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
2009.09583	Modeling Score Distributions and Continuous Covariates: A Bayesian Approach	Computer Vision practitioners must thoroughly understand their model's performance, but conditional evaluation is complex and error-prone. In biometric verification, model performance over continuous covariates---real-number attributes of images that affect performance---is particularly challenging to study. We develop...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	196,627
2107.02327	Connecting Spatially Coupled LDPC Code Chains for Bit-Interleaved Coded Modulation	This paper investigates the design of spatially coupled low-density parity-check (SC-LDPC) codes constructed from connected-chain ensembles for bit-interleaved coded modulation (BICM) schemes. For short coupling lengths, connecting multiple SC-LDPC chains can improve decoding performance over single-chains and impose s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	244,768
2106.13021	Improved Regret Bounds for Tracking Experts with Memory	We address the problem of sequential prediction with expert advice in a non-stationary environment with long-term memory guarantees in the sense of Bousquet and Warmuth [4]. We give a linear-time algorithm that improves on the best known regret bounds [26]. This algorithm incorporates a relative entropy projection step...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	242,929
2410.16302	Computational design of target-specific linear peptide binders with TransformerBeta	The computational prediction and design of peptide binders targeting specific linear epitopes is crucial in biological and biomedical research, yet it remains challenging due to their highly dynamic nature and the scarcity of experimentally solved binding data. To address this problem, we built an unprecedentedly large...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	500,973
2103.04689	Reverse Differentiation via Predictive Coding	Deep learning has redefined the field of artificial intelligence (AI) thanks to the rise of artificial neural networks, which are architectures inspired by their neurological counterpart in the brain. Through the years, this dualism between AI and neuroscience has brought immense benefits to both fields, allowing neura...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	223,727
cs/0411025	Bionic Humans Using EAP as Artificial Muscles Reality and Challenges	For many years, the idea of a human with bionic muscles immediately conjures up science fiction images of a TV series superhuman character that was implanted with bionic muscles and portrayed with strength and speed far superior to any normal human. As fantastic as this idea may seem, recent developments in electroacti...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	538,398
2502.07346	BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models	Previous multilingual benchmarks focus primarily on simple understanding tasks, but for large language models(LLMs), we emphasize proficiency in instruction following, reasoning, long context understanding, code generation, and so on. However, measuring these advanced capabilities across languages is underexplored. To ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	532,557
2411.19951	T2Vid: Translating Long Text into Multi-Image is the Catalyst for Video-LLMs	The success of Multimodal Large Language Models (MLLMs) in the image domain has garnered wide attention from the research community. Drawing on previous successful experiences, researchers have recently explored extending the success to the video understanding realms. Apart from training from scratch, an efficient way ...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	512,441
2002.05708	Simple Interactive Image Segmentation using Label Propagation through kNN graphs	Many interactive image segmentation techniques are based on semi-supervised learning. The user may label some pixels from each object and the SSL algorithm will propagate the labels from the labeled to the unlabeled pixels, finding object boundaries. This paper proposes a new SSL graph-based interactive image segmentat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	163,985
2307.16560	Line Search for Convex Minimization	Golden-section search and bisection search are the two main principled algorithms for 1d minimization of quasiconvex (unimodal) functions. The first one only uses function queries, while the second one also uses gradient queries. Other algorithms exist under much stronger assumptions, such as Newton's method. However, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	382,652
2403.14910	Defying Imbalanced Forgetting in Class Incremental Learning	We observe a high level of imbalance in the accuracy of different classes in the same old task for the first time. This intriguing phenomenon, discovered in replay-based Class Incremental Learning (CIL), highlights the imbalanced forgetting of learned classes, as their accuracy is similar before the occurrence of catas...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,302
2309.00127	FTA: Stealthy and Adaptive Backdoor Attack with Flexible Triggers on Federated Learning	Current backdoor attacks against federated learning (FL) strongly rely on universal triggers or semantic patterns, which can be easily detected and filtered by certain defense mechanisms such as norm clipping, comparing parameter divergences among local updates. In this work, we propose a new stealthy and robust backdo...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	389,201
2003.03759	3D Object Detection from a Single Fisheye Image Without a Single Fisheye Training Image	Existing monocular 3D object detection methods have been demonstrated on rectilinear perspective images and fail in images with alternative projections such as those acquired by fisheye cameras. Previous works on object detection in fisheye images have focused on 2D object detection, partly due to the lack of 3D datase...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,353
2205.03636	Deep Reinforcement Learning-Based Adaptive IRS Control with Limited Feedback Codebooks	Intelligent reflecting surfaces (IRS) consist of configurable meta-atoms, which can alter the wireless propagation environment through design of their reflection coefficients. We consider adaptive IRS control in the practical setting where (i) the IRS reflection coefficients are attained by adjusting tunable elements e...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	295,357
2406.13181	The Impact of Auxiliary Patient Data on Automated Chest X-Ray Report Generation and How to Incorporate It	This study investigates the integration of diverse patient data sources into multimodal language models for automated chest X-ray (CXR) report generation. Traditionally, CXR report generation relies solely on CXR images and limited radiology data, overlooking valuable information from patient health records, particular...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,735
0708.4149	On the complexity of nonnegative matrix factorization	Nonnegative matrix factorization (NMF) has become a prominent technique for the analysis of image databases, text databases and other information retrieval and clustering applications. In this report, we define an exact version of NMF. Then we establish several results about exact NMF: (1) that it is equivalent to a pr...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	611
2307.14107	Decoding ChatGPT: A Taxonomy of Existing Research, Current Challenges, and Possible Future Directions	Chat Generative Pre-trained Transformer (ChatGPT) has gained significant interest and attention since its launch in November 2022. It has shown impressive performance in various domains, including passing exams and creative writing. However, challenges and concerns related to biases and trust persist. In this work, we ...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	381,815
2407.17442	AHMF: Adaptive Hybrid-Memory-Fusion Model for Driver Attention Prediction	Accurate driver attention prediction can serve as a critical reference for intelligent vehicles in understanding traffic scenes and making informed driving decisions. Though existing studies on driver attention prediction improved performance by incorporating advanced saliency detection techniques, they overlooked the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	475,972
2206.08317	Paraformer: Fast and Accurate Parallel Transformer for Non-autoregressive End-to-End Speech Recognition	Transformers have recently dominated the ASR field. Although able to yield good performance, they involve an autoregressive (AR) decoder to generate tokens one by one, which is computationally inefficient. To speed up inference, non-autoregressive (NAR) methods, e.g. single-step NAR, were designed, to enable parallel g...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	303,085
2303.05399	Practical Statistical Considerations for the Clinical Validation of AI/ML-enabled Medical Diagnostic Devices	Artificial Intelligence (AI) and Machine-Learning (ML) models have been increasingly used in medical products, such as medical device software. General considerations on the statistical aspects for the evaluation of AI/ML-enabled medical diagnostic devices are discussed in this paper. We also provide relevant academic ...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	350,455
2411.14292	Hypothesis testing of symmetry in quantum dynamics	Symmetry plays a crucial role in quantum physics, dictating the behavior and dynamics of physical systems. In this paper, We develop a hypothesis-testing framework for quantum dynamics symmetry using a limited number of queries to the unknown unitary operation and establish the quantum max-relative entropy lower bound ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	510,101
1909.02244	Robust Navigation with Language Pretraining and Stochastic Sampling	Core to the vision-and-language navigation (VLN) challenge is building robust instruction representations and action decoding schemes, which can generalize well to previously unseen instructions and environments. In this paper, we report two simple but highly effective methods to address these challenges and lead to a ...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	144,144
2005.01482	A Globally Convergent State Observer for Multimachine Power Systems with Lossy Lines	We present the first solution to the problem of estimation of the state of multimachine power systems with lossy transmission lines. We consider the classical three-dimensional \fluxdecay" model of the power system and assume that the active and reactive power as well as the rotor angle and excitation voltage at each g...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	175,585
1707.09472	Weakly-supervised learning of visual relations	This paper introduces a novel approach for modeling visual relations between pairs of objects. We call relation a triplet of the form (subject, predicate, object) where the predicate is typically a preposition (eg. 'under', 'in front of') or a verb ('hold', 'ride') that links a pair of objects (subject, object). Learni...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,011
1902.08810	Deep Learning Approach on Information Diffusion in Heterogeneous Networks	There are many real-world knowledge based networked systems with multi-type interacting entities that can be regarded as heterogeneous networks including human connections and biological evolutions. One of the main issues in such networks is to predict information diffusion such as shape, growth and size of social even...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,273
2311.08942	Thermally-Resilient Soft Gripper for On-Orbit Operations	Research in soft manipulators has significantly enhanced object grasping capabilities, thanks to their adaptability to various shapes and sizes. Applying this technology to on-orbit servicing, especially during the capture and containment stages of active space debris removal missions, might offer a secure, adaptable, ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	407,926
2112.01583	The Representation Jensen-R\'enyi Divergence	We introduce a divergence measure between data distributions based on operators in reproducing kernel Hilbert spaces defined by kernels. The empirical estimator of the divergence is computed using the eigenvalues of positive definite Gram matrices that are obtained by evaluating the kernel over pairs of data points. Th...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	269,539
2302.10258	Neural Algorithmic Reasoning with Causal Regularisation	Recent work on neural algorithmic reasoning has investigated the reasoning capabilities of neural networks, effectively demonstrating they can learn to execute classical algorithms on unseen data coming from the train distribution. However, the performance of existing neural reasoners significantly degrades on out-of-d...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	346,723
1802.10011	Stochastic Control of Computation Offloading to a Helper with a Dynamically Loaded CPU	Due to densification of wireless networks, there exist abundance of idling computation resources at edge devices. These resources can be scavenged by offloading heavy computation tasks from small IoT devices in proximity, thereby overcoming their limitations and lengthening their battery lives. However, unlike dedicate...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	91,442
2303.11780	Debiased Contrastive Learning for Sequential Recommendation	Current sequential recommender systems are proposed to tackle the dynamic user preference learning with various neural techniques, such as Transformer and Graph Neural Networks (GNNs). However, inference from the highly sparse user behavior data may hinder the representation ability of sequential pattern encoding. To a...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	353,006
2202.06123	Models of human behavior for human-robot interaction and automated driving: How accurate do the models of human behavior need to be?	There are many examples of cases where access to improved models of human behavior and cognition has allowed creation of robots which can better interact with humans, and not least in road vehicle automation this is a rapidly growing area of research. Human-robot interaction (HRI) therefore provides an important applie...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	280,100
2410.20314	Wavelet-based Mamba with Fourier Adjustment for Low-light Image Enhancement	Frequency information (e.g., Discrete Wavelet Transform and Fast Fourier Transform) has been widely applied to solve the issue of Low-Light Image Enhancement (LLIE). However, existing frequency-based models primarily operate in the simple wavelet or Fourier space of images, which lacks utilization of valid global and l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	502,760
1709.01872	Synthetic Medical Images from Dual Generative Adversarial Networks	Currently there is strong interest in data-driven approaches to medical image classification. However, medical imaging data is scarce, expensive, and fraught with legal concerns regarding patient privacy. Typical consent forms only allow for patient data to be used in medical journals or education, meaning the majority...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	80,165
2405.13056	Large language models for sentiment analysis of newspaper articles during COVID-19: The Guardian	During the COVID-19 pandemic, the news media coverage encompassed a wide range of topics that includes viral transmission, allocation of medical resources, and government response measures. There have been studies on sentiment analysis of social media platforms during COVID-19 to understand the public response given th...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	455,782
2011.00635	Screening for an Infectious Disease as a Problem in Stochastic Control	There has been much recent interest in screening populations for an infectious disease. Here, we present a stochastic-control model, wherein the optimum screening policy is provably difficult to find, but wherein Thompson sampling has provably optimal performance guarantees in the form of Bayesian regret. Thompson samp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	204,308
2112.01194	Video-Text Pre-training with Learned Regions	Video-Text pre-training aims at learning transferable representations from large-scale video-text pairs via aligning the semantics between visual and textual information. State-of-the-art approaches extract visual features from raw pixels in an end-to-end fashion. However, these methods operate at frame-level directly ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	269,405
2202.03544	LwPosr: Lightweight Efficient Fine-Grained Head Pose Estimation	This paper presents a lightweight network for head pose estimation (HPE) task. While previous approaches rely on convolutional neural networks, the proposed network \textit{LwPosr} uses mixture of depthwise separable convolutional (DSC) and transformer encoder layers which are structured in two streams and three stages...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	279,241
2403.19374	A noise-tolerant, resource-saving probabilistic binary neural network implemented by the SOT-MRAM compute-in-memory system	We report a spin-orbit torque(SOT) magnetoresistive random-access memory(MRAM)-based probabilistic binary neural network(PBNN) for resource-saving and hardware noise-tolerant computing applications. With the presence of thermal fluctuation, the non-destructive SOT-driven magnetization switching characteristics lead to ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	442,319
2103.01640	Double Coverage with Machine-Learned Advice	We study the fundamental online k-server problem in a learning-augmented setting. While in the traditional online model, an algorithm has no information about the request sequence, we assume that there is given some advice (e.g. machine-learned predictions) on an algorithm's decision. There is, however, no guarantee on...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	222,700
2405.05292	Smart Portable Computer	Amidst the COVID-19 pandemic, with many organizations, schools, colleges, and universities transitioning to virtual platforms, students encountered difficulties in acquiring PCs such as desktops or laptops. The starting prices, around 15,000 INR, often failed to offer adequate system specifications, posing a challenge ...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	452,872
2312.14126	Entropic Open-set Active Learning	Active Learning (AL) aims to enhance the performance of deep models by selecting the most informative samples for annotation from a pool of unlabeled data. Despite impressive performance in closed-set settings, most AL methods fail in real-world scenarios where the unlabeled data contains unknown categories. Recently, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,506
1511.03602	Kolmogorov complexity version of Slepian-Wolf coding	Alice and Bob are given two correlated n-bit strings x_1 and, respectively, x_2, which they want to losslessly compress and send to Zack. They can either collaborate by sharing their strings, or work separately. We show that there is no disadvantage in the second scenario: Alice and Bob, without knowing the other party...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	48,774
2308.10973	SupEuclid: Extremely Simple, High Quality OoD Detection with Supervised Contrastive Learning and Euclidean Distance	Out-of-Distribution (OoD) detection has developed substantially in the past few years, with available methods approaching, and in a few cases achieving, perfect data separation on standard benchmarks. These results generally involve large or complex models, pretraining, exposure to OoD examples or extra hyperparameter ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	386,950
2407.12798	Multi-Granularity and Multi-modal Feature Interaction Approach for Text Video Retrieval	The key of the text-to-video retrieval (TVR) task lies in learning the unique similarity between each pair of text (consisting of words) and video (consisting of audio and image frames) representations. However, some problems exist in the representation alignment of video and text, such as a text, and further each word...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	474,082
2109.08346	Comfetch: Federated Learning of Large Networks on Constrained Clients via Sketching	Federated learning (FL) is a popular paradigm for private and collaborative model training on the edge. In centralized FL, the parameters of a global architecture (such as a deep neural network) are maintained and distributed by a central server/controller to clients who transmit model updates (gradients) back to the s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	255,873
1912.10427	Joint Face Super-Resolution and Deblurring Using a Generative Adversarial Network	Facial image super-resolution (SR) is an important preprocessing for facial image analysis, face recognition, and image-based 3D face reconstruction. Recent convolutional neural network (CNN) based method has shown excellent performance by learning mapping relation using pairs of low-resolution (LR) and high-resolution...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	158,319
2309.01966	AdaPlus: Integrating Nesterov Momentum and Precise Stepsize Adjustment on AdamW Basis	This paper proposes an efficient optimizer called AdaPlus which integrates Nesterov momentum and precise stepsize adjustment on AdamW basis. AdaPlus combines the advantages of AdamW, Nadam, and AdaBelief and, in particular, does not introduce any extra hyper-parameters. We perform extensive experimental evaluations on ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	389,873
1807.04920	On the Complexity of Value Iteration	Value iteration is a fundamental algorithm for solving Markov Decision Processes (MDPs). It computes the maximal $n$-step payoff by iterating $n$ times a recurrence equation which is naturally associated to the MDP. At the same time, value iteration provides a policy for the MDP that is optimal on a given finite horizo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	102,832
1203.3510	Irregular-Time Bayesian Networks	In many fields observations are performed irregularly along time, due to either measurement limitations or lack of a constant immanent rate. While discrete-time Markov models (as Dynamic Bayesian Networks) introduce either inefficient computation or an information loss to reasoning about such processes, continuous-time...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	14,958
2212.11274	SPIRiT-Diffusion: SPIRiT-driven Score-Based Generative Modeling for Vessel Wall imaging	Diffusion model is the most advanced method in image generation and has been successfully applied to MRI reconstruction. However, the existing methods do not consider the characteristics of multi-coil acquisition of MRI data. Therefore, we give a new diffusion model, called SPIRiT-Diffusion, based on the SPIRiT iterati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	337,746
2211.08892	Fast Graph Generation via Spectral Diffusion	Generating graph-structured data is a challenging problem, which requires learning the underlying distribution of graphs. Various models such as graph VAE, graph GANs, and graph diffusion models have been proposed to generate meaningful and reliable graphs, among which the diffusion models have achieved state-of-the-ar...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	330,807
2011.04439	FACEGAN: Facial Attribute Controllable rEenactment GAN	The face reenactment is a popular facial animation method where the person's identity is taken from the source image and the facial motion from the driving image. Recent works have demonstrated high quality results by combining the facial landmark based motion representations with the generative adversarial networks. T...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	205,584
1608.05949	Distributed Representations for Biological Sequence Analysis	Biological sequence comparison is a key step in inferring the relatedness of various organisms and the functional similarity of their components. Thanks to the Next Generation Sequencing efforts, an abundance of sequence data is now available to be processed for a range of bioinformatics applications. Embedding a biolo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	60,045
2407.00127	Multi-Species Object Detection in Drone Imagery for Population Monitoring of Endangered Animals	Animal populations worldwide are rapidly declining, and a technology that can accurately count endangered species could be vital for monitoring population changes over several years. This research focused on fine-tuning object detection models for drone images to create accurate counts of animal species. Hundreds of im...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	468,739
1912.07571	Fuzzy Logic based Autonomous Parking Systems -- Part III: A Fuzzy Decision Tree System	This paper proposes a robust design of Hybrid Fuzzy Controller for speed and steering angle control in an Intelligent Autonomous Parking System (IAPS). The Hybrid Fuzzy Controller consists of a Base Fuzzy Controller (BFC) and a Supervisory Fuzzy Decision Tree Controller (SFDTC). The BFC evolves from previous work on fu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	157,638
1403.4342	Spatial Performance Analysis and Design Principles for Wireless Peer Discovery	In wireless peer-to-peer networks that serve various proximity-based applications, peer discovery is the key to identifying other peers with which a peer can communicate and an understanding of its performance is fundamental to the design of an efficient discovery operation. This paper analyzes the performance of wirel...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	31,641
1710.00568	Indirect Match Highlights Detection with Deep Convolutional Neural Networks	Highlights in a sport video are usually referred as actions that stimulate excitement or attract attention of the audience. A big effort is spent in designing techniques which find automatically highlights, in order to automatize the otherwise manual editing process. Most of the state-of-the-art approaches try to solve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	81,886
1809.06427	A Convex-Combinatorial Model for Planar Caging	Caging is a promising tool which allows a robot to manipulate an object without directly reasoning about the contact dynamics involved. Furthermore, caging also provides useful guarantees in terms of robustness to uncertainty, and often serves as a way-point to a grasp. Unfortunately, previous work on caging is often b...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	108,055
1603.01943	Partially Block Markov Superposition Transmission of Gaussian Source with Nested Lattice Codes	This paper studies the transmission of Gaussian sources through additive white Gaussian noise (AWGN) channels in bandwidth expansion regime, i.e., the channel bandwidth is greater than the source bandwidth. To mitigate the error propagation phenomenon of conventional digital transmission schemes, we propose in this pap...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	52,959
1205.3062	Malware Detection Module using Machine Learning Algorithms to Assist in Centralized Security in Enterprise Networks	Malicious software is abundant in a world of innumerable computer users, who are constantly faced with these threats from various sources like the internet, local networks and portable drives. Malware is potentially low to high risk and can cause systems to function incorrectly, steal data and even crash. Malware may b...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	15,997
2408.16889	LLaVA-Chef: A Multi-modal Generative Model for Food Recipes	In the rapidly evolving landscape of online recipe sharing within a globalized context, there has been a notable surge in research towards comprehending and generating food recipes. Recent advancements in large language models (LLMs) like GPT-2 and LLaVA have paved the way for Natural Language Processing (NLP) approach...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	484,490
2104.10903	Blockchain based Privacy-Preserved Federated Learning for Medical Images: A Case Study of COVID-19 CT Scans	Medical health care centers are envisioned as a promising paradigm to handle the massive volume of data of COVID-19 patients using artificial intelligence (AI). Traditionally, AI techniques often require centralized data collection and training the model in a single organization, which is most common weakness due to th...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	231,756
1609.01136	Constructions of Optimal Cyclic $(r,\delta)$ Locally Repairable Codes	A code is said to be a $r$-local locally repairable code (LRC) if each of its coordinates can be repaired by accessing at most $r$ other coordinates. When some of the $r$ coordinates are also erased, the $r$-local LRC can not accomplish the local repair, which leads to the concept of $(r,\delta)$-locality. A $q$-ary $[...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	60,559
1807.02728	Abnormality Detection inside Blood Vessels with Mobile Nanomachines	Motivated by the numerous healthcare applications of molecular communication within Internet of Bio-Nano Things (IoBNT), this work addresses the problem of abnormality detection in a blood vessel using multiple biological embedded computing devices called cooperative biological nanomachines (CNs), and a common receiver...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	102,334
1706.06998	Secret Sharing and Shared Information	Secret sharing is a cryptographic discipline in which the goal is to distribute information about a secret over a set of participants in such a way that only specific authorized combinations of participants together can reconstruct the secret. Thus, secret sharing schemes are systems of variables in which it is very cl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	75,782
2003.04950	Synthesis of Control Barrier Functions Using a Supervised Machine Learning Approach	Control barrier functions are mathematical constructs used to guarantee safety for robotic systems. When integrated as constraints in a quadratic programming optimization problem, instantaneous control synthesis with real-time performance demands can be achieved for robotics applications. Prevailing use has assumed ful...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	167,706
2311.04402	Likelihood Ratio Confidence Sets for Sequential Decision Making	Certifiable, adaptive uncertainty estimates for unknown quantities are an essential ingredient of sequential decision-making algorithms. Standard approaches rely on problem-dependent concentration results and are limited to a specific combination of parameterization, noise family, and estimator. In this paper, we revis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	406,211
2502.11101	CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation	Large Language Models (LLMs) excel across a variety of language tasks yet are constrained by limited input lengths and high computational costs. Existing approaches\textemdash such as relative positional encodings (e.g., RoPE, ALiBi) and sliding window mechanisms\textemdash partially alleviate these issues but often re...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	534,192
1507.03719	A New Framework for Distributed Submodular Maximization	A wide variety of problems in machine learning, including exemplar clustering, document summarization, and sensor placement, can be cast as constrained submodular maximization problems. A lot of recent effort has been devoted to developing distributed algorithms for these problems. However, these results suffer from hi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	45,097
2010.09461	Normal Forms for (Semantically) Witness-Based Learners in Inductive Inference	We study learners (computable devices) inferring formal languages, a setting referred to as language learning in the limit or inductive inference. In particular, we require the learners we investigate to be witness-based, that is, to justify each of their mind changes. Besides being a natural requirement for a learning...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	201,545
1905.12132	Signal selection for estimation and identification in networks of dynamic systems: a graphical model approach	Network systems have become a ubiquitous modeling tool in many areas of science where nodes in a graph represent distributed processes and edges between nodes represent a form of dynamic coupling. When a network topology is already known (or partially known), two associated goals are (i) to derive estimators for nodes ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	132,663
1706.06160	User Intent Classification using Memory Networks: A Comparative Analysis for a Limited Data Scenario	In this report, we provide a comparative analysis of different techniques for user intent classification towards the task of app recommendation. We analyse the performance of different models and architectures for multi-label classification over a dataset with a relative large number of classes and only a handful examp...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	75,628
2003.06344	Automating Botnet Detection with Graph Neural Networks	Botnets are now a major source for many network attacks, such as DDoS attacks and spam. However, most traditional detection methods heavily rely on heuristically designed multi-stage detection criteria. In this paper, we consider the neural network design challenges of using modern deep learning techniques to learn pol...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	168,090
2210.08877	Data-Driven Short-Term Daily Operational Sea Ice Regional Forecasting	Global warming made the Arctic available for marine operations and created demand for reliable operational sea ice forecasts to make them safe. While ocean-ice numerical models are highly computationally intensive, relatively lightweight ML-based methods may be more efficient in this task. Many works have exploited dif...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	324,337
1103.4687	Vector Broadcast Channels: Optimal Threshold Selection Problem	Threshold feedback policies are well known and provably rate-wise optimal selective feedback techniques for communication systems requiring partial channel state information (CSI). However, optimal selection of thresholds at mobile users to maximize information theoretic data rates subject to feedback constraints is an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,734
1002.2412	A Probabilistic Model For Sequence Analysis	This paper presents a probabilistic approach for DNA sequence analysis. A DNA sequence consists of an arrangement of the four nucleotides A, C, T and G and different representation schemes are presented according to a probability measure associated with them. There are different ways that probability can be associated ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	5,685
2405.19946	Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf	Communication is a fundamental aspect of human society, facilitating the exchange of information and beliefs among people. Despite the advancements in large language models (LLMs), recent agents built with these often neglect the control over discussion tactics, which are essential in communication scenarios and games....	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	459,131
1605.04579	Communicating One Bit over a Delay Constrained Gaussian MIMO Channel with Feedback	The energy-optimal scheme is found for communicating one bit over a memoryless Gaussian channel with an ideal feedback channel. It is assumed that the channel is allowed to be used at most N times before decoding. The optimal coding/decoding strategy is derived by dynamic programming. It is found that feedback gives a ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,884
2004.14652	Question Rewriting for Conversational Question Answering	Conversational question answering (QA) requires the ability to correctly interpret a question in the context of previous conversation turns. We address the conversational QA task by decomposing it into question rewriting and question answering subtasks. The question rewriting (QR) subtask is specifically designed to re...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	174,966
2408.00883	Strategic Coalitions in Networked Contest Games	In competitive resource allocation formulations multiple agents compete over different contests by committing their limited resources in them. For these settings, contest games offer a game-theoretic foundation to analyze how players can efficiently invest their resources. In this class of games the resulting behavior ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	478,013
2112.14026	SECP-Net: SE-Connection Pyramid Network of Organ At Risk Segmentation for Nasopharyngeal Carcinoma	Nasopharyngeal carcinoma (NPC) is a kind of malignant tumor. Accurate and automatic segmentation of organs at risk (OAR) of computed tomography (CT) images is clinically significant. In recent years, deep learning models represented by U-Net have been widely applied in medical image segmentation tasks, which can help d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	273,435
2006.05806	Bandit Samplers for Training Graph Neural Networks	Several sampling algorithms with variance reduction have been proposed for accelerating the training of Graph Convolution Networks (GCNs). However, due to the intractable computation of optimal sampling distribution, these sampling algorithms are suboptimal for GCNs and are not applicable to more general graph neural n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,208
2502.07459	PerCul: A Story-Driven Cultural Evaluation of LLMs in Persian	Large language models predominantly reflect Western cultures, largely due to the dominance of English-centric training data. This imbalance presents a significant challenge, as LLMs are increasingly used across diverse contexts without adequate evaluation of their cultural competence in non-English languages, including...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	532,613
2109.07210	Life-Long Multi-Task Learning of Adaptive Path Tracking Policy for Autonomous Vehicle	This paper proposes a life-long adaptive path tracking policy learning method for autonomous vehicles that can self-evolve and self-adapt with multi-task knowledge. Firstly, the proposed method can learn a model-free control policy for path tracking directly from the historical driving experience, where the property of...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	255,434
1810.00902	Dealing with State Estimation in Fractional-Order Systems under Artifacts	Fractional-order dynamical systems are used to describe processes that exhibit long-term memory with power-law dependence. Notable examples include complex neurophysiological signals such as electroencephalogram (EEG) and blood-oxygen-level dependent (BOLD) signals. When analyzing different neurophysiological signals a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	109,282
2205.06885	PathologyBERT -- Pre-trained Vs. A New Transformer Language Model for Pathology Domain	Pathology text mining is a challenging task given the reporting variability and constant new findings in cancer sub-type definitions. However, successful text mining of a large pathology database can play a critical role to advance 'big data' cancer research like similarity-based treatment selection, case identificatio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	296,382
1401.3487	The DL-Lite Family and Relations	The recently introduced series of description logics under the common moniker DL-Lite has attracted attention of the description logic and semantic web communities due to the low computational complexity of inference, on the one hand, and the ability to represent conceptual modeling formalisms, on the other. The main a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	29,891
2003.02873	Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits	We propose the Generalized Policy Elimination (GPE) algorithm, an oracle-efficient contextual bandit (CB) algorithm inspired by the Policy Elimination algorithm of \cite{dudik2011}. We prove the first regret optimality guarantee theorem for an oracle-efficient CB algorithm competing against a nonparametric class with i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	167,057
1907.04228	Fundamental limits of quantum-secure covert communication over bosonic channels	We investigate the fundamental limit of quantum-secure covert communication over the lossy thermal noise bosonic channel, the quantum-mechanical model underlying many practical channels. We assume that the adversary has unlimited quantum information processing capabilities as well as access to all transmitted photons t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	138,053
2110.14461	Hand gesture detection in tests performed by older adults	Our team are developing a new online test that analyses hand movement features associated with ageing that can be completed remotely from the research centre. To obtain hand movement features, participants will be asked to perform a variety of hand gestures using their own computer cameras. However, it is challenging t...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	263,546
2305.07141	The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domain	The abilities to form and abstract concepts is key to human intelligence, but such abilities remain lacking in state-of-the-art AI systems. There has been substantial research on conceptual abstraction in AI, particularly using idealized domains such as Raven's Progressive Matrices and Bongard problems, but even when A...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	363,785
1603.09454	Exemplar-AMMs: Recognizing Crowd Movements from Pedestrian Trajectories	In this paper, we present a novel method to recognize the types of crowd movement from crowd trajectories using agent-based motion models (AMMs). Our idea is to apply a number of AMMs, referred to as exemplar-AMMs, to describe the crowd movement. Specifically, we propose an optimization framework that filters out the u...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,923
2206.11922	Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance	The utilization of artificial intelligence (AI) applications has experienced tremendous growth in recent years, bringing forth numerous benefits and conveniences. However, this expansion has also provoked ethical concerns, such as privacy breaches, algorithmic discrimination, security and reliability issues, transparen...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	304,419
2302.08150	Reanalyzing L2 Preposition Learning with Bayesian Mixed Effects and a Pretrained Language Model	We use both Bayesian and neural models to dissect a data set of Chinese learners' pre- and post-interventional responses to two tests measuring their understanding of English prepositions. The results mostly replicate previous findings from frequentist analyses and newly reveal crucial interactions between student abil...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	345,962
2008.06072	MIXCAPS: A Capsule Network-based Mixture of Experts for Lung Nodule Malignancy Prediction	Lung diseases including infections such as Pneumonia, Tuberculosis, and novel Coronavirus (COVID-19), together with Lung Cancer are significantly widespread and are, typically, considered life threatening. In particular, lung cancer is among the most common and deadliest cancers with a low 5-year survival rate. Timely ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	191,688
1702.07713	Multichannel Linear Prediction for Blind Reverberant Audio Source Separation	A class of methods based on multichannel linear prediction (MCLP) can achieve effective blind dereverberation of a source, when the source is observed with a microphone array. We propose an inventive use of MCLP as a pre-processing step for blind source separation with a microphone array. We show theoretically that, un...	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	68,828
2001.04197	Causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders	Causal discovery from data affected by latent confounders is an important and difficult challenge. Causal functional model-based approaches have not been used to present variables whose relationships are affected by latent confounders, while some constraint-based methods can present them. This paper proposes a causal f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,178
2005.13483	Kernel methods library for pattern analysis and machine learning in python	Kernel methods have proven to be powerful techniques for pattern analysis and machine learning (ML) in a variety of domains. However, many of their original or advanced implementations remain in Matlab. With the incredible rise and adoption of Python in the ML and data science world, there is a clear need for a well-de...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	179,024
1907.09006	Forward-Backward Decoding for Regularizing End-to-End TTS	Neural end-to-end TTS can generate very high-quality synthesized speech, and even close to human recording within similar domain text. However, it performs unsatisfactory when scaling it to challenging test sets. One concern is that the encoder-decoder with attention-based network adopts autoregressive generative seque...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	139,240
1807.09532	Aerial Imagery for Roof Segmentation: A Large-Scale Dataset towards Automatic Mapping of Buildings	arXiv admin note: This version has been removed as the user did not have the right to agree to the license at the time of submission	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	103,742

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