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
2004.01185	Introducing Anisotropic Minkowski Functionals and Quantitative Anisotropy Measures for Local Structure Analysis in Biomedical Imaging	The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level stru...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	170,845
2007.00843	Low-light Environment Neural Surveillance	We design and implement an end-to-end system for real-time crime detection in low-light environments. Unlike Closed-Circuit Television, which performs reactively, the Low-Light Environment Neural Surveillance provides real time crime alerts. The system uses a low-light video feed processed in real-time by an optical-fl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	185,237
1808.09468	Learning To Split and Rephrase From Wikipedia Edit History	Split and rephrase is the task of breaking down a sentence into shorter ones that together convey the same meaning. We extract a rich new dataset for this task by mining Wikipedia's edit history: WikiSplit contains one million naturally occurring sentence rewrites, providing sixty times more distinct split examples and...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	106,194
2411.14927	LiDAR-based End-to-end Temporal Perception for Vehicle-Infrastructure Cooperation	Temporal perception, the ability to detect and track objects over time, is critical in autonomous driving for maintaining a comprehensive understanding of dynamic environments. However, this task is hindered by significant challenges, including incomplete perception caused by occluded objects and observational blind sp...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	510,375
2301.04740	The Berkelmans-Pries Feature Importance Method: A Generic Measure of Informativeness of Features	Over the past few years, the use of machine learning models has emerged as a generic and powerful means for prediction purposes. At the same time, there is a growing demand for interpretability of prediction models. To determine which features of a dataset are important to predict a target variable $Y$, a Feature Impor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	340,150
2106.14167	PeCoQ: A Dataset for Persian Complex Question Answering over Knowledge Graph	Question answering systems may find the answers to users' questions from either unstructured texts or structured data such as knowledge graphs. Answering questions using supervised learning approaches including deep learning models need large training datasets. In recent years, some datasets have been presented for the...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	243,318
1304.1346	Domain Specific Language for Geometric Relations between Rigid Bodies targeted to robotic applications	This paper presents a DSL for geometric relations between rigid bodies such as relative position, orientation, pose, linear velocity, angular velocity, and twist. The DSL is the formal model of the recently proposed semantics for the standardization of geometric relations between rigid bodies, referred to as `geometric...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	23,511
2310.09792	SCME: A Self-Contrastive Method for Data-free and Query-Limited Model Extraction Attack	Previous studies have revealed that artificial intelligence (AI) systems are vulnerable to adversarial attacks. Among them, model extraction attacks fool the target model by generating adversarial examples on a substitute model. The core of such an attack is training a substitute model as similar to the target model as...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	399,951
2404.01744	Octopus v2: On-device language model for super agent	Language models have shown effectiveness in a variety of software applications, particularly in tasks related to automatic workflow. These models possess the crucial ability to call functions, which is essential in creating AI agents. Despite the high performance of large-scale language models in cloud environments, th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,563
1608.02927	Temporal Attention Model for Neural Machine Translation	Attention-based Neural Machine Translation (NMT) models suffer from attention deficiency issues as has been observed in recent research. We propose a novel mechanism to address some of these limitations and improve the NMT attention. Specifically, our approach memorizes the alignments temporally (within each sentence) ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	59,618
2404.05311	BruSLeAttack: A Query-Efficient Score-Based Black-Box Sparse Adversarial Attack	We study the unique, less-well understood problem of generating sparse adversarial samples simply by observing the score-based replies to model queries. Sparse attacks aim to discover a minimum number-the l0 bounded-perturbations to model inputs to craft adversarial examples and misguide model decisions. But, in contra...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	445,037
2208.09743	Where Shall I Touch? Vision-Guided Tactile Poking for Transparent Object Grasping	Picking up transparent objects is still a challenging task for robots. The visual properties of transparent objects such as reflection and refraction make the current grasping methods that rely on camera sensing fail to detect and localise them. However, humans can handle the transparent object well by first observing ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	313,818
1702.01285	On a Relationship between the Correct Probability of Estimation from Correlated Data and Mutual Information	Let $X$, $Y$ be two correlated discrete random variables. We consider an estimation of $X$ from encoded data $\varphi(Y)$ of $Y$ by some encoder function $\varphi(Y)$. We derive an inequality describing a relation of the correct probability of estimation and the mutual information between $X$ and $\varphi(Y)$. This ine...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,784
1806.07621	Smallest Ellipsoid Containing $p$-Sum of Ellipsoids with Application to Reachability Analysis	We study the problem of ellipsoidal bounding of convex set-valued data, where the convex set is obtained by the $p$-sum of finitely many ellipsoids, for any real $p\geq 1$. The notion of $p$-sum appears in the Brunn-Minkowski-Firey theory in convex analysis, and generalizes several well-known set-valued operations such...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	100,976
2008.08046	TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition	Tactile perception is crucial for a variety of robot tasks including grasping and in-hand manipulation. New advances in flexible, event-driven, electronic skins may soon endow robots with touch perception capabilities similar to humans. These electronic skins respond asynchronously to changes (e.g., in pressure, temper...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	192,300
2502.13110	MLPs at the EOC: Dynamics of Feature Learning	Since infinitely wide neural networks in the kernel regime are random feature models, the success of contemporary deep learning lies in the rich regime, where a satisfying theory should explain not only the convergence of gradient descent but the learning of features along the way. Such a theory should also cover pheno...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	535,205
1709.09402	Low-Complexity Iterative Detection for Orthogonal Time Frequency Space Modulation	We elaborate on the recently proposed orthogonal time frequency space (OTFS) modulation technique, which provides significant advantages over orthogonal frequency division multiplexing (OFDM) in Doppler channels. We first derive the input--output relation describing OTFS modulation and demodulation (mod/demod) for dela...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	81,623
2301.01459	Modeling the Central Supermassive Black Holes Mass of Quasars via LSTM Approach	One of the fundamental questions about quasars is related to their central supermassive black holes. The reason for the existence of these black holes with such a huge mass is still unclear and various models have been proposed to explain them. However, there is still no comprehensive explanation that is accepted by th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	339,244
2405.17718	AdapNet: Adaptive Noise-Based Network for Low-Quality Image Retrieval	Image retrieval aims to identify visually similar images within a database using a given query image. Traditional methods typically employ both global and local features extracted from images for matching, and may also apply re-ranking techniques to enhance accuracy. However, these methods often fail to account for the...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	458,077
2408.08707	Beam Prediction based on Large Language Models	In this letter, we use large language models (LLMs) to develop a high-performing and robust beam prediction method. We formulate the millimeter wave (mmWave) beam prediction problem as a time series forecasting task, where the historical observations are aggregated through cross-variable attention and then transformed ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	481,120
2501.00367	Who Gets Recommended? Investigating Gender, Race, and Country Disparities in Paper Recommendations from Large Language Models	This paper investigates the performance of several representative large models in the tasks of literature recommendation and explores potential biases in research exposure. The results indicate that not only LLMs' overall recommendation accuracy remains limited but also the models tend to recommend literature with grea...	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	true	521,642
2206.10338	Comparative Analysis of Dynamic Data Race Detection Techniques	The consequences of data races can be potentially very problematic [1], and it is important to determine what tools and methods are best at detecting them. The following conditions must be met for a data race to occur: two or more threads in a single process access the same memory location concurrently, at least one of...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	303,879
2006.10092	Housing Market Prediction Problem using Different Machine Learning Algorithms: A Case Study	Developing an accurate prediction model for housing prices is always needed for socio-economic development and well-being of citizens. In this paper, a diverse set of machine learning algorithms such as XGBoost, CatBoost, Random Forest, Lasso, Voting Regressor, and others, are being employed to predict the housing pric...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,756
1105.1823	Design of Low-Thrust Gravity Assist Trajectories to Europa	This paper presents the design of a mission to Europa using solar electric propulsion as main source of thrust. A direct transcription method based on Finite Elements in Time was used for the design and optimisation of the entire low-thrust gravity assist transfer from the Earth to Europa. Prior to that, a global searc...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	10,305
2203.08072	Neural Solvers for Fast and Accurate Numerical Optimal Control	Synthesizing optimal controllers for dynamical systems often involves solving optimization problems with hard real-time constraints. These constraints determine the class of numerical methods that can be applied: computationally expensive but accurate numerical routines are replaced by fast and inaccurate methods, trad...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	285,667
2306.13531	WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributes	The examination of blood samples at a microscopic level plays a fundamental role in clinical diagnostics, influencing a wide range of medical conditions. For instance, an in-depth study of White Blood Cells (WBCs), a crucial component of our blood, is essential for diagnosing blood-related diseases such as leukemia and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	375,310
2306.00914	Conditioning Diffusion Models via Attributes and Semantic Masks for Face Generation	Deep generative models have shown impressive results in generating realistic images of faces. GANs managed to generate high-quality, high-fidelity images when conditioned on semantic masks, but they still lack the ability to diversify their output. Diffusion models partially solve this problem and are able to generate ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	370,206
2202.05100	Adaptively Exploiting d-Separators with Causal Bandits	Multi-armed bandit problems provide a framework to identify the optimal intervention over a sequence of repeated experiments. Without additional assumptions, minimax optimal performance (measured by cumulative regret) is well-understood. With access to additional observed variables that d-separate the intervention from...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,763
2312.05632	Subject-Based Domain Adaptation for Facial Expression Recognition	Adapting a deep learning model to a specific target individual is a challenging facial expression recognition (FER) task that may be achieved using unsupervised domain adaptation (UDA) methods. Although several UDA methods have been proposed to adapt deep FER models across source and target data sets, multiple subject-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	414,167
2211.04188	DepthFormer: Multimodal Positional Encodings and Cross-Input Attention for Transformer-Based Segmentation Networks	Most approaches for semantic segmentation use only information from color cameras to parse the scenes, yet recent advancements show that using depth data allows to further improve performances. In this work, we focus on transformer-based deep learning architectures, that have achieved state-of-the-art performances on t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	329,168
1703.05443	Detecting the Hate Code on Social Media	Social media has become an indispensable part of the everyday lives of millions of people around the world. It provides a platform for expressing opinions and beliefs, communicated to a massive audience. However, this ease with which people can express themselves has also allowed for the large scale spread of propagand...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	70,079
2304.10900	A Common Misassumption in Online Experiments with Machine Learning Models	Online experiments such as Randomised Controlled Trials (RCTs) or A/B-tests are the bread and butter of modern platforms on the web. They are conducted continuously to allow platforms to estimate the causal effect of replacing system variant "A" with variant "B", on some metric of interest. These variants can differ in...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	359,601
1611.03942	Anomaly Detection in the Bitcoin System - A Network Perspective	The problem of anomaly detection has been studied for a long time, and many Network Analysis techniques have been proposed as solutions. Although some results appear to be quite promising, no method is clearly to be superior to the rest. In this paper, we particularly consider anomaly detection in the Bitcoin transacti...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	63,762
1908.08597	Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective	Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and Deaf culture. Despite the need for deep interdisciplinary knowledge, ...	true	false	false	false	false	false	false	false	true	false	false	true	false	true	false	false	false	true	142,595
1909.11212	Augmenting the Pathology Lab: An Intelligent Whole Slide Image Classification System for the Real World	Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin \& eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning sy...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	146,738
2501.01422	Multi-Modal Video Feature Extraction for Popularity Prediction	This work aims to predict the popularity of short videos using the videos themselves and their related features. Popularity is measured by four key engagement metrics: view count, like count, comment count, and share count. This study employs video classification models with different architectures and training methods...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	522,056
2205.13833	A Decentralised Control Strategy for Secondary Voltage Regulation	This paper proposes a decentralised secondary voltage control strategy that has several benefits over the existing centralised strategies. For that, a new structure for the control is proposed in terms of an inner and outer loops for each generator. The individual generators of a particular zone participate in the seco...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	299,108
2205.10907	Improved Modeling of Persistence Diagram	High-dimensional reduction methods are powerful tools for describing the main patterns in big data. One of these methods is the topological data analysis (TDA), which modeling the shape of the data in terms of topological properties. This method specifically translates the original data into two-dimensional system, whi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	297,920
1911.03053	Electric Analog Circuit Design with Hypernetworks and a Differential Simulator	The manual design of analog circuits is a tedious task of parameter tuning that requires hours of work by human experts. In this work, we make a significant step towards a fully automatic design method that is based on deep learning. The method selects the components and their configuration, as well as their numerical ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	152,535
2103.14877	Few-shot Semantic Image Synthesis Using StyleGAN Prior	This paper tackles a challenging problem of generating photorealistic images from semantic layouts in few-shot scenarios where annotated training pairs are hardly available but pixel-wise annotation is quite costly. We present a training strategy that performs pseudo labeling of semantic masks using the StyleGAN prior....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	227,003
2206.14507	Variational Quantum Approximate Support Vector Machine with Inference Transfer	A kernel-based quantum classifier is the most practical and influential quantum machine learning technique for the hyper-linear classification of complex data. We propose a Variational Quantum Approximate Support Vector Machine (VQASVM) algorithm that demonstrates empirical sub-quadratic run-time complexity with quantu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,309
2307.02329	Data-driven Predictive Latency for 5G: A Theoretical and Experimental Analysis Using Network Measurements	The advent of novel 5G services and applications with binding latency requirements and guaranteed Quality of Service (QoS) hastened the need to incorporate autonomous and proactive decision-making in network management procedures. The objective of our study is to provide a thorough analysis of predictive latency within...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	377,659
1203.2021	A new supervised non-linear mapping	Supervised mapping methods project multi-dimensional labeled data onto a 2-dimensional space attempting to preserve both data similarities and topology of classes. Supervised mappings are expected to help the user to understand the underlying original class structure and to classify new data visually. Several methods h...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	14,803
2405.12502	EntropyStop: Unsupervised Deep Outlier Detection with Loss Entropy	Unsupervised Outlier Detection (UOD) is an important data mining task. With the advance of deep learning, deep Outlier Detection (OD) has received broad interest. Most deep UOD models are trained exclusively on clean datasets to learn the distribution of the normal data, which requires huge manual efforts to clean the ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	455,551
1503.03011	Technical Analysis on Financial Forecasting	Financial forecasting is an estimation of future financial outcomes for a company, industry, country using historical internal accounting and sales data. We may predict the future outcome of BSE_SENSEX practically by some soft computing techniques and can also optimized using PSO (Particle Swarm Optimization), EA (Evol...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	41,003
1804.04212	Word2Vec applied to Recommendation: Hyperparameters Matter	Skip-gram with negative sampling, a popular variant of Word2vec originally designed and tuned to create word embeddings for Natural Language Processing, has been used to create item embeddings with successful applications in recommendation. While these fields do not share the same type of data, neither evaluate on the ...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	94,783
2410.01079	Concept Space Alignment in Multilingual LLMs	Multilingual large language models (LLMs) seem to generalize somewhat across languages. We hypothesize this is a result of implicit vector space alignment. Evaluating such alignment, we see that larger models exhibit very high-quality linear alignments between corresponding concepts in different languages. Our experime...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	493,596
1909.00952	Graph-based Transforms for Video Coding	In many state-of-the-art compression systems, signal transformation is an integral part of the encoding and decoding process, where transforms provide compact representations for the signals of interest. This paper introduces a class of transforms called graph-based transforms (GBTs) for video compression, and proposes...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	143,765
2107.05530	ROBIN: A Robust Optical Binary Neural Network Accelerator	Domain specific neural network accelerators have garnered attention because of their improved energy efficiency and inference performance compared to CPUs and GPUs. Such accelerators are thus well suited for resource-constrained embedded systems. However, mapping sophisticated neural network models on these accelerator...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	245,804
1810.03284	Noise-synchronizability of opinion dynamics	With the analysis of noise-induced synchronization of opinion dynamics with bounded confidence (BC), a natural and fundamental question is what opinion structures can be synchronized by noise. In the traditional Hegselmann-Krause (HK) model, each agent examines the opinion values of all the other ones and then choose n...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	false	false	109,778
2308.13872	Vision-Based Human Pose Estimation via Deep Learning: A Survey	Human pose estimation (HPE) has attracted a significant amount of attention from the computer vision community in the past decades. Moreover, HPE has been applied to various domains, such as human-computer interaction, sports analysis, and human tracking via images and videos. Recently, deep learning-based approaches h...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,090
2210.10249	Discovering Limitations of Image Quality Assessments with Noised Deep Learning Image Sets	Image quality is important, and can affect overall performance in image processing and computer vision as well as for numerous other reasons. Image quality assessment (IQA) is consequently a vital task in different applications from aerial photography interpretation to object detection to medical image analysis. In pre...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	324,841
2103.09560	Big Plastic Masses Detection using Sentinel 2 Images	This communication describes a preliminary research on detection of big masses of plastic (marine litter) on the oceans and seas using EO (Earth Observation) satellite systems. Free images from the Sentinel 2 (Copernicus Project) platform are used. To develop a plastic recognizer, we start with an image where we can fi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	225,198
1405.1486	Events and Controversies: Influences of a Shocking News Event on Information Seeking	It has been suggested that online search and retrieval contributes to the intellectual isolation of users within their preexisting ideologies, where people's prior views are strengthened and alternative viewpoints are infrequently encountered. This so-called "filter bubble" phenomenon has been called out as especially ...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	32,884
2307.05384	Stochastic Nested Compositional Bi-level Optimization for Robust Feature Learning	We develop and analyze stochastic approximation algorithms for solving nested compositional bi-level optimization problems. These problems involve a nested composition of $T$ potentially non-convex smooth functions in the upper-level, and a smooth and strongly convex function in the lower-level. Our proposed algorithm ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	378,721
2302.06403	Sources of Richness and Ineffability for Phenomenally Conscious States	Conscious states (states that there is something it is like to be in) seem both rich or full of detail, and ineffable or hard to fully describe or recall. The problem of ineffability, in particular, is a longstanding issue in philosophy that partly motivates the explanatory gap: the belief that consciousness cannot be ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	345,391
2112.04716	DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization	Despite overparameterization, deep networks trained via supervised learning are easy to optimize and exhibit excellent generalization. One hypothesis to explain this is that overparameterized deep networks enjoy the benefits of implicit regularization induced by stochastic gradient descent, which favors parsimonious so...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	270,620
1002.2171	Reverse Engineering Financial Markets with Majority and Minority Games using Genetic Algorithms	Using virtual stock markets with artificial interacting software investors, aka agent-based models (ABMs), we present a method to reverse engineer real-world financial time series. We model financial markets as made of a large number of interacting boundedly rational agents. By optimizing the similarity between the act...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	5,670
1304.1134	Rules, Belief Functions and Default Logic	This paper describes a natural framework for rules, based on belief functions, which includes a repre- sentation of numerical rules, default rules and rules allowing and rules not allowing contraposition. In particular it justifies the use of the Dempster-Shafer Theory for representing a particular class of rules, Beli...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,487
2401.17511	Linguistically Communicating Uncertainty in Patient-Facing Risk Prediction Models	This paper addresses the unique challenges associated with uncertainty quantification in AI models when applied to patient-facing contexts within healthcare. Unlike traditional eXplainable Artificial Intelligence (XAI) methods tailored for model developers or domain experts, additional considerations of communicating i...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	425,221
2409.02152	Fair Railway Network Design	When designing a public transportation network in a country, one may want to minimise the sum of travel duration of all inhabitants. This corresponds to a purely utilitarian view and does not involve any fairness consideration, as the resulting network will typically benefit the capital city and/or large central cities...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	485,606
1903.03862	Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them	Word embeddings are widely used in NLP for a vast range of tasks. It was shown that word embeddings derived from text corpora reflect gender biases in society. This phenomenon is pervasive and consistent across different word embedding models, causing serious concern. Several recent works tackle this problem, and propo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	123,840
1312.6134	An Algebra of Causal Chains	In this work we propose a multi-valued extension of logic programs under the stable models semantics where each true atom in a model is associated with a set of justifications, in a similar spirit than a set of proof trees. The main contribution of this paper is that we capture justifications into an algebra of truth v...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	29,321
2005.07107	Natural Way to Overcome the Catastrophic Forgetting in Neural Networks	Not so long ago, a method was discovered that successfully overcomes the catastrophic forgetting in neural networks. Although we know about the cases of using this method to preserve skills when adapting pre-trained networks to particular tasks, it has not obtained widespread distribution yet. In this paper, we would l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,194
2309.03921	C-CLIP: Contrastive Image-Text Encoders to Close the Descriptive-Commentative Gap	The interplay between the image and comment on a social media post is one of high importance for understanding its overall message. Recent strides in multimodal embedding models, namely CLIP, have provided an avenue forward in relating image and text. However the current training regime for CLIP models is insufficient ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,562
2108.13098	Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification	The goal of few-shot fine-grained image classification is to recognize rarely seen fine-grained objects in the query set, given only a few samples of this class in the support set. Previous works focus on learning discriminative image features from a limited number of training samples for distinguishing various fine-gr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,710
1907.04407	Sentiment Analysis Challenges in Persian Language	The rapid growth in data on the internet requires a data mining process to reach a decision to support insight. The Persian language has strong potential for deep research in any aspect of natural language processing, especially sentimental analysis approach. Thousands of websites and blogs updates and modifies by Pers...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	138,099
2003.11243	Volumization as a Natural Generalization of Weight Decay	We propose a novel regularization method, called \textit{volumization}, for neural networks. Inspired by physics, we define a physical volume for the weight parameters in neural networks, and we show that this method is an effective way of regularizing neural networks. Intuitively, this method interpolates between an $...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	169,558
1807.01480	A Stabilized Cut Streamline Diffusion Finite Element Method for Convection-Diffusion Problems on Surfaces	We develop a stabilized cut finite element method for the stationary convection diffusion problem on a surface embedded in ${\mathbb{R}}^d$. The cut finite element method is based on using an embedding of the surface into a three dimensional mesh consisting of tetrahedra and then using the restriction of the standard p...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	102,073
1310.7950	Technical Report: Distribution Temporal Logic: Combining Correctness with Quality of Estimation	We present a new temporal logic called Distribution Temporal Logic (DTL) defined over predicates of belief states and hidden states of partially observable systems. DTL can express properties involving uncertainty and likelihood that cannot be described by existing logics. A co-safe formulation of DTL is defined and al...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	true	28,068
2104.06160	Probabilistic Accumulate-then-Transmit in Wireless-Powered Covert Communications	In this paper, we investigate the optimal design of a wireless-powered covert communication (WP-CC) system, in which a probabilistic accumulate-then-transmit (ATT) protocol is proposed to maximize the communication covertness subject to a quality-of-service (QoS) requirement on communication. Specifically, in the consi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	229,980
1610.03906	Single Controller Stochastic Games for Optimized Moving Target Defense	Moving target defense (MTD) techniques that enable a system to randomize its configuration to thwart prospective attacks are an effective security solution for tomorrow's wireless networks. However, there is a lack of analytical techniques that enable one to quantify the benefits and tradeoffs of MTDs. In this paper, a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	62,312
2310.06913	A Comparative Study of Transformer-based Neural Text Representation Techniques on Bug Triaging	Often, the first step in managing bug reports is related to triaging a bug to the appropriate developer who is best suited to understand, localize, and fix the target bug. Additionally, assigning a given bug to a particular part of a software project can help to expedite the fixing process. However, despite the importa...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	true	398,758
2501.04734	Generative Style Transfer for MRI Image Segmentation: A Case of Glioma Segmentation in Sub-Saharan Africa	In Sub-Saharan Africa (SSA), the utilization of lower-quality Magnetic Resonance Imaging (MRI) technology raises questions about the applicability of machine learning methods for clinical tasks. This study aims to provide a robust deep learning-based brain tumor segmentation (BraTS) method tailored for the SSA populati...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	523,325
2105.02263	ADAM: A Sandbox for Implementing Language Learning	We present ADAM, a software system for designing and running child language learning experiments in Python. The system uses a virtual world to simulate a grounded language acquisition process in which the language learner utilizes cognitively plausible learning algorithms to form perceptual and linguistic representatio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	233,763
1912.05790	Zooming into Face Forensics: A Pixel-level Analysis	The stunning progress in face manipulation methods has made it possible to synthesize realistic fake face images, which poses potential threats to our society. It is urgent to have face forensics techniques to distinguish those tampered images. A large scale dataset "FaceForensics++" has provided enormous training data...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,194
2403.16224	Inverse Rendering of Glossy Objects via the Neural Plenoptic Function and Radiance Fields	Inverse rendering aims at recovering both geometry and materials of objects. It provides a more compatible reconstruction for conventional rendering engines, compared with the neural radiance fields (NeRFs). On the other hand, existing NeRF-based inverse rendering methods cannot handle glossy objects with local light i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,936
2402.11534	PreAct: Prediction Enhances Agent's Planning Ability	Addressing the disparity between forecasts and actual results can enable individuals to expand their thought processes and stimulate self-reflection, thus promoting accurate planning. In this research, we present PreAct, an agent framework that integrates prediction, reasoning, and action. By utilizing ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	430,445
2307.14938	Efficient Interaction-Aware Interval Analysis of Neural Network Feedback Loops	In this paper, we propose a computationally efficient framework for interval reachability of systems with neural network controllers. Our approach leverages inclusion functions for the open-loop system and the neural network controller to embed the closed-loop system into a larger-dimensional embedding system, where a ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	382,102
2311.13947	High-Ratio Compression for Machine-Generated Data	Machine-generated data is rapidly growing and poses challenges for data-intensive systems, especially as the growth of data outpaces the growth of storage space. To cope with the storage issue, compression plays a critical role in storage engines, particularly for data-intensive applications, where high compression rat...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	409,934
1801.02194	Private Computation of Systematically Encoded Data with Colluding Servers	Private Computation (PC), recently introduced by Sun and Jafar, is a generalization of Private Information Retrieval (PIR) in which a user wishes to privately compute an arbitrary function of data stored across several servers. We construct a PC scheme which accounts for server collusion, coded data, and non-linear fun...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,882
2408.10276	FEDKIM: Adaptive Federated Knowledge Injection into Medical Foundation Models	Foundation models have demonstrated remarkable capabilities in handling diverse modalities and tasks, outperforming conventional artificial intelligence (AI) approaches that are highly task-specific and modality-reliant. In the medical domain, however, the development of comprehensive foundation models is constrained b...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	481,795
1908.04655	Bayesian posterior repartitioning for nested sampling	Priors in Bayesian analyses often encode informative domain knowledge that can be useful in making the inference process more efficient. Occasionally, however, priors may be unrepresentative of the parameter values for a given dataset, which can result in inefficient parameter space exploration, or even incorrect infer...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	141,536
2008.01593	Learning Transition Models with Time-delayed Causal Relations	This paper introduces an algorithm for discovering implicit and delayed causal relations between events observed by a robot at arbitrary times, with the objective of improving data-efficiency and interpretability of model-based reinforcement learning (RL) techniques. The proposed algorithm initially predicts observatio...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	190,385
1804.06112	Human Motion Capture Using a Drone	Current motion capture (MoCap) systems generally require markers and multiple calibrated cameras, which can be used only in constrained environments. In this work we introduce a drone-based system for 3D human MoCap. The system only needs an autonomously flying drone with an on-board RGB camera and is usable in various...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	95,229
2403.00642	Rethinking The Uniformity Metric in Self-Supervised Learning	Uniformity plays an important role in evaluating learned representations, providing insights into self-supervised learning. In our quest for effective uniformity metrics, we pinpoint four principled properties that such metrics should possess. Namely, an effective uniformity metric should remain invariant to instance p...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	434,052
1212.5882	The Kernel-SME Filter for Multiple Target Tracking	We present a novel method called Kernel-SME filter for tracking multiple targets when the association of the measurements to the targets is unknown. The method is a further development of the Symmetric Measurement Equation (SME) filter, which removes the data association uncertainty of the original measurement equation...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	20,601
1709.04057	Parallelizing Linear Recurrent Neural Nets Over Sequence Length	Recurrent neural networks (RNNs) are widely used to model sequential data but their non-linear dependencies between sequence elements prevent parallelizing training over sequence length. We show the training of RNNs with only linear sequential dependencies can be parallelized over the sequence length using the parallel...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	80,590
2106.08882	Robust Training in High Dimensions via Block Coordinate Geometric Median Descent	Geometric median (\textsc{Gm}) is a classical method in statistics for achieving a robust estimation of the uncorrupted data; under gross corruption, it achieves the optimal breakdown point of 0.5. However, its computational complexity makes it infeasible for robustifying stochastic gradient descent (SGD) for high-dime...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	241,458
2007.02907	Including Image-based Perception in Disturbance Observer for Warehouse Drones	Grasping and releasing objects would cause oscillations to delivery drones in the warehouse. To reduce such undesired oscillations, this paper treats the to-be-delivered object as an unknown external disturbance and presents an image-based disturbance observer (DOB) to estimate and reject such disturbance. Different fr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	185,896
2402.02583	DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image Editing	Large-scale Text-to-Image (T2I) diffusion models have revolutionized image generation over the last few years. Although owning diverse and high-quality generation capabilities, translating these abilities to fine-grained image editing remains challenging. In this paper, we propose DiffEditor to rectify two weaknesses i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	426,631
2103.01746	Comparison of Methods Generalizing Max- and Average-Pooling	Max- and average-pooling are the most popular pooling methods for downsampling in convolutional neural networks. In this paper, we compare different pooling methods that generalize both max- and average-pooling. Furthermore, we propose another method based on a smooth approximation of the maximum function and put it in...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	222,732
2310.11014	Hyperspectral In-Memory Computing with Optical Frequency Combs and Programmable Optical Memories	The rapid advancements in machine learning across numerous industries have amplified the demand for extensive matrix-vector multiplication operations, thereby challenging the capacities of traditional von Neumann computing architectures. To address this, researchers are currently exploring alternatives such as in-memor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	400,481
2303.01979	ACL-SPC: Adaptive Closed-Loop system for Self-Supervised Point Cloud Completion	Point cloud completion addresses filling in the missing parts of a partial point cloud obtained from depth sensors and generating a complete point cloud. Although there has been steep progress in the supervised methods on the synthetic point cloud completion task, it is hardly applicable in real-world scenarios due to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	349,181
1903.09516	Was ist eine Professur fuer Kuenstliche Intelligenz?	The Federal Government of Germany aims to boost the research in the field of Artificial Intelligence (AI). For instance, 100 new professorships are said to be established. However, the white paper of the government does not answer what an AI professorship is at all. In order to give colleagues, politicians, and citizen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	125,075
1808.06250	Dynamic Temporal Alignment of Speech to Lips	Many speech segments in movies are re-recorded in a studio during postproduction, to compensate for poor sound quality as recorded on location. Manual alignment of the newly-recorded speech with the original lip movements is a tedious task. We present an audio-to-video alignment method for automating speech to lips ali...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	105,497
2011.04975	Evolving Nano Particle Cancer Treatments with Multiple Particle Types	Evolutionary algorithms have long been used for optimization problems where the appropriate size of solutions is unclear a priori. The applicability of this methodology is here investigated on the problem of designing a nano-particle (NP) based drug delivery system targeting cancer tumours. Utilizing a treatment compri...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	205,757
2402.14123	DeiSAM: Segment Anything with Deictic Prompting	Large-scale, pre-trained neural networks have demonstrated strong capabilities in various tasks, including zero-shot image segmentation. To identify concrete objects in complex scenes, humans instinctively rely on deictic descriptions in natural language, i.e., referring to something depending on the context such as "T...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	431,538
2309.02061	Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation	Click-Through Rate (CTR) prediction is a fundamental technique in recommendation and advertising systems. Recent studies have shown that implementing multi-scenario recommendations contributes to strengthening information sharing and improving overall performance. However, existing multi-scenario models only consider c...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	389,916
2103.04067	Visual Explanation using Attention Mechanism in Actor-Critic-based Deep Reinforcement Learning	Deep reinforcement learning (DRL) has great potential for acquiring the optimal action in complex environments such as games and robot control. However, it is difficult to analyze the decision-making of the agent, i.e., the reasons it selects the action acquired by learning. In this work, we propose Mask-Attention A3C ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	223,516

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