node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
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|---|---|---|---|---|
44,878 | 5 | Title: Decentralized Learning Made Easy with DecentralizePy
Abstract: Decentralized learning (DL) has gained prominence for its potential benefits in terms of scalability, privacy, and fault tolerance. It consists of many nodes that coordinate without a central server and exchange millions of parameters in the inherent... | [
3535
] | Train |
44,879 | 24 | Title: Agnostic PAC Learning of k-juntas Using L2-Polynomial Regression
Abstract: Many conventional learning algorithms rely on loss functions other than the natural 0-1 loss for computational efficiency and theoretical tractability. Among them are approaches based on absolute loss (L1 regression) and square loss (L2 r... | [] | Test |
44,880 | 16 | Title: Learning Channel Importance for High Content Imaging with Interpretable Deep Input Channel Mixing
Abstract: Uncovering novel drug candidates for treating complex diseases remain one of the most challenging tasks in early discovery research. To tackle this challenge, biopharma research established a standardized ... | [
32541
] | Train |
44,881 | 16 | Title: Generate Anything Anywhere in Any Scene
Abstract: Text-to-image diffusion models have attracted considerable interest due to their wide applicability across diverse fields. However, challenges persist in creating controllable models for personalized object generation. In this paper, we first identify the entangl... | [
3690,
34074,
11820,
15983,
41146
] | Train |
44,882 | 28 | Title: On the Structure of Higher Order MDS Codes
Abstract: A code of length n is said to be (combinatorially) (ρ, L)-list decodable if the Hamming ball of radius ρn around any vector in the ambient space does not contain more than L codewords. We study a recently introduced class of higher order MDS codes, which are c... | [] | Train |
44,883 | 16 | Title: Dual-Path Adaptation from Image to Video Transformers
Abstract: In this paper, we efficiently transfer the surpassing representation power of the vision foundation models, such as ViT and Swin, for video understanding with only a few trainable parameters. Previous adaptation methods have simultaneously considere... | [] | Train |
44,884 | 16 | Title: Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification
Abstract: Whole Slide Images (WSIs) or histopathology images are used in digital pathology. WSIs pose great challenges to deep learning models for clinical diagnosis, owing to their size and lack of pixel-level annotations. With ... | [] | Train |
44,885 | 16 | Title: Motion Question Answering via Modular Motion Programs
Abstract: In order to build artificial intelligence systems that can perceive and reason with human behavior in the real world, we must first design models that conduct complex spatio-temporal reasoning over motion sequences. Moving towards this goal, we prop... | [
10665
] | Train |
44,886 | 10 | Title: Can I say, now machines can think?
Abstract: Generative AI techniques have opened the path for new generations of machines in diverse domains. These machines have various capabilities for example, they can produce images, generate answers or stories, and write codes based on the"prompts"only provided by users. T... | [
13345,
12474,
13510,
4071
] | Validation |
44,887 | 24 | Title: Lucy-SKG: Learning to Play Rocket League Efficiently Using Deep Reinforcement Learning
Abstract: A successful tactic that is followed by the scientific community for advancing AI is to treat games as problems, which has been proven to lead to various breakthroughs. We adapt this strategy in order to study Rocket... | [] | Test |
44,888 | 34 | Title: Approximations for the Steiner Multicycle Problem
Abstract: nan | [] | Test |
44,889 | 16 | Title: On the Query Strategies for Efficient Online Active Distillation
Abstract: Deep Learning (DL) requires lots of time and data, resulting in high computational demands. Recently, researchers employ Active Learning (AL) and online distillation to enhance training efficiency and real-time model adaptation. This pape... | [
30096
] | Test |
44,890 | 16 | Title: Global Knowledge Calibration for Fast Open-Vocabulary Segmentation
Abstract: Recent advancements in pre-trained vision-language models, such as CLIP, have enabled the segmentation of arbitrary concepts solely from textual inputs, a process commonly referred to as open-vocabulary semantic segmentation (OVS). Howe... | [
28592,
33913,
38753,
29733
] | Train |
44,891 | 16 | Title: Sketch-based Medical Image Retrieval
Abstract: The amount of medical images stored in hospitals is increasing faster than ever; however, utilizing the accumulated medical images has been limited. This is because existing content-based medical image retrieval (CBMIR) systems usually require example images to cons... | [
11686
] | Test |
44,892 | 23 | Title: Diversity Awareness in Software Engineering Participant Research
Abstract: Diversity and inclusion are necessary prerequisites for shaping technological innovation that benefits society as a whole. A common indicator of diversity consideration is the representation of different social groups among software engin... | [] | Train |
44,893 | 24 | Title: SAPI: Surroundings-Aware Vehicle Trajectory Prediction at Intersections
Abstract: In this work we propose a deep learning model, i.e., SAPI, to predict vehicle trajectories at intersections. SAPI uses an abstract way to represent and encode surrounding environment by utilizing information from real-time map, rig... | [] | Validation |
44,894 | 16 | Title: One-shot neural band selection for spectral recovery
Abstract: Band selection has a great impact on the spectral recovery quality. To solve this ill-posed inverse problem, most band selection methods adopt hand-crafted priors or exploit clustering or sparse regularization constraints to find most prominent bands... | [] | Test |
44,895 | 16 | Title: Exploring Semantic Consistency in Unpaired Image Translation to Generate Data for Surgical Applications
Abstract: In surgical computer vision applications, obtaining labeled training data is challenging due to data-privacy concerns and the need for expert annotation. Unpaired image-to-image translation technique... | [] | Test |
44,896 | 16 | Title: A Spectral Perspective towards Understanding and Improving Adversarial Robustness
Abstract: Deep neural networks (DNNs) are incredibly vulnerable to crafted, imperceptible adversarial perturbations. While adversarial training (AT) has proven to be an effective defense approach, the AT mechanism for robustness im... | [] | Validation |
44,897 | 24 | Title: Automatic Trade-off Adaptation in Offline RL
Abstract: Recently, offline RL algorithms have been proposed that remain adaptive at runtime. For example, the LION algorithm \cite{lion} provides the user with an interface to set the trade-off between behavior cloning and optimality w.r.t. the estimated return at ru... | [] | Train |
44,898 | 16 | Title: Deep Image Compression Using Scene Text Quality Assessment
Abstract: nan | [
7115
] | Train |
44,899 | 24 | Title: Information fusion via symbolic regression: A tutorial in the context of human health
Abstract: nan | [] | Train |
44,900 | 28 | Title: Joint Precoding Design and Resource Allocation for C-RAN Wireless Fronthaul Systems
Abstract: This paper investigates the resource allocation problem combined with fronthaul precoding and access link sparse precoding design in cloud radio access network (C-RAN) wireless fronthaul systems.Multiple remote antenna ... | [] | Test |
44,901 | 34 | Title: Reducing Maximum Weighted Matching to the Largest Cardinality Matching in CONGEST
Abstract: In this paper, we reduce the maximum weighted matching problem to the largest cardinality matching in CONGEST . The paper presents two technical contributions. The first of them is a simple poly (log n, 1 ε , t, ln w t )-r... | [] | Train |
44,902 | 24 | Title: Interpreting Robustness Proofs of Deep Neural Networks
Abstract: In recent years numerous methods have been developed to formally verify the robustness of deep neural networks (DNNs). Though the proposed techniques are effective in providing mathematical guarantees about the DNNs behavior, it is not clear whethe... | [] | Validation |
44,903 | 16 | Title: Can SAM Boost Video Super-Resolution?
Abstract: The primary challenge in video super-resolution (VSR) is to handle large motions in the input frames, which makes it difficult to accurately aggregate information from multiple frames. Existing works either adopt deformable convolutions or estimate optical flow as ... | [
12704,
24074,
35263
] | Train |
44,904 | 16 | Title: Increasing Melanoma Diagnostic Confidence: Forcing the Convolutional Network to Learn from the Lesion
Abstract: Deep learning implemented with convolutional network architectures can exceed specialists' diagnostic accuracy. However, whole-image deep learning trained on a given dataset may not generalize to other... | [] | Validation |
44,905 | 16 | Title: Deep Learning for Human Parsing: A Survey
Abstract: —Human parsing is a key topic in image processing with many applications, such as surveillance analysis, human-robot interaction, person search, and clothing category classifi- cation, among many others. Recently, due to the success of deep learning in computer ... | [] | Train |
44,906 | 24 | Title: Learning Functional Transduction
Abstract: Research in machine learning has polarized into two general approaches for regression tasks: Transductive methods construct estimates directly from available data but are usually problem unspecific. Inductive methods can be much more specific but generally require compu... | [] | Train |
44,907 | 6 | Title: "Customization is Key": Four Characteristics of Textual Affordances for Accessible Data Visualization
Abstract: Current best practices recommend using textual descriptions to make data visualizations accessible to blind and low vision (BLV) screen reader users. While recent research has explored laying such desc... | [
29373
] | Test |
44,908 | 3 | Title: Domain-based user embedding for competing events on social media
Abstract: Online social networks offer vast opportunities for computational social science, but effective user embedding is crucial for downstream tasks. Traditionally, researchers have used pre-defined network-based user features, such as degree, ... | [] | Validation |
44,909 | 6 | Title: Participatory Design of AI with Children: Reflections on IDC Design Challenge
Abstract: Children growing up in the era of Artificial Intelligence (AI) will be most impacted by the technology across their life span. Participatory Design (PD) is widely adopted by the Interaction Design and Children (IDC) community... | [] | Validation |
44,910 | 13 | Title: Directed differential equation discovery using modified mutation and cross-over operators
Abstract: The discovery of equations with knowledge of the process origin is a tempting prospect. However, most equation discovery tools rely on gradient methods, which offer limited control over parameters. An alternative ... | [] | Train |
44,911 | 13 | Title: Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs
Abstract: Biological nervous systems are created in a fundamentally different way than current artificial neural networks. Despite its impressive results in a variety of different domains, deep learning often requires consid... | [
11884
] | Train |
44,912 | 4 | Title: ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning
Abstract: Data is a critical asset in AI, as high-quality datasets can significantly improve the performance of machine learning models. In safety-critical domains such as autonomous vehicles, offline deep reinforcement learning (offline DRL) i... | [
2466,
20781
] | Validation |
44,913 | 16 | Title: Patch Gradient Descent: Training Neural Networks on Very Large Images
Abstract: Traditional CNN models are trained and tested on relatively low resolution images (<300 px), and cannot be directly operated on large-scale images due to compute and memory constraints. We propose Patch Gradient Descent (PatchGD), an... | [] | Train |
44,914 | 25 | Title: Multi-View Multi-Task Representation Learning for Mispronunciation Detection
Abstract: The disparity in phonology between learner's native (L1) and target (L2) language poses a significant challenge for mispronunciation detection and diagnosis (MDD) systems. This challenge is further intensified by lack of annot... | [
35710
] | Validation |
44,915 | 26 | Title: Temporal Dynamics of Coordinated Online Behavior: Stability, Archetypes, and Influence
Abstract: Large-scale online campaigns, malicious or otherwise, require a significant degree of coordination among participants, which sparked interest in the study of coordinated online behavior. State-of-the-art methods for ... | [
24657
] | Train |
44,916 | 6 | Title: Designing for Passengers' Information Needs on Fellow Travelers: A Comparison of Day and Night Rides in Shared Automated Vehicles
Abstract: Shared automated mobility-on-demand promises efficient, sustainable, and flexible transportation. Nevertheless, security concerns, resilience, and their mutual influence - e... | [] | Train |
44,917 | 34 | Title: SAGE: A Storage-Based Approach for Scalable and Efficient Sparse Generalized Matrix-Matrix Multiplication
Abstract: Sparse generalized matrix-matrix multiplication (SpGEMM) is a fundamental operation for real-world network analysis. With the increasing size of real-world networks, the single-machine-based SpGEMM... | [] | Test |
44,918 | 30 | Title: PREFER: Prompt Ensemble Learning via Feedback-Reflect-Refine
Abstract: As an effective tool for eliciting the power of Large Language Models (LLMs), prompting has recently demonstrated unprecedented abilities across a variety of complex tasks. To further improve the performance, prompt ensemble has attracted sub... | [
40192,
33220,
33477,
40135,
17789
] | Test |
44,919 | 6 | Title: Open Medical Gesture: An Open-Source Experiment in Naturalistic Physical Interactions for Mixed and Virtual Reality Simulations
Abstract: Mixed (MR) and Virtual Reality (VR) simulations are hampered by requirements for hand controllers or attempts to perseverate in use of two-dimensional computer interface parad... | [] | Train |
44,920 | 10 | Title: The Roles of Symbols in Neural-based AI: They are Not What You Think!
Abstract: We propose that symbols are first and foremost external communication tools used between intelligent agents that allow knowledge to be transferred in a more efficient and effective manner than having to experience the world directly.... | [] | Train |
44,921 | 4 | Title: Unlocking Metaverse-as-a-Service The three pillars to watch: Privacy and Security, Edge Computing, and Blockchain
Abstract: In this article, the authors provide a comprehensive overview on three core pillars of metaverse-as-a-service (MaaS) platforms; privacy and security, edge computing, and blockchain technolo... | [
19353,
17573
] | Validation |
44,922 | 24 | Title: Accurate ignition detection of solid fuel particles using machine learning
Abstract: In the present work, accurate determination of single-particle ignition is focused on using high-speed optical diagnostics combined with machine learning approaches. Ignition of individual particles in a laminar flow reactor are... | [] | Train |
44,923 | 16 | Title: PE-YOLO: Pyramid Enhancement Network for Dark Object Detection
Abstract: Current object detection models have achieved good results on many benchmark datasets, detecting objects in dark conditions remains a large challenge. To address this issue, we propose a pyramid enhanced network (PENet) and joint it with YO... | [
3818
] | Test |
44,924 | 24 | Title: Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces
Abstract: Typical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used to generate samples from Gaussian noise. However, real world data often takes place in disc... | [
8308
] | Validation |
44,925 | 24 | Title: Finite-Sample Bounds for Adaptive Inverse Reinforcement Learning using Passive Langevin Dynamics
Abstract: Stochastic gradient Langevin dynamics (SGLD) are a useful methodology for sampling from probability distributions. This paper provides a finite sample analysis of a passive stochastic gradient Langevin dyna... | [] | Validation |
44,926 | 4 | Title: Unveiling the Risks of NFT Promotion Scams
Abstract: The rapid growth in popularity and hype surrounding digital assets such as art, video, and music in the form of non-fungible tokens (NFTs) has made them a lucrative investment opportunity, with NFT-based sales surpassing $25B in 2021 alone. However, the volati... | [
6696,
21562,
36075
] | Test |
44,927 | 4 | Title: Attacks on Continuous Chaos Communication and Remedies for Resource Limited Devices
Abstract: The Global Wearable market is anticipated to rise at a considerable rate in the next coming years and communication is a fundamental block in any wearable device. In communication, encryption methods are being used with... | [] | Validation |
44,928 | 10 | Title: Scalable Concept Extraction in Industry 4.0
Abstract: The industry 4.0 is leveraging digital technologies and machine learning techniques to connect and optimize manufacturing processes. Central to this idea is the ability to transform raw data into human understandable knowledge for reliable data-driven decisio... | [] | Test |
44,929 | 34 | Title: Turán's Theorem Through Algorithmic Lens
Abstract: The fundamental theorem of Tur\'{a}n from Extremal Graph Theory determines the exact bound on the number of edges $t_r(n)$ in an $n$-vertex graph that does not contain a clique of size $r+1$. We establish an interesting link between Extremal Graph Theory and Alg... | [] | Validation |
44,930 | 16 | Title: Object pop-up: Can we infer 3D objects and their poses from human interactions alone?
Abstract: The intimate entanglement between objects affordances and human poses is of large interest, among others, for behavioural sciences, cognitive psychology, and Computer Vision communities. In recent years, the latter ha... | [
25515,
38181,
4583
] | Train |
44,931 | 16 | Title: Cascade-DETR: Delving into High-Quality Universal Object Detection
Abstract: Object localization in general environments is a fundamental part of vision systems. While dominating on the COCO benchmark, recent Transformer-based detection methods are not competitive in diverse domains. Moreover, these methods stil... | [
18112
] | Train |
44,932 | 16 | Title: Informative Scene Graph Generation via Debiasing
Abstract: Scene graph generation aims to detect visual relationship triplets, (subject, predicate, object). Due to biases in data, current models tend to predict common predicates, e.g."on"and"at", instead of informative ones, e.g."standing on"and"looking at". Thi... | [
30784,
12779,
37652,
37099
] | Train |
44,933 | 28 | Title: A multivariate Riesz basis of ReLU neural networks
Abstract: We consider the trigonometric-like system of piecewise linear functions introduced recently by Daubechies, DeVore, Foucart, Hanin, and Petrova. We provide an alternative proof that this system forms a Riesz basis of $L_2([0,1])$ based on the Gershgorin... | [] | Validation |
44,934 | 7 | Title: Fairness- and uncertainty-aware data generation for data-driven design
Abstract: The design dataset is the backbone of data-driven design. Ideally, the dataset should be fairly distributed in both shape and property spaces to efficiently explore the underlying relationship. However, the classical experimental de... | [] | Train |
44,935 | 16 | Title: FANET Experiment: Real-Time Surveillance Applications Connected to Image Processing System
Abstract: The major goal of this paper is to use image enhancement techniques for enhancing and extracting data in FANET applications to improve the efficiency of surveillance. The proposed conceptual system design can imp... | [] | Train |
44,936 | 16 | Title: Boosting Few-shot Action Recognition with Graph-guided Hybrid Matching
Abstract: Class prototype construction and matching are core aspects of few-shot action recognition. Previous methods mainly focus on designing spatiotemporal relation modeling modules or complex temporal alignment algorithms. Despite the pro... | [
7331
] | Train |
44,937 | 30 | Title: Can Generative Large Language Models Perform ASR Error Correction?
Abstract: ASR error correction continues to serve as an important part of post-processing for speech recognition systems. Traditionally, these models are trained with supervised training using the decoding results of the underlying ASR system and... | [
21921,
45954,
13700,
8676,
33220,
11273,
5643,
29039,
29396
] | Validation |
44,938 | 23 | Title: Pre-trained Model-based Automated Software Vulnerability Repair: How Far are We?
Abstract: Various approaches are proposed to help under-resourced security researchers to detect and analyze software vulnerabilities. It is still incredibly time-consuming and labor-intensive for security researchers to fix vulnera... | [
23130,
43119
] | Train |
44,939 | 8 | Title: ASTrack: Automatic Detection and Removal of Web Tracking Code with Minimal Functionality Loss
Abstract: Recent advances in web technologies make it more difficult than ever to detect and block web tracking systems. In this work, we propose ASTrack, a novel approach to web tracking detection and removal. ASTrack ... | [] | Train |
44,940 | 16 | Title: Vision DiffMask: Faithful Interpretation of Vision Transformers with Differentiable Patch Masking
Abstract: The lack of interpretability of the Vision Transformer may hinder its use in critical real-world applications despite its effectiveness. To overcome this issue, we propose a post-hoc interpretability metho... | [] | Test |
44,941 | 34 | Title: Linear-time Computation of DAWGs, Symmetric Indexing Structures, and MAWs for Integer Alphabets
Abstract: The directed acyclic word graph (DAWG) of a string $y$ of length $n$ is the smallest (partial) DFA which recognizes all suffixes of $y$ with only $O(n)$ nodes and edges. In this paper, we show how to constru... | [
39787,
33534
] | Train |
44,942 | 24 | Title: Capturing Fine-grained Semantics in Contrastive Graph Representation Learning
Abstract: Graph contrastive learning defines a contrastive task to pull similar instances close and push dissimilar instances away. It learns discriminative node embeddings without supervised labels, which has aroused increasing attent... | [] | Train |
44,943 | 16 | Title: Graph Self-Supervised Learning for Endoscopic Image Matching
Abstract: Accurate feature matching and correspondence in endoscopic images play a crucial role in various clinical applications, including patient follow-up and rapid anomaly localization through panoramic image generation. However, developing robust ... | [] | Test |
44,944 | 24 | Title: Improving Transferability of Adversarial Examples via Bayesian Attacks
Abstract: This paper presents a substantial extension of our work published at ICLR. Our ICLR work advocated for enhancing transferability in adversarial examples by incorporating a Bayesian formulation into model parameters, which effectivel... | [
35323,
4052
] | Test |
44,945 | 16 | Title: Wise-IoU: Bounding Box Regression Loss with Dynamic Focusing Mechanism
Abstract: The loss function for bounding box regression (BBR) is essential to object detection. Its good definition will bring significant performance improvement to the model. Most existing works assume that the examples in the training data... | [
24264,
34003,
45447
] | Test |
44,946 | 24 | Title: Feature Selection for Forecasting
Abstract: This work investigates the importance of feature selection for improving the forecasting performance of machine learning algorithms for financial data. Artificial neural networks (ANN), convolutional neural networks (CNN), long-short term memory (LSTM) networks, as wel... | [] | Train |
44,947 | 30 | Title: Zero-Shot Cross-Lingual Summarization via Large Language Models
Abstract: Given a document in a source language, cross-lingual summarization (CLS) aims to generate a summary in a different target language. Recently, the emergence of Large Language Models (LLMs), such as GPT-3.5, ChatGPT and GPT-4, has attracted ... | [
12128,
33220,
35580,
13510,
15049,
41524,
12087,
35545,
39451,
4892,
43327
] | Train |
44,948 | 16 | Title: PARASOL: Parametric Style Control for Diffusion Image Synthesis
Abstract: We propose PARASOL, a multi-modal synthesis model that enables disentangled, parametric control of the visual style of the image by jointly conditioning synthesis on both content and a fine-grained visual style embedding. We train a latent... | [
34074,
10212,
16557
] | Train |
44,949 | 24 | Title: GC-Flow: A Graph-Based Flow Network for Effective Clustering
Abstract: Graph convolutional networks (GCNs) are \emph{discriminative models} that directly model the class posterior $p(y|\mathbf{x})$ for semi-supervised classification of graph data. While being effective, as a representation learning approach, the... | [] | Validation |
44,950 | 24 | Title: A Learnheuristic Approach to A Constrained Multi-Objective Portfolio Optimisation Problem
Abstract: Multi-objective portfolio optimisation is a critical problem researched across various fields of study as it achieves the objective of maximising the expected return while minimising the risk of a given portfolio ... | [] | Test |
44,951 | 24 | Title: Almost Sure Saddle Avoidance of Stochastic Gradient Methods without the Bounded Gradient Assumption
Abstract: We prove that various stochastic gradient descent methods, including the stochastic gradient descent (SGD), stochastic heavy-ball (SHB), and stochastic Nesterov's accelerated gradient (SNAG) methods, alm... | [] | Train |
44,952 | 8 | Title: Exposing the CSI: A Systematic Investigation of CSI-based Wi-Fi Sensing Capabilities and Limitations
Abstract: Thanks to the ubiquitous deployment of Wi-Fi hotspots, channel state information (CSI)-based Wi-Fi sensing can unleash game-changing applications in many fields, such as healthcare, security, and entert... | [] | Validation |
44,953 | 2 | Title: Stabilized profunctors and stable species of structures
Abstract: We introduce a new bicategorical model of linear logic based on profunctors between groupoids. This model is a new variation of the usual bicategory of profunctors, obtained by endowing groupoids with additional structure to constrain the profunct... | [] | Train |
44,954 | 17 | Title: A Survey of Developable Surfaces: From Shape Modeling to Manufacturing
Abstract: Developable surfaces are commonly observed in various applications such as architecture, product design, manufacturing, mechanical materials, and data physicalization as well as in the development of tangible interaction and deforma... | [] | Train |
44,955 | 16 | Title: Quality evaluation of point clouds: a novel no-reference approach using transformer-based architecture
Abstract: With the increased interest in immersive experiences, point cloud came to birth and was widely adopted as the first choice to represent 3D media. Besides several distortions that could affect the 3D c... | [] | Validation |
44,956 | 30 | Title: Long-form analogies generated by chatGPT lack human-like psycholinguistic properties
Abstract: Psycholinguistic analyses provide a means of evaluating large language model (LLM) output and making systematic comparisons to human-generated text. These methods can be used to characterize the psycholinguistic proper... | [
7048,
38235
] | Validation |
44,957 | 24 | Title: Dynamic Graph Neural Network with Adaptive Edge Attributes for Air Quality Predictions
Abstract: Air quality prediction is a typical spatio-temporal modeling problem, which always uses different components to handle spatial and temporal dependencies in complex systems separately. Previous models based on time se... | [] | Test |
44,958 | 4 | Title: Exploring placement of intrusion detection systems in rpl-based internet of things
Abstract: Intrusion detection is an indispensable part of RPL security due to its nature opening to attacks from insider attackers. While there are a good deal of studies that analyze different types of attack and propose intrusio... | [] | Train |
44,959 | 4 | Title: Ceibaco: REST API and Single Page Application for the generation and evaluation of bijective S-boxes
Abstract: In this paper we present the first REST API for the generation and evaluation of bijective S-boxes. We also present the first Single Page Application tool for researchers and students that allows the us... | [] | Validation |
44,960 | 3 | Title: Bike Frames: Understanding the Implicit Portrayal of Cyclists in the News
Abstract: Increasing the number of cyclists, whether for general transport or recreation, can provide health improvements and reduce the environmental impact of vehicular transportation. However, the public's perception of cycling may be d... | [
7362
] | Validation |
44,961 | 16 | Title: Learning with Explicit Shape Priors for Medical Image Segmentation
Abstract: Medical image segmentation is a fundamental task for medical image analysis and surgical planning. In recent years, UNet-based networks have prevailed in the field of medical image segmentation. However, convolution-neural networks (CNN... | [] | Test |
44,962 | 16 | Title: Advanced Underwater Image Restoration in Complex Illumination Conditions
Abstract: Underwater image restoration has been a challenging problem for decades since the advent of underwater photography. Most solutions focus on shallow water scenarios, where the scene is uniformly illuminated by the sunlight. However... | [] | Train |
44,963 | 8 | Title: Energy-Efficient WiFi Backscatter Communication for Green IoTs
Abstract: The boom of the Internet of Things has revolutionized people's lives, but it has also resulted in massive resource consumption and environmental pollution. Recently, Green IoT (GIoT) has become a worldwide consensus to address this issue. I... | [] | Test |
44,964 | 2 | Title: RDF Surfaces: Computer Says No
Abstract: Logic can define how agents are provided or denied access to resources, how to interlink resources using mining processes and provide users with choices for possible next steps in a workflow. These decisions are for the most part hidden, internal to machines processing da... | [] | Train |
44,965 | 16 | Title: GMSF: Global Matching Scene Flow
Abstract: We tackle the task of scene flow estimation from point clouds. Given a source and a target point cloud, the objective is to estimate a translation from each point in the source point cloud to the target, resulting in a 3D motion vector field. Previous dominant scene flo... | [
30191
] | Test |
44,966 | 24 | Title: Dataopsy: Scalable and Fluid Visual Exploration using Aggregate Query Sculpting
Abstract: We present aggregate query sculpting (AQS), a faceted visual query technique for large-scale multidimensional data. As a"born scalable"query technique, AQS starts visualization with a single visual mark representing an aggr... | [] | Validation |
44,967 | 4 | Title: FuncTeller: How Well Does eFPGA Hide Functionality?
Abstract: Hardware intellectual property (IP) piracy is an emerging threat to the global supply chain. Correspondingly, various countermeasures aim to protect hardware IPs, such as logic locking, camouflaging, and split manufacturing. However, these countermeas... | [] | Train |
44,968 | 10 | Title: The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence
Abstract: Recent advances in machine learning and AI, including Generative AI and LLMs, are disrupting technological innovation, product development, and society as a whole. AI's contribution to technology can come from multi... | [] | Train |
44,969 | 30 | Title: Semantic Tagging with LSTM-CRF
Abstract: In the present paper, two models are presented namely LSTM-CRF and BERT-LSTM-CRF for semantic tagging of universal semantic tag dataset. The experiments show that the first model is much easier to converge while the second model that leverages BERT embedding, takes a long... | [
29979
] | Validation |
44,970 | 24 | Title: Advancing Community Engaged Approaches to Identifying Structural Drivers of Racial Bias in Health Diagnostic Algorithms
Abstract: Much attention and concern has been raised recently about bias and the use of machine learning algorithms in healthcare, especially as it relates to perpetuating racial discrimination... | [] | Train |
44,971 | 30 | Title: EXnet: Efficient In-context Learning for Data-less Text classification
Abstract: Large pre-trained language models (PLMs) have made significant progress in encoding world knowledge and spawned a new set of learning paradigms including zero-shot, few-shot, and in-context learning. Many language tasks can be model... | [] | Train |
44,972 | 4 | Title: Scalable Attestation of Virtualized Execution Environments in Hybrid- and Multi-Cloud
Abstract: Existing attestation mechanisms lack scalability and support for heterogeneous virtual execution environments (VEEs), such as virtual machines and containers executed inside or outside hardware isolation on different ... | [] | Test |
44,973 | 30 | Title: Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph
Abstract: Conversational AI systems have emerged as key enablers of human-like interactions across diverse sectors. Nevertheless, the balance between linguis... | [
33953,
13700,
13223,
31215,
43641
] | Validation |
44,974 | 4 | Title: Minimize Web Applications vulnerabilities through the early Detection of CRLF Injection
Abstract: Carriage return (CR) and line feed (LF), also known as CRLF injection is a type of vulnerability that allows a hacker to enter special characters into a web application, altering its operation or confusing the admin... | [] | Validation |
44,975 | 6 | Title: Artistic control over the glitch in AI-generated motion capture
Abstract: Artificial intelligence (AI) models are prevalent today and provide a valuable tool for artists. However, a lesser-known artifact that comes with AI models that is not always discussed is the glitch. Glitches occur for various reasons; som... | [] | Validation |
44,976 | 27 | Title: Path-Constrained State Estimation for Rail Vehicles
Abstract: Globally rising demand for transportation by rail is pushing existing infrastructure to its capacity limits, necessitating the development of accurate, robust, and high-frequency positioning systems to ensure safe and efficient train operation. As ind... | [] | Train |
44,977 | 31 | Title: On the Theories Behind Hard Negative Sampling for Recommendation
Abstract: Negative sampling has been heavily used to train recommender models on large-scale data, wherein sampling hard examples usually not only accelerates the convergence but also improves the model accuracy. Nevertheless, the reasons for the e... | [
11150,
18151
] | Train |
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