Split (1)

train · 203k rows

node_id int64 0 76.9k	label int64 0 39	text stringlengths 13 124k	neighbors listlengths 0 3.32k	mask stringclasses 4 values
30,778	26	Title: Cultural-aware Machine Learning based Analysis of COVID-19 Vaccine Hesitancy Abstract: Understanding the COVID-19 vaccine hesitancy, such as who and why, is very crucial since a large-scale vaccine adoption remains as one of the most efficient methods of controlling the pandemic. Such an understanding also provi...	[]	Validation
30,779	23	Title: IoT Data Processing for Smart City and Semantic Web Applications Abstract: The world has been experiencing rapid urbanization over the last few decades, putting a strain on existing city infrastructure such as waste management, water supply management, public transport and electricity consumption. We are also se...	[]	Train
30,780	6	Title: Screen-based 3D Subjective Experiment Software Abstract: Recently, widespread 3D graphics (e.g., point clouds and meshes) have drawn considerable efforts from academia and industry to assess their perceptual quality by conducting subjective experiments. However, lacking a handy software for 3D subjective experim...	[]	Train
30,781	24	Title: Analysis of different temporal graph neural network configurations on dynamic graphs Abstract: In recent years, there has been an increasing interest in the use of graph neural networks (GNNs) for analyzing dynamic graphs, which are graphs that evolve over time. However, there is still a lack of understanding of...	[ 7729 ]	Train
30,782	4	Title: Metadata-based Malware Detection on Android using Machine Learning Abstract: In the digitized world, smartphones and their apps play an important role. To name just a few examples, some apps offer possibilities for entertainment, others for online banking, and others offer support for two-factor authentication. ...	[]	Train
30,783	38	Title: Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review Abstract: nan	[ 10281 ]	Train
30,784	16	Title: Prototype-Based Embedding Network for Scene Graph Generation Abstract: Current Scene Graph Generation (SGG) methods explore contextual information to predict relationships among entity pairs. However, due to the diverse visual appearance of numerous possible subject-object combinations, there is a large intra-cl...	[ 43042, 22819, 44932, 37099, 12779, 37652 ]	Test
30,785	27	Title: UAV Tracking with Lidar as a Camera Sensor in GNSS-Denied Environments Abstract: Light detection and ranging (LiDAR) sensor has become one of the primary sensors in robotics and autonomous system for high-accuracy situational awareness. In recent years, multi-modal LiDAR systems emerged, and among them, LiDAR-as...	[ 39536, 23052 ]	Test
30,786	4	Title: Identifying Vulnerable Third-Party Libraries from Textual Descriptions of Vulnerabilities and Libraries Abstract: To address security vulnerabilities arising from third-party libraries, security researchers maintain databases monitoring and curating vulnerability reports, e.g., the National Vulnerability Databas...	[ 23998, 13990, 6111 ]	Validation
30,787	31	Title: Evaluating ChatGPT text-mining of clinical records for obesity monitoring Abstract: Background: Veterinary clinical narratives remain a largely untapped resource for addressing complex diseases. Here we compare the ability of a large language model (ChatGPT) and a previously developed regular expression (RegexT)...	[ 36547, 25071 ]	Validation
30,788	30	Title: CARE: Co-Attention Network for Joint Entity and Relation Extraction Abstract: Joint entity and relation extraction is the fundamental task of information extraction, consisting of two subtasks: named entity recognition and relation extraction. Most existing joint extraction methods suffer from issues of feature ...	[]	Train
30,789	23	Title: Verse: A Python library for reasoning about multi-agent hybrid system scenarios Abstract: We present the Verse library with the aim of making hybrid system verification more usable for multi-agent scenarios. In Verse, decision making agents move in a map and interact with each other through sensors. The decision...	[]	Train
30,790	16	Title: Mitigating Task Interference in Multi-Task Learning via Explicit Task Routing with Non-Learnable Primitives Abstract: Multi-task learning (MTL) seeks to learn a single model to accomplish multiple tasks by leveraging shared information among the tasks. Existing MTL models, however, have been known to suffer from...	[]	Train
30,791	24	Title: Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs Abstract: To bridge the gaps between topology-aware Graph Neural Networks (GNNs) and inference-efficient Multi-Layer Perceptron (MLPs), GLNN proposes to distill knowledge from a well-trained teacher GNN into a student MLP. Despite their great ...	[ 25316 ]	Train
30,792	29	Title: Benchmarking Performance of Deep Learning Model for Material Segmentation on Two HPC Systems Abstract: Performance Benchmarking of HPC systems is an ongoing effort that seeks to provide information that will allow for increased performance and improve the job schedulers that manage these systems. We develop a be...	[]	Train
30,793	24	Title: A Probabilistic Transformation of Distance-Based Outliers Abstract: The scores of distance-based outlier detection methods are difficult to interpret, and it is challenging to determine a suitable cut-off threshold between normal and outlier data points without additional context. We describe a generic transform...	[]	Test
30,794	30	Title: Measuring Normative and Descriptive Biases in Language Models Using Census Data Abstract: We investigate in this paper how distributions of occupations with respect to gender is reflected in pre-trained language models. Such distributions are not always aligned to normative ideals, nor do they necessarily reflec...	[]	Test
30,795	16	Title: Computational Approaches for Traditional Chinese Painting: From the "Six Principles of Painting" Perspective Abstract: Traditional Chinese Painting (TCP) is an invaluable cultural heritage resource and a unique visual art style. In recent years, increasing interest has been placed on digitalizing TCPs to preserv...	[ 33848, 33220 ]	Validation
30,796	23	Title: Insights into Software Development Approaches: Mining Q&A Repositories Abstract: Context: Software practitioners adopt approaches like DevOps, Scrum, and Waterfall for high-quality software development. However, limited research has been conducted on exploring software development approaches concerning practitio...	[]	Test
30,797	16	Title: Dense Transformer based Enhanced Coding Network for Unsupervised Metal Artifact Reduction Abstract: CT images corrupted by metal artifacts have serious negative effects on clinical diagnosis. Considering the difficulty of collecting paired data with ground truth in clinical settings, unsupervised methods for met...	[]	Validation
30,798	4	Title: Deepfake CAPTCHA: A Method for Preventing Fake Calls Abstract: Deep learning technology has made it possible to generate realistic content of specific individuals. These ‘deepfakes’ can now be generated in real-time which enables attackers to impersonate people over audio and video calls. Moreover, some methods ...	[ 3936 ]	Validation
30,799	10	Title: Service Reservation and Pricing for Green Metaverses: A Stackelberg Game Approach Abstract: Metaverse enables users to communicate, collaborate and socialize with each other through their digital avatars. Due to the spatio-temporal characteristics, co-located users are served well by performing their software co...	[]	Train
30,800	24	Title: Robustness Implies Fairness in Causal Algorithmic Recourse Abstract: Algorithmic recourse discloses the internal procedures of a black-box decision process where decisions have significant consequences by providing recommendations to empower beneficiaries to achieve a more favorable outcome. To ensure an effecti...	[ 12513, 23111 ]	Train
30,801	30	Title: Sensi-BERT: Towards Sensitivity Driven Fine-Tuning for Parameter-Efficient BERT Abstract: Large pre-trained language models have recently gained significant traction due to their improved performance on various down-stream tasks like text classification and question answering, requiring only few epochs of fine-t...	[ 43641, 9076 ]	Train
30,802	13	Title: SPENSER: Towards a NeuroEvolutionary Approach for Convolutional Spiking Neural Networks Abstract: Spiking Neural Networks (SNNs) have attracted recent interest due to their energy efficiency and biological plausibility. However, the performance of SNNs still lags behind traditional Artificial Neural Networks (AN...	[ 1400 ]	Train
30,803	5	Title: ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales Abstract: As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead...	[ 7113 ]	Test
30,804	9	Title: Descriptive complexity for neural networks via Boolean networks Abstract: We investigate the descriptive complexity of a class of neural networks with unrestricted topologies and piecewise polynomial activation functions. We consider the general scenario where the running time is unlimited and floating-point num...	[ 36450, 15653 ]	Validation
30,805	4	Title: A Diamond Model Analysis on Twitter's Biggest Hack Abstract: Cyberattacks have prominently increased over the past few years now, and have targeted actors from a wide variety of domains. Understanding the motivation, infrastructure, attack vectors, etc. behind such attacks is vital to proactively work against pr...	[]	Train
30,806	24	Title: Two Sides of Miscalibration: Identifying Over and Under-Confidence Prediction for Network Calibration Abstract: Proper confidence calibration of deep neural networks is essential for reliable predictions in safety-critical tasks. Miscalibration can lead to model over-confidence and/or under-confidence; i.e., the...	[]	Validation
30,807	24	Title: Improved Sample Complexity Bounds for Distributionally Robust Reinforcement Learning Abstract: We consider the problem of learning a control policy that is robust against the parameter mismatches between the training environment and testing environment. We formulate this as a distributionally robust reinforcemen...	[ 9634, 29926, 15245, 38107, 40813, 28691, 5780, 32219 ]	Train
30,808	24	Title: Learning Gradually Non-convex Image Priors Using Score Matching Abstract: In this paper, we propose a unified framework of denoising score-based models in the context of graduated non-convex energy minimization. We show that for sufficiently large noise variance, the associated negative log density -- the energy...	[]	Validation
30,809	5	Title: Towards Persistent Memory based Stateful Serverless Computing for Big Data Applications Abstract: The Function-as-a-service (FaaS) computing model has recently seen significant growth especially for highly scalable, event-driven applications. The easy-to-deploy and cost-efficient fine-grained billing of FaaS is ...	[]	Validation
30,810	4	Title: autofz: Automated Fuzzer Composition at Runtime Abstract: Fuzzing has gained in popularity for software vulnerability detection by virtue of the tremendous effort to develop a diverse set of fuzzers. Thanks to various fuzzing techniques, most of the fuzzers have been able to demonstrate great performance on thei...	[]	Validation
30,811	27	Title: Model-Free and Learning-Free Proprioceptive Humanoid Movement Control Abstract: This paper presents a novel model-free method for humanoid-robot quasi-static movement control. Traditional model-based methods often require precise robot model parameters. Additionally, existing learning-based frameworks often trai...	[]	Train
30,812	24	Title: Specification-Driven Neural Network Reduction for Scalable Formal Verification Abstract: Formal verification of neural networks is essential before their deployment in safety-critical settings. However, existing methods for formally verifying neural networks are not yet scalable enough to handle practical proble...	[]	Train
30,813	6	Title: Quantified Canine: Inferring Dog Personality From Wearables Abstract: Being able to assess dog personality can be used to, for example, match shelter dogs with future owners, and personalize dog activities. Such an assessment typically relies on experts or psychological scales administered to dog owners, both of...	[]	Train
30,814	2	Title: Epistemic Logics of Structured Intensional Groups Abstract: Epistemic logics of intensional groups lift the assumption that membership in a group of agents is common knowledge. Instead of being represented directly as a set of agents, intensional groups are represented by a property that may change its extension...	[]	Train
30,815	6	Title: Metaverse: A Vision, Architectural Elements, and Future Directions for Scalable and Realtime Virtual Worlds Abstract: With the emergence of Cloud computing, Internet of Things-enabled Human-Computer Interfaces, Generative Artificial Intelligence, and high-accurate Machine and Deep-learning recognition and predic...	[]	Train
30,816	16	Title: MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments Abstract: Self-supervised learning can be used for mitigating the greedy needs of Vision Transformer networks for very large fully-annotated datasets. Different classes of self-supervised learning offer representations...	[]	Train
30,817	16	Title: AdvRain: Adversarial Raindrops to Attack Camera-based Smart Vision Systems Abstract: Vision-based perception modules are increasingly deployed in many applications, especially autonomous vehicles and intelligent robots. These modules are being used to acquire information about the surroundings and identify obsta...	[ 7856, 11443, 33198 ]	Train
30,818	28	Title: Flexible-Position MIMO for Wireless Communications: Fundamentals, Challenges, and Future Directions Abstract: The flexible-position multiple-input multiple-output (MIMO), such as fluid antennas and movable antennas, is a promising technology for future wireless communications. This is due to the fact that the po...	[]	Train
30,819	24	Title: On the existence of solutions to adversarial training in multiclass classification Abstract: We study three models of the problem of adversarial training in multiclass classification designed to construct robust classifiers against adversarial perturbations of data in the agnostic-classifier setting. We prove th...	[ 39184, 22061 ]	Validation
30,820	34	Title: Thin trees for laminar families Abstract: In the laminar-constrained spanning tree problem, the goal is to find a minimum-cost spanning tree which respects upper bounds on the number of times each cut in a given laminar family is crossed. This generalizes the well-studied degree-bounded spanning tree problem, as...	[]	Validation
30,821	16	Title: CoPR: Toward Accurate Visual Localization With Continuous Place-Descriptor Regression Abstract: Visual place recognition (VPR) is an image-based localization method that estimates the camera location of a query image by retrieving the most similar reference image from a map of geo-tagged reference images. In thi...	[]	Train
30,822	24	Title: Random Teachers are Good Teachers Abstract: In this work, we investigate the implicit regularization induced by teacher-student learning dynamics in self-distillation. To isolate its effect, we describe a simple experiment where we consider teachers at random initialization instead of trained teachers. Surprisin...	[]	Test
30,823	10	Title: Progress Note Understanding - Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 Shared Task Abstract: Daily progress notes are a common note type in the electronic health record (EHR) where healthcare providers document the patient's daily progress and treatment plans. The EHR is designed to docum...	[]	Train
30,824	16	Title: DDS: Decoupled Dynamic Scene-Graph Generation Network Abstract: —Scene-graph generation involves creating a struc- tural representation of the relationships between objects in a scene by predicting subject-object-relation triplets from input data. However, existing methods show poor performance in detecting trip...	[]	Validation
30,825	16	Title: Explicit Visual Prompting for Low-Level Structure Segmentations Abstract: We consider the generic problem of detecting low-level structures in images, which includes segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow regions, and detecting concealed objects. Whereas each such to...	[ 37218, 39108, 34387, 38612, 35641, 5497 ]	Validation
30,826	24	Title: Kernels, Data & Physics Abstract: Lecture notes from the course given by Professor Julia Kempe at the summer school"Statistical physics of Machine Learning"in Les Houches. The notes discuss the so-called NTK approach to problems in machine learning, which consists of gaining an understanding of generally unsolva...	[]	Train
30,827	27	Title: Coordinated Control of Path Tracking and Yaw Stability for Distributed Drive Electric Vehicle Based on AMPC and DYC Abstract: Maintaining both path-tracking accuracy and yaw stability of distributed drive electric vehicles (DDEVs) under various driving conditions presents a significant challenge in the field of ...	[ 44160, 8257, 18974 ]	Train
30,828	24	Title: Differentiable Frank-Wolfe Optimization Layer Abstract: Differentiable optimization has received a significant amount of attention due to its foundational role in the domain of machine learning based on neural networks. The existing methods leverages the optimality conditions and implicit function theorem to obt...	[ 30960 ]	Train
30,829	16	Title: Contrastive Model Adaptation for Cross-Condition Robustness in Semantic Segmentation Abstract: Standard unsupervised domain adaptation methods adapt models from a source to a target domain using labeled source data and unlabeled target data jointly. In model adaptation, on the other hand, access to the labeled s...	[ 26840, 45922, 33723 ]	Train
30,830	3	Title: Towards clinical AI fairness: A translational perspective Abstract: Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the issue of fairness remains a concern in high-stakes fields such as healthcare. Despite extensive discussion and efforts in algorithm development, AI ...	[]	Train
30,831	24	Title: Minimizing the Outage Probability in a Markov Decision Process Abstract: Standard Markov decision process (MDP) and reinforcement learning algorithms optimize the policy with respect to the expected gain. We propose an algorithm which enables to optimize an alternative objective: the probability that the gain is...	[ 22209, 16316 ]	Train
30,832	23	Title: Crucible: Graphical Test Cases for Alloy Models Abstract: Alloy is a declarative modeling language that is well suited for verifying system designs. Alloy models are automatically analyzed using the Analyzer, a toolset that helps the user understand their system by displaying the consequences of their properties...	[]	Train
30,833	24	Title: Differentially Private Distributed Estimation and Learning Abstract: We study distributed estimation and learning problems in a networked environment in which agents exchange information to estimate unknown statistical properties of random variables from their privately observed samples. By exchanging informatio...	[ 21415 ]	Test
30,834	24	Title: Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism Abstract: In this paper, we study offline Reinforcement Learning with Human Feedback (RLHF) where we aim to learn the human's underlying reward and the MDP's optimal policy from a set of trajectories induced by human choices. RLHF...	[ 2907, 9701 ]	Train
30,835	16	Title: Enhance-NeRF: Multiple Performance Evaluation for Neural Radiance Fields Abstract: The quality of three-dimensional reconstruction is a key factor affecting the effectiveness of its application in areas such as virtual reality (VR) and augmented reality (AR) technologies. Neural Radiance Fields (NeRF) can genera...	[ 43296, 11874, 19781, 32423, 38959, 21846, 4503, 41400, 34238 ]	Train
30,836	4	Title: Tortoise: An Authenticated Encryption Scheme Abstract: We present Tortoise, an experimental nonce-based authenticated encryption scheme modeled on the Synthetic Counter-in-Tweak framework to convert any block cipher into Authenticated Encryption with Associated Data. Our work supports two modes: nonce-respecting...	[]	Train
30,837	24	Title: Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise Abstract: We consider the stochastic optimization problem with smooth but not necessarily convex objectives in the heavy-tailed noise regime, where the stochastic gradient's noise is assum...	[]	Test
30,838	10	Title: Approximate inference of marginals using the IBIA framework Abstract: Exact inference of marginals in probabilistic graphical models (PGM) is known to be intractable, necessitating the use of approximate methods. Most of the existing variational techniques perform iterative message passing in loopy graphs which ...	[ 42622 ]	Train
30,839	34	Title: Erasing-based lossless compression method for streaming floating-point time series Abstract: There are a prohibitively large number of floating-point time series data generated at an unprecedentedly high rate. An efficient, compact and lossless compression for time series data is of great importance for a wide r...	[ 35149 ]	Train
30,840	24	Title: SHARP: Sparsity and Hidden Activation RePlay for Neuro-Inspired Continual Learning Abstract: Deep neural networks (DNNs) struggle to learn in dynamic environments since they rely on fixed datasets or stationary environments. Continual learning (CL) aims to address this limitation and enable DNNs to accumulate kn...	[]	Test
30,841	28	Title: Deep Learning-empowered Predictive Precoder Design for OTFS Transmission in URLLC Abstract: To guarantee excellent reliability performance in ultra-reliable low-latency communications (URLLC), pragmatic precoder design is an effective approach. However, an efficient precoder design highly depends on the accurate...	[]	Train
30,842	30	Title: Learning Robust Self-attention Features for Speech Emotion Recognition with Label-adaptive Mixup Abstract: Speech Emotion Recognition (SER) is to recognize human emotions in a natural verbal interaction scenario with machines, which is considered as a challenging problem due to the ambiguous human emotions. Desp...	[]	Validation
30,843	8	Title: FLSTRA: Federated Learning in Stratosphere Abstract: We propose a federated learning (FL) in stratosphere (FLSTRA) system, where a high altitude platform station (HAPS) facilitates a large number of terrestrial clients to collaboratively learn a global model without sharing the training data. FLSTRA overcomes th...	[ 25278 ]	Train
30,844	16	Title: MATT: Multimodal Attention Level Estimation for e-learning Platforms Abstract: This work presents a new multimodal system for remote attention level estimation based on multimodal face analysis. Our multimodal approach uses different parameters and signals obtained from the behavior and physiological processes t...	[ 26080, 44435 ]	Validation
30,845	16	Title: Enhancing Landmark Detection in Cluttered Real-World Scenarios with Vision Transformers Abstract: Visual place recognition tasks often encounter significant challenges in landmark detection due to the presence of irrelevant objects such as humans, cars, and trees, despite the remarkable progress achieved by prev...	[]	Test
30,846	36	Title: For One and All: Individual and Group Fairness in the Allocation of Indivisible Goods Abstract: Fair allocation of indivisible goods is a well-explored problem. Traditionally, research focused on individual fairness - are individual agents satisfied with their allotted share? - and group fairness - are groups of...	[]	Train
30,847	4	Title: A Uniform Representation of Classical and Quantum Source Code for Static Code Analysis Abstract: The emergence of quantum computing raises the question of how to identify (security-relevant) programming errors during development. However, current static code analysis tools fail to model information specific to q...	[]	Train
30,848	26	Title: Prospecting Community Development Strength based on Economic Graph: From Categorization to Scoring Abstract: Recent years have witnessed a growing number of researches on community characterization. In contrast to the large body of researches on the categorical measures (rise or decline) for evaluating the commu...	[]	Train
30,849	30	Title: InstructIE: A Chinese Instruction-based Information Extraction Dataset Abstract: We introduce a new Information Extraction (IE) task dubbed Instruction-based IE, which aims to ask the system to follow specific instructions or guidelines to extract information. To facilitate research in this area, we construct a ...	[ 1811, 13700, 38102 ]	Test
30,850	16	Title: Personal Protective Equipment Detection in Extreme Construction Conditions Abstract: Object detection has been widely applied for construction safety management, especially personal protective equipment (PPE) detection. Though the existing PPE detection models trained on conventional datasets have achieved excel...	[]	Train
30,851	28	Title: On the Degrees of Freedom and Eigenfunctions of Line-of-Sight Holographic MIMO Communications Abstract: We consider a line-of-sight communication link between two holographic surfaces (HoloSs). We provide a closed-form expression for the number of effective degrees of freedom (eDoF), i.e., the number of orthogon...	[]	Train
30,852	30	Title: Letz Translate: Low-Resource Machine Translation for Luxembourgish Abstract: Natural language processing of Low-Resource Languages (LRL) is often challenged by the lack of data. Therefore, achieving accurate machine translation (MT) in a low-resource environment is a real problem that requires practical solution...	[]	Validation
30,853	16	Title: TAEC: Unsupervised Action Segmentation with Temporal-Aware Embedding and Clustering Abstract: Temporal action segmentation in untrimmed videos has gained increased attention recently. However, annotating action classes and frame-wise boundaries is extremely time consuming and cost intensive, especially on large-...	[]	Train
30,854	24	Title: EasyTPP: Towards Open Benchmarking the Temporal Point Processes Abstract: Continuous-time event sequences play a vital role in real-world domains such as healthcare, finance, online shopping, social networks, and so on. To model such data, temporal point processes (TPPs) have emerged as the most advanced generat...	[ 33328, 45406, 43586, 29454 ]	Test
30,855	16	Title: Score-based Generative Models for Photoacoustic Image Reconstruction with Rotation Consistency Constraints Abstract: Photoacoustic tomography (PAT) is a newly emerged imaging modality which enables both high optical contrast and acoustic depth of penetration. Reconstructing images of photoacoustic tomography fro...	[]	Train
30,856	24	Title: Two-stage Denoising Diffusion Model for Source Localization in Graph Inverse Problems Abstract: Source localization is the inverse problem of graph information dissemination and has broad practical applications. However, the inherent intricacy and uncertainty in information dissemination pose significant challen...	[]	Train
30,857	10	Title: Learning to Solve Constraint Satisfaction Problems with Recurrent Transformer Abstract: Constraint satisfaction problems (CSPs) are about finding values of variables that satisfy the given constraints. We show that Transformer extended with recurrence is a viable approach to learning to solve CSPs in an end-to-e...	[ 35996, 2413 ]	Test
30,858	27	Title: Multi-Modal Multi-Task (3MT) Road Segmentation Abstract: Multi-modal systems have the capacity of producing more reliable results than systems with a single modality in road detection due to perceiving different aspects of the scene. We focus on using raw sensor inputs instead of, as it is typically done in many...	[ 3938 ]	Train
30,859	24	Title: VIBR: Learning View-Invariant Value Functions for Robust Visual Control Abstract: End-to-end reinforcement learning on images showed significant progress in the recent years. Data-based approach leverage data augmentation and domain randomization while representation learning methods use auxiliary losses to lear...	[]	Train
30,860	27	Title: An Informative Path Planning Framework for Active Learning in UAV-based Semantic Mapping Abstract: Unmanned aerial vehicles (UAVs) are frequently used for aerial mapping and general monitoring tasks. Recent progress in deep learning enabled automated semantic segmentation of imagery to facilitate the interpretat...	[]	Train
30,861	16	Title: High-Resolution Vision Transformers for Pixel-Level Identification of Structural Components and Damage Abstract: Visual inspection is predominantly used to evaluate the state of civil structures, but recent developments in unmanned aerial vehicles (UAVs) and artificial intelligence have increased the speed, safe...	[]	Train
30,862	30	Title: Vec2Vec: A Compact Neural Network Approach for Transforming Text Embeddings with High Fidelity Abstract: Vector embeddings have become ubiquitous tools for many language-related tasks. A leading embedding model is OpenAI's text-ada-002 which can embed approximately 6,000 words into a 1,536-dimensional vector. Wh...	[ 33247 ]	Train
30,863	30	Title: Robust Open-Set Spoken Language Identification and the CU MultiLang Dataset Abstract: Most state-of-the-art spoken language identification models are closed-set; in other words, they can only output a language label from the set of classes they were trained on. Open-set spoken language identification systems, ho...	[]	Test
30,864	27	Title: SMAT: A Self-Reinforcing Framework for Simultaneous Mapping and Tracking in Unbounded Urban Environments Abstract: With the increasing prevalence of robots in daily life, it is crucial to enable robots to construct a reliable map online to navigate in unbounded and changing environments. Although existing method...	[]	Train
30,865	10	Title: Three-way causal attribute partial order structure analysis Abstract: As an emerging concept cognitive learning model, partial order formal structure analysis (POFSA) has been widely used in the field of knowledge processing. In this paper, we propose the method named three-way causal attribute partial order str...	[]	Train
30,866	23	Title: Time-based Repair for Asynchronous Wait Flaky Tests in Web Testing Abstract: Asynchronous waits are one of the most prevalent root causes of flaky tests and a major time-influential factor of web application testing. To investigate the characteristics of asynchronous wait flaky tests and their fixes in web testi...	[]	Train
30,867	30	Title: Detecting and Characterizing Political Incivility on Social Media Abstract: Researchers of political communication study the impact and perceptions of political incivility on social media. Yet, so far, relatively few works attempted to automatically detect and characterize political incivility. In our work, we s...	[]	Train
30,868	30	Title: Multimodal Detection of Social Spambots in Twitter using Transformers Abstract: Although not all bots are malicious, the vast majority of them are responsible for spreading misinformation and manipulating the public opinion about several issues, i.e., elections and many more. Therefore, the early detection of so...	[ 13020, 8806 ]	Train
30,869	16	Title: Global Proxy-based Hard Mining for Visual Place Recognition Abstract: Learning deep representations for visual place recognition is commonly performed using pairwise or triple loss functions that highly depend on the hardness of the examples sampled at each training iteration. Existing techniques address this by...	[]	Train
30,870	16	Title: FIRE: Food Image to REcipe generation Abstract: Food computing has emerged as a prominent multidisciplinary field of research in recent years. An ambitious goal of food computing is to develop end-to-end intelligent systems capable of autonomously producing recipe information for a food image. Current image-to-r...	[ 13700, 28744, 7849, 18892, 35742 ]	Validation
30,871	24	Title: Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features Abstract: Transfer learning with a small amount of target data is an effective and common approach to adapting a pre-trained model to distribution shifts. In some situations, target data labels may be expensive to obtain, ...	[ 18147, 28405 ]	Train
30,872	16	Title: Label Calibration for Semantic Segmentation Under Domain Shift Abstract: Performance of a pre-trained semantic segmentation model is likely to substantially decrease on data from a new domain. We show a pre-trained model can be adapted to unlabelled target domain data by calculating soft-label prototypes under t...	[ 18065 ]	Train
30,873	24	Title: Channel and Gradient-Importance Aware Device Scheduling for Over-the-Air Federated Learning Abstract: Federated learning (FL) is a popular privacy-preserving distributed training scheme, where multiple devices collaborate to train machine learning models by uploading local model updates. To improve communication...	[]	Train
30,874	16	Title: 360$^\circ$ from a Single Camera: A Few-Shot Approach for LiDAR Segmentation Abstract: Deep learning applications on LiDAR data suffer from a strong domain gap when applied to different sensors or tasks. In order for these methods to obtain similar accuracy on different data in comparison to values reported on p...	[ 34590, 22767 ]	Train
30,875	16	Title: Data-Efficient Large Scale Place Recognition with Graded Similarity Supervision Abstract: Visual place recognition (VPR) is a fundamental task of computer vision for visual localization. Existing methods are trained using image pairs that either depict the same place or not. Such a binary indication does not con...	[ 40721, 18422 ]	Test
30,876	24	Title: iDML: Incentivized Decentralized Machine Learning Abstract: With the rising emergence of decentralized and opportunistic approaches to machine learning, end devices are increasingly tasked with training deep learning models on-devices using crowd-sourced data that they collect themselves. These approaches are de...	[ 14788, 3839 ]	Validation
30,877	6	Title: The Effect of an Exergame on the Shadow Play Skill Based on Muscle Memory for Young Female Participants: The Case of Forehand Drive in Table Tennis Abstract: Learning and practicing table tennis with traditional methods is a long, tedious process and may even lead to the internalization of incorrect techniques i...	[]	Validation

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