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
2010.03370	A study on using image based machine learning methods to develop the surrogate models of stamp forming simulations	In the design optimization of metal forming, it is increasingly significant to use surrogate models to analyse the finite element analysis (FEA) simulations. However, traditional surrogate models using scalar based machine learning methods (SBMLMs) fall in short of accuracy and generalizability. This is because SBMLMs ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	199,385
2012.07403	One-Shot Learning with Triplet Loss for Vegetation Classification Tasks	Triplet loss function is one of the options that can significantly improve the accuracy of the One-shot Learning tasks. Starting from 2015, many projects use Siamese networks and this kind of loss for face recognition and object classification. In our research, we focused on two tasks related to vegetation. The first o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	211,444
2104.02330	Visual Alignment Constraint for Continuous Sign Language Recognition	Vision-based Continuous Sign Language Recognition (CSLR) aims to recognize unsegmented signs from image streams. Overfitting is one of the most critical problems in CSLR training, and previous works show that the iterative training scheme can partially solve this problem while also costing more training time. In this s...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	228,689
1708.03209	Tosca: Operationalizing Commitments Over Information Protocols	The notion of commitment is widely studied as a high-level abstraction for modeling multiagent interaction. An important challenge is supporting flexible decentralized enactments of commitment specifications. In this paper, we combine recent advances on specifying commitments and information protocols. Specifically, we...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	78,729
2005.03642	On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation	The standard training algorithm in neural machine translation (NMT) suffers from exposure bias, and alternative algorithms have been proposed to mitigate this. However, the practical impact of exposure bias is under debate. In this paper, we link exposure bias to another well-known problem in NMT, namely the tendency t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	176,215
1908.06449	RefNet: A Reference-aware Network for Background Based Conversation	Existing conversational systems tend to generate generic responses. Recently, Background Based Conversations (BBCs) have been introduced to address this issue. Here, the generated responses are grounded in some background information. The proposed methods for BBCs are able to generate more informative responses, they e...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	142,021
2403.19647	Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models	We introduce methods for discovering and applying sparse feature circuits. These are causally implicated subnetworks of human-interpretable features for explaining language model behaviors. Circuits identified in prior work consist of polysemantic and difficult-to-interpret units like attention heads or neurons, render...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	442,430
2501.00747	DIVE: Diversified Iterative Self-Improvement	Recent advances in large language models (LLMs) have demonstrated the effectiveness of Iterative Self-Improvement (ISI) techniques. However, continuous training on self-generated data leads to reduced output diversity, a limitation particularly critical in reasoning tasks where diverse solution paths are essential. We ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	521,784
2502.12518	New Constant Dimension Codes From the Inserting Mixed Dimension Construction and Multilevel Construction	Constant dimension codes (CDCs) are essential for error correction in random network coding. A fundamental problem of CDCs is to determine their maximal possible size for given parameters. Inserting construction and multilevel construction are two effective techniques for constructing CDCs. We first provide a sufficien...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	534,911
2212.06965	Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks	Physics-Informed Neural Networks (PINNs) are gaining popularity as a method for solving differential equations. While being more feasible in some contexts than the classical numerical techniques, PINNs still lack credibility. A remedy for that can be found in Uncertainty Quantification (UQ) which is just beginning to e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	336,256
1701.04005	Geographic Space as a Living Structure for Predicting Human Activities Using Big Data	Inspired by Christopher Alexanders conception of the world - space is not lifeless or neutral but a living structure involving far more small things than large ones a topological representation has been previously developed to characterize the living structure or the wholeness of geographic space. This paper further de...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	66,793
2408.05614	ICGMM: CXL-enabled Memory Expansion with Intelligent Caching Using Gaussian Mixture Model	Compute Express Link (CXL) emerges as a solution for wide gap between computational speed and data communication rates among host and multiple devices. It fosters a unified and coherent memory space between host and CXL storage devices such as such as Solid-state drive (SSD) for memory expansion, with a corresponding D...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	479,861
1403.7335	Emotion Analysis Platform on Chinese Microblog	Weibo, as the largest social media service in China, has billions of messages generated every day. The huge number of messages contain rich sentimental information. In order to analyze the emotional changes in accordance with time and space, this paper presents an Emotion Analysis Platform (EAP), which explores the emo...	false	false	false	false	false	true	false	false	true	false	false	false	false	true	false	false	false	false	31,894
2306.05677	A fast reduced order method for linear parabolic inverse source problems	In this paper, we propose a novel, computationally efficient reduced order method to solve linear parabolic inverse source problems. Our approach provides accurate numerical solutions without relying on specific training data. The forward solution is constructed using a Krylov sequence, while the source term is recover...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	372,288
1907.04613	Neural Networks as Explicit Word-Based Rules	Filters of convolutional networks used in computer vision are often visualized as image patches that maximize the response of the filter. We use the same approach to interpret weight matrices in simple architectures for natural language processing tasks. We interpret a convolutional network for sentiment classification...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	138,149
0803.0954	Selective association rule generation	Mining association rules is a popular and well researched method for discovering interesting relations between variables in large databases. A practical problem is that at medium to low support values often a large number of frequent itemsets and an even larger number of association rules are found in a database. A wid...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	1,398
2205.02220	Chasing Streams with Existential Rules	We study reasoning with existential rules to perform query answering over streams of data. On static databases, this problem has been widely studied, but its extension to rapidly changing data has not yet been considered. To bridge this gap, we extend LARS, a well-known framework for rule-based stream reasoning, to sup...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	294,876
2110.01778	Version Reconciliation for Collaborative Databases	We propose MindPalace, a prototype of a versioned database for efficient collaborative data management. MindPalace supports offline collaboration, where users work independently without real-time correspondence. The core of MindPalace is a critical step of offline collaboration: reconciling divergent branches made by s...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	258,889
1803.04249	SO-Net: Self-Organizing Network for Point Cloud Analysis	This paper presents SO-Net, a permutation invariant architecture for deep learning with orderless point clouds. The SO-Net models the spatial distribution of point cloud by building a Self-Organizing Map (SOM). Based on the SOM, SO-Net performs hierarchical feature extraction on individual points and SOM nodes, and ult...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,417
2107.11433	A general sample complexity analysis of vanilla policy gradient	We adapt recent tools developed for the analysis of Stochastic Gradient Descent (SGD) in non-convex optimization to obtain convergence and sample complexity guarantees for the vanilla policy gradient (PG). Our only assumptions are that the expected return is smooth w.r.t. the policy parameters, that its $H$-step trunca...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	247,585
2404.17875	Noisy Node Classification by Bi-level Optimization based Multi-teacher Distillation	Previous graph neural networks (GNNs) usually assume that the graph data is with clean labels for representation learning, but it is not true in real applications. In this paper, we propose a new multi-teacher distillation method based on bi-level optimization (namely BO-NNC), to conduct noisy node classification on th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	450,038
2404.11483	AgentKit: Structured LLM Reasoning with Dynamic Graphs	We propose an intuitive LLM prompting framework (AgentKit) for multifunctional agents. AgentKit offers a unified framework for explicitly constructing a complex "thought process" from simple natural language prompts. The basic building block in AgentKit is a node, containing a natural language prompt for a specific sub...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	447,515
2407.13170	Unified-EGformer: Exposure Guided Lightweight Transformer for Mixed-Exposure Image Enhancement	Despite recent strides made by AI in image processing, the issue of mixed exposure, pivotal in many real-world scenarios like surveillance and photography, remains inadequately addressed. Traditional image enhancement techniques and current transformer models are limited with primary focus on either overexposure or und...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	474,266
2402.09008	Multi-Query Focused Disaster Summarization via Instruction-Based Prompting	Automatic summarization of mass-emergency events plays a critical role in disaster management. The second edition of CrisisFACTS aims to advance disaster summarization based on multi-stream fact-finding with a focus on web sources such as Twitter, Reddit, Facebook, and Webnews. Here, participants are asked to develop s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	429,331
2010.13544	Meta-Learning for Neural Relation Classification with Distant Supervision	Distant supervision provides a means to create a large number of weakly labeled data at low cost for relation classification. However, the resulting labeled instances are very noisy, containing data with wrong labels. Many approaches have been proposed to select a subset of reliable instances for neural model training,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	203,170
2309.10238	PolicyGPT: Automated Analysis of Privacy Policies with Large Language Models	Privacy policies serve as the primary conduit through which online service providers inform users about their data collection and usage procedures. However, in a bid to be comprehensive and mitigate legal risks, these policy documents are often quite verbose. In practical use, users tend to click the Agree button direc...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	392,920
1911.11314	Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification	Many real-world applications, such as city-scale traffic monitoring and control, requires large-scale re-identification. However, previous ReID methods often failed to address two limitations in existing ReID benchmarks, i.e., low spatiotemporal coverage and sample imbalance. Notwithstanding their demonstrated success ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	155,079
2111.10617	Extracting Deformation-Aware Local Features by Learning to Deform	Despite the advances in extracting local features achieved by handcrafted and learning-based descriptors, they are still limited by the lack of invariance to non-rigid transformations. In this paper, we present a new approach to compute features from still images that are robust to non-rigid deformations to circumvent ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	267,385
1410.3015	Heuristic Monte Carlo Method Applied to Cooperative Motion Algorithm for Binary Lattice Fluid	The Cooperative Motion Algorithm is an efficient lattice method to simulate dense polymer systems and is often used with two different criteria to generate a Markov chain in the configuration space. While the first method is the well-established Metropolis algorithm, the other one is an heuristic algorithm which needs ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	36,674
2403.07951	SAMDA: Leveraging SAM on Few-Shot Domain Adaptation for Electronic Microscopy Segmentation	It has been shown that traditional deep learning methods for electronic microscopy segmentation usually suffer from low transferability when samples and annotations are limited, while large-scale vision foundation models are more robust when transferring between different domains but facing sub-optimal improvement unde...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	437,113
2005.14381	Bayesian network structure learning with causal effects in the presence of latent variables	Latent variables may lead to spurious relationships that can be misinterpreted as causal relationships. In Bayesian Networks (BNs), this challenge is known as learning under causal insufficiency. Structure learning algorithms that assume causal insufficiency tend to reconstruct the ancestral graph of a BN, where bi-dir...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	179,250
2308.15003	Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints	Unlike cloud-based deep learning models that are often large and uniform, edge-deployed models usually demand customization for domain-specific tasks and resource-limited environments. Such customization processes can be costly and time-consuming due to the diversity of edge scenarios and the training load for each sce...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	388,527
1307.1890	Solution of Rectangular Fuzzy Games by Principle of Dominance Using LR-type Trapezoidal Fuzzy Numbers	Fuzzy Set Theory has been applied in many fields such as Operations Research, Control Theory, and Management Sciences etc. In particular, an application of this theory in Managerial Decision Making Problems has a remarkable significance. In this Paper, we consider a solution of Rectangular Fuzzy game with pay-off as im...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	25,670
2408.02767	4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models	Constraining a numerical weather prediction (NWP) model with observations via 4D variational (4D-Var) data assimilation is often difficult to implement in practice due to the need to develop and maintain a software-based tangent linear model and adjoint model. One of the most common 4D-Var algorithms uses an incrementa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	478,754
2102.07851	Dynamics and Control of a Flapping Wing UAV with Abdomen Undulation Inspired by Monarch Butterfly	This paper presents a dynamic model and a control system for a flapping-wing unmanned aerial vehicle. Inspired by flight characteristics captured from live Monarch butterflies, a new dynamic model is presented to account the effects of low-frequency flapping and abdomen undulation. We developed it according to Lagrangi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	220,251
1810.12401	Application of Clustering Methods to Anomaly Detection in Fibrous Media	The paper considers the problem of anomaly detection in 3D images of fibre materials. The spatial Stochastic Expectation Maximisation algorithm and Adaptive Weights Clustering are applied to solve this problem. The initial 3D grey scale image was divided into small cubes subject to clustering. For each cube clustering ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	111,752
1306.2735	On the Impact of Relay-side Channel State Information on Opportunistic Relaying	In this paper, outage performance of network topology-aware distributed opportunistic relay selection strategies is studied with focus on the impact of different levels of channel state information (CSI) available at relays. Specifically, two scenarios with (a) exact instantaneous and (b) only statistical CSI are compa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	25,153
2010.10935	An Eager Splitting Strategy for Online Decision Trees	Decision tree ensembles are widely used in practice. In this work, we study in ensemble settings the effectiveness of replacing the split strategy for the state-of-the-art online tree learner, Hoeffding Tree, with a rigorous but more eager splitting strategy that we had previously published as Hoeffding AnyTime Tree. H...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,061
2212.01816	Joint graph learning from Gaussian observations in the presence of hidden nodes	Graph learning problems are typically approached by focusing on learning the topology of a single graph when signals from all nodes are available. However, many contemporary setups involve multiple related networks and, moreover, it is often the case that only a subset of nodes is observed while the rest remain hidden....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	334,586
1901.08456	Semantic Classification of Tabular Datasets via Character-Level Convolutional Neural Networks	A character-level convolutional neural network (CNN) motivated by applications in "automated machine learning" (AutoML) is proposed to semantically classify columns in tabular data. Simulated data containing a set of base classes is first used to learn an initial set of weights. Hand-labeled data from the CKAN reposito...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	119,479
2304.11215	ChatGPT: More than a Weapon of Mass Deception, Ethical challenges and responses from the Human-Centered Artificial Intelligence (HCAI) perspective	This article explores the ethical problems arising from the use of ChatGPT as a kind of generative AI and suggests responses based on the Human-Centered Artificial Intelligence (HCAI) framework. The HCAI framework is appropriate because it understands technology above all as a tool to empower, augment, and enhance huma...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	359,721
2103.03939	NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification	Malicious software (malware) poses an increasing threat to the security of communication systems as the number of interconnected mobile devices increases exponentially. While some existing malware detection and classification approaches successfully leverage network traffic data, they treat network flows between pairs ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	223,463
1611.06474	Nazr-CNN: Fine-Grained Classification of UAV Imagery for Damage Assessment	We propose Nazr-CNN1, a deep learning pipeline for object detection and fine-grained classification in images acquired from Unmanned Aerial Vehicles (UAVs) for damage assessment and monitoring. Nazr-CNN consists of two components. The function of the first component is to localize objects (e.g. houses or infrastructure...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	64,198
2204.11447	Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models	A retrieval model should not only interpolate the training data but also extrapolate well to the queries that are different from the training data. While neural retrieval models have demonstrated impressive performance on ad-hoc search benchmarks, we still know little about how they perform in terms of interpolation an...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	293,155
1405.4945	Distributed Resource Allocation in Device-to-Device Enhanced Cellular Networks	Cellular network performance can significantly benefit from direct device-to-device (D2D) communication, but interference from cochannel D2D communication limits the performance gain. In hybrid networks consisting of D2D and cellular links, finding the optimal interference management is challenging. In particular, we s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	33,222
2212.00724	SWL-Adapt: An Unsupervised Domain Adaptation Model with Sample Weight Learning for Cross-User Wearable Human Activity Recognition	In practice, Wearable Human Activity Recognition (WHAR) models usually face performance degradation on the new user due to user variance. Unsupervised domain adaptation (UDA) becomes the natural solution to cross-user WHAR under annotation scarcity. Existing UDA models usually align samples across domains without diffe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	334,162
2407.21794	Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey	Detecting out-of-distribution (OOD) samples is crucial for ensuring the safety of machine learning systems and has shaped the field of OOD detection. Meanwhile, several other problems are closely related to OOD detection, including anomaly detection (AD), novelty detection (ND), open set recognition (OSR), and outlier ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	477,675
1901.00959	QFlow: A Learning Approach to High QoE Video Streaming at the Wireless Edge	The predominant use of wireless access networks is for media streaming applications, which are only gaining popularity as ever more devices become available for this purpose. However, current access networks treat all packets identically, and lack the agility to determine which clients are most in need of service at a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	117,887
2102.07838	A Comparison of Deep-Learning Methods for Analysing and Predicting Business Processes	Deep-learning models such as Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) have been successfully used for process-mining tasks. They have achieved better performance for different predictive tasks than traditional approaches. We extend the existing body of research by testing four different var...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	220,243
cs/0604064	Quantum Fuzzy Sets: Blending Fuzzy Set Theory and Quantum Computation	In this article we investigate a way in which quantum computing can be used to extend the class of fuzzy sets. The core idea is to see states of a quantum register as characteristic functions of quantum fuzzy subsets of a given set. As the real unit interval is embedded in the Bloch sphere, every fuzzy set is automatic...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	539,391
2105.05126	Continuous User Authentication using IoT Wearable Sensors	Over the past several years, the electrocardiogram (ECG) has been investigated for its uniqueness and potential to discriminate between individuals. This paper discusses how this discriminatory information can help in continuous user authentication by a wearable chest strap which uses dry electrodes to obtain a single ...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	234,725
2301.02647	Universal adaptive optics for microscopy through embedded neural network control	The resolution and contrast of microscope imaging is often affected by aberrations introduced by imperfect optical systems and inhomogeneous refractive structures in specimens. Adaptive optics (AO) compensates these aberrations and restores diffraction limited performance. A wide range of AO solutions have been introdu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	339,554
2412.14462	Affordance-Aware Object Insertion via Mask-Aware Dual Diffusion	As a common image editing operation, image composition involves integrating foreground objects into background scenes. In this paper, we expand the application of the concept of Affordance from human-centered image composition tasks to a more general object-scene composition framework, addressing the complex interplay ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	518,707
2201.08992	Enhancing and Dissecting Crowd Counting By Synthetic Data	In this article, we propose a simulated crowd counting dataset CrowdX, which has a large scale, accurate labeling, parameterized realization, and high fidelity. The experimental results of using this dataset as data enhancement show that the performance of the proposed streamlined and efficient benchmark network ESA-Ne...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	276,512
2105.08582	Vision Transformer for Fast and Efficient Scene Text Recognition	Scene text recognition (STR) enables computers to read text in natural scenes such as object labels, road signs and instructions. STR helps machines perform informed decisions such as what object to pick, which direction to go, and what is the next step of action. In the body of work on STR, the focus has always been o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	235,800
2202.03844	EvoPruneDeepTL: An Evolutionary Pruning Model for Transfer Learning based Deep Neural Networks	In recent years, Deep Learning models have shown a great performance in complex optimization problems. They generally require large training datasets, which is a limitation in most practical cases. Transfer learning allows importing the first layers of a pre-trained architecture and connecting them to fully-connected l...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	279,361
1304.7638	Lobby index as a network centrality measure	We study the lobby index (l-index for short) as a local node centrality measure for complex networks. The l-inde is compared with degree (a local measure), betweenness and Eigenvector centralities (two global measures) in the case of biological network (Yeast interaction protein-protein network) and a linguistic networ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	24,278
2312.00289	Robust Generalized Proportional Integral Control for Trajectory Tracking of Soft Actuators in a Pediatric Wearable Assistive Device	Soft robotics hold promise in the development of safe yet powered assistive wearable devices for infants. Key to this is the development of closed-loop controllers that can help regulate pneumatic pressure in the device's actuators in an effort to induce controlled motion at the user's limbs and be able to track differ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	411,987
2304.01553	Heating and dynamics of the Solar atmosphere	The solar atmosphere shows anomalous variation in temperature, starting from the 5500 K photosphere to the million-degree Kelvin corona. The corona itself expands into the interstellar medium as the free streaming solar wind, which modulates and impacts the near-Earth space weather. The precise source regions of differ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	356,126
2409.12031	PhysMamba: Efficient Remote Physiological Measurement with SlowFast Temporal Difference Mamba	Facial-video based Remote photoplethysmography (rPPG) aims at measuring physiological signals and monitoring heart activity without any contact, showing significant potential in various applications. Previous deep learning based rPPG measurement are primarily based on CNNs and Transformers. However, the limited recepti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	489,408
2210.14226	FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks	Personalized federated learning is aimed at allowing numerous clients to train personalized models while participating in collaborative training in a communication-efficient manner without exchanging private data. However, many personalized federated learning algorithms assume that clients have the same neural network ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	326,466
2007.05785	Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks	Spiking Neural Networks (SNNs) have attracted enormous research interest due to temporal information processing capability, low power consumption, and high biological plausibility. However, the formulation of efficient and high-performance learning algorithms for SNNs is still challenging. Most existing learning method...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	186,785
1605.05365	Dynamic Frame skip Deep Q Network	Deep Reinforcement Learning methods have achieved state of the art performance in learning control policies for the games in the Atari 2600 domain. One of the important parameters in the Arcade Learning Environment (ALE) is the frame skip rate. It decides the granularity at which agents can control game play. A frame s...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	55,992
2305.16092	AI Techniques in the Microservices Life-Cycle: A Systematic Mapping Study	The use of AI in microservices (MSs) is an emerging field as indicated by a substantial number of surveys. However these surveys focus on a specific problem using specific AI techniques, therefore not fully capturing the growth of research and the rise and disappearance of trends. In our systematic mapping study, we ta...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	367,909
1606.08651	Two-way relay beamforming optimization for full-duplex SWIPT systems	In this paper, we investigate the problem of two-way relay beamforming optimization to maximize the achievable sum-rate of a simultaneous wireless information and power transfer (SWIPT) system with a full-duplex (FD) multiple-input multiple-output (MIMO) amplify-and-forward (AF) relay. In particular, we address the opt...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	57,892
1805.09799	Prediction of Autism Treatment Response from Baseline fMRI using Random Forests and Tree Bagging	Treating children with autism spectrum disorders (ASD) with behavioral interventions, such as Pivotal Response Treatment (PRT), has shown promise in recent studies. However, deciding which therapy is best for a given patient is largely by trial and error, and choosing an ineffective intervention results in loss of valu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	98,502
2206.12571	CV 3315 Is All You Need : Semantic Segmentation Competition	This competition focus on Urban-Sense Segmentation based on the vehicle camera view. Class highly unbalanced Urban-Sense images dataset challenge the existing solutions and further studies. Deep Conventional neural network-based semantic segmentation methods such as encoder-decoder architecture and multi-scale and pyra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	304,653
2412.11318	Generics are puzzling. Can language models find the missing piece?	Generic sentences express generalisations about the world without explicit quantification. Although generics are central to everyday communication, building a precise semantic framework has proven difficult, in part because speakers use generics to generalise properties with widely different statistical prevalence. In ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	517,355
1309.1524	Guided Self-Organization of Input-Driven Recurrent Neural Networks	We review attempts that have been made towards understanding the computational properties and mechanisms of input-driven dynamical systems like RNNs, and reservoir computing networks in particular. We provide details on methods that have been developed to give quantitative answers to the questions above. Following this...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	26,870
2109.11320	Nine Challenges in Artificial Intelligence and Wireless Communications for 6G	In recent years, techniques developed in artificial intelligence (AI), especially those in machine learning (ML), have been successfully applied in various areas, leading to a widespread belief that AI will collectively play an important role in future wireless communications. To accomplish the aspiration, we present n...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	256,906
2002.03069	Adaptive Approximate Policy Iteration	Model-free reinforcement learning algorithms combined with value function approximation have recently achieved impressive performance in a variety of application domains. However, the theoretical understanding of such algorithms is limited, and existing results are largely focused on episodic or discounted Markov decis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	163,124
1608.04079	Twisted Centralizer Codes	Given an $n\times n$ matrix $A$ over a field $F$ and a scalar $a\in F$, we consider the linear codes $C(A,a):=\{B\in F^{n\times n}\mid \,AB=aBA\}$ of length $n^2$. We call $C(A,a)$ a twisted centralizer code. We investigate properties of these codes including their dimensions, minimum distances, parity-check matrices, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	59,774
2212.05051	VindLU: A Recipe for Effective Video-and-Language Pretraining	The last several years have witnessed remarkable progress in video-and-language (VidL) understanding. However, most modern VidL approaches use complex and specialized model architectures and sophisticated pretraining protocols, making the reproducibility, analysis and comparisons of these frameworks difficult. Hence, i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	335,662
1707.05390	TensorLog: Deep Learning Meets Probabilistic DBs	We present an implementation of a probabilistic first-order logic called TensorLog, in which classes of logical queries are compiled into differentiable functions in a neural-network infrastructure such as Tensorflow or Theano. This leads to a close integration of probabilistic logical reasoning with deep-learning infr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	77,215
1502.02733	Bandwidth Efficient and Rate-Matched Low-Density Parity-Check Coded Modulation	A new coded modulation scheme is proposed. At the transmitter, the concatenation of a distribution matcher and a systematic binary encoder performs probabilistic signal shaping and channel coding. At the receiver, the output of a bitwise demapper is fed to a binary decoder. No iterative demapping is performed. Rate ada...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	40,075
2206.14421	Cyclical Kernel Adaptive Metropolis	We propose cKAM, cyclical Kernel Adaptive Metropolis, which incorporates a cyclical stepsize scheme to allow control for exploration and sampling. We show that on a crafted bimodal distribution, existing Adaptive Metropolis type algorithms would fail to converge to the true posterior distribution. We point out that thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,282
1308.5546	Sparse and Non-Negative BSS for Noisy Data	Non-negative blind source separation (BSS) has raised interest in various fields of research, as testified by the wide literature on the topic of non-negative matrix factorization (NMF). In this context, it is fundamental that the sources to be estimated present some diversity in order to be efficiently retrieved. Spar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	26,647
2012.08588	FoggySight: A Scheme for Facial Lookup Privacy	Advances in deep learning algorithms have enabled better-than-human performance on face recognition tasks. In parallel, private companies have been scraping social media and other public websites that tie photos to identities and have built up large databases of labeled face images. Searches in these databases are now ...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	211,800
1703.09068	Make Hawkes Processes Explainable by Decomposing Self-Triggering Kernels	Hawkes Processes capture self-excitation and mutual-excitation between events when the arrival of an event makes future events more likely to happen. Identification of such temporal covariance can reveal the underlying structure to better predict future events. In this paper, we present a new framework to decompose dis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	70,696
1211.4081	Network Equivalence in the Presence of an Eavesdropper	We consider networks of noisy degraded wiretap channels in the presence of an eavesdropper. For the case where the eavesdropper can wiretap at most one channel at a time, we show that the secrecy capacity region, for a broad class of channels and any given network topology and communication demands, is equivalent to th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,773
2104.05477	Stochastic Stability of Discrete-time Phase-coupled Oscillators over Uncertain and Random Networks	This article studies stochastic relative phase stability, i.e., stochastic phase-cohesiveness, of discrete-time phase-coupled oscillators. Stochastic phase-cohesiveness in two types of networks is studied. First, we consider oscillators coupled with 2{\pi}-periodic odd functions over underlying undirected graphs subjec...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	229,741
2311.14542	ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schr\"odinger Bridge	Diffusion models break down the challenging task of generating data from high-dimensional distributions into a series of easier denoising steps. Inspired by this paradigm, we propose a novel approach that extends the diffusion framework into modality space, decomposing the complex task of RGB image generation into simp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	410,146
1607.03296	Implicit Negative Feedback in Clinical Information Retrieval	In this paper, we reflect on ways to improve the quality of bio-medical information retrieval by drawing implicit negative feedback from negated information in noisy natural language search queries. We begin by studying the extent to which negations occur in clinical texts and quantify their detrimental effect on retri...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	58,490
2408.13248	Foundational Model for Electron Micrograph Analysis: Instruction-Tuning Small-Scale Language-and-Vision Assistant for Enterprise Adoption	Semiconductor imaging and analysis are critical yet understudied in deep learning, limiting our ability for precise control and optimization in semiconductor manufacturing. We introduce a small-scale multimodal framework for analyzing semiconductor electron microscopy images (MAEMI) through vision-language instruction ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	483,070
2411.16189	Enhancing Multi-Agent Consensus through Third-Party LLM Integration: Analyzing Uncertainty and Mitigating Hallucinations in Large Language Models	Large Language Models (LLMs) still face challenges when dealing with complex reasoning tasks, often resulting in hallucinations, which limit the practical application of LLMs. To alleviate this issue, this paper proposes a new method that integrates different LLMs to expand the knowledge boundary, reduce dependence on ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	true	false	false	false	510,938
2305.17369	Modularized Zero-shot VQA with Pre-trained Models	Large-scale pre-trained models (PTMs) show great zero-shot capabilities. In this paper, we study how to leverage them for zero-shot visual question answering (VQA). Our approach is motivated by a few observations. First, VQA questions often require multiple steps of reasoning, which is still a capability that most PTMs...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	368,552
2109.04762	Dual-State Capsule Networks for Text Classification	Text classification systems based on contextual embeddings are not viable options for many of the low resource languages. On the other hand, recently introduced capsule networks have shown performance in par with these text classification models. Thus, they could be considered as a viable alternative for text classific...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	254,532
2111.05457	Optimizing Number, Placement, and Backhaul Connectivity of Multi-UAV Networks	Multi-Unmanned Aerial Vehicle (UAV) Networks is a promising solution to providing wireless coverage to ground users in challenging rural areas (such as Internet of Things (IoT) devices in farmlands), where the traditional cellular networks are sparse or unavailable. A key challenge in such networks is the 3D placement ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	265,797
2305.15304	Towards Biomechanics-Aware Design of a Steerable Drilling Robot for Spinal Fixation Procedures with Flexible Pedicle Screws	Towards reducing the failure rate of spinal fixation surgical procedures in osteoporotic patients, we propose a unique biomechanically-aware framework for the design of a novel concentric tube steerable drilling robot (CT-SDR). The proposed framework leverages a patient-specific finite element (FE) biomechanics model d...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	367,559
2110.15252	Federated Learning with Heterogeneous Differential Privacy	Federated learning (FL) takes a first step towards privacy-preserving machine learning by training models while keeping client data local. Models trained using FL may still leak private client information through model updates during training. Differential privacy (DP) may be employed on model updates to provide privac...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	263,821
2412.00152	Dynamic Neural Curiosity Enhances Learning Flexibility for Autonomous Goal Discovery	The autonomous learning of new goals in robotics remains a complex issue to address. Here, we propose a model where curiosity influence learning flexibility. To do so, this paper proposes to root curiosity and attention together by taking inspiration from the Locus Coeruleus-Norepinephrine system along with various cog...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	512,537
2112.01317	Monolith to Microservices: Representing Application Software through Heterogeneous Graph Neural Network	Monolithic software encapsulates all functional capabilities into a single deployable unit. But managing it becomes harder as the demand for new functionalities grow. Microservice architecture is seen as an alternate as it advocates building an application through a set of loosely coupled small services wherein each se...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	269,440
1803.00210	A Hybrid Artificial-Noise and Secret-Key Scheme for Securing OFDM Transmissions in V2G Networks	We propose a new scheme to enhance the physical-layer security of wireless single-input single-output orthogonal-frequency division-multiplexing (OFDM) transmissions from an electric vehicle, Alice, to the aggregator, Bob, in the presence of an eavesdropper, Eve. To prevent information leakage to Eve, Alice exploits th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	91,626
2212.11702	Robust Meta-Representation Learning via Global Label Inference and Classification	Few-shot learning (FSL) is a central problem in meta-learning, where learners must efficiently learn from few labeled examples. Within FSL, feature pre-training has recently become an increasingly popular strategy to significantly improve generalization performance. However, the contribution of pre-training is often ov...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	337,856
2001.11279	Goal-directed graph construction using reinforcement learning	Graphs can be used to represent and reason about systems and a variety of metrics have been devised to quantify their global characteristics. However, little is currently known about how to construct a graph or improve an existing one given a target objective. In this work, we formulate the construction of a graph as a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	162,031
2105.04888	Hierarchical RNNs-Based Transformers MADDPG for Mixed Cooperative-Competitive Environments	At present, attention mechanism has been widely applied to the fields of deep learning models. Structural models that based on attention mechanism can not only record the relationships between features position, but also can measure the importance of different features based on their weights. By establishing dynamicall...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	234,652
2304.01611	Q2ATransformer: Improving Medical VQA via an Answer Querying Decoder	Medical Visual Question Answering (VQA) systems play a supporting role to understand clinic-relevant information carried by medical images. The questions to a medical image include two categories: close-end (such as Yes/No question) and open-end. To obtain answers, the majority of the existing medical VQA methods relie...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	356,148
2410.09097	Recent advancements in LLM Red-Teaming: Techniques, Defenses, and Ethical Considerations	Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, but their vulnerability to jailbreak attacks poses significant security risks. This survey paper presents a comprehensive analysis of recent advancements in attack strategies and defense mechanisms within the fi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	497,431
0707.2229	The Computation of All 4R Serial Spherical Wrists With an Isotropic Architecture	A spherical wrist of the serial type with n revolute (R) joints is said to be isotropic if it can attain a posture whereby the singular values of its Jacobian matrix are all equal to sqrt(n/3). What isotropy brings about is robustness to manufacturing, assembly, and measurement errors, thereby guaranteeing a maximum or...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	438
cs/0305041	Factorization of Language Models through Backing-Off Lattices	Factorization of statistical language models is the task that we resolve the most discriminative model into factored models and determine a new model by combining them so as to provide better estimate. Most of previous works mainly focus on factorizing models of sequential events, each of which allows only one factoriz...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,853

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