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
35,278	24	Title: Filter-Aware Model-Predictive Control Abstract: Partially-observable problems pose a trade-off between reducing costs and gathering information. They can be solved optimally by planning in belief space, but that is often prohibitively expensive. Model-predictive control (MPC) takes the alternative approach of us...	[]	Train
35,279	22	Title: Amortizing Pragmatic Program Synthesis with Rankings Abstract: In program synthesis, an intelligent system takes in a set of user-generated examples and returns a program that is logically consistent with these examples. The usage of Rational Speech Acts (RSA) framework has been successful in building \emph{prag...	[ 31042 ]	Train
35,280	24	Title: Supporting Future Electrical Utilities: Using Deep Learning Methods in EMS and DMS Algorithms Abstract: Electrical power systems are increasing in size, complexity, as well as dynamics due to the growing integration of renewable energy resources, which have sporadic power generation. This necessitates the develo...	[]	Train
35,281	17	Title: Subspace Culling for Ray-Box Intersection Abstract: Ray tracing is an essential operation for realistic image synthesis. The acceleration of ray tracing has been studied for a long period of time because algorithms such as light transport simulations require a large amount of ray tracing. One of the major approa...	[]	Validation
35,282	16	Title: Learning Object-Centric Neural Scattering Functions for Free-viewpoint Relighting and Scene Composition Abstract: Photorealistic object appearance modeling from 2D images is a constant topic in vision and graphics. While neural implicit methods (such as Neural Radiance Fields) have shown high-fidelity view synth...	[ 37860, 29526 ]	Train
35,283	6	Title: Digitization of Pathology Labs: A Review of Lessons Learned Abstract: Pathology laboratories are increasingly using digital workflows. This has the potential of increasing lab efficiency, but the digitization process also involves major challenges. Several reports have been published describing the individual ex...	[]	Train
35,284	24	Title: Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate Training Abstract: Adversarial examples (AEs) for DNNs have been shown to be transferable: AEs that successfully fool white-box surrogate models can also deceive other black-box models with different architect...	[ 13642, 41578, 4052, 12309, 27004 ]	Train
35,285	30	Title: Uncovering Drift in Textual Data: An Unsupervised Method for Detecting and Mitigating Drift in Machine Learning Models Abstract: Drift in machine learning refers to the phenomenon where the statistical properties of data or context, in which the model operates, change over time leading to a decrease in its perfo...	[]	Train
35,286	16	Title: AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation Abstract: During interactive segmentation, a model and a user work together to delineate objects of interest in a 3D point cloud. In an iterative process, the model assigns each data point to an object (or the background), while the user corrects...	[ 18070 ]	Validation
35,287	16	Title: Rigidity-Aware Detection for 6D Object Pose Estimation Abstract: Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus produci...	[ 20768, 21802 ]	Validation
35,288	24	Title: V2N Service Scaling with Deep Reinforcement Learning Abstract: The fifth generation (5G) of wireless networks is set out to meet the stringent requirements of vehicular use cases. Edge computing resources can aid in this direction by moving processing closer to end-users, reducing latency. However, given the sto...	[ 34293 ]	Train
35,289	23	Title: An Assessment of ChatGPT on Log Data Abstract: Recent development of large language models (LLMs), such as ChatGPT has been widely applied to a wide range of software engineering tasks. Many papers have reported their analysis on the potential advantages and limitations of ChatGPT for writing code, summarization...	[ 6535, 615, 38543, 23252, 26357, 40538, 43769, 12602, 16827 ]	Test
35,290	27	Title: High-Speed Autonomous Racing Using Trajectory-Aided Deep Reinforcement Learning Abstract: The classical method of autonomous racing uses real-time localisation to follow a precalculated optimal trajectory. In contrast, end-to-end deep reinforcement learning (DRL) can train agents to race using only raw LiDAR sca...	[ 26884 ]	Test
35,291	24	Title: Numerical Methods For PDEs Over Manifolds Using Spectral Physics Informed Neural Networks Abstract: We introduce an approach for solving PDEs over manifolds using physics informed neural networks whose architecture aligns with spectral methods. The networks are trained to take in as input samples of an initial c...	[]	Train
35,292	24	Title: Guiding Pretraining in Reinforcement Learning with Large Language Models Abstract: Reinforcement learning algorithms typically struggle in the absence of a dense, well-shaped reward function. Intrinsically motivated exploration methods address this limitation by rewarding agents for visiting novel states or tran...	[ 17153, 37252, 21893, 651, 23307, 14991, 2578, 21782, 11292, 41247, 45736, 27437, 16194, 3526, 9414, 7632, 38353, 8157, 5484, 4470, 15993, 18812 ]	Train
35,293	16	Title: A Convolutional Vision Transformer for Semantic Segmentation of Side-Scan Sonar Data Abstract: Distinguishing among different marine benthic habitat characteristics is of key importance in a wide set of seabed operations ranging from installations of oil rigs to laying networks of cables and monitoring the impac...	[ 5878 ]	Train
35,294	16	Title: Multimodal Transformer for Material Segmentation Abstract: Leveraging information across diverse modalities is known to enhance performance on multimodal segmentation tasks. However, effectively fusing information from different modalities remains challenging due to the unique characteristics of each modality. I...	[ 17515 ]	Train
35,295	33	Title: Optimal Approximate Minimization of One-Letter Weighted Finite Automata Abstract: In this paper, we study the approximate minimization problem of weighted finite automata (WFAs): to compute the best possible approximation of a WFA given a bound on the number of states. By reformulating the problem in terms of Ha...	[]	Train
35,296	23	Title: COMEX: A Tool for Generating Customized Source Code Representations Abstract: Learning effective representations of source code is critical for any Machine Learning for Software Engineering (ML4SE) system. Inspired by natural language processing, large language models (LLMs) like Codex and CodeGen treat code as ...	[]	Validation
35,297	16	Title: HybridMIM: A Hybrid Masked Image Modeling Framework for 3D Medical Image Segmentation Abstract: Masked image modeling (MIM) with transformer backbones has recently been exploited as a powerful self-supervised pre-training technique. The existing MIM methods adopt the strategy to mask random patches of the image ...	[]	Validation
35,298	16	Title: Cross-Task Attention Network: Improving Multi-Task Learning for Medical Imaging Applications Abstract: Multi-task learning (MTL) is a powerful approach in deep learning that leverages the information from multiple tasks during training to improve model performance. In medical imaging, MTL has shown great potenti...	[]	Train
35,299	24	Title: Using Models Based on Cognitive Theory to Predict Human Behavior in Traffic: A Case Study Abstract: The development of automated vehicles has the potential to revolutionize transportation, but they are currently unable to ensure a safe and time-efficient driving style. Reliable models predicting human behavior a...	[ 6435, 44004, 29686 ]	Train
35,300	24	Title: An information-Theoretic Approach to Semi-supervised Transfer Learning Abstract: Transfer learning is a valuable tool in deep learning as it allows propagating information from one"source dataset"to another"target dataset", especially in the case of a small number of training examples in the latter. Yet, discrep...	[]	Test
35,301	13	Title: Cardiac Arrhythmia Detection using Artificial Neural Network Abstract: The prime purpose of this project is to develop a portable cardiac abnormality monitoring device which can drastically improvise the quality of the monitoring and the overall safety of the device. While a generic, low cost, wearable battery p...	[]	Train
35,302	24	Title: Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations Abstract: Robust reinforcement learning (RL) seeks to train policies that can perform well under environment perturbations or adversarial attacks. Existing approaches typically assume that the space of possible perturbations re...	[]	Train
35,303	16	Title: MonoEdge: Monocular 3D Object Detection Using Local Perspectives Abstract: We propose a novel approach for monocular 3D object detection by leveraging local perspective effects of each object. While the global perspective effect shown as size and position variations has been exploited for monocular 3D detection ...	[]	Validation
35,304	8	Title: PolarStar: Expanding the Scalability Horizon of Diameter-3 Networks Abstract: In this paper, we present PolarStar, a novel family of diameter-3 network topologies derived from the star product of two low-diameter factor graphs. The proposed PolarStar construction gives the largest known diameter-3 network topolo...	[]	Train
35,305	24	Title: Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations Abstract: Physics-informed neural networks have emerged as an alternative method for solving partial differential equations. However, for complex problems, the training of such networks can still require high-fid...	[]	Train
35,306	16	Title: Segmentation of Industrial Burner Flames: A Comparative Study from Traditional Image Processing to Machine and Deep Learning Abstract: In many industrial processes, such as power generation, chemical production, and waste management, accurately monitoring industrial burner flame characteristics is crucial for sa...	[ 34977 ]	Test
35,307	30	Title: Incorporating L2 Phonemes Using Articulatory Features for Robust Speech Recognition Abstract: The limited availability of non-native speech datasets presents a major challenge in automatic speech recognition (ASR) to narrow the performance gap between native and non-native speakers. To address this, the focus of...	[]	Train
35,308	28	Title: An Optimal Two-Step Decoding at Receivers with Side Information in PSK-Modulated Index Coding Abstract: This paper studies noisy index coding problems over single-input single-output broadcast channels. The codewords from a chosen index code of length $N$ are transmitted after $2^N$-PSK modulation over an AWGN c...	[]	Train
35,309	34	Title: Linear Programming based Reductions for Multiple Visit TSP and Vehicle Routing Problems Abstract: Multiple TSP ($\mathrm{mTSP}$) is a important variant of $\mathrm{TSP}$ where a set of $k$ salesperson together visit a set of $n$ cities. The $\mathrm{mTSP}$ problem has applications to many real life applications ...	[]	Validation
35,310	10	Title: Trash to Treasure: Using text-to-image models to inform the design of physical artefacts Abstract: Text-to-image generative models have recently exploded in popularity and accessibility. Yet so far, use of these models in creative tasks that bridge the 2D digital world and the creation of physical artefacts has ...	[ 7973 ]	Validation
35,311	31	Title: Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search Abstract: In this paper, we present a prompting framework called LLMCS that leverages large language models, such as code-davinci-002 of GPT-3, to perform few-shot conversational query rewriting for conversa...	[ 2771, 397, 9318, 31703 ]	Train
35,312	8	Title: On Modeling Network Slicing Communication Resources with SARSA Optimization Abstract: Network slicing is a crucial enabler to support the composition and deployment of virtual network infrastructures required by the dynamic behavior of networks like 5G/6G mobile networks, IoT-aware networks, e-health systems, an...	[]	Test
35,313	33	Title: Complete Multiparty Session Type Projection with Automata Abstract: Multiparty session types (MSTs) are a type-based approach to verifying communication protocols. Central to MSTs is a projection operator: a partial function that maps protocols represented as global types to correct-by-construction implementatio...	[ 25182 ]	Train
35,314	16	Title: Simple Baselines for Interactive Video Retrieval with Questions and Answers Abstract: To date, the majority of video retrieval systems have been optimized for a"single-shot"scenario in which the user submits a query in isolation, ignoring previous interactions with the system. Recently, there has been renewed in...	[]	Train
35,315	34	Title: The Complexity of Cluster Vertex Splitting and Company Abstract: Clustering a graph when the clusters can overlap can be seen from three different angles: We may look for cliques that cover the edges of the graph, we may look to add or delete few edges to uncover the cluster structure, or we may split vertices t...	[ 30023 ]	Validation
35,316	4	Title: Blocking JavaScript without Breaking the Web: An Empirical Investigation Abstract: Modern websites heavily rely on JavaScript (JS) to implement legitimate functionality as well as privacy-invasive advertising and tracking. Browser extensions such as NoScript block any script not loaded by a trusted list of endpo...	[]	Train
35,317	16	Title: XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing Abstract: The hardware-efficiency and accuracy of Deep Neural Networks (DNNs) implemented on In-memory Computing (IMC) architectures primarily depend on the DNN architecture and the peripheral circuit par...	[]	Train
35,318	16	Title: Natural scene reconstruction from fMRI signals using generative latent diffusion Abstract: In neural decoding research, one of the most intriguing topics is the reconstruction of perceived natural images based on fMRI signals. Previous studies have succeeded in re-creating different aspects of the visuals, such ...	[]	Train
35,319	27	Title: Learning to Explore Indoor Environments using Autonomous Micro Aerial Vehicles Abstract: In this paper, we address the challenge of exploring unknown indoor aerial environments using autonomous aerial robots with Size Weight and Power (SWaP) constraints. The SWaP constraints induce limits on mission time requiri...	[]	Train
35,320	24	Title: GQFedWAvg: Optimization-Based Quantized Federated Learning in General Edge Computing Systems Abstract: The optimal implementation of federated learning (FL) in practical edge computing systems has been an outstanding problem. In this paper, we propose an optimization-based quantized FL algorithm, which can appro...	[]	Train
35,321	24	Title: Regeneration Learning: A Learning Paradigm for Data Generation Abstract: Machine learning methods for conditional data generation usually build a mapping from source conditional data X to target data Y. The target Y (e.g., text, speech, music, image, video) is usually high-dimensional and complex, and contains i...	[ 4088, 27850, 28532 ]	Validation
35,322	24	Title: Deep Generative Modeling with Backward Stochastic Differential Equations Abstract: This paper proposes a novel deep generative model, called BSDE-Gen, which combines the flexibility of backward stochastic differential equations (BSDEs) with the power of deep neural networks for generating high-dimensional comple...	[ 24466 ]	Train
35,323	16	Title: A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking Abstract: The robustness of deep neural networks is usually lacking under adversarial examples, common corruptions, and distribution shifts, which becomes an important research problem in the development of deep learn...	[ 6551, 18347, 44944, 10583, 39263 ]	Train
35,324	16	Title: Collaborative Feature Learning for Fine-grained Facial Forgery Detection and Segmentation Abstract: Detecting maliciously falsified facial images and videos has attracted extensive attention from digital-forensics and computer-vision communities. An important topic in manipulation detection is the localization o...	[ 31769, 25474 ]	Train
35,325	27	Title: Constrained Reinforcement Learning using Distributional Representation for Trustworthy Quadrotor UAV Tracking Control Abstract: Simultaneously accurate and reliable tracking control for quadrotors in complex dynamic environments is challenging. As aerodynamics derived from drag forces and moment variations are c...	[ 8946 ]	Train
35,326	16	Title: Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation Abstract: Large text-to-image diffusion models have exhibited impressive proficiency in generating high-quality images. However, when applying these models to video domain, ensuring temporal consistency across video frames remains a formidable ch...	[ 20960, 11841, 13474, 11655, 10216, 12841, 14956, 40979, 23669, 17526, 34074 ]	Validation
35,327	16	Title: Open-vocabulary Object Segmentation with Diffusion Models Abstract: The goal of this paper is to extract the visual-language correspondence from a pre-trained text-to-image diffusion model, in the form of segmentation map, i.e., simultaneously generating images and segmentation masks for the corresponding visual...	[ 5807, 17938, 45080, 42907, 13660, 7678 ]	Test
35,328	27	Title: RoMo-HER: Robust Model-based Hindsight Experience Replay Abstract: Sparse rewards are one of the factors leading to low sample efficiency in multi-goal reinforcement learning (RL). Based on Hindsight Experience Replay (HER), model-based relabeling methods have been proposed to relabel goals using virtual traject...	[]	Train
35,329	24	Title: Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff Abstract: Previous work has shown that DNNs with large depth $L$ and $L_{2}$-regularization are biased towards learning low-dimensional representations of the inputs, which can be interpreted as minimizing a notion of rank $R^{(0)}(f)...	[]	Train
35,330	7	Title: Reduced order modelling using parameterized non-uniform boundary conditions in room acoustic simulations Abstract: Quick simulations for iterative evaluations of multi-design variables and boundary conditions are essential to find the optimal acoustic conditions in building design. We propose to use the reduced ...	[]	Train
35,331	39	Title: On the Complexity of Finding a Sparse Connected Spanning Subgraph in a non-Uniform Failure Model Abstract: We study a generalization of the classic Spanning Tree problem that allows for a non-uniform failure model. More precisely, edges are either \emph{safe} or \emph{unsafe} and we assume that failures only aff...	[]	Train
35,332	31	Title: Capturing Popularity Trends: A Simplistic Non-Personalized Approach for Enhanced Item Recommendation Abstract: Recommender systems have been gaining increasing research attention over the years. Most existing recommendation methods focus on capturing users' personalized preferences through historical user-item i...	[]	Test
35,333	26	Title: Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation Abstract: The multi-criteria (MC) recommender system, which leverages MC rating information in a wide range of e-commerce areas, is ubiquitous nowadays. Surprisingly, although graph ...	[]	Train
35,334	27	Title: Base Placement Optimization for Coverage Mobile Manipulation Tasks Abstract: Base placement optimization (BPO) is a fundamental capability for mobile manipulation and has been researched for decades. However, it is still very challenging for some reasons. First, compared with humans, current robots are extremely...	[]	Train
35,335	16	Title: KST-Mixer: kinematic spatio-temporal data mixer for colon shape estimation Abstract: ABSTRACT We propose a spatio-temporal mixing kinematic data estimation method to estimate the shape of the colon with deformations caused by colonoscope insertion. Endoscope tracking or a navigation system that navigates physic...	[]	Test
35,336	24	Title: Preserving Linear Separability in Continual Learning by Backward Feature Projection Abstract: Catastrophic forgetting has been a major challenge in continual learning, where the model needs to learn new tasks with limited or no access to data from previously seen tasks. To tackle this challenge, methods based on...	[ 32570, 24719 ]	Test
35,337	16	Title: Face Clustering for Connection Discovery from Event Images Abstract: Social graphs are very useful for many applications, such as recommendations and community detections. However, they are only accessible to big social network operators due to both data availability and privacy concerns. Event images also captu...	[]	Train
35,338	24	Title: Non-Stochastic CDF Estimation Using Threshold Queries Abstract: Estimating the empirical distribution of a scalar-valued data set is a basic and fundamental task. In this paper, we tackle the problem of estimating an empirical distribution in a setting with two challenging features. First, the algorithm does not...	[ 45387 ]	Train
35,339	23	Title: Replicability Study: Corpora For Understanding Simulink Models & Projects Abstract: Background: Empirical studies on widely used model-based development tools such as MATLAB/Simulink are limited despite the tools' importance in various industries. Aims: The aim of this paper is to investigate the reproducibility...	[]	Train
35,340	27	Title: RobotKube: Orchestrating Large-Scale Cooperative Multi-Robot Systems with Kubernetes and ROS Abstract: Modern cyber-physical systems (CPS) such as Cooperative Intelligent Transport Systems (C-ITS) are increasingly defined by the software which operates these systems. In practice, microservice architectures can b...	[ 7065, 20559 ]	Train
35,341	27	Title: High-Speed High-Accuracy Spatial Curve Tracking Using Motion Primitives in Industrial Robots Abstract: Industrial robots are increasingly deployed in applications requiring an end effector tool to closely track a specified path, such as in spraying and welding. Performance and productivity present possibly confl...	[]	Validation
35,342	4	Title: Joint Space-Time Sparsity Based Jamming Detection for Mission-Critical mMTC Networks Abstract: For mission-critical massive machine-type communications (mMTC) applications, the messages are required to be delivered in real-time. However, due to the weak security protection capabilities of the low-cost and low-co...	[]	Train
35,343	27	Title: Underwater Autonomous Tank Cleaning Rover Abstract: In order to keep aquatic ecosystems safe and healthy, it is imperative that cleaning be done frequently. This research suggests the use of autonomous underwater rovers for effective underwater cleaning as a novel approach to this issue. The enhanced sensing and...	[]	Validation
35,344	16	Title: Toward Sufficient Spatial-Frequency Interaction for Gradient-aware Underwater Image Enhancement Abstract: Underwater images suffer from complex and diverse degradation, which inevitably affects the performance of underwater visual tasks. However, most existing learning-based Underwater image enhancement (UIE) me...	[ 32967 ]	Train
35,345	10	Title: Efficient micro data centres deployment for mobile healthcare monitoring systems in IoT urban scenarios Abstract: ABSTRACT The Internet of Things (IoT) has caused an exponential increase in the number of connected devices. This brings the Internet closer to everyday activities and enables data collection that ca...	[]	Validation
35,346	30	Title: D-CALM: A Dynamic Clustering-based Active Learning Approach for Mitigating Bias Abstract: Despite recent advancements, NLP models continue to be vulnerable to bias. This bias often originates from the uneven distribution of real-world data and can propagate through the annotation process. Escalated integration o...	[ 25017 ]	Train
35,347	22	Title: Worst-Case Input Generation for Concurrent Programs under Non-Monotone Resource Metrics Abstract: Worst-case input generation aims to automatically generate inputs that exhibit the worst-case performance of programs. It has several applications, and can, for example, detect vulnerabilities to denial-of-service a...	[]	Train
35,348	16	Title: Norm-guided latent space exploration for text-to-image generation Abstract: Text-to-image diffusion models show great potential in synthesizing a large variety of concepts in new compositions and scenarios. However, their latent seed space is still not well understood and has been shown to have an impact in gene...	[ 43867, 6052 ]	Train
35,349	3	Title: Utilizing the International Classification of Functioning, Disability and Health (ICF) in forming a personal health index Abstract: We propose a new model for comprehensively monitoring the health status of individuals by calculating a personal health index. The central framework of the model is the Internationa...	[]	Test
35,350	30	Title: Predicting Hateful Discussions on Reddit using Graph Transformer Networks and Communal Context Abstract: We propose a system to predict harmful discussions on social media platforms. Our solution uses contextual deep language models and proposes the novel idea of integrating state-of-the-art Graph Transformer Ne...	[ 37410 ]	Validation
35,351	16	Title: Mx2M: Masked Cross-Modality Modeling in Domain Adaptation for 3D Semantic Segmentation Abstract: Existing methods of cross-modal domain adaptation for 3D semantic segmentation predict results only via 2D-3D complementarity that is obtained by cross-modal feature matching. However, as lacking supervision in the t...	[]	Test
35,352	10	Title: Stock Market Price Prediction: A Hybrid LSTM and Sequential Self-Attention based Approach Abstract: One of the most enticing research areas is the stock market, and projecting stock prices may help investors profit by making the best decisions at the correct time. Deep learning strategies have emerged as a criti...	[ 6747 ]	Train
35,353	4	Title: MVAM: Multi-variant Attacks on Memory for IoT Trust Computing Abstract: The growth of the Internet of Things (IoT) and the availability of low-cost cloud services have led to an increase in the sensory and data processing needs of IoT systems. TrustZone is a hardware-based security solution designed for ARM proc...	[]	Train
35,354	16	Title: 3D Line Mapping Revisited Abstract: In contrast to sparse keypoints, a handful of line segments can concisely encode the high-level scene layout, as they often delineate the main structural elements. In addition to offering strong geometric cues, they are also omnipresent in urban landscapes and indoor scenes. D...	[]	Train
35,355	3	Title: Beyond Transactional Democracy: A Study of Civic Tech in Canada Abstract: Technologies are increasingly enrolled in projects to involve civilians in the work of policy-making, often under the label of 'civic technology'. But conventional forms of participation through transactions such as voting provide limited ...	[]	Train
35,356	24	Title: GCNH: A Simple Method For Representation Learning On Heterophilous Graphs Abstract: Graph Neural Networks (GNNs) are well-suited for learning on homophilous graphs, i.e., graphs in which edges tend to connect nodes of the same type. Yet, achievement of consistent GNN performance on heterophilous graphs remains a...	[ 43193 ]	Validation
35,357	30	Title: Rule-based detection of access to education and training in Germany Abstract: As a result of transformation processes, the German labor market is highly dependent on vocational training, retraining and continuing education. To match training seekers and offers, we present a novel approach towards the automated d...	[]	Test
35,358	26	Title: Resource Allocation of Federated Learning Assisted Mobile Augmented Reality System in the Metaverse Abstract: Metaverse has become a buzzword recently. Mobile augmented reality (MAR) is a promising approach to providing users with an immersive experience in the Metaverse. However, due to limitations of bandwidth...	[ 30258 ]	Train
35,359	13	Title: Generating Oscillation Activity with Echo State Network to Mimic the Behavior of a Simple Central Pattern Generator Abstract: This paper presents a method for reproducing a simple central pattern generator (CPG) using a modified Echo State Network (ESN). Conventionally, the dynamical reservoir needs to be damped...	[ 13645 ]	Train
35,360	16	Title: An Efficient Plane Extraction Approach for Bundle Adjustment on LiDAR Point clouds Abstract: Bundle adjustment (BA) on LiDAR point clouds has been extensively investigated in recent years due to its ability to optimize multiple poses together, resulting in high accuracy and global consistency for point cloud. Ho...	[]	Test
35,361	7	Title: Novel Simulation-Inspired Roller Spreading Strategies for Fine and Highly Cohesive Metal Powders Abstract: When fine powders are to be used in powder bed metal additive manufacturing (AM), a roller is typically utilized for spreading. However, the cohesive nature of fine metal powder still presents challenges, r...	[ 28169 ]	Train
35,362	6	Title: The Right Variety: Improving Expressive Range Analysis with Metric Selection Methods Abstract: Expressive Range Analysis (ERA), an approach for visualising the output of Procedural Content Generation (PCG) systems, is widely used within PCG research to evaluate and compare generators, often to make comparative s...	[ 34283 ]	Train
35,363	6	Title: First steps towards quantum machine learning applied to the classification of event-related potentials Abstract: Low information transfer rate is a major bottleneck for brain-computer interfaces based on non-invasive electroencephalography (EEG) for clinical applications. This led to the development of more robu...	[]	Train
35,364	2	Title: Complexity Analysis for Call-by-Value Higher-Order Rewriting Abstract: In this short paper, we consider a form of higher-order rewriting with a call-by-value evaluation strategy so as to model call-by-value programs. We briefly present a cost-size semantics to call-by-value rewriting: a class of algebraic interp...	[]	Test
35,365	16	Title: Adaptive Low Rank Adaptation of Segment Anything to Salient Object Detection Abstract: Foundation models, such as OpenAI's GPT-3 and GPT-4, Meta's LLaMA, and Google's PaLM2, have revolutionized the field of artificial intelligence. A notable paradigm shift has been the advent of the Segment Anything Model (SAM),...	[ 32635, 13700, 6942, 5815 ]	Train
35,366	27	Title: ExploitFlow, cyber security exploitation routes for Game Theory and AI research in robotics Abstract: This paper addresses the prevalent lack of tools to facilitate and empower Game Theory and Artificial Intelligence (AI) research in cybersecurity. The primary contribution is the introduction of ExploitFlow (EF)...	[]	Test
35,367	30	Title: 3D Rotation and Translation for Hyperbolic Knowledge Graph Embedding Abstract: The main objective of Knowledge Graph (KG) embeddings is to learn low-dimensional representations of entities and relations, enabling the prediction of missing facts. A significant challenge in achieving better KG embeddings lies in c...	[]	Validation
35,368	24	Title: The Regular Expression Inference Challenge Abstract: We propose \emph{regular expression inference (REI)} as a challenge for code/language modelling, and the wider machine learning community. REI is a supervised machine learning (ML) and program synthesis task, and poses the problem of finding minimal regular ex...	[ 392, 32758 ]	Train
35,369	24	Title: Deep Neural Networks for Encrypted Inference with TFHE Abstract: Fully homomorphic encryption (FHE) is an encryption method that allows to perform computation on encrypted data, without decryption. FHE preserves the privacy of the users of online services that handle sensitive data, such as health data, biometri...	[ 8021, 36021 ]	Validation
35,370	24	Title: Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations Abstract: Joint-embedding based learning (e.g., SimCLR, MoCo, DINO) and reconstruction-based learning (e.g., BEiT, SimMIM, MAE) are the two leading paradigms for self-supervised learning of vision tran...	[ 29873, 19787, 15269, 35885 ]	Train
35,371	16	Title: TriDet: Temporal Action Detection with Relative Boundary Modeling Abstract: In this paper, we present a one-stage framework TriDet for temporal action detection. Existing methods often suffer from imprecise boundary predictions due to the ambiguous action boundaries in videos. To alleviate this problem, we propo...	[ 14760, 46001, 38937 ]	Test
35,372	16	Title: Road Extraction With Satellite Images and Partial Road Maps Abstract: Road extraction is a process of automatically generating road maps mainly from satellite images. Existing models all target to generate roads from the scratch despite that a large number of road maps, though incomplete, are publicly available ...	[ 4664 ]	Train
35,373	26	Title: Cultural Differences in Signed Ego Networks on Twitter: An Investigatory Analysis Abstract: Human social behaviour has been observed to adhere to certain structures. One such structure, the Ego Network Model (ENM), has been found almost ubiquitously in human society. Recently, this model has been extended to inc...	[]	Test
35,374	3	Title: Survivor-Centered Transformative Justice: An Approach to Designing Alongside Domestic Violence Stakeholders in US Muslim Communities Abstract: While domestic violence (DV) is prevalent in all socioeconomic settings, identity highly impacts how one experiences and recovers from abuse. This work examines US-based ...	[]	Train
35,375	30	Title: Learning to Retrieve In-Context Examples for Large Language Models Abstract: Large language models (LLMs) have demonstrated their ability to learn in-context, allowing them to perform various tasks based on a few input-output examples. However, the effectiveness of in-context learning is heavily reliant on the q...	[ 13700, 19492, 18572, 12724, 27669, 32213, 38262 ]	Train
35,376	30	Title: How to use LLMs for Text Analysis Abstract: This guide introduces Large Language Models (LLM) as a highly versatile text analysis method within the social sciences. As LLMs are easy-to-use, cheap, fast, and applicable on a broad range of text analysis tasks, ranging from text annotation and classification to sen...	[ 39642, 28980, 36751 ]	Test
35,377	16	Title: FRA: A novel Face Representation Augmentation algorithm for face recognition Abstract: P.O	[]	Test

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