropy production (EP) from trajectory data via machine learning. A crucial element of such algorithms is the identification of a loss function whose minimization guarantees the accurate EP estimation. In this study, we show that th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	349,529
2410.01771	Bayesian Binary Search	We present Bayesian Binary Search (BBS), a novel probabilistic variant of the classical binary search/bisection algorithm. BBS leverages machine learning/statistical techniques to estimate the probability density of the search space and modifies the bisection step to split based on probability density rather than the t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	493,936
2008.10748	An empirical investigation of different classifiers, encoding and ensemble schemes for next event prediction using business process event logs	There is a growing need for empirical benchmarks that support researchers and practitioners in selecting the best machine learning technique for given prediction tasks. In this paper, we consider the next event prediction task in business process predictive monitoring and we extend our previously published benchmark by...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,074
1612.00385	Temporal Attention-Gated Model for Robust Sequence Classification	Typical techniques for sequence classification are designed for well-segmented sequences which have been edited to remove noisy or irrelevant parts. Therefore, such methods cannot be easily applied on noisy sequences expected in real-world applications. In this paper, we present the Temporal Attention-Gated Model (TAGM...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	64,873
2309.06286	Transferability analysis of data-driven additive manufacturing knowledge: a case study between powder bed fusion and directed energy deposition	Data-driven research in Additive Manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature to emerge. The knowledge in these works consists of AM and Artificial Intelligence (AI) contexts that have not been mined and formalized in an integrated way. Moreover,...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	391,374
1809.09613	Size Agnostic Change Point Detection Framework for Evolving Networks	Changes in the structure of observed social and complex networks' structure can indicate a significant underlying change in an organization, or reflect the response of the network to an external event. Automatic detection of change points in evolving networks is rudimentary to the research and the understanding of the ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	108,745
1904.07765	An Evaluation Framework for Interactive Recommender System	Traditional recommender systems present a relatively static list of recommendations to a user where the feedback is typically limited to an accept/reject or a rating model. However, these simple modes of feedback may only provide limited insights as to why a user likes or dislikes an item and what aspects of the item t...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	127,878
2501.05408	TimeRL: Efficient Deep Reinforcement Learning with Polyhedral Dependence Graphs	Modern deep learning (DL) workloads increasingly use complex deep reinforcement learning (DRL) algorithms that generate training data within the learning loop. This results in programs with several nested loops and dynamic data dependencies between tensors. While DL systems with eager execution support such dynamism, t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	523,566
1911.11726	Network Embedding: An Overview	Networks are one of the most powerful structures for modeling problems in the real world. Downstream machine learning tasks defined on networks have the potential to solve a variety of problems. With link prediction, for instance, one can predict whether two persons will become friends on a social network. Many machine...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,205
1905.05892	Pareto-Optimal Allocation of Transactive Energy at Market Equilibrium in Distribution Systems: A Constrained Vector Optimization Approach	In a grid constrained transactive distribution system market, distribution locational marginal pricing DLMP is influenced by the distance from the substation to an energy user, thereby causing households that are further away from the substation to be charged more. The Jain index of fairness, which has been recently ap...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	130,843
1405.5550	Application of Artificial Neural Networks in Predicting Abrasion Resistance of Solution Polymerized Styrene-Butadiene Rubber Based Composites	Abrasion resistance of solution polymerized styrene-butadiene rubber (SSBR) based composites is a typical and crucial property in practical applications. Previous studies show that the abrasion resistance can be calculated by the multiple linear regression model. In our study, considering this relationship can also be ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	33,282
2202.01764	JaQuAD: Japanese Question Answering Dataset for Machine Reading Comprehension	Question Answering (QA) is a task in which a machine understands a given document and a question to find an answer. Despite impressive progress in the NLP area, QA is still a challenging problem, especially for non-English languages due to the lack of annotated datasets. In this paper, we present the Japanese Question ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	278,577
2402.17906	Representation learning in multiplex graphs: Where and how to fuse information?	In recent years, unsupervised and self-supervised graph representation learning has gained popularity in the research community. However, most proposed methods are focused on homogeneous networks, whereas real-world graphs often contain multiple node and edge types. Multiplex graphs, a special type of heterogeneous gra...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	433,194
2209.09329	MAN: Multi-Action Networks Learning	Learning control policies with large discrete action spaces is a challenging problem in the field of reinforcement learning due to present inefficiencies in exploration. With high dimensional action spaces, there are a large number of potential actions in each individual dimension over which policies would be learned. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	318,461
1702.06506	PixelNet: Representation of the pixels, by the pixels, and for the pixels	We explore design principles for general pixel-level prediction problems, from low-level edge detection to mid-level surface normal estimation to high-level semantic segmentation. Convolutional predictors, such as the fully-convolutional network (FCN), have achieved remarkable success by exploiting the spatial redundan...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	68,625
2409.07823	Online vs Offline: A Comparative Study of First-Party and Third-Party Evaluations of Social Chatbots	This paper explores the efficacy of online versus offline evaluation methods in assessing conversational chatbots, specifically comparing first-party direct interactions with third-party observational assessments. By extending a benchmarking dataset of user dialogs with empathetic chatbots with offline third-party eval...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	487,677
2101.10587	Low Resource Recognition and Linking of Biomedical Concepts from a Large Ontology	Tools to explore scientific literature are essential for scientists, especially in biomedicine, where about a million new papers are published every year. Many such tools provide users the ability to search for specific entities (e.g. proteins, diseases) by tracking their mentions in papers. PubMed, the most well known...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	216,992
2405.14189	Semantic-guided Prompt Organization for Universal Goal Hijacking against LLMs	With the rising popularity of Large Language Models (LLMs), assessing their trustworthiness through security tasks has gained critical importance. Regarding the new task of universal goal hijacking, previous efforts have concentrated solely on optimization algorithms, overlooking the crucial role of the prompt. To fill...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	456,297
2402.05976	RankSum An unsupervised extractive text summarization based on rank fusion	In this paper, we propose Ranksum, an approach for extractive text summarization of single documents based on the rank fusion of four multi-dimensional sentence features extracted for each sentence: topic information, semantic content, significant keywords, and position. The Ranksum obtains the sentence saliency rankin...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	428,106
2203.06690	Algebraic Learning: Towards Interpretable Information Modeling	Along with the proliferation of digital data collected using sensor technologies and a boost of computing power, Deep Learning (DL) based approaches have drawn enormous attention in the past decade due to their impressive performance in extracting complex relations from raw data and representing valuable information. M...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	285,199
1602.03320	Graph Wavelets via Sparse Cuts: Extended Version	Modeling information that resides on vertices of large graphs is a key problem in several real-life applications, ranging from social networks to the Internet-of-things. Signal Processing on Graphs and, in particular, graph wavelets can exploit the intrinsic smoothness of these datasets in order to represent them in a ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	51,986
1103.2491	Heterogeneous Learning in Zero-Sum Stochastic Games with Incomplete Information	Learning algorithms are essential for the applications of game theory in a networking environment. In dynamic and decentralized settings where the traffic, topology and channel states may vary over time and the communication between agents is impractical, it is important to formulate and study games of incomplete infor...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	9,586
2409.18053	DualAD: Dual-Layer Planning for Reasoning in Autonomous Driving	We present a novel autonomous driving framework, DualAD, designed to imitate human reasoning during driving. DualAD comprises two layers: a rule-based motion planner at the bottom layer that handles routine driving tasks requiring minimal reasoning, and an upper layer featuring a rule-based text encoder that converts d...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	492,089
1909.08496	Exploring Bit-Slice Sparsity in Deep Neural Networks for Efficient ReRAM-Based Deployment	Emerging resistive random-access memory (ReRAM) has recently been intensively investigated to accelerate the processing of deep neural networks (DNNs). Due to the in-situ computation capability, analog ReRAM crossbars yield significant throughput improvement and energy reduction compared to traditional digital methods....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	145,991
1512.01859	Statistical Signatures of Structural Organization: The case of long memory in renewal processes	Identifying and quantifying memory are often critical steps in developing a mechanistic understanding of stochastic processes. These are particularly challenging and necessary when exploring processes that exhibit long-range correlations. The most common signatures employed rely on second-order temporal statistics and ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	49,875
2310.00646	Source Attribution for Large Language Model-Generated Data	The impressive performances of Large Language Models (LLMs) and their immense potential for commercialization have given rise to serious concerns over the Intellectual Property (IP) of their training data. In particular, the synthetic texts generated by LLMs may infringe the IP of the data being used to train the LLMs....	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	396,076
2304.03763	Clutter Detection and Removal in 3D Scenes with View-Consistent Inpainting	Removing clutter from scenes is essential in many applications, ranging from privacy-concerned content filtering to data augmentation. In this work, we present an automatic system that removes clutter from 3D scenes and inpaints with coherent geometry and texture. We propose techniques for its two key components: 3D se...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,936
2502.07254	Fairness in Multi-Agent AI: A Unified Framework for Ethical and Equitable Autonomous Systems	Ensuring fairness in decentralized multi-agent systems presents significant challenges due to emergent biases, systemic inefficiencies, and conflicting agent incentives. This paper provides a comprehensive survey of fairness in multi-agent AI, introducing a novel framework where fairness is treated as a dynamic, emerge...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	532,508
1710.02410	End-to-end Driving via Conditional Imitation Learning	Deep networks trained on demonstrations of human driving have learned to follow roads and avoid obstacles. However, driving policies trained via imitation learning cannot be controlled at test time. A vehicle trained end-to-end to imitate an expert cannot be guided to take a specific turn at an upcoming intersection. T...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	82,168
2207.06687	Breaking Correlation Shift via Conditional Invariant Regularizer	Recently, generalization on out-of-distribution (OOD) data with correlation shift has attracted great attentions. The correlation shift is caused by the spurious attributes that correlate to the class label, as the correlation between them may vary in training and test data. For such a problem, we show that given the c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	307,963
2105.06811	Quantified Sleep: Machine learning techniques for observational n-of-1 studies	This paper applies statistical learning techniques to an observational Quantified-Self (QS) study to build a descriptive model of sleep quality. A total of 472 days of my sleep data was collected with an Oura ring and combined with lifestyle, environmental, and psychological data. Such n-of-1 QS projects pose a number ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	235,237
1502.01228	Linear-time Online Action Detection From 3D Skeletal Data Using Bags of Gesturelets	Sliding window is one direct way to extend a successful recognition system to handle the more challenging detection problem. While action recognition decides only whether or not an action is present in a pre-segmented video sequence, action detection identifies the time interval where the action occurred in an unsegmen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	39,913
2207.04316	Improving Diffusion Model Efficiency Through Patching	Diffusion models are a powerful class of generative models that iteratively denoise samples to produce data. While many works have focused on the number of iterations in this sampling procedure, few have focused on the cost of each iteration. We find that adding a simple ViT-style patching transformation can considerab...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	307,157
2206.12617	Language Models as Knowledge Embeddings	Knowledge embeddings (KE) represent a knowledge graph (KG) by embedding entities and relations into continuous vector spaces. Existing methods are mainly structure-based or description-based. Structure-based methods learn representations that preserve the inherent structure of KGs. They cannot well represent abundant l...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	304,661
2411.18183	Equi join query acceleration using algebraic signatures (Published at IADIS'2008 Applied Computing conf.)	Evaluation of join queries is very challenging since they have to deal with an increasing data size. We study the relational join query processing realized by hash tables and we focus on the case of equi join queries. We propose to use a new form of signatures, the algebraic signatures, for fast comparison between valu...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	511,765

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