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
37,078	24	Title: On the Limitations of Physics-Informed Deep Learning: Illustrations Using First-Order Hyperbolic Conservation Law-Based Traffic Flow Models Abstract: Since its introduction in 2017, physics-informed deep learning (PIDL) has garnered growing popularity in understanding the systems governed by physical laws in ter...	[ 23957, 27871 ]	Test
37,079	16	Title: A marker-less human motion analysis system for motion-based biomarker discovery in knee disorders Abstract: In recent years the NHS has been having increased difficulty seeing all low-risk patients, this includes but not limited to suspected osteoarthritis (OA) patients. To help address the increased waiting lis...	[]	Validation
37,080	30	Title: Emulating Reader Behaviors for Fake News Detection Abstract: The wide dissemination of fake news has affected our lives in many aspects, making fake news detection important and attracting increasing attention. Existing approaches make substantial contributions in this field by modeling news from a single-modal ...	[]	Test
37,081	8	Title: Toward immersive communications in 6G Abstract: The sixth generation (6G) networks are expected to enable immersive communications and bridge the physical and the virtual worlds. Integrating extended reality, holography, and haptics, immersive communications will revolutionize how people work, entertain, and com...	[ 18222 ]	Validation
37,082	16	Title: Differentially Private Video Activity Recognition Abstract: In recent years, differential privacy has seen significant advancements in image classification; however, its application to video activity recognition remains under-explored. This paper addresses the challenges of applying differential privacy to video...	[]	Train
37,083	31	Title: Typo-Robust Representation Learning for Dense Retrieval Abstract: Dense retrieval is a basic building block of information retrieval applications. One of the main challenges of dense retrieval in real-world settings is the handling of queries containing misspelled words. A popular approach for handling misspelle...	[]	Test
37,084	24	Title: Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks Abstract: In targeted poisoning attacks, an attacker manipulates an agent-environment interaction to force the agent into adopting a policy of interest, called target policy. Prior work has primarily fo...	[ 14379 ]	Train
37,085	10	Title: The Planner Optimization Problem: Formulations and Frameworks Abstract: Identifying internal parameters for planning is crucial to maximizing the performance of a planner. However, automatically tuning internal parameters which are conditioned on the problem instance is especially challenging. A recent line of w...	[]	Test
37,086	6	Title: Building Trust Profiles in Conditionally Automated Driving Abstract: Trust is crucial for ensuring the safety, security, and widespread adoption of automated vehicles (AVs), and if trust is lacking, drivers and the public may not be willing to use them. This research seeks to investigate trust profiles in order ...	[]	Test
37,087	24	Title: Contextual Reliability: When Different Features Matter in Different Contexts Abstract: Deep neural networks often fail catastrophically by relying on spurious correlations. Most prior work assumes a clear dichotomy into spurious and reliable features; however, this is often unrealistic. For example, most of the ...	[ 28106 ]	Train
37,088	16	Title: A Cross-direction Task Decoupling Network for Small Logo Detection Abstract: Logo detection plays an integral role in many applications. However, handling small logos is still difficult since they occupy too few pixels in the image, which burdens the extraction of discriminative features. The aggregation of smal...	[]	Validation
37,089	30	Title: Which Factors Predict the Chat Experience of a Natural Language Generation Dialogue Service? Abstract: In this paper, we proposed a conceptual model to predict the chat experience in a natural language generation dialog system. We evaluated the model with 120 participants with Partial Least Squares Structural Eq...	[]	Test
37,090	13	Title: Data Aware Neural Architecture Search Abstract: Neural Architecture Search (NAS) is a popular tool for automatically generating Neural Network (NN) architectures. In early NAS works, these tools typically optimized NN architectures for a single metric, such as accuracy. However, in the case of resource constrain...	[]	Train
37,091	34	Title: Towards Generating Hop-constrained s-t Simple Path Graphs Abstract: Graphs have been widely used in real-world applications, in which investigating relations between vertices is an important task. In this paper, we study the problem of generating the k-hop-constrained s-t simple path graph, i.e., the subgraph co...	[]	Train
37,092	3	Title: Disinformation 2.0 in the Age of AI: A Cybersecurity Perspective Abstract: With the explosive advancement of AI technologies in recent years, the scene of the disinformation research is also expected to rapidly change. In this viewpoint article, in particular, we first present the notion of"disinformation 2.0"in...	[]	Validation
37,093	27	Title: Older Adults' Task Preferences for Robot Assistance in the Home Abstract: Artificial intelligence technologies that can assist with at-home tasks have the potential to help older adults age in place. Robot assistance in particular has been applied towards physical and cognitive support for older adults living in...	[]	Test
37,094	24	Title: PAGAR: Imitation Learning with Protagonist Antagonist Guided Adversarial Reward Abstract: Imitation learning (IL) algorithms often rely on inverse reinforcement learning (IRL) to first learn a reward function from expert demonstrations. However, IRL can suffer from identifiability issues and there is no performa...	[]	Train
37,095	6	Title: SHITARA: Sending Haptic Induced Touchable Alarm by Ring-shaped Air vortex Abstract: proof-of-concept device to determine the air vortex ring’s accuracy and noticeability when it hits a DHH person’s hair. We propose SHITARA, a novel accessibility method with air vortex rings that provides a non-contact haptic cue...	[]	Train
37,096	16	Title: PointHPS: Cascaded 3D Human Pose and Shape Estimation from Point Clouds Abstract: Human pose and shape estimation (HPS) has attracted increasing attention in recent years. While most existing studies focus on HPS from 2D images or videos with inherent depth ambiguity, there are surging need to investigate HPS fr...	[]	Validation
37,097	36	Title: Finding Possible and Necessary Winners in Spatial Voting with Partial Information Abstract: We consider spatial voting where candidates are located in the Euclidean $d$-dimensional space and each voter ranks candidates based on their distance from the voter's ideal point. We explore the case where information ab...	[]	Train
37,098	16	Title: Denoising Diffusion Probabilistic Models for Robust Image Super-Resolution in the Wild Abstract: Diffusion models have shown promising results on single-image super-resolution and other image- to-image translation tasks. Despite this success, they have not outperformed state-of-the-art GAN models on the more cha...	[ 26145, 40943, 19954, 500, 25498, 40828 ]	Train
37,099	16	Title: Generalized Unbiased Scene Graph Generation Abstract: Existing Unbiased Scene Graph Generation (USGG) methods only focus on addressing the predicate-level imbalance that high-frequency classes dominate predictions of rare ones, while overlooking the concept-level imbalance. Actually, even if predicates themselve...	[ 30784, 34145, 44932, 31558, 2184, 12779, 30964, 37652, 5915 ]	Validation
37,100	30	Title: Does ChatGPT resemble humans in language use? Abstract: Large language models (LLMs) and LLM-driven chatbots such as ChatGPT have shown remarkable capacities in comprehending and producing language. However, their internal workings remain a black box in cognitive terms, and it is unclear whether LLMs and chatbot...	[ 22115, 19720, 1481, 21485, 14606, 45844, 26357, 6010, 17726 ]	Train
37,101	16	Title: InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data Abstract: Identifying moving objects is a crucial capability for autonomous navigation, consistent map generation, and future trajectory prediction of objects. In this paper, we propose a novel network that addresses the challenge of segmenting movi...	[ 43486 ]	Test
37,102	10	Title: Leveraging Large Language Models for Topic Classification in the Domain of Public Affairs Abstract: The analysis of public affairs documents is crucial for citizens as it promotes transparency, accountability, and informed decision-making. It allows citizens to understand government policies, participate in publ...	[ 13700, 33220, 13510, 20170, 40658, 29396, 12602 ]	Test
37,103	30	Title: Extreme Classification for Answer Type Prediction in Question Answering Abstract: Semantic answer type prediction (SMART) is known to be a useful step towards effective question answering (QA) systems. The SMART task involves predicting the top-$k$ knowledge graph (KG) types for a given natural language question...	[]	Test
37,104	30	Title: What happens before and after: Multi-Event Commonsense in Event Coreference Resolution Abstract: Event coreference models cluster event mentions pertaining to the same real-world event. Recent models rely on contextualized representations to recognize coreference among lexically or contextually similar mentions....	[ 19904, 6061 ]	Train
37,105	23	Title: CONCORD: Clone-Aware Contrastive Learning for Source Code Abstract: Deep Learning (DL) models to analyze source code have shown immense promise during the past few years. More recently, self-supervised pre-training has gained traction for learning generic code representations valuable for many downstream SE task...	[ 36617 ]	Train
37,106	24	Title: Multicalibration as Boosting for Regression Abstract: We study the connection between multicalibration and boosting for squared error regression. First we prove a useful characterization of multicalibration in terms of a ``swap regret'' like condition on squared error. Using this characterization, we give an exc...	[ 19937, 29754, 39407, 30047 ]	Test
37,107	24	Title: Revisiting Test Time Adaptation under Online Evaluation Abstract: This paper proposes a novel online evaluation protocol for Test Time Adaptation (TTA) methods, which penalizes slower methods by providing them with fewer samples for adaptation. TTA methods leverage unlabeled data at test time to adapt to distrib...	[ 32448 ]	Validation
37,108	27	Title: We are all Individuals: The Role of Robot Personality and Human Traits in Trustworthy Interaction Abstract: As robots take on roles in our society, it is important that their appearance, behaviour and personality are appropriate for the job they are given and are perceived favourably by the people with whom they...	[ 16355, 1604 ]	Train
37,109	24	Title: OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting Abstract: Seasonal-trend decomposition is one of the most fundamental concepts in time series analysis that supports various downstream tasks, including time series anomaly detection and forecasting. Howe...	[ 40463 ]	Test
37,110	30	Title: Characterizing and Measuring Linguistic Dataset Drift Abstract: NLP models often degrade in performance when real world data distributions differ markedly from training data. However, existing dataset drift metrics in NLP have generally not considered specific dimensions of linguistic drift that affect model per...	[]	Test
37,111	24	Title: Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning Abstract: Decentralized learning enables serverless training of deep neural networks (DNNs) in a distributed manner on multiple nodes. This allows for the use of large datasets, as well as the ability to train wit...	[]	Validation
37,112	16	Title: Dynamic Video Frame Interpolation with integrated Difficulty Pre-Assessment Abstract: Video frame interpolation(VFI) has witnessed great progress in recent years. While existing VFI models still struggle to achieve a good trade-off between accuracy and efficiency: fast models often have inferior accuracy; accura...	[]	Train
37,113	6	Title: Concept-Based Visual Analysis of Dynamic Textual Data Abstract: Analyzing how interrelated ideas flow within and between multiple social groups helps understand the propagation of information, ideas, and thoughts on social media. The existing dynamic text analysis work on idea flow analysis is mostly based on th...	[]	Train
37,114	27	Title: Constraint Inference in Control Tasks from Expert Demonstrations via Inverse Optimization Abstract: Inferring unknown constraints is a challenging and crucial problem in many robotics applications. When only expert demonstrations are available, it becomes essential to infer the unknown domain constraints to depl...	[]	Train
37,115	16	Title: Improving the performance of object detection by preserving label distribution Abstract: Object detection is a task that performs position identification and label classification of objects in images or videos. The information obtained through this process plays an essential role in various tasks in the field of...	[]	Train
37,116	6	Title: Towards Anatomy Education with Generative AI-based Virtual Assistants in Immersive Virtual Reality Environments Abstract: Anatomy education is essential to support medical students in understanding the morphology, location, and spatial relationships of anatomical structures. Virtual reality (VR) and interactive ...	[ 45827, 35580 ]	Validation
37,117	10	Title: Vertex-based Networks to Accelerate Path Planning Algorithms Abstract: Path planning plays a crucial role in various autonomy applications, and RRT* is one of the leading solutions in this field. In this paper, we propose the utilization of vertex-based networks to enhance the sampling process of RRT*, leading t...	[]	Train
37,118	16	Title: SimNP: Learning Self-Similarity Priors Between Neural Points Abstract: Existing neural field representations for 3D object reconstruction either (1) utilize object-level representations, but suffer from low-quality details due to conditioning on a global latent code, or (2) are able to perfectly reconstruct the ...	[]	Train
37,119	27	Title: RoboCook: Long-Horizon Elasto-Plastic Object Manipulation with Diverse Tools Abstract: Humans excel in complex long-horizon soft body manipulation tasks via flexible tool use: bread baking requires a knife to slice the dough and a rolling pin to flatten it. Often regarded as a hallmark of human cognition, tool u...	[]	Train
37,120	10	Title: Understanding Real-World AI Planning Domains: A Conceptual Framework Abstract: Planning is a pivotal ability of any intelligent system being developed for real-world applications. AI planning is concerned with researching and developing planning systems that automatically compute plans that satisfy some user obj...	[]	Train
37,121	16	Title: PIAT: Parameter Interpolation based Adversarial Training for Image Classification Abstract: Adversarial training has been demonstrated to be the most effective approach to defend against adversarial attacks. However, existing adversarial training methods show apparent oscillations and overfitting issue in the tr...	[]	Train
37,122	30	Title: Reducing Barriers to Self-Supervised Learning: HuBERT Pre-training with Academic Compute Abstract: Self-supervised learning (SSL) has led to great strides in speech processing. However, the resources needed to train these models has become prohibitively large as they continue to scale. Currently, only a few grou...	[ 46133 ]	Train
37,123	9	Title: Hardness of Ruling Out Short Proofs of Kolmogorov Randomness Abstract: A meta-complexity assumption, Feasible Chaitin Incompleteness (FCI), asserts the hardness of ruling out length $t$ proofs that string $x$ is Kolmogorov random (e.g. $x{\in}R$), by analogy to Chaitin's result that proving $x{\in}R$ is typicall...	[]	Train
37,124	24	Title: C(NN)FD - a deep learning framework for turbomachinery CFD analysis Abstract: Deep Learning methods have seen a wide range of successful applications across different industries. Up until now, applications to physical simulations such as CFD (Computational Fluid Dynamics), have been limited to simple test-cases ...	[]	Test
37,125	24	Title: Extending the Forward Forward Algorithm Abstract: The Forward Forward algorithm, proposed by Geoffrey Hinton in November 2022, is a novel method for training neural networks as an alternative to backpropagation. In this project, we replicate Hinton's experiments on the MNIST dataset, and subsequently extend the ...	[ 10762 ]	Train
37,126	16	Title: FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention Abstract: Diffusion models excel at text-to-image generation, especially in subject-driven generation for personalized images. However, existing methods are inefficient due to the subject-specific fine-tuning, which is computationa...	[ 10624, 29536, 7458, 30402, 35940, 24550, 29389, 45933, 20687, 27184, 28532, 26809, 43867, 18205, 14047 ]	Train
37,127	16	Title: Improving Anomaly Segmentation with Multi-Granularity Cross-Domain Alignment Abstract: Anomaly segmentation plays a crucial role in identifying anomalous objects within images, which facilitates the detection of road anomalies for autonomous driving. Although existing methods have shown impressive results in ano...	[ 20371, 8253 ]	Train
37,128	16	Title: A Fast Fourier Convolutional Deep Neural Network For Accurate and Explainable Discrimination Of Wheat Yellow Rust And Nitrogen Deficiency From Sentinel-2 Time-Series Data Abstract: Accurate and timely detection of plant stress is essential for yield protection, allowing better-targeted intervention strategies. R...	[ 17085 ]	Train
37,129	27	Title: A Unified Perspective on Multiple Shooting In Differential Dynamic Programming Abstract: Differential Dynamic Programming (DDP) is an efficient computational tool for solving nonlinear optimal control problems. It was originally designed as a single shooting method and thus is sensitive to the initial guess supp...	[]	Train
37,130	24	Title: Heterogeneous Federated Learning via Personalized Generative Networks Abstract: Federated Learning (FL) allows several clients to construct a common global machine-learning model without having to share their data. FL, however, faces the challenge of statistical heterogeneity between the client's data, which deg...	[ 10783 ]	Train
37,131	29	Title: Database management system performance comparisons: A systematic survey Abstract: Efficiency has been a pivotal aspect of the software industry since its inception, as a system that serves the end-user fast, and the service provider cost-efficiently benefits all parties. A database management system (DBMS) is an...	[]	Validation
37,132	24	Title: Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness Abstract: In this paper, we develop a new criterion,"insufficiently justified disparate impact"(IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, u...	[]	Validation
37,133	16	Title: A Simple Framework for Open-Vocabulary Segmentation and Detection Abstract: We present OpenSeeD, a simple Open-vocabulary Segmentation and Detection framework that jointly learns from different segmentation and detection datasets. To bridge the gap of vocabulary and annotation granularity, we first introduce a p...	[ 17633, 32995, 37987, 25222, 37254, 12523, 5583, 43701, 19386, 4443 ]	Test
37,134	27	Title: 6-DoF Robotic Grasping with Transformer Abstract: —Robotic grasping aims to detect graspable points and their corresponding gripper conﬁgurations in a particular scene, and is fundamental for robot manipulation. Existing research works have demonstrated the potential of using a transformer model for robotic gras...	[]	Train
37,135	16	Title: Deep Learning on Implicit Neural Representations of Shapes Abstract: Implicit Neural Representations (INRs) have emerged in the last few years as a powerful tool to encode continuously a variety of different signals like images, videos, audio and 3D shapes. When applied to 3D shapes, INRs allow to overcome the f...	[ 44052, 2037, 30182 ]	Train
37,136	30	Title: Deep Dive into the Language of International Relations: NLP-based Analysis of UNESCO's Summary Records Abstract: Cultural heritage is an arena of international relations that interests all states worldwide. The inscription process on the UNESCO World Heritage List and the UNESCO Representative List of the Intang...	[ 37006 ]	Train
37,137	16	Title: 6D Object Pose Estimation from Approximate 3D Models for Orbital Robotics Abstract: We present a novel technique to estimate the 6D pose of objects from single images where the 3D geometry of the object is only given approximately and not as a precise 3D model. To achieve this, we employ a dense 2D-to-3D corresp...	[ 22369 ]	Test
37,138	16	Title: Evolutionary Augmentation Policy Optimization for Self-supervised Learning Abstract: Self-supervised Learning (SSL) is a machine learning algorithm for pretraining Deep Neural Networks (DNNs) without requiring manually labeled data. The central idea of this learning technique is based on an auxiliary stage aka p...	[]	Test
37,139	16	Title: SuperpixelGraph: Semi-automatic generation of building footprint through semantic-sensitive superpixel and neural graph networks Abstract: Most urban applications necessitate building footprints in the form of concise vector graphics with sharp boundaries rather than pixel-wise raster images. This need contrasts...	[]	Test
37,140	24	Title: Balanced Audiovisual Dataset for Imbalance Analysis Abstract: The imbalance problem is widespread in the field of machine learning, which also exists in multimodal learning areas caused by the intrinsic discrepancy between modalities of samples. Recent works have attempted to solve the modality imbalance problem...	[]	Test
37,141	28	Title: The greedy side of the LASSO: New algorithms for weighted sparse recovery via loss function-based orthogonal matching pursuit Abstract: We propose a class of greedy algorithms for weighted sparse recovery by considering new loss function-based generalizations of Orthogonal Matching Pursuit (OMP). Given a (regula...	[]	Train
37,142	10	Title: Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification Abstract: Patent classification aims to assign multiple International Patent Classification (IPC) codes to a given patent. Recent methods for automatically classifying patents mainly focus on analyzing the text descriptions of...	[]	Train
37,143	28	Title: Spiking Neural Networks for Detecting Satellite-Based Internet-of-Things Signals Abstract: With the rapid growth of IoT networks, ubiquitous coverage is becoming increasingly necessary. Low Earth Orbit (LEO) satellite constellations for IoT have been proposed to provide coverage to regions where terrestrial syst...	[ 23388 ]	Validation
37,144	24	Title: Solving Falkner-Skan type equations via Legendre and Chebyshev Neural Blocks Abstract: In this paper, a new deep-learning architecture for solving the non-linear Falkner-Skan equation is proposed. Using Legendre and Chebyshev neural blocks, this approach shows how orthogonal polynomials can be used in neural net...	[]	Train
37,145	5	Title: Learned Lock-free Search Data Structures Abstract: Non-blocking search data structures offer scalability with a progress guarantee on high-performance multi-core architectures. In the recent past,"learned queries"have gained remarkable attention. It refers to predicting the rank of a key computed by machine lear...	[]	Validation
37,146	16	Title: Find Beauty in the Rare: Contrastive Composition Feature Clustering for Nontrivial Cropping Box Regression Abstract: Automatic image cropping algorithms aim to recompose images like human-being photographers by generating the cropping boxes with improved composition quality. Cropping box regression approaches le...	[]	Validation
37,147	16	Title: A Siamese-based Verification System for Open-set Architecture Attribution of Synthetic Images Abstract: Despite the wide variety of methods developed for synthetic image attribution, most of them can only attribute images generated by models or architectures included in the training set and do not work with unkn...	[ 6683, 6367 ]	Train
37,148	24	Title: Widespread Increases in Future Wildfire Risk to Global Forest Carbon Offset Projects Revealed by Explainable AI Abstract: Carbon offset programs are critical in the fight against climate change. One emerging threat to the long-term stability and viability of forest carbon offset projects is wildfires, which can ...	[]	Train
37,149	28	Title: Static Power Consumption Modeling and Measurement of Reconfigurable Intelligent Surfaces Abstract: Reconfigurable intelligent surfaces (RISs) are anticipated to transform wireless communication in a way that is both economical and energy efficient. Revealing the practical power consumption characteristics of RIS...	[]	Validation
37,150	28	Title: Space MIMO: Direct Unmodified Handheld to Multi-Satellite Communication Abstract: This paper examines the uplink transmission of a single-antenna handsheld user to a cluster of satellites, with a focus on utilizing the inter-satellite links to enable cooperative signal detection. Two cases are studied: one with ...	[]	Train
37,151	38	Title: The Many Publics of Science: Using Altmetrics to Identify Common Communication Channels by Scientific field Abstract: Altmetrics have led to new quantitative studies of science through social media interactions. However, there are no models of science communication that respond to the multiplicity of non-academi...	[]	Train
37,152	16	Title: ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation Abstract: We present a comprehensive solution to learn and improve text-to-image models from human preference feedback. To begin with, we build ImageReward -- the first general-purpose text-to-image human preference reward model ...	[ 6145, 13953, 10768, 42137, 28580, 7850, 26673, 7732, 22201, 2502, 10056, 3538, 8915, 21714, 14047, 32108, 36844, 17647, 36084, 44537, 43771 ]	Train
37,153	24	Title: Time-series Anomaly Detection based on Difference Subspace between Signal Subspaces Abstract: This paper proposes a new method for anomaly detection in time-series data by incorporating the concept of difference subspace into the singular spectrum analysis (SSA). The key idea is to monitor slight temporal variat...	[]	Train
37,154	24	Title: One-class systems seamlessly fit in the forward-forward algorithm Abstract: The forward-forward algorithm presents a new method of training neural networks by updating weights during an inference, performing parameter updates for each layer individually. This immediately reduces memory requirements during traini...	[]	Train
37,155	16	Title: An End-to-End Multi-Task Learning Model for Image-based Table Recognition Abstract: Image-based table recognition is a challenging task due to the diversity of table styles and the complexity of table structures. Most of the previous methods focus on a non-end-to-end approach which divides the problem into two s...	[ 11432 ]	Train
37,156	16	Title: New Insights on Relieving Task-Recency Bias for Online Class Incremental Learning Abstract: To imitate the ability of keeping learning of human, continual learning which can learn from a never-ending data stream has attracted more interests recently. In all settings, the online class incremental learning (CIL), ...	[ 45354, 24011 ]	Train
37,157	24	Title: Detecting Signs of Model Change with Continuous Model Selection Based on Descriptive Dimensionality Abstract: We address the issue of detecting changes of models that lie behind a data stream. The model refers to an integer-valued structural information such as the number of free parameters in a parametric model...	[]	Train
37,158	5	Title: Fast and Straggler-Tolerant Distributed SGD with Reduced Computation Load Abstract: In distributed machine learning, a central node outsources computationally expensive calculations to external worker nodes. The properties of optimization procedures like stochastic gradient descent (SGD) can be leveraged to miti...	[]	Validation
37,159	27	Title: Evolutionary-Based Online Motion Planning Framework for Quadruped Robot Jumping Abstract: Offline evolutionary-based methodologies have supplied a successful motion planning framework for the quadrupedal jump. However, the time-consuming computation caused by massive population evolution in offline evolutionary-...	[]	Validation
37,160	39	Title: Matrices inducing generalized metric on sequences Abstract: nan	[]	Train
37,161	24	Title: Three-way Imbalanced Learning based on Fuzzy Twin SVM Abstract: Three-way decision (3WD) is a powerful tool for granular computing to deal with uncertain data, commonly used in information systems, decision-making, and medical care. Three-way decision gets much research in traditional rough set models. However, ...	[]	Test
37,162	16	Title: Decomposed Cross-Modal Distillation for RGB-based Temporal Action Detection Abstract: Temporal action detection aims to predict the time intervals and the classes of action instances in the video. Despite the promising performance, existing two-stream models exhibit slow inference speed due to their reliance on ...	[]	Train
37,163	24	Title: On Dynamic Regret and Constraint Violations in Constrained Online Convex Optimization Abstract: A constrained version of the online convex optimization (OCO) problem is considered. With slotted time, for each slot, first an action is chosen. Subsequently the loss function and the constraint violation penalty eva...	[]	Train
37,164	4	Title: Pentimento: Data Remanence in Cloud FPGAs Abstract: Cloud FPGAs strike an alluring balance between computational efficiency, energy efficiency, and cost. It is the flexibility of the FPGA architecture that enables these benefits, but that very same flexibility that exposes new security vulnerabilities. We show t...	[]	Train
37,165	16	Title: Out-of-distribution Few-shot Learning For Edge Devices without Model Fine-tuning Abstract: Few-shot learning (FSL) via customization of a deep learning network with limited data has emerged as a promising technique to achieve personalized user experiences on edge devices. However, existing FSL methods primarily ...	[]	Train
37,166	16	Title: Generalized Lightness Adaptation with Channel Selective Normalization Abstract: Lightness adaptation is vital to the success of image processing to avoid unexpected visual deterioration, which covers multiple aspects, e.g., low-light image enhancement, image retouching, and inverse tone mapping. Existing methods...	[ 9798 ]	Validation
37,167	23	Title: Exposing Software Engineering Students to Stressful Projects: Does Diversity Matter? Abstract: Software development teams have to face stress caused by deadlines, staff turnover, or individual differences in commitment, expertise, and time zones. While students are typically taught the theory of software project...	[]	Validation
37,168	24	Title: Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding Abstract: Soft-thresholding has been widely used in neural networks. Its basic network structure is a two-layer convolution neural network with soft-thresholding. Due to the network's nature of nonlinearity and nonconve...	[]	Train
37,169	16	Title: FaceFusion: Exploiting Full Spectrum of Multiple Datasets Abstract: The size of training dataset is known to be among the most dominating aspects of training high-performance face recognition embedding model. Building a large dataset from scratch could be cumbersome and time-intensive, while combining multiple a...	[]	Validation
37,170	16	Title: Polygon Detection for Room Layout Estimation using Heterogeneous Graphs and Wireframes Abstract: This paper presents a neural network based semantic plane detection method utilizing polygon representations. The method can for example be used to solve room layout estimations tasks. The method is built on, combine...	[]	Validation
37,171	10	Title: Solving Quantum-Inspired Perfect Matching Problems via Tutte's Theorem-Based Hybrid Boolean Constraints Abstract: Determining the satisfiability of Boolean constraint-satisfaction problems with different types of constraints, that is hybrid constraints, is a well-studied problem with important applications. We s...	[]	Test
37,172	16	Title: Soil Image Segmentation Based on Mask R-CNN Abstract: The complex background in the soil image collected in the field natural environment will affect the subsequent soil image recognition based on machine vision. Segmenting the soil center area from the soil image can eliminate the influence of the complex backg...	[]	Train
37,173	10	Title: On Kenn's Rule of Combination Applied to Breast Cancer Precision Therapy Abstract: This short technical note points out an erroneous claim about a new rule of combination of basic belief assignments presented recently by Kenn et al. in 2023, referred as Kenn's rule of combination (or just as KRC for short). We p...	[]	Train
37,174	24	Title: Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion Abstract: This paper presents a comprehensive theoretical analysis of the graph p-Laplacian regularized framelet network (pL-UFG) to establish a solid understanding of its properties. ...	[ 16466, 26770 ]	Train
37,175	24	Title: Distribution Shift Inversion for Out-of-Distribution Prediction Abstract: Machine learning society has witnessed the emergence of a myriad of Out-of-Distribution (OoD) algorithms, which address the distribution shift between the training and the testing distribution by searching for a unified predictor or invari...	[ 20232, 41654 ]	Train
37,176	6	Title: Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining Abstract: Personalized head and neck cancer therapeutics have greatly improved survival rates for patients, but are often leading to understudied long-lasting symptoms which affect quali...	[]	Train
37,177	30	Title: Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages Abstract: We introduce the Universal Speech Model (USM), a single large model that performs automatic speech recognition (ASR) across 100+ languages. This is achieved by pre-training the encoder of the model on a large unlabeled multilingual d...	[ 28771, 18777, 26825, 4650, 7052, 11918, 8015, 2960, 13807, 19089, 7059, 30542, 31219, 11199, 476, 1983 ]	Test

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