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
20,278	16	Title: DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction Abstract: We present DejaVu, a novel framework which leverages conditional image regeneration as additional supervision during training to improve deep networks for dense prediction tasks such as segmentation, depth estimation, and surface nor...	[ 40512, 39250, 6470 ]	Train
20,279	13	Title: Asynchronous Evolution of Deep Neural Network Architectures Abstract: Many evolutionary algorithms (EAs) take advantage of parallel evaluation of candidates. However, if evaluation times vary significantly, many worker nodes (i.e.,\ compute clients) are idle much of the time, waiting for the next generation to b...	[ 2474 ]	Train
20,280	30	Title: Towards an Automatic Consolidation of French Law Abstract: We present preliminary results about Legistix, a tool we are developing to automatically consolidate the French and European law. Legistix is based both on regular expressions used in several compound grammars, similar to the successive passes of a compi...	[]	Validation
20,281	24	Title: Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts Abstract: Training machine learning models robust to distribution shifts is critical for real-world applications. Some robust training algorithms (e.g., Group DRO) specialize to group shifts and require group information on all trainin...	[ 16339 ]	Validation
20,282	24	Title: HypBO: Expert-Guided Chemist-in-the-Loop Bayesian Search for New Materials Abstract: Robotics and automation offer massive accelerations for solving intractable, multivariate scientific problems such as materials discovery, but the available search spaces can be dauntingly large. Bayesian optimization (BO) has e...	[]	Train
20,283	28	Title: DFT-Based Channel Estimation for Holographic MIMO Abstract: Holographic MIMO (hMIMO) systems with a massive number of individually controlled antennas N make minimum mean square error (MMSE) channel estimation particularly challenging, due to its computational complexity that scales as $N^3$ . This paper investi...	[]	Train
20,284	28	Title: Performance Analysis of Centralized and Distributed Massive MIMO for MTC Abstract: Massive Multiple-Input Multiple-Output (mMIMO) is one of the essential technologies introduced by the Fifth Generation (5G) of wireless communication systems. However, although mMIMO provides many benefits for wireless communicati...	[]	Validation
20,285	17	Title: Tensorformer: Normalized Matrix Attention Transformer for High-quality Point Cloud Reconstruction Abstract: Surface reconstruction from raw point clouds has been studied for decades in the computer graphics community, which is highly demanded by modeling and rendering applications nowadays. Classic solutions, su...	[]	Train
20,286	24	Title: Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics Abstract: Discovering a suitable coordinate transformation for nonlinear systems enables the construction of simpler models, facilitating prediction, control, and optimization for comp...	[ 5188, 3838 ]	Train
20,287	24	Title: Promoting Exploration in Memory-Augmented Adam using Critical Momenta Abstract: Adaptive gradient-based optimizers, particularly Adam, have left their mark in training large-scale deep learning models. The strength of such optimizers is that they exhibit fast convergence while being more robust to hyperparameter...	[]	Train
20,288	16	Title: FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation Abstract: The great potential of unsupervised monocular depth estimation has been demonstrated by many works due to low annotation cost and impressive accuracy comparable to supervised methods. To further improve the performance, recent works mainly f...	[]	Validation
20,289	34	Title: An Improved Deterministic Algorithm for the Online Min-Sum Set Cover Problem Abstract: We study the online variant of the Min-Sum Set Cover (MSSC) problem, a generalization of the well-known list update problem. In the MSSC problem, an algorithm has to maintain the time-varying permutation of the list of $n$ ele...	[]	Train
20,290	8	Title: Deep Reinforcement Learning for Uplink Scheduling in NOMA-URLLC Networks Abstract: This article addresses the problem of Ultra Reliable Low Latency Communications (URLLC) in wireless networks, a framework with particularly stringent constraints imposed by many Internet of Things (IoT) applications from diverse s...	[]	Test
20,291	37	Title: Pre-trained Embeddings for Entity Resolution: An Experimental Analysis [Experiment, Analysis & Benchmark] Abstract: Many recent works on Entity Resolution (ER) leverage Deep Learning techniques involving language models to improve effectiveness. This is applied to both main steps of ER, i.e., blocking and matchi...	[ 40176 ]	Train
20,292	16	Title: Learning INR for Event-guided Rolling Shutter Frame Correction, Deblur, and Interpolation Abstract: Images captured by rolling shutter (RS) cameras under fast camera motion often contain obvious image distortions and blur, which can be modeled as a row-wise combination of a sequence of global shutter (GS) frames...	[ 29165, 37495 ]	Train
20,293	4	Title: SoK: Content Moderation for End-to-End Encryption Abstract: Popular messaging applications now enable end-to-end-encryption (E2EE) by default, and E2EE data storage is becoming common. These important advances for security and privacy create new content moderation challenges for online services, because services...	[ 33578 ]	Train
20,294	16	Title: Improving Image Tracing with Convolutional Autoencoders by High-Pass Filter Preprocessing Abstract: The process of transforming a raster image into a vector representation is known as image tracing. This study looks into several processing methods that include high-pass filtering, autoencoding, and vectorization...	[]	Test
20,295	4	Title: PLAN: Variance-Aware Private Mean Estimation Abstract: Differentially private mean estimation is an important building block in privacy-preserving algorithms for data analysis and machine learning. Though the trade-off between privacy and utility is well understood in the worst case, many datasets exhibit struct...	[ 11364, 27446 ]	Test
20,296	36	Title: Multi-channel Autobidding with Budget and ROI Constraints Abstract: In digital online advertising, advertisers procure ad impressions simultaneously on multiple platforms, or so-called channels, such as Google Ads, Meta Ads Manager, etc., each of which consists of numerous ad auctions. We study how an advertiser...	[ 12264, 24431, 32624, 9298, 21788 ]	Train
20,297	26	Title: Bridging Nations: Quantifying the Role of Multilinguals in Communication on Social Media Abstract: Social media enables the rapid spread of many kinds of information, from pop culture memes to social movements. However, little is known about how information crosses linguistic boundaries. We apply causal inferenc...	[]	Validation
20,298	15	Title: ADC/DAC-Free Analog Acceleration of Deep Neural Networks with Frequency Transformation Abstract: The edge processing of deep neural networks (DNNs) is becoming increasingly important due to its ability to extract valuable information directly at the data source to minimize latency and energy consumption. Frequen...	[ 41457, 17845, 15119 ]	Train
20,299	16	Title: Data-Driven Stochastic Motion Evaluation and Optimization with Image by Spatially-Aligned Temporal Encoding Abstract: This paper proposes a probabilistic motion prediction method for long motions. The motion is predicted so that it accomplishes a task from the initial state observed in the given image. While our...	[ 21173 ]	Train
20,300	16	Title: Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking Abstract: Multi-Object Tracking (MOT) aims to detect and associate all desired objects across frames. Most methods accomplish the task by explicitly or implicitly leveraging strong cues (i.e., spatial and appearance information), which exhibit powerf...	[ 31169, 39370 ]	Validation
20,301	24	Title: Interaction models for remaining useful life estimation Abstract: The paper deals with the problem of controlling the state of industrial devices according to the readings of their sensors. The current methods rely on one approach to feature extraction in which the prediction occurs. We proposed a technique to b...	[]	Train
20,302	30	Title: Trimming Phonetic Alignments Improves the Inference of Sound Correspondence Patterns from Multilingual Wordlists Abstract: Sound correspondence patterns form the basis of cognate detection and phonological reconstruction in historical language comparison. Methods for the automatic inference of correspondence pat...	[]	Train
20,303	38	Title: Altmetrics can capture research evidence: a study across types of studies in COVID-19 literature Abstract: COVID-19 has greatly impacted science. It has become a global research front that constitutes a unique phenomenon of interest for the scientometric community. Accordingly, there has been a proliferation of ...	[]	Train
20,304	23	Title: Embedded Software Development with Digital Twins: Specific Requirements for Small and Medium-Sized Enterprises Abstract: The transformation to Industry 4.0 changes the way embedded software systems are developed. Digital twins have the potential for cost-effective software development and maintenance strategies....	[]	Test
20,305	16	Title: Defensive Perception: Estimation and Monitoring of Neural Network Performance under Deployment Abstract: In this paper, we propose a method for addressing the issue of unnoticed catastrophic deployment and domain shift in neural networks for semantic segmentation in autonomous driving. Our approach is based on t...	[]	Train
20,306	16	Title: Weakly-Supervised Text Instance Segmentation Abstract: Text segmentation is a challenging vision task with many downstream applications. Current text segmentation methods require pixel-level annotations, which are expensive in the cost of human labor and limited in application scenarios. In this paper, we take t...	[ 44561 ]	Test
20,307	24	Title: Federated Learning for Early Dropout Prediction on Healthy Ageing Applications Abstract: The provision of social care applications is crucial for elderly people to improve their quality of life and enables operators to provide early interventions. Accurate predictions of user dropouts in healthy ageing applicati...	[ 20443 ]	Train
20,308	16	Title: Robust Lane Detection through Self Pre-training with Masked Sequential Autoencoders and Fine-tuning with Customized PolyLoss Abstract: Lane detection is crucial for vehicle localization which makes it the foundation for automated driving and many intelligent and advanced driving assistant systems. Available visi...	[ 13847 ]	Validation
20,309	36	Title: Bandit Social Learning: Exploration under Myopic Behavior Abstract: We study social learning dynamics where the agents collectively follow a simple multi-armed bandit protocol. Agents arrive sequentially, choose arms and receive associated rewards. Each agent observes the full history (arms and rewards) of the p...	[]	Test
20,310	20	Title: A Scalable Method for Readable Tree Layouts Abstract: Large tree structures are ubiquitous and real-world relational datasets often have information associated with nodes (e.g., labels or other attributes) and edges (e.g., weights or distances) that need to be communicated to the viewers. Yet, scalable, easy to ...	[]	Train
20,311	31	Title: Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation Abstract: On-device recommender systems recently have garnered increasing attention due to their advantages of providing prompt response and securing privacy. To stay current with evolving user interests, cloud-based recomm...	[]	Train
20,312	27	Title: Semantic and Topological Mapping using Intersection Identification Abstract: This article presents a novel approach to identifying and classifying intersections for semantic and topological mapping. More specifically, the proposed novel approach has the merit of generating a semantically meaningful map containin...	[]	Train
20,313	30	Title: XSemPLR: Cross-Lingual Semantic Parsing in Multiple Natural Languages and Meaning Representations Abstract: Cross-Lingual Semantic Parsing (CLSP) aims to translate queries in multiple natural languages (NLs) into meaning representations (MRs) such as SQL, lambda calculus, and logic forms.However, existing CLSP m...	[ 36494 ]	Train
20,314	16	Title: Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator Abstract: In this paper, we introduce a novel approach to fine-grained cross-view geo-localization. Our method aligns a warped ground image with a corresponding GPS-tagged satellite image covering the same area using homograp...	[ 23552, 18218, 34901 ]	Validation
20,315	31	Title: Unsupervised Story Discovery from Continuous News Streams via Scalable Thematic Embedding Abstract: Unsupervised discovery of stories with correlated news articles in real-time helps people digest massive news streams without expensive human annotations. A common approach of the existing studies for unsupervised...	[]	Validation
20,316	28	Title: The Radon Signed Cumulative Distribution Transform and its applications in classification of Signed Images Abstract: Here we describe a new image representation technique based on the mathematics of transport and optimal transport. The method relies on the combination of the well-known Radon transform for images...	[]	Train
20,317	24	Title: Integrating Edge-AI in Structural Health Monitoring domain Abstract: Structural health monitoring (SHM) tasks like damage detection are crucial for decision-making regarding maintenance and deterioration. For example, crack detection in SHM is crucial for bridge maintenance as crack progression can lead to struc...	[]	Train
20,318	24	Title: Heterophily-Aware Graph Attention Network Abstract: Graph Neural Networks (GNNs) have shown remarkable success in graph representation learning. Unfortunately, current weight assignment schemes in standard GNNs, such as the calculation based on node degrees or pair-wise representations, can hardly be effective i...	[]	Test
20,319	16	Title: DocumentCLIP: Linking Figures and Main Body Text in Reflowed Documents Abstract: Vision-language pretraining models have achieved great success in supporting multimedia applications by understanding the alignments between images and text. While existing vision-language pretraining models primarily focus on under...	[ 10624, 45777, 39280, 37766 ]	Train
20,320	26	Title: Representing Edge Flows on Graphs via Sparse Cell Complexes Abstract: Obtaining sparse, interpretable representations of observable data is crucial in many machine learning and signal processing tasks. For data representing flows along the edges of a graph, an intuitively interpretable way to obtain such represe...	[ 23882 ]	Test
20,321	24	Title: UGSL: A Unified Framework for Benchmarking Graph Structure Learning Abstract: Graph neural networks (GNNs) demonstrate outstanding performance in a broad range of applications. While the majority of GNN applications assume that a graph structure is given, some recent methods substantially expanded the applicabil...	[ 44836, 40478 ]	Train
20,322	30	Title: Machine Translation by Projecting Text into the Same Phonetic-Orthographic Space Using a Common Encoding Abstract: The use of subword embedding has proved to be a major innovation in Neural Machine Translation (NMT). It helps NMT to learn better context vectors for Low Resource Languages (LRLs) so as to predict ...	[]	Test
20,323	24	Title: Bayesian Flow Networks Abstract: This paper introduces Bayesian Flow Networks (BFNs), a new class of generative model in which the parameters of a set of independent distributions are modified with Bayesian inference in the light of noisy data samples, then passed as input to a neural network that outputs a seco...	[ 38936 ]	Test
20,324	16	Title: Deep Omni-supervised Learning for Rib Fracture Detection from Chest Radiology Images Abstract: Deep learning (DL)-based rib fracture detection has shown promise of playing an important role in preventing mortality and improving patient outcome. Normally, developing DL-based object detection models requires huge ...	[ 28377, 22495 ]	Test
20,325	16	Title: AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator Abstract: Designing robust machine learning systems remains an open problem, and there is a need for benchmark problems that cover both environmental changes and evaluation on a downstream task. In this work, we introduce AVOIDDS, a realisti...	[]	Train
20,326	16	Title: A Hybrid Approach To Real-Time Multi-Object Tracking Abstract: Multi-Object Tracking, also known as Multi-Target Tracking, is a significant area of computer vision that has many uses in a variety of settings. The development of deep learning, which has encouraged researchers to propose more and more work in this...	[]	Test
20,327	1	Title: WMFormer++: Nested Transformer for Visible Watermark Removal via Implict Joint Learning Abstract: Watermarking serves as a widely adopted approach to safeguard media copyright. In parallel, the research focus has extended to watermark removal techniques, offering an adversarial means to enhance watermark robustn...	[]	Train
20,328	24	Title: Bayesian Optimization for Function Compositions with Applications to Dynamic Pricing Abstract: Bayesian Optimization (BO) is used to find the global optima of black box functions. In this work, we propose a practical BO method of function compositions where the form of the composition is known but the constituen...	[ 33096 ]	Validation
20,329	24	Title: Improved Regret Bounds for Online Kernel Selection under Bandit Feedback Abstract: In this paper, we improve the regret bound for online kernel selection under bandit feedback. Previous algorithm enjoys a $O((\Vert f\Vert^2_{\mathcal{H}_i}+1)K^{\frac{1}{3}}T^{\frac{2}{3}})$ expected bound for Lipschitz loss func...	[]	Train
20,330	23	Title: Towards a Definition of Complex Software System Abstract: Complex Systems were identified and studied in different fields, such as physics, biology, and economics. These systems exhibit exciting properties such as self-organization, robust order, and emergence. In recent years, software systems displaying behavi...	[]	Train
20,331	8	Title: Online Network Slicing for Real Time Applications in Large-scale Satellite Networks Abstract: In this work, we investigate resource allocation strategy for real time communication (RTC) over satellite networks with virtual network functions. Enhanced by inter-satellite links (ISLs), in-orbit computing and networ...	[ 10966 ]	Train
20,332	30	Title: Question Answering as Programming for Solving Time-Sensitive Questions Abstract: In this work we try to apply Large Language Models (LLMs) to reframe the Question Answering task as Programming (QAaP). Due to the inherent dynamic nature of the real world, factual questions frequently involve a symbolic constraint...	[ 1528, 10165 ]	Train
20,333	24	Title: A Policy for Early Sequence Classification Abstract: Sequences are often not received in their entirety at once, but instead, received incrementally over time, element by element. Early predictions yielding a higher benefit, one aims to classify a sequence as accurately as possible, as soon as possible, without ...	[ 15762 ]	Train
20,334	31	Title: Empowering Dual-Encoder with Query Generator for Cross-Lingual Dense Retrieval Abstract: In monolingual dense retrieval, lots of works focus on how to distill knowledge from cross-encoder re-ranker to dual-encoder retriever and these methods achieve better performance due to the effectiveness of cross-encoder re...	[]	Validation
20,335	13	Title: Larger Offspring Populations Help the (1 + (λ, λlambda)) Genetic Algorithm to Overcome the Noise Abstract: Evolutionary algorithms are known to be robust to noise in the evaluation of the fitness. In particular, larger offspring population sizes often lead to strong robustness. We analyze to what extent the (1 +...	[ 25713 ]	Train
20,336	16	Title: DenseBAM-GI: Attention Augmented DeneseNet with momentum aided GRU for HMER Abstract: The task of recognising Handwritten Mathematical Expressions (HMER) is crucial in the fields of digital education and scholarly research. However, it is difficult to accurately determine the length and complex spatial relations...	[]	Train
20,337	24	Title: Collect, Measure, Repeat: Reliability Factors for Responsible AI Data Collection Abstract: The rapid entry of machine learning approaches in our daily activities and high-stakes domains demands transparency and scrutiny of their fairness and reliability. To help gauge machine learning models' robustness, researc...	[]	Train
20,338	9	Title: The complexity of decomposing a graph into a matching and a bounded linear forest Abstract: Deciding whether a graph can be edge-decomposed into a matching and a $k$-bounded linear forest was recently shown by Campbell, H{\"o}rsch and Moore to be NP-complete for every $k \ge 9$, and solvable in polynomial time f...	[]	Validation
20,339	30	Title: Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations Abstract: Extracting generalized and robust representations is a major challenge in emotion recognition in conversations (ERC). To address this, we propose a supervised adversarial contrastive learning (SACL) framework for learn...	[ 26921 ]	Train
20,340	16	Title: Efficient Self-supervised Continual Learning with Progressive Task-correlated Layer Freezing Abstract: Inspired by the success of Self-supervised learning (SSL) in learning visual representations from unlabeled data, a few recent works have studied SSL in the context of continual learning (CL), where multiple ta...	[ 32216 ]	Train
20,341	16	Title: BOLLWM: A real-world dataset for bollworm pest monitoring from cotton fields in India Abstract: This paper presents a dataset of agricultural pest images captured over five years by thousands of small holder farmers and farming extension workers across India. The dataset has been used to support a mobile applica...	[]	Train
20,342	30	Title: Two-stage Pipeline for Multilingual Dialect Detection Abstract: Dialect Identification is a crucial task for localizing various Large Language Models. This paper outlines our approach to the VarDial 2023 shared task. Here we have to identify three or two dialects from three languages each which results in a 9-wa...	[]	Train
20,343	24	Title: QUBO-inspired Molecular Fingerprint for Chemical Property Prediction Abstract: Molecular fingerprints are widely used for predicting chemical properties, and selecting appropriate fingerprints is important. We generate new fingerprints based on the assumption that a performance of prediction using a more effecti...	[ 2913 ]	Validation
20,344	31	Title: HGCC: Enhancing Hyperbolic Graph Convolution Networks on Heterogeneous Collaborative Graph for Recommendation Abstract: Due to the naturally power-law distributed nature of user-item interaction data in recommendation tasks, hyperbolic space modeling has recently been introduced into collaborative filtering meth...	[]	Train
20,345	27	Title: Rethinking Closed-Loop Training for Autonomous Driving Abstract: nan	[ 37832, 26553, 32036 ]	Train
20,346	27	Title: Learning to Place Unseen Objects Stably using a Large-scale Simulation Abstract: Object placement is a fundamental task for robots, yet it remains challenging for partially observed objects. Existing methods for object placement have limitations, such as the requirement for a complete 3D model of the object or t...	[ 33062 ]	Train
20,347	24	Title: Out-of-Variable Generalization for Discriminative Models Abstract: The ability of an agent to do well in new environments is a critical aspect of intelligence. In machine learning, this ability is known as $\textit{strong}$ or $\textit{out-of-distribution}$ generalization. However, merely considering differences...	[]	Train
20,348	30	Title: Voting Booklet Bias: Stance Detection in Swiss Federal Communication Abstract: In this study, we use recent stance detection methods to study the stance (for, against or neutral) of statements in official information booklets for voters. Our main goal is to answer the fundamental question: are topics to be voted...	[]	Validation
20,349	24	Title: ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations Abstract: Self-Supervised Learning (SSL) is a paradigm that leverages unlabeled data for model training. Empirical studies show that SSL can achieve promising performance in distribution shift scenarios, where the downstream and traini...	[ 29857, 18058, 29787, 34527 ]	Train
20,350	16	Title: D-IF: Uncertainty-aware Human Digitization via Implicit Distribution Field Abstract: Realistic virtual humans play a crucial role in numerous industries, such as metaverse, intelligent healthcare, and self-driving simulation. But creating them on a large scale with high levels of realism remains a challenge. The...	[ 32384, 6739, 40867 ]	Test
20,351	24	Title: fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks Abstract: To design with AI models, user experience (UX) designers must assess the fit between the model and user needs. Based on user research, they need to contextualize the model’s behavior and potential fail...	[ 33967, 36755, 27631 ]	Test
20,352	4	Title: ArctyrEX : Accelerated Encrypted Execution of General-Purpose Applications Abstract: Fully Homomorphic Encryption (FHE) is a cryptographic method that guarantees the privacy and security of user data during computation. FHE algorithms can perform unlimited arithmetic computations directly on encrypted data witho...	[ 45749 ]	Validation
20,353	24	Title: Diffusion Models for Constrained Domains Abstract: Denoising diffusion models are a recent class of generative models which achieve state-of-the-art results in many domains such as unconditional image generation and text-to-speech tasks. They consist of a noising process destroying the data and a backward stage ...	[ 40833, 5770, 12830 ]	Train
20,354	24	Title: Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations Abstract: Recent work has observed an intriguing ''Neural Collapse'' phenomenon in well-trained neural networks, where the last-layer representations of training samples with the same label collapse into each other. This appe...	[]	Train
20,355	30	Title: Mask-guided BERT for Few Shot Text Classification Abstract: Transformer-based language models have achieved significant success in various domains. However, the data-intensive nature of the transformer architecture requires much labeled data, which is challenging in low-resource scenarios (i.e., few-shot learnin...	[ 45505, 39170, 45189, 36263, 40136, 44272, 16471, 7996, 23230, 1151 ]	Train
20,356	5	Title: Enforcing Data Geolocation Policies in Public Clouds using Trusted Computing Abstract: With the advancement in technology, Cloud computing always amazes the world with revolutionizing solutions that automate and simplify complex computational tasks. The advantages like no maintenance cost, accessibility, data ba...	[]	Train
20,357	24	Title: Efficient Training of Deep Equilibrium Models Abstract: Deep equilibrium models (DEQs) have proven to be very powerful for learning data representations. The idea is to replace traditional (explicit) feedforward neural networks with an implicit fixed-point equation, which allows to decouple the forward and backw...	[]	Train
20,358	26	Title: Misinformation as Information Pollution Abstract: Social media feed algorithms are designed to optimize online social engagements for the purpose of maximizing advertising profits, and therefore have an incentive to promote controversial posts including misinformation. By thinking about misinformation as informa...	[]	Train
20,359	4	Title: STDLens: Model Hijacking-Resilient Federated Learning for Object Detection Abstract: Federated Learning (FL) has been gaining popularity as a collaborative learning framework to train deep learning-based object detection models over a distributed population of clients. Despite its advantages, FL is vulnerable to...	[]	Validation
20,360	27	Title: Autonomous Rendezvous with Non-cooperative Target Objects with Swarm Chasers and Observers Abstract: ,	[ 21312, 3545, 14254 ]	Train
20,361	36	Title: Sub-game optimal strategies in concurrent games with prefix-independent objectives Abstract: We investigate concurrent two-player win/lose stochastic games on finite graphs with prefix-independent objectives. We characterize subgame optimal strategies and use this characterization to show various memory transfer...	[]	Test
20,362	24	Title: Optimization and Optimizers for Adversarial Robustness Abstract: Empirical robustness evaluation (RE) of deep learning models against adversarial perturbations entails solving nontrivial constrained optimization problems. Existing numerical algorithms that are commonly used to solve them in practice predominantl...	[]	Train
20,363	8	Title: Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks Abstract: In this article, we advocate for the design of ad hoc artificial intelligence (AI)/machine learning (ML) models to facilitate their usage in future smart infrastructures based on communication networks. To motivate...	[]	Train
20,364	16	Title: Efficient Multi-Grained Knowledge Reuse for Class Incremental Segmentation Abstract: Class Incremental Semantic Segmentation (CISS) has been a trend recently due to its great significance in real-world applications. Although the existing CISS methods demonstrate remarkable performance, they either leverage the h...	[]	Validation
20,365	34	Title: Shortest Beer Path Queries based on Graph Decomposition Abstract: Given a directed edge-weighted graph $G=(V, E)$ with beer vertices $B\subseteq V$, a beer path between two vertices $u$ and $v$ is a path between $u$ and $v$ that visits at least one beer vertex in $B$, and the beer distance between two vertices i...	[]	Test
20,366	6	Title: Agent-based Simulation for Online Mental Health Matching Abstract: Online mental health communities (OMHCs) are an effective and accessible channel to give and receive social support for individuals with mental and emotional issues. However, a key challenge on these platforms is finding suitable partners to inte...	[]	Train
20,367	16	Title: A Novel Driver Distraction Behavior Detection Method Based on Self-Supervised Learning With Masked Image Modeling Abstract: Driver distraction causes a significant number of traffic accidents every year, resulting in economic losses and casualties. Currently, the level of automation in commercial vehicles is far...	[ 2903 ]	Train
20,368	27	Title: Recent Advancements in Deep Learning Applications and Methods for Autonomous Navigation - A Comprehensive Review Abstract: This review article is an attempt to survey all recent AI based techniques used to deal with major functions in This review paper presents a comprehensive overview of end-to-end deep learnin...	[ 21312, 36423, 32589, 9074, 29877, 3545 ]	Test
20,369	16	Title: PDIWS: Thermal Imaging Dataset for Person Detection in Intrusion Warning Systems Abstract: In this paper, we present a synthetic thermal imaging dataset for Person Detection in Intrusion Warning Systems (PDIWS). The dataset consists of a training set with 2000 images and a test set with 500 images. Each image is...	[]	Test
20,370	8	Title: Performance of Joint XR and Best-Effort eMBB Traffic in 5G-Advanced Networks Abstract: In this paper, we address the joint performance of eXtended reality (XR) and best-effort enhanced mobile broadband (eMBB) traffic for a 5G-Advanced system. Although XR users require stringent throughput and latency performance...	[]	Train
20,371	24	Title: Free Lunch for Domain Adversarial Training: Environment Label Smoothing Abstract: A fundamental challenge for machine learning models is how to generalize learned models for out-of-distribution (OOD) data. Among various approaches, exploiting invariant features by Domain Adversarial Training (DAT) received wides...	[ 29135, 24375, 16782, 37127 ]	Validation
20,372	24	Title: Distributional Offline Policy Evaluation with Predictive Error Guarantees Abstract: We study the problem of estimating the distribution of the return of a policy using an offline dataset that is not generated from the policy, i.e., distributional offline policy evaluation (OPE). We propose an algorithm called Fi...	[ 8480, 10572 ]	Validation
20,373	22	Title: Duoidally enriched Freyd categories Abstract: nan	[ 10995 ]	Train
20,374	4	Title: Verifiable Manufacturing Using Blockchain Abstract: We propose a blockchain-based solution for enabling verifiability of manufacturing processes. We base our solution on the methodology of verifiable computing which, originally developed for cloud computing, enables clients to outsource computations to more powe...	[]	Train
20,375	24	Title: ZipLM: Hardware-Aware Structured Pruning of Language Models Abstract: The breakthrough performance of large language models (LLMs) comes with large computational footprints and high deployment costs. In this paper, we progress towards resolving this problem by proposing a new structured compression approach for ...	[ 41554, 6979, 34486, 17510 ]	Train
20,376	16	Title: Semantic Adversarial Attacks on Face Recognition through Significant Attributes Abstract: Face recognition is known to be vulnerable to adversarial face images. Existing works craft face adversarial images by indiscriminately changing a single attribute without being aware of the intrinsic attributes of the imag...	[]	Train
20,377	24	Title: On Invariance, Equivariance, Correlation and Convolution of Spherical Harmonic Representations for Scalar and Vectorial Data Abstract: The mathematical representations of data in the Spherical Harmonic (SH) domain has recently regained increasing interest in the machine learning community. This technical report ...	[]	Validation

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