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
2412.18426	GUI Testing Arena: A Unified Benchmark for Advancing Autonomous GUI Testing Agent	Nowadays, research on GUI agents is a hot topic in the AI community. However, current research focuses on GUI task automation, limiting the scope of applications in various GUI scenarios. In this paper, we propose a formalized and comprehensive environment to evaluate the entire process of automated GUI Testing (GTAren...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	520,419
2403.13370	Counting Network for Learning from Majority Label	The paper proposes a novel problem in multi-class Multiple-Instance Learning (MIL) called Learning from the Majority Label (LML). In LML, the majority class of instances in a bag is assigned as the bag's label. LML aims to classify instances using bag-level majority classes. This problem is valuable in various applicat...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	439,611
1202.2892	Recommender System Based on Algorithm of Bicluster Analysis RecBi	In this paper we propose two new algorithms based on biclustering analysis, which can be used at the basis of a recommender system for educational orientation of Russian School graduates. The first algorithm was designed to help students make a choice between different university faculties when some of their preference...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	14,315
2209.04471	MCIBI++: Soft Mining Contextual Information Beyond Image for Semantic Segmentation	Co-occurrent visual pattern makes context aggregation become an essential paradigm for semantic segmentation.The existing studies focus on modeling the contexts within image while neglecting the valuable semantics of the corresponding category beyond image. To this end, we propose a novel soft mining contextual informa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	316,791
2008.01011	Phase Transitions in Rate Distortion Theory and Deep Learning	Rate distortion theory is concerned with optimally encoding a given signal class $\mathcal{S}$ using a budget of $R$ bits, as $R\to\infty$. We say that $\mathcal{S}$ can be compressed at rate $s$ if we can achieve an error of $\mathcal{O}(R^{-s})$ for encoding $\mathcal{S}$; the supremal compression rate is denoted $s^...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	190,180
1907.03411	Unbiased estimators for random design regression	In linear regression we wish to estimate the optimum linear least squares predictor for a distribution over $d$-dimensional input points and real-valued responses, based on a small sample. Under standard random design analysis, where the sample is drawn i.i.d. from the input distribution, the least squares solution for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,857
2207.07971	A Survey of Decision Making in Adversarial Games	Game theory has by now found numerous applications in various fields, including economics, industry, jurisprudence, and artificial intelligence, where each player only cares about its own interest in a noncooperative or cooperative manner, but without obvious malice to other players. However, in many practical applicat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	308,397
2004.00605	EPOS: Estimating 6D Pose of Objects with Symmetries	We present a new method for estimating the 6D pose of rigid objects with available 3D models from a single RGB input image. The method is applicable to a broad range of objects, including challenging ones with global or partial symmetries. An object is represented by compact surface fragments which allow handling symme...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	170,693
2012.00161	SuperCell: A Wide-Area Coverage Solution Using High-Gain, High-Order Sectorized Antennas on Tall Towers	In this article we introduce a novel solution called SuperCell, which can improve the return on investment (ROI) for rural area network coverage. SuperCell offers two key technical features: it uses tall towers with high-gain antennas for wide coverage and high-order sectorization for high capacity. We show that a solu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	209,040
2001.09912	Depthwise-STFT based separable Convolutional Neural Networks	In this paper, we propose a new convolutional layer called Depthwise-STFT Separable layer that can serve as an alternative to the standard depthwise separable convolutional layer. The construction of the proposed layer is inspired by the fact that the Fourier coefficients can accurately represent important features suc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	161,701
0809.3181	Framework for Dynamic Evaluation of Muscle Fatigue in Manual Handling Work	Muscle fatigue is defined as the point at which the muscle is no longer able to sustain the required force or work output level. The overexertion of muscle force and muscle fatigue can induce acute pain and chronic pain in human body. When muscle fatigue is accumulated, the functional disability can be resulted as musc...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	2,374
2303.10460	Average Probability of Error for Single Uniprior Index Coding over Rayleigh Fading Channel	Ong and Ho developed optimal linear index codes for single uniprior index coding problems (ICPs) by finding a spanning tree for each of the strongly connected components of the corresponding information-flow graphs, following which Thomas et al. considered the same class of ICPs over Rayleigh fading channel. They devel...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	352,463
2412.03745	Deep Variational Bayesian Modeling of Haze Degradation Process	Relying on the representation power of neural networks, most recent works have often neglected several factors involved in haze degradation, such as transmission (the amount of light reaching an observer from a scene over distance) and atmospheric light. These factors are generally unknown, making dehazing problems ill...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	514,085
2303.18230	Procedure-Aware Pretraining for Instructional Video Understanding	Our goal is to learn a video representation that is useful for downstream procedure understanding tasks in instructional videos. Due to the small amount of available annotations, a key challenge in procedure understanding is to be able to extract from unlabeled videos the procedural knowledge such as the identity of th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,509
1712.03941	Fast Nearest-Neighbor Classification using RNN in Domains with Large Number of Classes	In scenarios involving text classification where the number of classes is large (in multiples of 10000s) and training samples for each class are few and often verbose, nearest neighbor methods are effective but very slow in computing a similarity score with training samples of every class. On the other hand, machine le...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	86,524
2202.10717	Quantum Differential Privacy: An Information Theory Perspective	Differential privacy has been an exceptionally successful concept when it comes to providing provable security guarantees for classical computations. More recently, the concept was generalized to quantum computations. While classical computations are essentially noiseless and differential privacy is often achieved by a...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	281,637
2303.03907	GaussianMLR: Learning Implicit Class Significance via Calibrated Multi-Label Ranking	Existing multi-label frameworks only exploit the information deduced from the bipartition of the labels into a positive and negative set. Therefore, they do not benefit from the ranking order between positive labels, which is the concept we introduce in this paper. We propose a novel multi-label ranking method: Gaussia...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	349,886
2404.13149	Beyond Self-Consistency: Ensemble Reasoning Boosts Consistency and Accuracy of LLMs in Cancer Staging	Advances in large language models (LLMs) have encouraged their adoption in the healthcare domain where vital clinical information is often contained in unstructured notes. Cancer staging status is available in clinical reports, but it requires natural language processing to extract the status from the unstructured text...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	448,183
1611.03566	Construction Inspection through Spatial Database	This paper presents a novel pipeline for development of an efficient set of tools for extracting information from the video of a structure, captured by an Unmanned Aircraft System (UAS) to produce as-built documentation to aid inspection of large multi-storied building during construction. Our system uses the output fr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	63,712
2303.14038	Accelerating Vision-Language Pretraining with Free Language Modeling	The state of the arts in vision-language pretraining (VLP) achieves exemplary performance but suffers from high training costs resulting from slow convergence and long training time, especially on large-scale web datasets. An essential obstacle to training efficiency lies in the entangled prediction rate (percentage of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	353,924
2406.12373	WebCanvas: Benchmarking Web Agents in Online Environments	For web agents to be practically useful, they must adapt to the continuously evolving web environment characterized by frequent updates to user interfaces and content. However, most existing benchmarks only capture the static aspects of the web. To bridge this gap, we introduce WebCanvas, an innovative online evaluatio...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	465,370
2409.10756	VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching	Large Language Models (LLMs) have shown promise in tasks like code translation, prompting interest in their potential for automating software vulnerability detection (SVD) and patching (SVP). To further research in this area, establishing a benchmark is essential for evaluating the strengths and limitations of LLMs in ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	488,871
1812.00950	Generative Adversarial Self-Imitation Learning	This paper explores a simple regularizer for reinforcement learning by proposing Generative Adversarial Self-Imitation Learning (GASIL), which encourages the agent to imitate past good trajectories via generative adversarial imitation learning framework. Instead of directly maximizing rewards, GASIL focuses on reproduc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	115,391
2412.21180	STITCHER: Real-Time Trajectory Planning with Motion Primitive Search	Autonomous high-speed navigation through large, complex environments requires real-time generation of agile trajectories that are dynamically feasible, collision-free, and satisfy state or actuator constraints. Most modern trajectory planning techniques rely on numerical optimization because high-quality, expressive tr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	521,475
1512.01250	Assessing forensic evidence by computing belief functions	We first discuss certain problems with the classical probabilistic approach for assessing forensic evidence, in particular its inability to distinguish between lack of belief and disbelief, and its inability to model complete ignorance within a given population. We then discuss Shafer belief functions, a generalization...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	49,786
2110.04810	Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting	Prediction of movements is essential for successful cooperation with intelligent systems. We propose a model that integrates organized spatial information as given through the moving body's skeletal structure. This inherent structure is exploited in our model through application of Graph Convolutions and we demonstrate...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	260,049
1102.2216	On the Capacity of Memoryless Channels with Synchronization Errors	Memoryless channels with synchronization errors as defined by a stochastic channel matrix allowing for symbol insertions and deletions in addition to random errors are considered. Such channels are information stable, hence their Shannon capacity exists. However, computation of the channel capacity is formidable, and o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,111
2008.05250	Optimizing fire allocation in a NCW-type model	In this paper, we introduce a non-linear Lanchester model of NCW-type and investigate an optimization problem for this model, where only the Red force is supplied by several supply agents. Optimal fire allocation of the Blue force is sought in the form of a piece-wise constant function of time. A threatening rate is co...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	191,465
1112.3712	Analysis and Extension of Arc-Cosine Kernels for Large Margin Classification	We investigate a recently proposed family of positive-definite kernels that mimic the computation in large neural networks. We examine the properties of these kernels using tools from differential geometry; specifically, we analyze the geometry of surfaces in Hilbert space that are induced by these kernels. When this g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	13,485
2404.10617	Optimizing Performance on Trinity Utilizing Machine Learning, Proxy Applications and Scheduling Priorities	The sheer number of nodes continues to increase in todays supercomputers, the first half of Trinity alone contains more than 9400 compute nodes. Since the speed of todays clusters are limited by the slowest nodes, it more important than ever to identify slow nodes, improve their performance if it can be done, and assur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	447,173
2211.02585	Material Named Entity Recognition (MNER) for Knowledge-driven Materials Using Deep Learning Approach	The scientific literature contains a wealth of cutting-edge knowledge in the field of materials science, as well as useful data (e.g., numerical data from experimental results, material properties and structure). These data are critical for data-driven machine learning (ML) and deep learning (DL) methods to accelerate ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	328,622
2108.02557	Comparison of Lossless Image Formats	In recent years, a bag with image and video compression formats has been torn. However, most of them are focused on lossy compression and only marginally support the lossless mode. In this paper, I will focus on lossless formats and the critical question: "Which one is the most efficient?" It turned out that FLIF is cu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	249,364
2410.11686	A Survey of Low-shot Vision-Language Model Adaptation via Representer Theorem	The advent of pre-trained vision-language foundation models has revolutionized the field of zero/few-shot (i.e., low-shot) image recognition. The key challenge to address under the condition of limited training data is how to fine-tune pre-trained vision-language models in a parameter-efficient manner. Previously, nume...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	498,672
1411.0814	A random algorithm for low-rank decomposition of large-scale matrices with missing entries	A Random SubMatrix method (RSM) is proposed to calculate the low-rank decomposition of large-scale matrices with known entry percentage \rho. RSM is very fast as the floating-point operations (flops) required are compared favorably with the state-of-the-art algorithms. Meanwhile RSM is very memory-saving. With known en...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	37,284
2412.15253	Using Machine Learning to Distinguish Human-written from Machine-generated Creative Fiction	Following the universal availability of generative AI systems with the release of ChatGPT, automatic detection of deceptive text created by Large Language Models has focused on domains such as academic plagiarism and "fake news". However, generative AI also poses a threat to the livelihood of creative writers, and perh...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	519,013
2111.05199	Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information	Modeling the spatiotemporal nature of the spread of infectious diseases can provide useful intuition in understanding the time-varying aspect of the disease spread and the underlying complex spatial dependency observed in people's mobility patterns. Besides, the county level multiple related time series information can...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,722
2312.15058	The State of Documentation Practices of Third-party Machine Learning Models and Datasets	Model stores offer third-party ML models and datasets for easy project integration, minimizing coding efforts. One might hope to find detailed specifications of these models and datasets in the documentation, leveraging documentation standards such as model and dataset cards. In this study, we use statistical analysis ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	417,854
2407.09352	Imaging Interiors: An Implicit Solution to Electromagnetic Inverse Scattering Problems	Electromagnetic Inverse Scattering Problems (EISP) have gained wide applications in computational imaging. By solving EISP, the internal relative permittivity of the scatterer can be non-invasively determined based on the scattered electromagnetic fields. Despite previous efforts to address EISP, achieving better solut...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,536
2205.08379	A CMOS-based Characterisation Platform for Emerging RRAM Technologies	Mass characterisation of emerging memory devices is an essential step in modelling their behaviour for integration within a standard design flow for existing integrated circuit designers. This work develops a novel characterisation platform for emerging resistive devices with a capacity of up to 1 million devices on-ch...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	296,915
1703.05693	SVDNet for Pedestrian Retrieval	This paper proposes the SVDNet for retrieval problems, with focus on the application of person re-identification (re-ID). We view each weight vector within a fully connected (FC) layer in a convolutional neuron network (CNN) as a projection basis. It is observed that the weight vectors are usually highly correlated. Th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,122
1807.00459	How To Backdoor Federated Learning	Federated learning enables thousands of participants to construct a deep learning model without sharing their private training data with each other. For example, multiple smartphones can jointly train a next-word predictor for keyboards without revealing what individual users type. We demonstrate that any participant i...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	101,842
2404.13278	Federated Transfer Learning with Task Personalization for Condition Monitoring in Ultrasonic Metal Welding	Ultrasonic metal welding (UMW) is a key joining technology with widespread industrial applications. Condition monitoring (CM) capabilities are critically needed in UMW applications because process anomalies significantly deteriorate the joining quality. Recently, machine learning models emerged as a promising tool for ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	448,228
2312.17624	XAI for In-hospital Mortality Prediction via Multimodal ICU Data	Predicting in-hospital mortality for intensive care unit (ICU) patients is key to final clinical outcomes. AI has shown advantaged accuracy but suffers from the lack of explainability. To address this issue, this paper proposes an eXplainable Multimodal Mortality Predictor (X-MMP) approaching an efficient, explainable ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	418,811
2311.18639	Targeted Reduction of Causal Models	Why does a phenomenon occur? Addressing this question is central to most scientific inquiries and often relies on simulations of scientific models. As models become more intricate, deciphering the causes behind phenomena in high-dimensional spaces of interconnected variables becomes increasingly challenging. Causal Rep...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	411,753
2210.04487	Quasi-cyclic Hermitian construction of binary quantum codes	In this paper, we propose a sufficient condition for a family of 2-generator self-orthogonal quasi-cyclic codes with respect to Hermitian inner product. Supported in the Hermitian construction, we show algebraic constructions of good quantum codes. 30 new binary quantum codes with good parameters improving the best-kno...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	322,475
1604.06582	Kernelized Covariance for Action Recognition	In this paper we aim at increasing the descriptive power of the covariance matrix, limited in capturing linear mutual dependencies between variables only. We present a rigorous and principled mathematical pipeline to recover the kernel trick for computing the covariance matrix, enhancing it to model more complex, non-l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,961
2301.00337	Separable Tendon-Driven Robotic Manipulator with a Long, Flexible, Passive Proximal Section	This work tackles practical issues which arise when using a tendon-driven robotic manipulator (TDRM) with a long, flexible, passive proximal section in medical applications. Tendon-driven devices are preferred in medicine for their improved outcomes via minimally invasive procedures, but TDRMs come with unique challeng...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	338,871
1802.09298	Beyond Pixels: Leveraging Geometry and Shape Cues for Online Multi-Object Tracking	This paper introduces geometry and object shape and pose costs for multi-object tracking in urban driving scenarios. Using images from a monocular camera alone, we devise pairwise costs for object tracks, based on several 3D cues such as object pose, shape, and motion. The proposed costs are agnostic to the data associ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	91,303
2408.03957	GNN-Based Joint Channel and Power Allocation in Heterogeneous Wireless Networks	The optimal allocation of channels and power resources plays a crucial role in ensuring minimal interference, maximal data rates, and efficient energy utilisation. As a successful approach for tackling resource management problems in wireless networks, Graph Neural Networks (GNNs) have attracted a lot of attention. Thi...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	479,211
2102.07951	ResNet-LDDMM: Advancing the LDDMM Framework using Deep Residual Networks	In deformable registration, the geometric framework - large deformation diffeomorphic metric mapping or LDDMM, in short - has inspired numerous techniques for comparing, deforming, averaging and analyzing shapes or images. Grounded in flows, which are akin to the equations of motion used in fluid dynamics, LDDMM algori...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	220,285
2211.11629	PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework	Visual object tracking is essential to intelligent robots. Most existing approaches have ignored the online latency that can cause severe performance degradation during real-world processing. Especially for unmanned aerial vehicles (UAVs), where robust tracking is more challenging and onboard computation is limited, th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,811
1805.07483	Tell Me Something New: A New Framework for Asynchronous Parallel Learning	We present a novel approach for parallel computation in the context of machine learning that we call "Tell Me Something New" (TMSN). This approach involves a set of independent workers that use broadcast to update each other when they observe "something new". TMSN does not require synchronization or a head node and is ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	97,840
2306.17797	HIDFlowNet: A Flow-Based Deep Network for Hyperspectral Image Denoising	Hyperspectral image (HSI) denoising is essentially ill-posed since a noisy HSI can be degraded from multiple clean HSIs. However, current deep learning-based approaches ignore this fact and restore the clean image with deterministic mapping (i.e., the network receives a noisy HSI and outputs a clean HSI). To alleviate ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	376,811
1712.05812	Occam's razor is insufficient to infer the preferences of irrational agents	Inverse reinforcement learning (IRL) attempts to infer human rewards or preferences from observed behavior. Since human planning systematically deviates from rationality, several approaches have been tried to account for specific human shortcomings. However, the general problem of inferring the reward function of an ag...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	86,774
1302.4986	Exploiting System Hierarchy to Compute Repair Plans in Probabilistic Model-based Diagnosis	The goal of model-based diagnosis is to isolate causes of anomalous system behavior and recommend inexpensive repair actions in response. In general, precomputing optimal repair policies is intractable. To date, investigators addressing this problem have explored approximations that either impose restrictions on the sy...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,260
1711.05195	A learning problem that is independent of the set theory ZFC axioms	We consider the following statistical estimation problem: given a family F of real valued functions over some domain X and an i.i.d. sample drawn from an unknown distribution P over X, find h in F such that the expectation of h w.r.t. P is probably approximately equal to the supremum over expectations on members of F. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	84,517
2410.23109	NASM: Neural Anisotropic Surface Meshing	This paper introduces a new learning-based method, NASM, for anisotropic surface meshing. Our key idea is to propose a graph neural network to embed an input mesh into a high-dimensional (high-d) Euclidean embedding space to preserve curvature-based anisotropic metric by using a dot product loss between high-d edge vec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	503,905
1811.06274	Effect of correlations on routing and modeling of Time Varying Communication Networks	Most of the real world networks are complex as well as evolving. Therefore, it is important to study the effect of network topology on the dynamics of traffic and congestion in the network. To account this problem, we have designed a time-varying network model where a new node will join a node in the existing network w...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	113,493
2210.09162	Table-To-Text generation and pre-training with TabT5	Encoder-only transformer models have been successfully applied to different table understanding tasks, as in TAPAS (Herzig et al., 2020). A major limitation of these architectures is that they are constrained to classification-like tasks such as cell selection or entailment detection. We present TABT5, an encoder-decod...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	324,439
1907.06704	PPO Dash: Improving Generalization in Deep Reinforcement Learning	Deep reinforcement learning is prone to overfitting, and traditional benchmarks such as Atari 2600 benchmark can exacerbate this problem. The Obstacle Tower Challenge addresses this by using randomized environments and separate seeds for training, validation, and test runs. This paper examines various improvements and ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	138,683
2404.05262	Robust Anthropomorphic Robotic Manipulation through Biomimetic Distributed Compliance	The impressive capabilities of humans to robustly perform manipulation relies on compliant interactions, enabled through the structure and materials spatially distributed in our hands. We propose by mimicking this distributed compliance in an anthropomorphic robotic hand, the open-loop manipulation robustness increases...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	445,016
cs/0602020	Inter-Block Permuted Turbo Codes	The structure and size of the interleaver used in a turbo code critically affect the distance spectrum and the covariance property of a component decoder's information input and soft output. This paper introduces a new class of interleavers, the inter-block permutation (IBP) interleavers, that can be build on any exist...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,255
2403.04656	Chain of Thought Explanation for Dialogue State Tracking	Dialogue state tracking (DST) aims to record user queries and goals during a conversational interaction achieved by maintaining a predefined set of slots and their corresponding values. Current approaches decide slot values opaquely, while humans usually adopt a more deliberate approach by collecting information from r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	435,680
1412.7049	Friendship Paradox and Attention Economics	The friendship paradox is revisited by considering both local and global averages of friends. How the economics of attention affects the recruitment of friends is examined. Statistical implications of varying individual attentions are investigated and it is argued that this is one reason why the mean of friends is high...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	38,757
2409.08253	The Design of Informative Take-Over Requests for Semi-Autonomous Cyber-Physical Systems: Combining Spoken Language and Visual Icons in a Drone-Controller Setting	The question of how cyber-physical systems should interact with human partners that can take over control or exert oversight is becoming more pressing, as these systems are deployed for an ever larger range of tasks. Drawing on the literatures on handing over control during semi-autonomous driving and human-robot inter...	true	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	487,830
1808.04043	Faster and More Robust Mesh-based Algorithms for Obstacle k-Nearest Neighbour	We are interested in the problem of finding $k$ nearest neighbours in the plane and in the presence of polygonal obstacles ($\textit{OkNN}$). Widely used algorithms for OkNN are based on incremental visibility graphs, which means they require costly and online visibility checking and have worst-case quadratic running t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	105,059
2305.16645	Summarizing Stream Data for Memory-Constrained Online Continual Learning	Replay-based methods have proved their effectiveness on online continual learning by rehearsing past samples from an auxiliary memory. With many efforts made on improving training schemes based on the memory, however, the information carried by each sample in the memory remains under-investigated. Under circumstances w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,189
2411.12188	Constant Rate Schedule: Constant-Rate Distributional Change for Efficient Training and Sampling in Diffusion Models	We propose a noise schedule that ensures a constant rate of change in the probability distribution of diffused data throughout the diffusion process. To obtain this schedule, we measure the probability-distributional change of diffused data by simulating the forward process and use it to determine the noise schedule be...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	509,330
2405.05524	Universal Adversarial Perturbations for Vision-Language Pre-trained Models	Vision-language pre-trained (VLP) models have been the foundation of numerous vision-language tasks. Given their prevalence, it becomes imperative to assess their adversarial robustness, especially when deploying them in security-crucial real-world applications. Traditionally, adversarial perturbations generated for th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	452,953
2010.03630	Revisiting Batch Normalization for Improving Corruption Robustness	The performance of DNNs trained on clean images has been shown to decrease when the test images have common corruptions. In this work, we interpret corruption robustness as a domain shift and propose to rectify batch normalization (BN) statistics for improving model robustness. This is motivated by perceiving the shift...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	199,459
2302.07137	Deep Non-Monotonic Reasoning for Visual Abstract Reasoning Tasks	While achieving unmatched performance on many well-defined tasks, deep learning models have also been used to solve visual abstract reasoning tasks, which are relatively less well-defined, and have been widely used to measure human intelligence. However, current deep models struggle to match human abilities to solve su...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	345,634
2207.06817	Pseudo-Labeling Based Practical Semi-Supervised Meta-Training for Few-Shot Learning	Most existing few-shot learning (FSL) methods require a large amount of labeled data in meta-training, which is a major limit. To reduce the requirement of labels, a semi-supervised meta-training (SSMT) setting has been proposed for FSL, which includes only a few labeled samples and numbers of unlabeled samples in base...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	308,003
1711.09219	Stacked Kernel Network	Kernel methods are powerful tools to capture nonlinear patterns behind data. They implicitly learn high (even infinite) dimensional nonlinear features in the Reproducing Kernel Hilbert Space (RKHS) while making the computation tractable by leveraging the kernel trick. Classic kernel methods learn a single layer of nonl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	85,354
cs/9803101	Synthesizing Customized Planners from Specifications	Existing plan synthesis approaches in artificial intelligence fall into two categories -- domain independent and domain dependent. The domain independent approaches are applicable across a variety of domains, but may not be very efficient in any one given domain. The domain dependent approaches need to be (re)designed ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	540,376
2203.02123	Detecting Offensive Language on Social Networks: An End-to-end Detection Method based on Graph Attention Networks	The pervasiveness of offensive language on the social network has caused adverse effects on society, such as abusive behavior online. It is urgent to detect offensive language and curb its spread. Existing research shows that methods with community structure features effectively improve the performance of offensive lan...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	283,647
2305.07826	Frequency-aware Dimension Selection for Static Word Embedding by Mixed Product Distance	Static word embedding is still useful, particularly for context-unavailable tasks, because in the case of no context available, pre-trained language models often perform worse than static word embeddings. Although dimension is a key factor determining the quality of static word embeddings, automatic dimension selection...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	364,042
2401.17880	Graph Attention-based Reinforcement Learning for Trajectory Design and Resource Assignment in Multi-UAV Assisted Communication	In the multiple unmanned aerial vehicle (UAV)- assisted downlink communication, it is challenging for UAV base stations (UAV BSs) to realize trajectory design and resource assignment in unknown environments. The cooperation and competition between UAV BSs in the communication network leads to a Markov game problem. Mul...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	false	false	false	425,363
2308.09779	EAVL: Explicitly Align Vision and Language for Referring Image Segmentation	Referring image segmentation (RIS) aims to segment an object mentioned in natural language from an image. The main challenge is text-to-pixel fine-grained correlation. In the previous methods, the final results are obtained by convolutions with a fixed kernel, which follows a similar pattern as traditional image segmen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	386,425
2401.16402	A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect	Visual Anomaly Detection (VAD) endeavors to pinpoint deviations from the concept of normality in visual data, widely applied across diverse domains, e.g., industrial defect inspection, and medical lesion detection. This survey comprehensively examines recent advancements in VAD by identifying three primary challenges: ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	424,805
1803.00479	Tracked Instance Search	In this work we propose tracking as a generic addition to the instance search task. From video data perspective, much information that can be used is not taken into account in the traditional instance search approach. This work aims to provide insights on exploiting such existing information by means of tracking and th...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	91,689
1802.02427	MRI Tumor Segmentation with Densely Connected 3D CNN	Glioma is one of the most common and aggressive types of primary brain tumors. The accurate segmentation of subcortical brain structures is crucial to the study of gliomas in that it helps the monitoring of the progression of gliomas and aids the evaluation of treatment outcomes. However, the large amount of required h...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,770
2207.05315	CANF-VC: Conditional Augmented Normalizing Flows for Video Compression	This paper presents an end-to-end learning-based video compression system, termed CANF-VC, based on conditional augmented normalizing flows (CANF). Most learned video compression systems adopt the same hybrid-based coding architecture as the traditional codecs. Recent research on conditional coding has shown the sub-op...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	307,496
2205.10577	Non-Autoregressive Neural Machine Translation: A Call for Clarity	Non-autoregressive approaches aim to improve the inference speed of translation models by only requiring a single forward pass to generate the output sequence instead of iteratively producing each predicted token. Consequently, their translation quality still tends to be inferior to their autoregressive counterparts du...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	297,766
1105.0060	Signal Processing in Large Systems: a New Paradigm	For a long time, detection and parameter estimation methods for signal processing have relied on asymptotic statistics as the number $n$ of observations of a population grows large comparatively to the population size $N$, i.e. $n/N\to \infty$. Modern technological and societal advances now demand the study of sometime...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,187
2004.14288	Actor-Critic Reinforcement Learning for Control with Stability Guarantee	Reinforcement Learning (RL) and its integration with deep learning have achieved impressive performance in various robotic control tasks, ranging from motion planning and navigation to end-to-end visual manipulation. However, stability is not guaranteed in model-free RL by solely using data. From a control-theoretic pe...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	174,833
1501.02905	Sampling Online Social Networks via Heterogeneous Statistics	Most sampling techniques for online social networks (OSNs) are based on a particular sampling method on a single graph, which is referred to as a statistics. However, various realizing methods on different graphs could possibly be used in the same OSN, and they may lead to different sampling efficiencies, i.e., asympto...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	39,226
2009.06423	A Task Allocation Approach for Human-Robot Collaboration in Product Defects Inspection Scenarios	The presence and coexistence of human operators and collaborative robots in shop-floor environments raises the need for assigning tasks to either operators or robots, or both. Depending on task characteristics, operator capabilities and the involved robot functionalities, it is of the utmost importance to design strate...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	195,643
1405.5902	Impossibility of Gathering, a Certification	Recent advances in Distributed Computing highlight models and algorithms for autonomous swarms of mobile robots that self-organise and cooperate to solve global objectives. The overwhelming majority of works so far considers handmade algorithms and proofs of correctness. This paper builds upon a previously proposed for...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	33,315
2401.16871	Node Flux-Linkage Synchronizing Control of Power Systems with 100% Wind Power Generation Based on Capacitor Voltage Balancing Scheme	This paper proposes a node flux-linkage synchronizing control method (NFSCM) for power systems with 100% wind power generation based on a capacitor voltage balancing scheme (CVBS). Different from the conventional grid-forming controllers, NFSCM is designed to regulate inverters as virtual flux-linkage sources. Auto-syn...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	425,018
2102.00655	Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning	Data heterogeneity has been identified as one of the key features in federated learning but often overlooked in the lens of robustness to adversarial attacks. This paper focuses on characterizing and understanding its impact on backdooring attacks in federated learning through comprehensive experiments using synthetic ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	217,865
2303.09987	Breast Cancer Histopathology Image based Gene Expression Prediction using Spatial Transcriptomics data and Deep Learning	Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy. Spatial transcriptomics technologies may address these challenges, as they provide a wealth of information about gene expression at the cell level, but they are expensive, hindering their use in large-scale clinical on...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,264
2311.09459	On Convex Optimal Value Functions For POSGs	Multi-agent planning and reinforcement learning can be challenging when agents cannot see the state of the world or communicate with each other due to communication costs, latency, or noise. Partially Observable Stochastic Games (POSGs) provide a mathematical framework for modelling such scenarios. This paper aims to i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	408,137
1608.03630	Distributed-memory large deformation diffeomorphic 3D image registration	We present a parallel distributed-memory algorithm for large deformation diffeomorphic registration of volumetric images that produces large isochoric deformations (locally volume preserving). Image registration is a key technology in medical image analysis. Our algorithm uses a partial differential equation constraine...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	59,694
1912.03444	PidginUNMT: Unsupervised Neural Machine Translation from West African Pidgin to English	Over 800 languages are spoken across West Africa. Despite the obvious diversity among people who speak these languages, one language significantly unifies them all - West African Pidgin English. There are at least 80 million speakers of West African Pidgin English. However, there is no known natural language processing...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	156,592
2106.02795	Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding	Attentional mechanisms are order-invariant. Positional encoding is a crucial component to allow attention-based deep model architectures such as Transformer to address sequences or images where the position of information matters. In this paper, we propose a novel positional encoding method based on learnable Fourier f...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	239,029
1905.10389	Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound	Exploration in reinforcement learning (RL) suffers from the curse of dimensionality when the state-action space is large. A common practice is to parameterize the high-dimensional value and policy functions using given features. However existing methods either have no theoretical guarantee or suffer a regret that is ex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,038
1704.03615	Predictive-Corrective Networks for Action Detection	While deep feature learning has revolutionized techniques for static-image understanding, the same does not quite hold for video processing. Architectures and optimization techniques used for video are largely based off those for static images, potentially underutilizing rich video information. In this work, we rethink...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,665
1105.6060	Alignment of Microtubule Imagery	This work discusses preliminary work aimed at simulating and visualizing the growth process of a tiny structure inside the cell---the microtubule. Difficulty of recording the process lies in the fact that the tissue preparation method for electronic microscopes is highly destructive to live cells. Here in this paper, o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	10,588
1206.5245	A new parameter Learning Method for Bayesian Networks with Qualitative Influences	We propose a new method for parameter learning in Bayesian networks with qualitative influences. This method extends our previous work from networks of binary variables to networks of discrete variables with ordered values. The specified qualitative influences correspond to certain order restrictions on the parameters ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	16,785
2305.07895	OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models	Large models have recently played a dominant role in natural language processing and multimodal vision-language learning. However, their effectiveness in text-related visual tasks remains relatively unexplored. In this paper, we conducted a comprehensive evaluation of Large Multimodal Models, such as GPT4V and Gemini, ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	364,077

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