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
2409.16430	A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions	Large Language Models(LLMs) have revolutionized various applications in natural language processing (NLP) by providing unprecedented text generation, translation, and comprehension capabilities. However, their widespread deployment has brought to light significant concerns regarding biases embedded within these models....	true	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	491,338
1704.05623	Maximum Likelihood Detection for Cooperative Molecular Communication	In this paper, symbol-by-symbol maximum likelihood (ML) detection is proposed for a cooperative diffusion-based molecular communication (MC) system. In this system, a fusion center (FC) chooses the transmitter's symbol that is more likely, given the likelihood of the observations from multiple receivers (RXs). We propo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	72,043
1107.0019	Searching for Bayesian Network Structures in the Space of Restricted Acyclic Partially Directed Graphs	Although many algorithms have been designed to construct Bayesian network structures using different approaches and principles, they all employ only two methods: those based on independence criteria, and those based on a scoring function and a search procedure (although some methods combine the two). Within the score+s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	11,093
2411.09787	ART-Rx: A Proportional-Integral-Derivative (PID) Controlled Adaptive Real-Time Threshold Receiver for Molecular Communication	Molecular communication (MC) in microfluidic channels faces significant challenges in signal detection due to the stochastic nature of molecule propagation and dynamic, noisy environments. Conventional detection methods often struggle under varying channel conditions, leading to high bit error rates (BER) and reduced c...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	508,365
2411.15967	CNNs for Style Transfer of Digital to Film Photography	The use of deep learning in stylistic effect generation has seen increasing use over recent years. In this work, we use simple convolutional neural networks to model Cinestill800T film given a digital input. We test the effect of different loss functions, the addition of an input noise channel and the use of random sca...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,839
2212.10705	Control of Continuous Quantum Systems with Many Degrees of Freedom based on Convergent Reinforcement Learning	With the development of experimental quantum technology, quantum control has attracted increasing attention due to the realization of controllable artificial quantum systems. However, because quantum-mechanical systems are often too difficult to analytically deal with, heuristic strategies and numerical algorithms whic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	337,563
2404.12256	An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehicles	The autonomous driving industry is expected to grow by over 20 times in the coming decade and, thus, motivate researchers to delve into it. The primary focus of their research is to ensure safety, comfort, and efficiency. An autonomous vehicle has several modules responsible for one or more of the aforementioned items....	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	447,803
2403.12605	Online Marketplace: A Benchmark for Data Management in Microservices	Microservice architectures have become a popular approach for designing scalable distributed applications. Despite their extensive use in industrial settings for over a decade, there is limited understanding of the data management challenges that arise in these applications. Consequently, it has been difficult to advan...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	439,268
2402.14616	The Impact of Word Splitting on the Semantic Content of Contextualized Word Representations	When deriving contextualized word representations from language models, a decision needs to be made on how to obtain one for out-of-vocabulary (OOV) words that are segmented into subwords. What is the best way to represent these words with a single vector, and are these representations of worse quality than those of in...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	431,765
2308.08090	Separate the Wheat from the Chaff: Model Deficiency Unlearning via Parameter-Efficient Module Operation	Large language models (LLMs) have been widely used in various applications but are known to suffer from issues related to untruthfulness and toxicity. While parameter-efficient modules (PEMs) have demonstrated their effectiveness in equipping models with new skills, leveraging PEMs for deficiency unlearning remains und...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	385,760
1503.03355	Automatic Unsupervised Tensor Mining with Quality Assessment	A popular tool for unsupervised modelling and mining multi-aspect data is tensor decomposition. In an exploratory setting, where and no labels or ground truth are available how can we automatically decide how many components to extract? How can we assess the quality of our results, so that a domain expert can factor th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	41,041
2104.01711	Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning	With the ubiquitous graph-structured data in various applications, models that can learn compact but expressive vector representations of nodes have become highly desirable. Recently, bearing the message passing paradigm, graph neural networks (GNNs) have greatly advanced the performance of node representation learning...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	228,443
2404.11576	State-space Decomposition Model for Video Prediction Considering Long-term Motion Trend	Stochastic video prediction enables the consideration of uncertainty in future motion, thereby providing a better reflection of the dynamic nature of the environment. Stochastic video prediction methods based on image auto-regressive recurrent models need to feed their predictions back into the latent space. Conversely...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	447,543
1503.06870	The Lifecycles of Apps in a Social Ecosystem	Apps are emerging as an important form of on-line content, and they combine aspects of Web usage in interesting ways --- they exhibit a rich temporal structure of user adoption and long-term engagement, and they exist in a broader social ecosystem that helps drive these patterns of adoption and engagement. It has been ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	41,410
1907.04599	Adding Common Randomness Can Remove the Secrecy Constraints in Communication Networks	In communication networks secrecy constraints usually incur an extra limit in capacity or generalized degrees-of-freedom (GDoF), in the sense that a penalty in capacity or GDoF is incurred due to the secrecy constraints. Over the past decades a significant amount of effort has been made by the researchers to understand...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	138,148
1304.2722	Stochastic Simulation of Bayesian Belief Networks	This paper examines Bayesian belief network inference using simulation as a method for computing the posterior probabilities of network variables. Specifically, it examines the use of a method described by Henrion, called logic sampling, and a method described by Pearl, called stochastic simulation. We first review the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,731
2208.01373	DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction	Leveraging labelled data from multiple domains to enable prediction in another domain without labels is a significant, yet challenging problem. To address this problem, we introduce the framework DAPDAG (\textbf{D}omain \textbf{A}daptation via \textbf{P}erturbed \textbf{DAG} Reconstruction) and propose to learn an auto...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	311,146
2402.05052	Causal Representation Learning from Multiple Distributions: A General Setting	In many problems, the measured variables (e.g., image pixels) are just mathematical functions of the latent causal variables (e.g., the underlying concepts or objects). For the purpose of making predictions in changing environments or making proper changes to the system, it is helpful to recover the latent causal varia...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	427,704
2106.02668	Emergent Communication of Generalizations	To build agents that can collaborate effectively with others, recent research has trained artificial agents to communicate with each other in Lewis-style referential games. However, this often leads to successful but uninterpretable communication. We argue that this is due to the game objective: communicating about a s...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	238,962
2203.01327	Hyperspectral Pixel Unmixing with Latent Dirichlet Variational Autoencoder	We present a method for hyperspectral pixel {\it unmixing}. The proposed method assumes that (1) {\it abundances} can be encoded as Dirichlet distributions and (2) spectra of {\it endmembers} can be represented as multivariate Normal distributions. The method solves the problem of abundance estimation and endmember ext...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	283,343
2004.11300	CoInGP: Convolutional Inpainting with Genetic Programming	We investigate the use of Genetic Programming (GP) as a convolutional predictor for missing pixels in images. The training phase is performed by sweeping a sliding window over an image, where the pixels on the border represent the inputs of a GP tree. The output of the tree is taken as the predicted value for the centr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	173,873
1712.08250	ReabsNet: Detecting and Revising Adversarial Examples	Though deep neural network has hit a huge success in recent studies and applica- tions, it still remains vulnerable to adversarial perturbations which are imperceptible to humans. To address this problem, we propose a novel network called ReabsNet to achieve high classification accuracy in the face of various attacks. ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	87,160
1907.11049	Grammatical Sequence Prediction for Real-Time Neural Semantic Parsing	While sequence-to-sequence (seq2seq) models achieve state-of-the-art performance in many natural language processing tasks, they can be too slow for real-time applications. One performance bottleneck is predicting the most likely next token over a large vocabulary; methods to circumvent this bottleneck are a current re...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	139,769
1104.2156	Structural Analysis of Network Traffic Matrix via Relaxed Principal Component Pursuit	The network traffic matrix is widely used in network operation and management. It is therefore of crucial importance to analyze the components and the structure of the network traffic matrix, for which several mathematical approaches such as Principal Component Analysis (PCA) were proposed. In this paper, we first argu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	9,958
1812.03071	Design of a Networked Controller for a Two-Wheeled Inverted Pendulum Robot	The topic of this paper is to use an intuitive model-based approach to design a networked controller for a recent benchmark scenario. The benchmark problem is to remotely control a two-wheeled inverted pendulum robot via W-LAN communication. The robot has to keep a vertical upright position. Incorporating wireless comm...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	115,925
1802.00179	Full Image Recover for Block-Based Compressive Sensing	Recent years, compressive sensing (CS) has improved greatly for the application of deep learning technology. For convenience, the input image is usually measured and reconstructed block by block. This usually causes block effect in reconstructed images. In this paper, we present a novel CNN-based network to solve this ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,364
2006.08967	Robot Perception enables Complex Navigation Behavior via Self-Supervised Learning	Learning visuomotor control policies in robotic systems is a fundamental problem when aiming for long-term behavioral autonomy. Recent supervised-learning-based vision and motion perception systems, however, are often separately built with limited capabilities, while being restricted to few behavioral skills such as pa...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	182,378
2312.05464	Identifying and Mitigating Model Failures through Few-shot CLIP-aided Diffusion Generation	Deep learning models can encounter unexpected failures, especially when dealing with challenging sub-populations. One common reason for these failures is the occurrence of objects in backgrounds that are rarely seen during training. To gain a better understanding of these failure modes, human-interpretable descriptions...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	414,097
2107.12438	Debiasing In-Sample Policy Performance for Small-Data, Large-Scale Optimization	Motivated by the poor performance of cross-validation in settings where data are scarce, we propose a novel estimator of the out-of-sample performance of a policy in data-driven optimization.Our approach exploits the optimization problem's sensitivity analysis to estimate the gradient of the optimal objective value wit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	247,888
2101.08934	AS-Net: Fast Photoacoustic Reconstruction with Multi-feature Fusion from Sparse Data	Photoacoustic (PA) imaging is a biomedical imaging modality capable of acquiring high-contrast images of optical absorption at depths much greater than traditional optical imaging techniques. However, practical instrumentation and geometry limit the number of available acoustic sensors surrounding the imaging target, w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	216,452
2502.06192	Right Time to Learn:Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation	Knowledge distillation (KD) is a powerful strategy for training deep neural networks (DNNs). Although it was originally proposed to train a more compact ``student'' model from a large ``teacher'' model, many recent efforts have focused on adapting it to promote generalization of the model itself, such as online KD and ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	531,975
1411.5595	Linking GloVe with word2vec	The Global Vectors for word representation (GloVe), introduced by Jeffrey Pennington et al. is reported to be an efficient and effective method for learning vector representations of words. State-of-the-art performance is also provided by skip-gram with negative-sampling (SGNS) implemented in the word2vec tool. In this...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	37,748
1802.04140	Making "fetch" happen: The influence of social and linguistic context on nonstandard word growth and decline	In an online community, new words come and go: today's "haha" may be replaced by tomorrow's "lol." Changes in online writing are usually studied as a social process, with innovations diffusing through a network of individuals in a speech community. But unlike other types of innovation, language change is shaped and con...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	90,153
2106.10832	Online Handbook of Argumentation for AI: Volume 2	This volume contains revised versions of the papers selected for the second volume of the Online Handbook of Argumentation for AI (OHAAI). Previously, formal theories of argument and argument interaction have been proposed and studied, and this has led to the more recent study of computational models of argument. Argum...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	242,174
2501.00838	Spatially-guided Temporal Aggregation for Robust Event-RGB Optical Flow Estimation	Current optical flow methods exploit the stable appearance of frame (or RGB) data to establish robust correspondences across time. Event cameras, on the other hand, provide high-temporal-resolution motion cues and excel in challenging scenarios. These complementary characteristics underscore the potential of integratin...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	521,819
2103.13109	A Fine-Grained Dataset and its Efficient Semantic Segmentation for Unstructured Driving Scenarios	Research in autonomous driving for unstructured environments suffers from a lack of semantically labeled datasets compared to its urban counterpart. Urban and unstructured outdoor environments are challenging due to the varying lighting and weather conditions during a day and across seasons. In this paper, we introduce...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	226,392
2404.05107	Reconstructing Retinal Visual Images from 3T fMRI Data Enhanced by Unsupervised Learning	The reconstruction of human visual inputs from brain activity, particularly through functional Magnetic Resonance Imaging (fMRI), holds promising avenues for unraveling the mechanisms of the human visual system. Despite the significant strides made by deep learning methods in improving the quality and interpretability ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,946
2205.10053	What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders	The last years have witnessed the emergence of a promising self-supervised learning strategy, referred to as masked autoencoding. However, there is a lack of theoretical understanding of how masking matters on graph autoencoders (GAEs). In this work, we present masked graph autoencoder (MaskGAE), a self-supervised lear...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	297,535
math/9910062	Efficient sphere-covering and converse measure concentration via generalized coding theorems	Suppose A is a finite set equipped with a probability measure P and let M be a ``mass'' function on A. We give a probabilistic characterization of the most efficient way in which A^n can be almost-covered using spheres of a fixed radius. An almost-covering is a subset C_n of A^n, such that the union of the spheres cent...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,753
1904.03366	The Steep Road to Happily Ever After: An Analysis of Current Visual Storytelling Models	Visual storytelling is an intriguing and complex task that only recently entered the research arena. In this work, we survey relevant work to date, and conduct a thorough error analysis of three very recent approaches to visual storytelling. We categorize and provide examples of common types of errors, and identify key...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	126,691
2302.02266	Space-Time Conflict Spheres for Constrained Multi-Agent Motion Planning	Multi-agent motion planning (MAMP) is a critical challenge in applications such as connected autonomous vehicles and multi-robot systems. In this paper, we propose a space-time conflict resolution approach for MAMP. We formulate the problem using a novel, flexible sphere-based discretization for trajectories. Our appro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	343,929
1910.03759	An event-triggered transmission scheduling strategy for remote state estimation in the presence of an eavesdropper	We consider a remote state estimation problem in the presence of an eavesdropper over packet dropping links. A smart sensor transmits its local estimates to a legitimate remote estimator, in the course of which an eavesdropper can randomly overhear the transmission. This problem has been well studied for unstable dynam...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	148,579
2108.05340	Person Re-identification via Attention Pyramid	In this paper, we propose an attention pyramid method for person re-identification. Unlike conventional attention-based methods which only learn a global attention map, our attention pyramid exploits the attention regions in a multi-scale manner because human attention varies with different scales. Our attention pyrami...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	250,278
2004.11056	Analytic Simplification of Neural Network based Intra-Prediction Modes for Video Compression	With the increasing demand for video content at higher resolutions, it is evermore critical to find ways to limit the complexity of video encoding tasks in order to reduce costs, power consumption and environmental impact of video services. In the last few years, algorithms based on Neural Networks (NN) have been shown...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	173,804
2010.01897	PUM at SemEval-2020 Task 12: Aggregation of Transformer-based models' features for offensive language recognition	In this paper, we describe the PUM team's entry to the SemEval-2020 Task 12. Creating our solution involved leveraging two well-known pretrained models used in natural language processing: BERT and XLNet, which achieve state-of-the-art results in multiple NLP tasks. The models were fine-tuned for each subtask separatel...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	198,831
1909.01683	Deep Learning-Aided Tabu Search Detection for Large MIMO Systems	In this study, we consider the application of deep learning (DL) to tabu search (TS) detection in large multiple-input multiple-output (MIMO) systems. First, we propose a deep neural network architecture for symbol detection, termed the fast-convergence sparsely connected detection network (FS-Net), which is obtained b...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	143,973
2402.14179	Bangla AI: A Framework for Machine Translation Utilizing Large Language Models for Ethnic Media	Ethnic media, which caters to diaspora communities in host nations, serves as a vital platform for these communities to both produce content and access information. Rather than utilizing the language of the host nation, ethnic media delivers news in the language of the immigrant community. For instance, in the USA, Ban...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	431,561
2111.11208	Self-Supervised Class Incremental Learning	Existing Class Incremental Learning (CIL) methods are based on a supervised classification framework sensitive to data labels. When updating them based on the new class data, they suffer from catastrophic forgetting: the model cannot discern old class data clearly from the new. In this paper, we explore the performance...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	267,587
2108.02665	Deep Reinforcement Learning for Continuous Docking Control of Autonomous Underwater Vehicles: A Benchmarking Study	Docking control of an autonomous underwater vehicle (AUV) is a task that is integral to achieving persistent long term autonomy. This work explores the application of state-of-the-art model-free deep reinforcement learning (DRL) approaches to the task of AUV docking in the continuous domain. We provide a detailed formu...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	249,407
1707.00201	Rank-1 Constrained Multichannel Wiener Filter for Speech Recognition in Noisy Environments	Multichannel linear filters, such as the Multichannel Wiener Filter (MWF) and the Generalized Eigenvalue (GEV) beamformer are popular signal processing techniques which can improve speech recognition performance. In this paper, we present an experimental study on these linear filters in a specific speech recognition ta...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	76,313
2406.08184	MobileAgentBench: An Efficient and User-Friendly Benchmark for Mobile LLM Agents	Large language model (LLM)-based mobile agents are increasingly popular due to their capability to interact directly with mobile phone Graphic User Interfaces (GUIs) and their potential to autonomously manage daily tasks. Despite their promising prospects in both academic and industrial sectors, little research has foc...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	463,378
2407.00067	Perceptron Collaborative Filtering	While multivariate logistic regression classifiers are a great way of implementing collaborative filtering - a method of making automatic predictions about the interests of a user by collecting preferences or taste information from many other users, we can also achieve similar results using neural networks. A recommend...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	468,702
2103.00833	Fast threshold optimization for multi-label audio tagging using Surrogate gradient learning	Multi-label audio tagging consists of assigning sets of tags to audio recordings. At inference time, thresholds are applied on the confidence scores outputted by a probabilistic classifier, in order to decide which classes are detected active. In this work, we consider having at disposal a trained classifier and we see...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	222,424
2205.08207	DynPL-SVO: A Robust Stereo Visual Odometry for Dynamic Scenes	Most feature-based stereo visual odometry (SVO) approaches estimate the motion of mobile robots by matching and tracking point features along a sequence of stereo images. However, in dynamic scenes mainly comprising moving pedestrians, vehicles, etc., there are insufficient robust static point features to enable accura...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	296,854
2209.06259	Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization	The ability to accelerate the design of biological sequences can have a substantial impact on the progress of the medical field. The problem can be framed as a global optimization problem where the objective is an expensive black-box function such that we can query large batches restricted with a limitation of a low nu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	317,332
1702.08070	PubTree: A Hierarchical Search Tool for the MEDLINE Database	Keeping track of the ever-increasing body of scientific literature is an escalating challenge. We present PubTree a hierarchical search tool that efficiently searches the PubMed/MEDLINE dataset based upon a decision tree constructed using >26 million abstracts. The tool is implemented as a webpage, where users are aske...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	68,908
2301.03028	Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement	Time series forecasting has been a widely explored task of great importance in many applications. However, it is common that real-world time series data are recorded in a short time period, which results in a big gap between the deep model and the limited and noisy time series. In this work, we propose to address the t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	339,665
1308.5094	Complexity of evolutionary equilibria in static fitness landscapes	A fitness landscape is a genetic space -- with two genotypes adjacent if they differ in a single locus -- and a fitness function. Evolutionary dynamics produce a flow on this landscape from lower fitness to higher; reaching equilibrium only if a local fitness peak is found. I use computational complexity to question th...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	26,597
1801.09627	Barrier-Certified Adaptive Reinforcement Learning with Applications to Brushbot Navigation	This paper presents a safe learning framework that employs an adaptive model learning algorithm together with barrier certificates for systems with possibly nonstationary agent dynamics. To extract the dynamic structure of the model, we use a sparse optimization technique. We use the learned model in combination with c...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	89,147
2307.06036	Information Rate-Harvested Power Tradeoff in THz SWIPT Systems Employing Resonant Tunnelling Diode-based EH Circuits	In this paper, we study THz simultaneous wireless information and power transfer (SWIPT) systems. Since coherent information detection is challenging at THz frequencies and Schottky diodes may not be efficient for THz energy harvesting (EH) and information detection, we employ unipolar amplitude shift keying (ASK) modu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	378,945
2104.01140	Ideology-driven polarisation in online ratings: the review bombing of The Last of Us Part II	A review bomb is a large and quick surge in online reviews about a product, service, or business, coordinated by a group of people willing to manipulate public opinion about that entity. This study challenges the assumption that review bombing is solely a phenomenon of misinformation and connects motivations and substa...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	228,252
2312.01017	Unveiling the Power of Audio-Visual Early Fusion Transformers with Dense Interactions through Masked Modeling	Humans possess a remarkable ability to integrate auditory and visual information, enabling a deeper understanding of the surrounding environment. This early fusion of audio and visual cues, demonstrated through cognitive psychology and neuroscience research, offers promising potential for developing multimodal percepti...	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	412,269
2207.11248	Brain tumor detection using artificial convolutional neural networks	In this paper, a convolutional neural network (CNN) was used to classify NMR images of human brains with 4 different types of tumors: meningioma, glioma and pituitary gland tumors. During the training phase of this project, an accuracy of 100% was obtained, meanwhile, in the evaluation phase the precision was 96%.	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	309,571
2411.13862	Image Compression Using Novel View Synthesis Priors	Real-time visual feedback is essential for tetherless control of remotely operated vehicles, particularly during inspection and manipulation tasks. Though acoustic communication is the preferred choice for medium-range communication underwater, its limited bandwidth renders it impractical to transmit images or videos i...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	509,946
2101.10450	LAIF: AI, Deep Learning for Germany Suetterlin Letter Recognition and Generation	One of the successful early implementation of deep learning AI technology was on letter recognition. With the recent breakthrough of artificial intelligence (AI) brings more solid technology for complex problems like handwritten letter recognition and even automatic generation of them. In this research, we proposed dee...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	216,936
1912.08628	Unsupervised Change Detection in Multi-temporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network	With the development of Earth observation technology, very-high-resolution (VHR) image has become an important data source of change detection. Nowadays, deep learning methods have achieved conspicuous performance in the change detection of VHR images. Nonetheless, most of the existing change detection models based on ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,879
2306.04090	PlayBest: Professional Basketball Player Behavior Synthesis via Planning with Diffusion	Dynamically planning in complex systems has been explored to improve decision-making in various domains. Professional basketball serves as a compelling example of a dynamic spatio-temporal game, encompassing context-dependent decision-making. However, processing the diverse on-court signals and navigating the vast spac...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	371,598
2203.15402	Physics-informed deep-learning applications to experimental fluid mechanics	High-resolution reconstruction of flow-field data from low-resolution and noisy measurements is of interest due to the prevalence of such problems in experimental fluid mechanics, where the measurement data are in general sparse, incomplete and noisy. Deep-learning approaches have been shown suitable for such super-res...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	288,389
1908.08288	Dealing with uncertainty in agent-based models for short-term predictions	Agent-based models (ABM) are gaining traction as one of the most powerful modelling tools within the social sciences. They are particularly suited to simulating complex systems. Despite many methodological advances within ABM, one of the major drawbacks is their inability to incorporate real-time data to make accurate ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	142,512
2309.01030	Online Adaptive Mahalanobis Distance Estimation	Mahalanobis metrics are widely used in machine learning in conjunction with methods like $k$-nearest neighbors, $k$-means clustering, and $k$-medians clustering. Despite their importance, there has not been any prior work on applying sketching techniques to speed up algorithms for Mahalanobis metrics. In this paper, we...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	389,512
2412.18483	A region-wide, multi-year set of crop field boundary labels for Africa	African agriculture is undergoing rapid transformation. Annual maps of crop fields are key to understanding the nature of this transformation, but such maps are currently lacking and must be developed using advanced machine learning models trained on high resolution remote sensing imagery. To enable the development of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,436
2405.17612	A note on the error analysis of data-driven closure models for large eddy simulations of turbulence	In this work, we provide a mathematical formulation for error propagation in flow trajectory prediction using data-driven turbulence closure modeling. Under the assumption that the predicted state of a large eddy simulation prediction must be close to that of a subsampled direct numerical simulation, we retrieve an upp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	458,024
2302.10878	Complete Gr\"obner basis for lattice codes	In this work, two algorithms are developed related to lattice codes. In the first one, an extended complete Gr\"obner basis is computed for the label code of a lattice. This basis supports all term orderings associated with a total degree order offering information about de label code of the lattice. The second one is ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	346,989
2401.02653	A Deep Q-Learning based Smart Scheduling of EVs for Demand Response in Smart Grids	Economic and policy factors are driving the continuous increase in the adoption and usage of electrical vehicles (EVs). However, despite being a cleaner alternative to combustion engine vehicles, EVs have negative impacts on the lifespan of microgrid equipment and energy balance due to increased power demand and the ti...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	419,794
1503.00311	Reducing ADC Sampling Rate with Compressive Sensing	Many communication systems involve high bandwidth, while sparse, radio frequency (RF) signals. Working with high frequency signals requires appropriate system-level components such as high-speed analog-to-digital converters (ADC). In particular, an analog signal should be sampled at rates that meet the Nyquist requirem...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	40,693
2202.02750	Estimating the Euclidean quantum propagator with deep generative modeling of Feynman paths	Feynman path integrals provide an elegant, classically inspired representation for the quantum propagator and the quantum dynamics, through summing over a huge manifold of all possible paths. From computational and simulational perspectives, the ergodic tracking of the whole path manifold is a hard problem. Machine lea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,930
2103.11834	Generation and Simulation of Yeast Microscopy Imagery with Deep Learning	Time-lapse fluorescence microscopy (TLFM) is an important and powerful tool in synthetic biological research. Modeling TLFM experiments based on real data may enable researchers to repeat certain experiments with minor effort. This thesis is a study towards deep learning-based modeling of TLFM experiments on the image ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	225,963
2012.12901	Lattice gauge equivariant convolutional neural networks	We propose Lattice gauge equivariant Convolutional Neural Networks (L-CNNs) for generic machine learning applications on lattice gauge theoretical problems. At the heart of this network structure is a novel convolutional layer that preserves gauge equivariance while forming arbitrarily shaped Wilson loops in successive...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	213,058
1605.07571	Sequential Neural Models with Stochastic Layers	How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural generative model. The c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	56,305
2008.01253	An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario	The paper describes an ongoing effort in developing a declarative system for supporting operators in the Nuclear Power Plant (NPP) control room. The focus is on two modules: diagnosis and explanation of events that happened in NPPs. We describe an Answer Set Programming (ASP) representation of an NPP, which consists of...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	190,255
2309.15028	Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding	Inference-time search algorithms such as Monte-Carlo Tree Search (MCTS) may seem unnecessary when generating natural language text based on state-of-the-art reinforcement learning such as Proximal Policy Optimization (PPO). In this paper, we demonstrate that it is possible to get extra mileage out of PPO by integrating...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	394,823
2007.14850	Mechatronics-Driven Musical Expressivity for Robotic Percussionists	Musical expressivity is an important aspect of musical performance for humans as well as robotic musicians. We present a novel mechatronics-driven implementation of Brushless Direct Current (BLDC) motors in a robotic marimba player, named Shimon, designed to improve speed, dynamic range (loudness), and ultimately perce...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	189,506
1611.05373	DeepCas: an End-to-end Predictor of Information Cascades	Information cascades, effectively facilitated by most social network platforms, are recognized as a major factor in almost every social success and disaster in these networks. Can cascades be predicted? While many believe that they are inherently unpredictable, recent work has shown that some key properties of informat...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	64,005
1102.4135	Location Cheating: A Security Challenge to Location-based Social Network Services	Location-based mobile social network services such as foursquare and Gowalla have grown exponentially over the past several years. These location-based services utilize the geographical position to enrich user experiences in a variety of contexts, including location-based searching and location-based mobile advertising...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	9,297
2304.10837	A Comprehensive Review on Ontologies for Scenario-based Testing in the Context of Autonomous Driving	The verification and validation of autonomous driving vehicles remains a major challenge due to the high complexity of autonomous driving functions. Scenario-based testing is a promising method for validating such a complex system. Ontologies can be utilized to produce test scenarios that are both meaningful and releva...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	359,579
2411.01178	LLM4PR: Improving Post-Ranking in Search Engine with Large Language Models	Alongside the rapid development of Large Language Models (LLMs), there has been a notable increase in efforts to integrate LLM techniques in information retrieval (IR) and search engines (SE). Recently, an additional post-ranking stage is suggested in SE to enhance user satisfaction in practical applications. Neverthel...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	504,948
2109.05317	Bayesian Topic Regression for Causal Inference	Causal inference using observational text data is becoming increasingly popular in many research areas. This paper presents the Bayesian Topic Regression (BTR) model that uses both text and numerical information to model an outcome variable. It allows estimation of both discrete and continuous treatment effects. Furthe...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	254,743
1911.12216	ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context	Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics. Most deep learning-based solutions for EMR analysis concentrate on learning the clinical visit embedding and exploring the relations between visits. Although those wor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,337
2403.08464	Diffusion Models with Implicit Guidance for Medical Anomaly Detection	Diffusion models have advanced unsupervised anomaly detection by improving the transformation of pathological images into pseudo-healthy equivalents. Nonetheless, standard approaches may compromise critical information during pathology removal, leading to restorations that do not align with unaffected regions in the or...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	437,350
2310.06239	Model Tuning or Prompt Tuning? A Study of Large Language Models for Clinical Concept and Relation Extraction	Objective To develop soft prompt-based learning algorithms for large language models (LLMs), examine the shape of prompts, prompt-tuning using frozen/unfrozen LLMs, transfer learning, and few-shot learning abilities. Methods We developed a soft prompt-based LLM model and compared 4 training strategies including (1) fin...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	398,488
2106.07998	Revisiting the Calibration of Modern Neural Networks	Accurate estimation of predictive uncertainty (model calibration) is essential for the safe application of neural networks. Many instances of miscalibration in modern neural networks have been reported, suggesting a trend that newer, more accurate models produce poorly calibrated predictions. Here, we revisit this ques...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	241,147
2106.03750	Smart Village: An IoT Based Digital Transformation	Almost 46% of the world's population resides in a rural landscape. Smart villages, alongside smart cities, are in need of time for future economic growth, improved agriculture, better health, and education. The smart village is a concept that improves the traditional rural aspects with the help of digital transformatio...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	true	239,434
1808.00733	Approximate Probabilistic Neural Networks with Gated Threshold Logic	Probabilistic Neural Network (PNN) is a feed-forward artificial neural network developed for solving classification problems. This paper proposes a hardware implementation of an approximated PNN (APNN) algorithm in which the conventional exponential function of the PNN is replaced with gated threshold logic. The weight...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	true	104,447
2307.04601	InPars Toolkit: A Unified and Reproducible Synthetic Data Generation Pipeline for Neural Information Retrieval	Recent work has explored Large Language Models (LLMs) to overcome the lack of training data for Information Retrieval (IR) tasks. The generalization abilities of these models have enabled the creation of synthetic in-domain data by providing instructions and a few examples on a prompt. InPars and Promptagator have pion...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	378,459
2206.04687	Swan: A Neural Engine for Efficient DNN Training on Smartphone SoCs	The need to train DNN models on end-user devices (e.g., smartphones) is increasing with the need to improve data privacy and reduce communication overheads. Unlike datacenter servers with powerful CPUs and GPUs, modern smartphones consist of a diverse collection of specialized cores following a system-on-a-chip (SoC) a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	301,729
2305.13002	Rethinking Semi-supervised Learning with Language Models	Semi-supervised learning (SSL) is a popular setting aiming to effectively utilize unlabelled data to improve model performance in downstream natural language processing (NLP) tasks. Currently, there are two popular approaches to make use of unlabelled data: Self-training (ST) and Task-adaptive pre-training (TAPT). ST u...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	366,296
2201.04361	Evolutionary Optimization for Proactive and Dynamic Computing Resource Allocation in Open Radio Access Network	Intelligent techniques are urged to achieve automatic allocation of the computing resource in Open Radio Access Network (O-RAN), to save computing resource, increase utilization rate of them and decrease the delay. However, the existing problem formulation to solve this resource allocation problem is unsuitable as it d...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	275,083
2409.12723	Optimal Cosserat-based deformation control for robotic manipulation of linear objects	The robotic shape control of deformable linear objects has garnered increasing interest within the robotics community. Despite recent progress, the majority of shape control approaches can be classified into two main groups: open-loop control, which relies on physically realistic models to represent the object, and clo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	489,697
2204.04898	PM4Py-GPU: a High-Performance General-Purpose Library for Process Mining	Open-source process mining provides many algorithms for the analysis of event data which could be used to analyze mainstream processes (e.g., O2C, P2P, CRM). However, compared to commercial tools, they lack the performance and struggle to analyze large amounts of data. This paper presents PM4Py-GPU, a Python process mi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	290,832
2007.02460	An Automated and Robust Image Watermarking Scheme Based on Deep Neural Networks	Digital image watermarking is the process of embedding and extracting a watermark covertly on a cover-image. To dynamically adapt image watermarking algorithms, deep learning-based image watermarking schemes have attracted increased attention during recent years. However, existing deep learning-based watermarking metho...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	185,751

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