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
36,878	4	Title: Differential Privacy with Random Projections and Sign Random Projections Abstract: In this paper, we develop a series of differential privacy (DP) algorithms from a family of random projections (RP) for general applications in machine learning, data mining, and information retrieval. Among the presented algorith...	[]	Train
36,879	27	Title: SuperDriverAI: Towards Design and Implementation for End-to-End Learning-Based Autonomous Driving Abstract: Fully autonomous driving has been widely studied and is becoming increasingly feasible. However, such autonomous driving has yet to be achieved on public roads, because of various uncertainties due to surr...	[]	Train
36,880	24	Title: Global Optimality in Bivariate Gradient-based DAG Learning Abstract: Recently, a new class of non-convex optimization problems motivated by the statistical problem of learning an acyclic directed graphical model from data has attracted significant interest. While existing work uses standard first-order optimizat...	[]	Train
36,881	16	Title: Object counting from aerial remote sensing images: application to wildlife and marine mammals Abstract: Anthropogenic activities pose threats to wildlife and marine fauna, prompting the need for efficient animal counting methods. This research study utilizes deep learning techniques to automate counting tasks. I...	[]	Test
36,882	24	Title: Fake News Detection and Behavioral Analysis: Case of COVID-19 Abstract: While the world has been combating COVID-19 for over three years, an ongoing "Infodemic" due to the spread of fake news regarding the pandemic has also been a global issue. The existence of the fake news impact different aspect of our daily ...	[ 39680 ]	Train
36,883	24	Title: Beyond Confidence: Reliable Models Should Also Consider Atypicality Abstract: While most machine learning models can provide confidence in their predictions, confidence is insufficient to understand a prediction's reliability. For instance, the model may have a low confidence prediction if the input is not well-...	[]	Train
36,884	24	Title: Approximate Thompson Sampling via Epistemic Neural Networks Abstract: Thompson sampling (TS) is a popular heuristic for action selection, but it requires sampling from a posterior distribution. Unfortunately, this can become computationally intractable in complex environments, such as those modeled using neural ...	[ 10012 ]	Test
36,885	16	Title: Learning a 3D Morphable Face Reflectance Model from Low-Cost Data Abstract: Modeling non-Lambertian effects such as facial specularity leads to a more realistic 3D Morphable Face Model. Existing works build parametric models for diffuse and specular albedo using Light Stage data. However, only diffuse and specul...	[]	Train
36,886	3	Title: Policy design in data economy: In need for a public online news (eco)system? Abstract: Socio-technical design embeds social investigations and inquiries into (Information) Technology Design processes. In this position paper, we propose, by using the aforementioned approach the design of technology and policies c...	[]	Test
36,887	24	Title: FP8 versus INT8 for efficient deep learning inference Abstract: Recently, the idea of using FP8 as a number format for neural network training has been floating around the deep learning world. Given that most training is currently conducted with entire networks in FP32, or sometimes FP16 with mixed-precision, th...	[ 28909, 44402, 30324, 17429 ]	Train
36,888	16	Title: Human Pose Estimation from Ambiguous Pressure Recordings with Spatio-temporal Masked Transformers Abstract: Despite the impressive performance of vision-based pose estimators, they generally fail to perform well under adverse vision conditions and often don't satisfy the privacy demands of customers. As a result...	[]	Test
36,889	28	Title: Bayesian Over-the-Air FedAvg via Channel Driven Stochastic Gradient Langevin Dynamics Abstract: The recent development of scalable Bayesian inference methods has renewed interest in the adoption of Bayesian learning as an alternative to conventional frequentist learning that offers improved model calibration via...	[ 44268 ]	Train
36,890	27	Title: SphereMap: Dynamic Multi-Layer Graph Structure for Rapid Safety-Aware UAV Planning Abstract: A flexible topological representation consisting of a two-layer graph structure built on-board an Unmanned Aerial Vehicle (UAV) by continuously filling the free space of an occupancy map with intersecting spheres is prop...	[ 35630, 29201, 27877, 35213 ]	Validation
36,891	24	Title: Minimum Width for Deep, Narrow MLP: A Diffeomorphism and the Whitney Embedding Theorem Approach Abstract: Recently, there has been significant attention on determining the minimum width for the universal approximation property of deep, narrow MLPs. Among these challenges, approximating a continuous function unde...	[]	Train
36,892	27	Title: Learning Tri-mode Grasping for Ambidextrous Robot Picking Abstract: Object picking in cluttered scenes is a widely investigated field of robot manipulation, however, ambidextrous robot picking is still an important and challenging issue. We found the fusion of different prehensile actions (grasp and suction) can...	[ 16816 ]	Test
36,893	30	Title: A Sequence-to-Sequence Approach for Arabic Pronoun Resolution Abstract: This paper proposes a sequence-to-sequence learning approach for Arabic pronoun resolution, which explores the effectiveness of using advanced natural language processing (NLP) techniques, specifically Bi-LSTM and the BERT pre-trained Langua...	[]	Validation
36,894	24	Title: Zero-shot Task Preference Addressing Enabled by Imprecise Bayesian Continual Learning Abstract: Like generic multi-task learning, continual learning has the nature of multi-objective optimization, and therefore faces a trade-off between the performance of different tasks. That is, to optimize for the current tas...	[ 17699, 16906, 11035, 44542 ]	Train
36,895	23	Title: Neural-Based Test Oracle Generation: A Large-scale Evaluation and Lessons Learned Abstract: Defining test oracles is crucial and central to test development, but manual construction of oracles is expensive. While recent neural-based automated test oracle generation techniques have shown promise, their real-world...	[ 25840, 36594 ]	Validation
36,896	34	Title: Polynomial-time Approximation of Independent Set Parameterized by Treewidth Abstract: We prove the following result about approximating the maximum independent set in a graph. Informally, we show that any approximation algorithm with a ``non-trivial'' approximation ratio (as a function of the number of vertices ...	[]	Train
36,897	24	Title: Contrastive Learning of Temporal Distinctiveness for Survival Analysis in Electronic Health Records Abstract: Survival analysis plays a crucial role in many healthcare decisions, where the risk prediction for the events of interest can support an informative outlook for a patient's medical journey. Given the exi...	[]	Validation
36,898	24	Title: Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods Abstract: Eﬃcient computation of the optimal transport distance between two distributions serves as an algorithm subroutine that empowers various applications. This paper develops a scalable ﬁrst-order optimization-based method t...	[]	Train
36,899	6	Title: Generative AI in Computing Education: Perspectives of Students and Instructors Abstract: Generative models are now capable of producing natural language text that is, in some cases, comparable in quality to the text produced by people. In the computing education context, these models are being used to generate c...	[ 3314, 35107 ]	Train
36,900	4	Title: A New Hybrid Cryptosystem Involving DNA, Rabin, One Time Pad and Fiestel Abstract: Information security is a crucial need in the modern world. Data security is a real concern, and many customers and organizations need to protect their sensitive information from unauthorized parties and attackers. In previous yea...	[]	Train
36,901	16	Title: EgoBlur: Responsible Innovation in Aria Abstract: Project Aria pushes the frontiers of Egocentric AI with large-scale real-world data collection using purposely designed glasses with privacy first approach. To protect the privacy of bystanders being recorded by the glasses, our research protocols are designed to...	[ 13679 ]	Train
36,902	16	Title: Next-generation Surgical Navigation: Multi-view Marker-less 6DoF Pose Estimation of Surgical Instruments Abstract: State-of-the-art research of traditional computer vision is increasingly leveraged in the surgical domain. A particular focus in computer-assisted surgery is to replace marker-based tracking systems...	[]	Train
36,903	30	Title: SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2) Abstract: We present the findings of SemEval-2023 Task 2 on Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2). Divided into 13 tracks, the task focused on methods to identify complex fine-grained named entities...	[ 5793, 13185, 38849, 38897, 17940, 29045, 3482, 26462 ]	Train
36,904	6	Title: “That’s important, but...”: How Computer Science Researchers Anticipate Unintended Consequences of Their Research Innovations Abstract: Computer science research has led to many breakthrough innovations but has also been scrutinized for enabling technology that has negative, unintended consequences for society. ...	[ 26392, 44731 ]	Train
36,905	24	Title: Utilizing Domain Knowledge: Robust Machine Learning for Building Energy Prediction with Small, Inconsistent Datasets Abstract: The demand for a huge amount of data for machine learning (ML) applications is currently a bottleneck in an empirically dominated field. We propose a method to combine prior knowledge wi...	[]	Train
36,906	30	Title: Are Machine Rationales (Not) Useful to Humans? Measuring and Improving Human Utility of Free-text Rationales Abstract: Among the remarkable emergent capabilities of large language models (LMs) is free-text rationalization; beyond certain scale, large LMs are capable of generating seemingly useful rationalization...	[ 20969, 16429 ]	Train
36,907	27	Title: LP-SLAM: Language-Perceptive RGB-D SLAM system based on Large Language Model Abstract: Simultaneous localization and mapping (SLAM) is a critical technology that enables autonomous robots to be aware of their surrounding environment. With the development of deep learning, SLAM systems can achieve a higher level ...	[ 41336, 295 ]	Train
36,908	30	Title: Stop Pre-Training: Adapt Visual-Language Models to Unseen Languages Abstract: Vision-Language Pre-training (VLP) has advanced the performance of many vision-language tasks, such as image-text retrieval, visual entailment, and visual reasoning.The pre-training mostly utilizes lexical databases and image queries i...	[]	Validation
36,909	5	Title: OSP: Boosting Distributed Model Training with 2-stage Synchronization Abstract: Distributed deep learning (DDL) is a promising research area, which aims to increase the efficiency of training deep learning tasks with large size of datasets and models. As the computation capability of DDL nodes continues to incre...	[ 20706 ]	Train
36,910	16	Title: What Happened 3 Seconds Ago? Inferring the Past with Thermal Imaging Abstract: Inferring past human motion from RGB images is challenging due to the inherent uncertainty of the prediction problem. Thermal images, on the other hand, encode traces of past human-object interactions left in the environment via therm...	[]	Validation
36,911	30	Title: DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models Abstract: Generative Pre-trained Transformer (GPT) models have exhibited exciting progress in capabilities, capturing the interest of practitioners and the public alike. Yet, while the literature on the trustworthiness of GPT models remai...	[ 46016, 41570, 37411, 31653, 12424, 33256, 12602, 28575 ]	Train
36,912	25	Title: Deep learning-based denoising streamed from mobile phones improves speech-in-noise understanding for hearing aid users Abstract: The hearing loss of almost half a billion people is commonly treated with hearing aids. However, current hearing aids often do not work well in real-world noisy environments. We presen...	[]	Train
36,913	27	Title: Double Deep Reinforcement Learning Techniques for Low Dimensional Sensing Mapless Navigation of Terrestrial Mobile Robots Abstract: In this work, we present two Deep Reinforcement Learning (Deep-RL) approaches to enhance the problem of mapless navigation for a terrestrial mobile robot. Our methodology focus on c...	[]	Validation
36,914	24	Title: Agile gesture recognition for capacitive sensing devices: adapting on-the-job Abstract: Automated hand gesture recognition has been a focus of the AI community for decades. Traditionally, work in this domain revolved largely around scenarios assuming the availability of the flow of images of the operator's/user'...	[]	Train
36,915	24	Title: Framelet Message Passing Abstract: Graph neural networks (GNNs) have achieved champion in wide applications. Neural message passing is a typical key module for feature propagation by aggregating neighboring features. In this work, we propose a new message passing based on multiscale framelet transforms, called F...	[ 16466 ]	Test
36,916	15	Title: Revet: A Language and Compiler for Dataflow Threads Abstract: Spatial dataflow architectures such as reconfigurable dataflow accelerators (RDA) can provide much higher performance and efficiency than CPUs and GPUs. In particular, vectorized reconfigurable dataflow accelerators (vRDA) in recent literature represe...	[]	Train
36,917	7	Title: Full-Range Approximation for the Theis Well Function Using Ramanujan's Series and Bounds for the Exponential Integral Abstract: The solution of the governing equation representing the drawdown in a horizontal confined aquifer, where groundwater flow is unsteady, is provided in terms of the exponential integral, ...	[]	Validation
36,918	16	Title: MedBLIP: Bootstrapping Language-Image Pre-training from 3D Medical Images and Texts Abstract: Vision-language pre-training (VLP) models have been demonstrated to be effective in many computer vision applications. In this paper, we consider developing a VLP model in the medical domain for making computer-aided di...	[ 10624, 24756, 42425, 6842, 13564, 13438 ]	Validation
36,919	24	Title: Approximately Stationary Bandits with Knapsacks Abstract: Bandits with Knapsacks (BwK), the generalization of the Bandits problem under global budget constraints, has received a lot of attention in recent years. Previous work has focused on one of the two extremes: Stochastic BwK where the rewards and consumptio...	[]	Train
36,920	16	Title: Trainable Loss Weights in Super-Resolution Abstract: —In recent years, research on super-resolution has primarily focused on the development of unsupervised models, blind networks, and the use of optimization methods in non-blind models. But, limited research has discussed the loss function in the super-resoluti...	[]	Train
36,921	8	Title: ILCAS: Imitation Learning-Based Configuration-Adaptive Streaming for Live Video Analytics with Cross-Camera Collaboration Abstract: The high-accuracy and resource-intensive deep neural networks (DNNs) have been widely adopted by live video analytics (VA), where camera videos are streamed over the network to reso...	[ 32535 ]	Test
36,922	24	Title: Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach Abstract: Fair resource allocation is one of the most important topics in communication networks. Existing solutions almost exclusively assume each user utility function is known and concave. Thi...	[ 3653, 39718 ]	Test
36,923	23	Title: ZC3: Zero-Shot Cross-Language Code Clone Detection Abstract: Developers introduce code clones to improve programming productivity. Many existing studies have achieved impressive performance in monolingual code clone detection. However, during software development, more and more developers write semantically equi...	[ 10698, 6866, 3355, 44687 ]	Validation
36,924	24	Title: Discrete-Time Nonlinear Feedback Linearization via Physics-Informed Machine Learning Abstract: We present a physics-informed machine learning (PIML) scheme for the feedback linearization of nonlinear discrete-time dynamical systems. The PIML finds the nonlinear transformation law, thus ensuring stability via pol...	[]	Train
36,925	16	Title: VBSF-TLD: Validation-Based Approach for Soft Computing-Inspired Transfer Learning in Drone Detection Abstract: With the increasing utilization of Internet of Things (IoT) enabled drones in diverse applications like photography, delivery, and surveillance, concerns regarding privacy and security have become more ...	[]	Train
36,926	24	Title: Estimating Causal Effects using a Multi-task Deep Ensemble Abstract: A number of methods have been proposed for causal effect estimation, yet few have demonstrated efficacy in handling data with complex structures, such as images. To fill this gap, we propose Causal Multi-task Deep Ensemble (CMDE), a novel frame...	[ 42448 ]	Train
36,927	11	Title: Trust-Aware Resilient Control and Coordination of Connected and Automated Vehicles Abstract: We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to navigate through a conflict area. Adversarial attacks such as Sybil attacks can cause safety violations resulting in collisio...	[]	Train
36,928	3	Title: MED1stMR: Mixed Reality to Enhance Training of Medical First Responder]{MED1stMR: Mixed Reality to Enhance the Training of Medical First Responders for Challenging Contexts Abstract: Mass-casualty incidents with a large number of injured persons caused by human-made or by natural disasters are increasing globall...	[]	Validation
36,929	24	Title: Beyond Convergence: Identifiability of Machine Learning and Deep Learning Models Abstract: Machine learning (ML) and deep learning models are extensively used for parameter optimization and regression problems. However, not all inverse problems in ML are ``identifiable,'' indicating that model parameters may not...	[]	Train
36,930	8	Title: 6G Network Operation Support System Abstract: 6G is the next-generation intelligent and integrated digital information infrastructure, characterized by ubiquitous interconnection, native intelligence, multi-dimensional perception, global coverage, green and low-carbon, native network security, etc. 6G will reali...	[]	Validation
36,931	6	Title: CrossCode: Multi-level Visualization of Program Execution Abstract: Program visualizations help to form useful mental models of how programs work, and to reason and debug code. But these visualizations exist at a fixed level of abstraction, e.g., line-by-line. In contrast, programmers switch between many levels ...	[ 8390 ]	Train
36,932	16	Title: Context Normalization for Robust Image Classification Abstract: Normalization is a pre-processing step that converts the data into a more usable representation. As part of the deep neural networks (DNNs), the batch normalization (BN) technique uses normalization to address the problem of internal covariate shift...	[]	Validation
36,933	14	Title: How to automatise proofs of operator statements: Moore-Penrose inverse - a case study Abstract: We describe a recently developed algebraic framework for proving first-order statements about linear operators by computations with noncommutative polynomials. Furthermore, we present our new SageMath package operator...	[ 17338 ]	Train
36,934	16	Title: On the detection of Out-Of-Distribution samples in Multiple Instance Learning Abstract: The deployment of machine learning solutions in real-world scenarios often involves addressing the challenge of out-of-distribution (OOD) detection. While significant efforts have been devoted to OOD detection in classical su...	[ 18945, 17565 ]	Train
36,935	27	Title: Tuning Legged Locomotion Controllers via Safe Bayesian Optimization Abstract: In this paper, we present a data-driven strategy to simplify the deployment of model-based controllers in legged robotic hardware platforms. Our approach leverages a model-free safe learning algorithm to automate the tuning of control ...	[ 6995, 27079 ]	Train
36,936	30	Title: Robust Natural Language Understanding with Residual Attention Debiasing Abstract: Natural language understanding (NLU) models often suffer from unintended dataset biases. Among bias mitigation methods, ensemble-based debiasing methods, especially product-of-experts (PoE), have stood out for their impressive empi...	[]	Train
36,937	27	Title: Geometric Fault-Tolerant Control of Quadrotors in Case of Rotor Failures: An Attitude Based Comparative Study Abstract: The ability of aerial robots to operate in the presence of failures is crucial in various applications that demand continuous operations, such as surveillance, monitoring, and inspection. In th...	[]	Validation
36,938	31	Title: Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation Abstract: Recent years have witnessed the great successes of embedding-based methods in recommender systems. Despite their decent performance, we argue one potential limitation of these methods — the embedding magnitude has not been explicitly...	[ 1316 ]	Validation
36,939	27	Title: Learning Graph-Enhanced Commander-Executor for Multi-Agent Navigation Abstract: This paper investigates the multi-agent navigation problem, which requires multiple agents to reach the target goals in a limited time. Multi-agent reinforcement learning (MARL) has shown promising results for solving this issue. How...	[]	Train
36,940	24	Title: Reaction coordinate flows for model reduction of molecular kinetics Abstract: In this work, we introduce a flow based machine learning approach, called reaction coordinate (RC) flow, for discovery of low-dimensional kinetic models of molecular systems. The RC flow utilizes a normalizing flow to design the coordi...	[]	Train
36,941	16	Title: When Visible-to-Thermal Facial GAN Beats Conditional Diffusion Abstract: Thermal facial imagery offers valuable insight into physiological states such as inflammation and stress by detecting emitted radiation in the infrared spectrum, which is unseen in the visible spectra. Telemedicine applications could benefi...	[ 6731, 19669 ]	Train
36,942	16	Title: Controllable Inversion of Black-Box Face-Recognition Models via Diffusion Abstract: Face recognition models embed a face image into a low-dimensional identity vector containing abstract encodings of identity-specific facial features that allow individuals to be distinguished from one another. We tackle the chall...	[]	Train
36,943	24	Title: Structural Explanations for Graph Neural Networks using HSIC Abstract: Graph neural networks (GNNs) are a type of neural model that tackle graphical tasks in an end-to-end manner. Recently, GNNs have been receiving increased attention in machine learning and data mining communities because of the higher performa...	[]	Train
36,944	24	Title: Predicting the performance of hybrid ventilation in buildings using a multivariate attention-based biLSTM Encoder-Decoder neural network Abstract: Hybrid ventilation is an energy-efficient solution to provide fresh air for most climates, given that it has a reliable control system. To operate such systems optima...	[]	Test
36,945	24	Title: A Distinct Unsupervised Reference Model From The Environment Helps Continual Learning Abstract: The existing continual learning methods are mainly focused on fully-supervised scenarios and are still not able to take advantage of unlabeled data available in the environment. Some recent works tried to investigate ...	[]	Train
36,946	24	Title: Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis Abstract: Safe deployment of deep neural networks in high-stake real-world applications require theoretically sound uncertainty quantification. Conformal prediction (CP) is a p...	[]	Test
36,947	16	Title: Learning 3D-Aware Image Synthesis with Unknown Pose Distribution Abstract: Existing methods for 3D-aware image synthesis largely depend on the 3D pose distribution pre-estimated on the training set. An inaccurate estimation may mislead the model into learning faulty geometry. This work proposes PoF3D that frees ...	[ 39746, 19652, 16523, 3251, 26902, 14525, 19647 ]	Train
36,948	6	Title: SAPIEN: Affective Virtual Agents Powered by Large Language Models Abstract: In this demo paper, we introduce SAPIEN, a platform for high-fidelity virtual agents driven by large language models that can hold open domain conversations with users in 13 different languages, and display emotions through facial expres...	[ 36179, 33220, 2549 ]	Validation
36,949	24	Title: Randomized Quantization is All You Need for Differential Privacy in Federated Learning Abstract: Federated learning (FL) is a common and practical framework for learning a machine model in a decentralized fashion. A primary motivation behind this decentralized approach is data privacy, ensuring that the learner ...	[ 42513 ]	Test
36,950	4	Title: Multi-Biometric Fuzzy Vault based on Face and Fingerprints Abstract: The fuzzy vault scheme has been established as cryptographic primitive suitable for privacy-preserving biometric authentication. To improve accuracy and privacy protection, biometric information of multiple characteristics can be fused at featu...	[]	Test
36,951	16	Title: Implicit Ray Transformers for Multiview Remote Sensing Image Segmentation Abstract: The mainstream convolutional neural network (CNN)-based remote sensing (RS) image semantic segmentation approaches typically rely on massively labeled training data. Such a paradigm struggles with the problem of RS multiview scen...	[ 29015 ]	Train
36,952	16	Title: Real time dense anomaly detection by learning on synthetic negative data Abstract: Most approaches to dense anomaly detection rely on generative modeling or on discriminative methods that train with negative data. We consider a recent hybrid method that optimizes the same shared representation according to cross...	[ 15768 ]	Test
36,953	8	Title: Resident Population Density-Inspired Deployment of K-tier Aerial Cellular Network Abstract: Using unmanned aerial vehicles (UAVs) to enhance network coverage has proven a variety of benefits compared to terrestrial counterparts. One of the commonly used mathematical tools to model the locations of the UAVs is st...	[ 39335 ]	Validation
36,954	2	Title: Canonicity and Computability in Homotopy Type Theory Abstract: This dissertation gives an overview of Martin Lof's dependant type theory, focusing on its computational content and addressing a question of possibility of fully canonical and computable semantic presentation.	[]	Train
36,955	34	Title: Tight Approximations for Graphical House Allocation Abstract: The Graphical House Allocation (GHA) problem asks: how can $n$ houses (each with a fixed non-negative value) be assigned to the vertices of an undirected graph $G$, so as to minimize the sum of absolute differences along the edges of $G$? This problem...	[ 20236 ]	Train
36,956	16	Title: Robust Single Rotation Averaging Revisited Abstract: In this work, we propose a novel method for robust single rotation averaging that can efficiently handle an extremely large fraction of outliers. Our approach is to minimize the total truncated least unsquared deviations (TLUD) cost of geodesic distances. The ...	[ 16022, 4526 ]	Train
36,957	24	Title: A Survey on Graph Classification and Link Prediction based on GNN Abstract: Traditional convolutional neural networks are limited to handling Euclidean space data, overlooking the vast realm of real-life scenarios represented as graph data, including transportation networks, social networks, and reference networ...	[]	Train
36,958	16	Title: Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling Abstract: In recent years, single-frame image super-resolution (SR) has become more realistic by considering the zooming effect and using real-world short- and long-focus image pairs. In this paper, we further investigate the feasibility of ...	[]	Train
36,959	16	Title: LatentAugment: Data Augmentation via Guided Manipulation of GAN's Latent Space Abstract: Data Augmentation (DA) is a technique to increase the quantity and diversity of the training data, and by that alleviate overfitting and improve generalisation. However, standard DA produces synthetic data for augmentation w...	[]	Train
36,960	27	Title: Fast and Noise-Resilient Magnetic Field Mapping on a Low-Cost UAV Using Gaussian Process Regression Abstract: This study presents a comprehensive approach to mapping local magnetic field anomalies with robustness to magnetic noise from an unmanned aerial vehicle (UAV). The UAV collects magnetic field measurement...	[]	Validation
36,961	30	Title: A Survey of Resources and Methods for Natural Language Processing of Serbian Language Abstract: The Serbian language is a Slavic language spoken by over 12 million speakers and well understood by over 15 million people. In the area of natural language processing, it can be considered a low-resourced language. Al...	[]	Train
36,962	30	Title: Creative Data Generation: A Review Focusing on Text and Poetry Abstract: The rapid advancement in machine learning has led to a surge in automatic data generation, making it increasingly challenging to differentiate between naturally or human-generated data and machine-generated data. Despite these advancements,...	[ 28158 ]	Train
36,963	24	Title: Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion Abstract: Graph neural networks are widely used tools for graph prediction tasks. Motivated by their empirical performance, prior works have developed generalization bounds for graph neural networks, which scale with graph s...	[ 32962, 21731, 35910, 14474, 36398, 12447 ]	Test
36,964	30	Title: NOWJ at COLIEE 2023 - Multi-Task and Ensemble Approaches in Legal Information Processing Abstract: This paper presents the NOWJ team's approach to the COLIEE 2023 Competition, which focuses on advancing legal information processing techniques and applying them to real-world legal scenarios. Our team tackles the ...	[ 13865, 37349 ]	Validation
36,965	18	Title: Compact and Low-Loss PCM-based Silicon Photonic MZIs for Photonic Neural Networks Abstract: We present an optimized Mach-Zehnder Interferometer (MZI) with phase change materials for photonic neural networks (PNNs). With 0.2 dB loss, -38 dB crosstalk, and length of 52 micrometer, the designed MZI significantly im...	[ 21967 ]	Train
36,966	1	Title: Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining? Abstract: The multimedia community has shown a significant interest in perceiving and representing the physical world with multimodal pretrained neural network models, and among them, the visual-language pertaining (VLP) is, cu...	[ 10624, 40192, 5891, 13700, 33220, 42983, 15049, 26380, 16878, 33019, 35118, 4251, 27454 ]	Train
36,967	10	Title: Structural Embeddings of Tools for Large Language Models Abstract: It is evident that the current state of Large Language Models (LLMs) necessitates the incorporation of external tools. The lack of straightforward algebraic and logical reasoning is well documented and prompted researchers to develop frameworks w...	[ 40192, 14920, 25786, 5078, 634, 35580 ]	Test
36,968	11	Title: Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction Abstract: Efficient multi-robot task allocation (MRTA) is fundamental to various time-sensitive applications such as disaster response, warehouse operations, and construction. This ...	[ 41829 ]	Train
36,969	28	Title: Sharper Asymptotically Optimal CDC Schemes via Combinatorial Designs Abstract: Coded distributed computing (CDC) was introduced to greatly reduce the communication load for MapReduce computing systems. Such a system has $K$ nodes, $N$ input files, and $Q$ Reduce functions. Each input file is mapped by $r$ nodes ...	[ 27498, 5124, 6807 ]	Train
36,970	23	Title: Program Dependence Net and Its Slice for Verifying Linear Temporal Properties Abstract: The finite-state model checking of software is still limited by the notorious state-explosion problem. The dependence-based program slicing is effective to reduce the verification time and is orthogonal to other reduction tec...	[ 44601 ]	Validation
36,971	24	Title: Hundreds Guide Millions: Adaptive Offline Reinforcement Learning with Expert Guidance Abstract: Offline reinforcement learning (RL) optimizes the policy on a previously collected dataset without any interactions with the environment, yet usually suffers from the distributional shift problem. To mitigate this iss...	[]	Test
36,972	3	Title: AGI labs need an internal audit function Abstract: The paper argues that organizations that have the stated goal of building artificial general intelligence (AGI) need an internal audit function. First, it explains what internal audit is: a specific team that performs an ongoing assessment of an organization's r...	[ 38338, 33220, 32550, 4744, 24170, 5071, 39322, 2930, 32410, 1917 ]	Train
36,973	16	Title: Can We Evaluate Domain Adaptation Models Without Target-Domain Labels? A Metric for Unsupervised Evaluation of Domain Adaptation Abstract: Unsupervised domain adaptation (UDA) involves adapting a model trained on a label-rich source domain to an unlabeled target domain. However, in real-world scenarios, the abse...	[]	Train
36,974	16	Title: Permutation-Aware Action Segmentation via Unsupervised Frame-to-Segment Alignment Abstract: This paper presents an unsupervised transformer-based framework for temporal activity segmentation which leverages not only frame-level cues but also segment-level cues. This is in contrast with previous methods which oft...	[]	Train
36,975	23	Title: Software development in startup companies: A systematic mapping study Abstract: nan	[ 36531, 38035, 37434, 42363, 14135, 30906, 14267, 7357 ]	Train
36,976	24	Title: Limitless stability for Graph Convolutional Networks Abstract: This work establishes rigorous, novel and widely applicable stability guarantees and transferability bounds for graph convolutional networks -- without reference to any underlying limit object or statistical distribution. Crucially, utilized graph-sh...	[ 5980 ]	Train
36,977	24	Title: Deep incremental learning models for financial temporal tabular datasets with distribution shifts Abstract: We present a robust deep incremental learning framework for regression tasks on financial temporal tabular datasets which is built upon the incremental use of commonly available tabular and time series pre...	[ 20958 ]	Train

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