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30
Title: A Relaxed Optimization Approach for Adversarial Attacks against Neural Machine Translation Models Abstract: In this paper, we propose an optimization-based adversarial attack against Neural Machine Translation (NMT) models. First, we propose an optimization problem to generate adversarial examples that are seman...
[]
Train
32,779
4
Title: The Design Principle of Blockchain: An Initiative for the SoK of SoKs Abstract: security, scalability, decentralization, applicability, governance and regulation, system design, and cross-chain interoperability. Both research and practice are more centered around the first category of privacy and security and th...
[ 12505, 37309 ]
Test
32,780
39
Title: $\mathcal{P}$-matchings Parameterized by Treewidth Abstract: A \emph{matching} is a subset of edges in a graph $G$ that do not share an endpoint. A matching $M$ is a \emph{$\mathcal{P}$-matching} if the subgraph of $G$ induced by the endpoints of the edges of $M$ satisfies property $\mathcal{P}$. For example, if...
[]
Train
32,781
4
Title: Chrisimos: A useful Proof-of-Work for finding Minimal Dominating Set of a graph Abstract: Hash-based Proof-of-Work (PoW) used in the Bitcoin Blockchain leads to high energy consumption and resource wastage. In this paper, we aim to re-purpose the energy by replacing the hash function with real-life problems havi...
[]
Test
32,782
27
Title: Light-Weight Pointcloud Representation with Sparse Gaussian Process Abstract: This paper presents a framework to represent high-fidelity pointcloud sensor observations for efficient communication and storage. The proposed approach exploits Sparse Gaussian Process to encode pointcloud into a compact form. Our app...
[ 6985, 35092 ]
Validation
32,783
27
Title: Learning-on-the-Drive: Self-supervised Adaptation of Visual Offroad Traversability Models Abstract: Autonomous off-road driving requires understanding traversability, which refers to the suitability of a given terrain to drive over. When offroad vehicles travel at high speed ($>10m/s$), they need to reason at lo...
[ 41293, 42255 ]
Validation
32,784
10
Title: V-LoL: A Diagnostic Dataset for Visual Logical Learning Abstract: Despite the successes of recent developments in visual AI, different shortcomings still exist; from missing exact logical reasoning, to abstract generalization abilities, to understanding complex and noisy scenes. Unfortunately, existing benchmark...
[]
Train
32,785
23
Title: LExecutor: Learning-Guided Execution Abstract: Executing code is essential for various program analysis tasks, e.g., to detect bugs that manifest through exceptions or to obtain execution traces for further dynamic analysis. However, executing an arbitrary piece of code is often difficult in practice, e.g., beca...
[ 9571 ]
Train
32,786
24
Title: Editable Graph Neural Network for Node Classifications Abstract: Despite Graph Neural Networks (GNNs) have achieved prominent success in many graph-based learning problem, such as credit risk assessment in financial networks and fake news detection in social networks. However, the trained GNNs still make errors ...
[ 41436, 13549 ]
Train
32,787
34
Title: Maximum Coverage in Sublinear Space, Faster Abstract: Given a collection of $m$ sets from a universe $\mathcal{U}$, the Maximum Set Coverage problem consists of finding $k$ sets whose union has largest cardinality. This problem is NP-Hard, but the solution can be approximated by a polynomial time algorithm up to...
[]
Test
32,788
13
Title: Informed Down-Sampled Lexicase Selection: Identifying productive training cases for efficient problem solving Abstract: Genetic Programming (GP) often uses large training sets and requires all individuals to be evaluated on all training cases during selection. Random down-sampled lexicase selection evaluates ind...
[ 27941, 18502, 12818, 30455, 1721 ]
Train
32,789
24
Title: Deep Learning Driven Detection of Tsunami Related Internal GravityWaves: a path towards open-ocean natural hazards detection Abstract: Tsunamis can trigger internal gravity waves (IGWs) in the ionosphere, perturbing the Total Electron Content (TEC) - referred to as Traveling Ionospheric Disturbances (TIDs) that ...
[]
Train
32,790
24
Title: Provable Robustness for Streaming Models with a Sliding Window Abstract: The literature on provable robustness in machine learning has primarily focused on static prediction problems, such as image classification, in which input samples are assumed to be independent and model performance is measured as an expect...
[]
Train
32,791
4
Title: Unique Identification of 50, 000+ Virtual Reality Users from Head & Hand Motion Data Abstract: With the recent explosive growth of interest and investment in virtual reality (VR) and the so-called"metaverse,"public attention has rightly shifted toward the unique security and privacy threats that these platforms ...
[ 17573, 8871, 30600, 9112, 36223 ]
Test
32,792
30
Title: Making Metadata More FAIR Using Large Language Models Abstract: With the global increase in experimental data artifacts, harnessing them in a unified fashion leads to a major stumbling block - bad metadata. To bridge this gap, this work presents a Natural Language Processing (NLP) informed application, called FA...
[]
Test
32,793
34
Title: Subset Sum in Time 2n/2/poly(n) Abstract: A major goal in the area of exact exponential algorithms is to give an algorithm for the (worst-case) $n$-input Subset Sum problem that runs in time $2^{(1/2 - c)n}$ for some constant $c>0$. In this paper we give a Subset Sum algorithm with worst-case running time $O(2^{...
[]
Train
32,794
27
Title: Should Collaborative Robots be Transparent? Abstract: We often assume that robots which collaborate with humans should behave in ways that are transparent (e.g., legible, explainable). These transparent robots intentionally choose actions that convey their internal state to nearby humans: for instance, a transpa...
[]
Train
32,795
4
Title: Thwarting Code-Reuse and Side-Channel Attacks in Embedded Systems Abstract: Embedded devices are increasingly present in our everyday life. They often process critical information, and hence, rely on cryptographic protocols to achieve security. However, embedded devices remain vulnerable to attackers seeking to ...
[ 30980 ]
Train
32,796
24
Title: InstructionGPT-4: A 200-Instruction Paradigm for Fine-Tuning MiniGPT-4 Abstract: Multimodal large language models acquire their instruction-following capabilities through a two-stage training process: pre-training on image-text pairs and fine-tuning on supervised vision-language instruction data. Recent studies ...
[ 8608, 10624, 13700, 12709, 29999, 41104, 27282, 15413, 19671, 19578, 2811 ]
Test
32,797
30
Title: Improving Generalization of Adapter-Based Cross-lingual Transfer with Scheduled Unfreezing Abstract: Standard fine-tuning of language models typically performs well on in-distribution data, but suffers with generalization to distribution shifts. In this work, we aim to improve generalization of adapter-based cro...
[ 26501, 2687 ]
Train
32,798
24
Title: Semi-Implicit Denoising Diffusion Models (SIDDMs) Abstract: Despite the proliferation of generative models, achieving fast sampling during inference without compromising sample diversity and quality remains challenging. Existing models such as Denoising Diffusion Probabilistic Models (DDPM) deliver high-quality,...
[]
Train
32,799
16
Title: TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models Abstract: Data augmentation has been established as an efficacious approach to supplement useful information for low-resource datasets. Traditional augmentation techniques such as noise injection and image transformations ...
[ 12261 ]
Validation
32,800
16
Title: Self-supervised pseudo-colorizing of masked cells Abstract: Self-supervised learning, which is strikingly referred to as the dark matter of intelligence, is gaining more attention in biomedical applications of deep learning. In this work, we introduce a novel self-supervision objective for the analysis of cells ...
[]
Train
32,801
23
Title: How are We Detecting Inconsistent Method Names? An Empirical Study from Code Review Perspective Abstract: Proper naming of methods can make program code easier to understand, and thus enhance software maintainability. Yet, developers may use inconsistent names due to poor communication or a lack of familiarity w...
[]
Train
32,802
16
Title: Mapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection with Single Point Supervision Abstract: Training a convolutional neural network (CNN) to detect infrared small targets in a fully supervised manner has gained remarkable research interests in recent years, but is highly labor ex...
[ 39153, 2620 ]
Train
32,803
4
Title: Application of BadNets in Spam Filters Abstract: Spam filters are a crucial component of modern email systems, as they help to protect users from unwanted and potentially harmful emails. However, the effectiveness of these filters is dependent on the quality of the machine learning models that power them. In thi...
[]
Train
32,804
30
Title: Recursive Neural Networks with Bottlenecks Diagnose (Non-)Compositionality Abstract: A recent line of work in NLP focuses on the (dis)ability of models to generalise compositionally for artificial languages. However, when considering natural language tasks, the data involved is not strictly, or locally, composit...
[]
Train
32,805
11
Title: Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM Abstract: As artificial intelligence spreads out to numerous fields, the application of AI to sports analytics is also in the spotlight. However, one of the major challenges is the difficulty of automated ac...
[]
Train
32,806
24
Title: Automatic Debiased Learning from Positive, Unlabeled, and Exposure Data Abstract: We address the issue of binary classification from positive and unlabeled data (PU classification) with a selection bias in the positive data. During the observation process, (i) a sample is exposed to a user, (ii) the user then re...
[]
Train
32,807
24
Title: FedIL: Federated Incremental Learning from Decentralized Unlabeled Data with Convergence Analysis Abstract: Most existing federated learning methods assume that clients have fully labeled data to train on, while in reality, it is hard for the clients to get task-specific labels due to users' privacy concerns, hi...
[]
Validation
32,808
24
Title: A Dynamic Temporal Self-attention Graph Convolutional Network for Traffic Prediction Abstract: Accurate traffic prediction in real time plays an important role in Intelligent Transportation System (ITS) and travel navigation guidance. There have been many attempts to predict short-term traffic status which consi...
[]
Test
32,809
3
Title: Building Resilience to Climate Driven Extreme Events with Computing Innovations: A Convergence Accelerator Report Abstract: In 2022, the National Science Foundation (NSF) funded the Computing Research Association (CRA) to conduct a workshop to frame and scope a potential Convergence Accelerator research track on...
[]
Train
32,810
16
Title: Automatic detection of aerial survey ground control points based on Yolov5-OBB Abstract: The use of ground control points (GCPs) for georeferencing is the most common strategy in unmanned aerial vehicle (UAV) photogrammetry, but at the same time their collection represents the most time-consuming and expensive p...
[]
Validation
32,811
3
Title: Changes in Policy Preferences in German Tweets During the COVID Pandemic Abstract: nan
[]
Test
32,812
27
Title: Towards Automatic Identification of Globally Valid Geometric Flat Outputs via Numerical Optimization Abstract: Differential flatness enables efficient planning and control for underactuated robotic systems, but we lack a systematic and practical means of identifying a flat output (or determining whether one exis...
[]
Train
32,813
24
Title: Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels Abstract: A noisy training set usually leads to the degradation of the generalization and robustness of neural networks. In this paper, we propose a novel theoretically guaranteed clean sample selection framework for learning with noisy labels. ...
[]
Train
32,814
16
Title: CAILA: Concept-Aware Intra-Layer Adapters for Compositional Zero-Shot Learning Abstract: Compositionality, the ability to combine existing concepts and generalize towards novel compositions, is a key functionality for intelligent entities. Here, we study the problem of Compositional Zero-Shot Learning (CZSL), wh...
[]
Train
32,815
7
Title: Neural Network Accelerated Process Design of Polycrystalline Microstructures Abstract: Computational experiments are exploited in finding a well-designed processing path to optimize material structures for desired properties. This requires understanding the interplay between the processing-(micro)structure-prope...
[]
Train
32,816
16
Title: Exploring the Optimization Objective of One-Class Classification for Anomaly Detection Abstract: One-class classification (OCC) is a longstanding method for anomaly detection. With the powerful representation capability of the pre-trained backbone, OCC methods have witnessed significant performance improvements....
[]
Train
32,817
25
Title: Stuttering detection using speaker representations and self-supervised contextual embeddings Abstract: nan
[ 24320, 12437 ]
Train
32,818
33
Title: Probabilistic Planning with Prioritized Preferences over Temporal Logic Objectives Abstract: This paper studies temporal planning in probabilistic environments, modeled as labeled Markov decision processes (MDPs), with user preferences over multiple temporal goals. Existing works reflect such preferences as a pr...
[]
Validation
32,819
4
Title: Characterizing Cyber Attacks against Space Systems with Missing Data: Framework and Case Study Abstract: Cybersecurity of space systems is an emerging topic, but there is no single dataset that documents cyber attacks against space systems that have occurred in the past. These incidents are often scattered in me...
[]
Train
32,820
24
Title: CLIP4MC: An RL-Friendly Vision-Language Model for Minecraft Abstract: One of the essential missions in the AI research community is to build an autonomous embodied agent that can attain high-level performance across a wide spectrum of tasks. However, acquiring reward/penalty in all open-ended tasks is unrealisti...
[ 22816, 18427, 39669 ]
Train
32,821
39
Title: A note on local search for hitting sets Abstract: Let $\pi$ be a property of pairs $(G,Z)$, where $G$ is a graph and $Z\subseteq V(G)$. In the \emph{minimum $\pi$-hitting set problem}, given an input graph $G$, we want to find a smallest set $X\subseteq V(G)$ such that $X$ intersects every set $Z\subseteq V(G)$ ...
[]
Test
32,822
38
Title: A Novel Scholar Embedding Model for Interdisciplinary Collaboration Abstract: Interdisciplinary collaboration has become a driving force for scientific breakthroughs, and evaluating scholars’ performance in interdisciplinary researches is essential for promoting such collaborations. However, traditional scholar ...
[ 4509 ]
Train
32,823
36
Title: Approximating the Value of Energy-Parity Objectives in Simple Stochastic Games Abstract: We consider simple stochastic games $\mathcal G$ with energy-parity objectives, a combination of quantitative rewards with a qualitative parity condition. The Maximizer tries to avoid running out of energy while simultaneous...
[ 23154 ]
Validation
32,824
23
Title: The Probabilistic Bounds on the Feasibility of the Defect Prediction Models in Real-World Testing Environments Abstract: The research on developing software defect prediction (SDP) models is targeted at reducing the workload on the tester and, thereby, the time spent on the targeted module. However, while a cons...
[]
Train
32,825
16
Title: LiDAR2Map: In Defense of LiDAR-Based Semantic Map Construction Using Online Camera Distillation Abstract: Semantic map construction under bird's-eye view (BEV) plays an essential role in autonomous driving. In contrast to camera image, LiDAR provides the accurate 3D observations to project the captured 3D featur...
[ 45767 ]
Train
32,826
20
Title: Betti Number for Point Sets Abstract: Topology is the foundation for many industrial applications ranging from CAD to simulation analysis. Computational topology mostly focuses on structured data such as mesh. However, unstructured datasets such as point sets remain a virgin land for topology scientists. The sig...
[ 23088 ]
Train
32,827
16
Title: Hybrid-Supervised Dual-Search: Leveraging Automatic Learning for Loss-free Multi-Exposure Image Fusion Abstract: Multi-exposure image fusion (MEF) has emerged as a prominent solution to address the limitations of digital imaging in representing varied exposure levels. Despite its advancements, the field grapples...
[ 31163, 36829, 41182 ]
Test
32,828
16
Title: A deep-learning approach to early identification of suggested sexual harassment from videos Abstract: Sexual harassment, sexual abuse, and sexual violence are prevalent problems in this day and age. Women's safety is an important issue that needs to be highlighted and addressed. Given this issue, we have studied...
[]
Train
32,829
30
Title: PANACEA: An Automated Misinformation Detection System on COVID-19 Abstract: In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-checking module, which is supported by novel natural language ...
[ 32889, 18239 ]
Train
32,830
16
Title: EA-LSS: Edge-aware Lift-splat-shot Framework for 3D BEV Object Detection Abstract: In recent years, great progress has been made in the Lift-Splat-Shot-based (LSS-based) 3D object detection method. However, inaccurate depth estimation remains an important constraint to the accuracy of camera-only and multi-model...
[]
Test
32,831
30
Title: Polyglot or Not? Measuring Multilingual Encyclopedic Knowledge Retrieval from Foundation Language Models Abstract: In this work, we evaluate the capacity for foundation models to retrieve encyclopedic knowledge across a wide range of languages, topics, and contexts. To support this effort, we 1) produce a new da...
[ 32944, 33220, 13700, 1917 ]
Train
32,832
16
Title: SoccerNet-Caption: Dense Video Captioning for Soccer Broadcasts Commentaries Abstract: Soccer is more than just a game - it is a passion that transcends borders and unites people worldwide. From the roar of the crowds to the excitement of the commentators, every moment of a soccer match is a thrill. Yet, with so...
[ 13425, 20169 ]
Train
32,833
13
Title: Multitasking Evolutionary Algorithm Based on Adaptive Seed Transfer for Combinatorial Problem Abstract: nan
[]
Validation
32,834
7
Title: Comparison of Neural FEM and Neural Operator Methods for applications in Solid Mechanics Abstract: Machine Learning methods belong to the group of most up-to-date approaches for solving partial differential equations. The current work investigates two classes, Neural FEM and Neural Operator Methods, for the use ...
[]
Train
32,835
24
Title: Make Transformer Great Again for Time Series Forecasting: Channel Aligned Robust Dual Transformer Abstract: Recent studies have demonstrated the great power of deep learning methods, particularly Transformer and MLP, for time series forecasting. Despite its success in NLP and CV, many studies found that Transfor...
[ 16576, 21778, 28917, 23527 ]
Train
32,836
22
Title: Builtin Types viewed as Inductive Families Abstract: State of the art optimisation passes for dependently typed languages can help erase the redundant information typical of invariant-rich data structures and programs. These automated processes do not dramatically change the structure of the data, even though mo...
[ 14723 ]
Test
32,837
24
Title: Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification Abstract: We consider the problem of uncertainty quantification in high dimensional regression and classification for which deep ensemble have proven to be promising methods. Recent observations have shown that deep e...
[]
Validation
32,838
24
Title: Evaluating AI systems under uncertain ground truth: a case study in dermatology Abstract: For safety, AI systems in health undergo thorough evaluations before deployment, validating their predictions against a ground truth that is assumed certain. However, this is actually not the case and the ground truth may b...
[ 24617, 43683, 8644, 6109 ]
Train
32,839
24
Title: Supervised Auto-Encoding Twin-Bottleneck Hashing Abstract: Deep hashing has shown to be a complexity-efficient solution for the Approximate Nearest Neighbor search problem in high dimensional space. Many methods usually build the loss function from pairwise or triplet data points to capture the local similarity ...
[]
Train
32,840
27
Title: Optical flow-based vascular respiratory motion compensation Abstract: This paper develops a new vascular respiratory motion compensation algorithm, Motion-Related Compensation (MRC), to conduct vascular respiratory motion compensation by extrapolating the correlation between invisible vascular and visible non-va...
[ 29786 ]
Train
32,841
33
Title: A weakly universal weighted cellular automaton in the heptagrid with 7 states Abstract: In this paper we prove that there is a weakly universal weighted cellular automaton in the heptagrid, the tessellation {7,3} of the hyperbolic plane, with 6 states. The present paper improves the same result deposited on arXi...
[ 33427 ]
Train
32,842
16
Title: Cross-domain Iterative Network for Simultaneous Denoising, Limited-angle Reconstruction, and Attenuation Correction of Low-dose Cardiac SPECT Abstract: Single-Photon Emission Computed Tomography (SPECT) is widely applied for the diagnosis of ischemic heart diseases. Low-dose (LD) SPECT aims to minimize radiation...
[]
Train
32,843
24
Title: Upscaling Global Hourly GPP with Temporal Fusion Transformer (TFT) Abstract: Reliable estimates of Gross Primary Productivity (GPP), crucial for evaluating climate change initiatives, are currently only available from sparsely distributed eddy covariance tower sites. This limitation hampers access to reliable GP...
[]
Test
32,844
16
Title: Partial-View Object View Synthesis via Filtered Inversion Abstract: We propose Filtering Inversion (FINV), a learning framework and optimization process that predicts a renderable 3D object representation from one or few partial views. FINV addresses the challenge of synthesizing novel views of objects from part...
[ 30566 ]
Train
32,845
10
Title: Inferring Preferences from Demonstrations in Multi-objective Reinforcement Learning: A Dynamic Weight-based Approach Abstract: Many decision-making problems feature multiple objectives. In such problems, it is not always possible to know the preferences of a decision-maker for different objectives. However, it i...
[]
Train
32,846
24
Title: Flexible Job Shop Scheduling via Dual Attention Network Based Reinforcement Learning Abstract: Flexible manufacturing has given rise to complex scheduling problems such as the flexible job shop scheduling problem (FJSP). In FJSP, operations can be processed on multiple machines, leading to intricate relationship...
[]
Test
32,847
16
Title: Dual Stage Stylization Modulation for Domain Generalized Semantic Segmentation Abstract: Obtaining sufficient labeled data for training deep models is often challenging in real-life applications. To address this issue, we propose a novel solution for single-source domain generalized semantic segmentation. Recent...
[ 40287 ]
Test
32,848
16
Title: A New Perspective for Shuttlecock Hitting Event Detection Abstract: This article introduces a novel approach to shuttlecock hitting event detection. Instead of depending on generic methods, we capture the hitting action of players by reasoning over a sequence of images. To learn the features of hitting events in...
[]
Test
32,849
2
Title: A system of inference based on proof search: an extended abstract Abstract: Gentzen designed his natural deduction proof system to "come as close as possible to actual reasoning." Indeed, natural deduction proofs closely resemble the static structure of logical reasoning in mathematical arguments. However, diffe...
[]
Train
32,850
24
Title: Finding Needles in Haystack: Formal Generative Models for Efficient Massive Parallel Simulations Abstract: The increase in complexity of autonomous systems is accompanied by a need of data-driven development and validation strategies. Advances in computer graphics and cloud clusters have opened the way to massiv...
[]
Test
32,851
10
Title: Knowledge Graph Completion based on Tensor Decomposition for Disease Gene Prediction Abstract: Accurate identification of disease genes has consistently been one of the keys to decoding a disease's molecular mechanism. Most current approaches focus on constructing biological networks and utilizing machine learni...
[]
Train
32,852
16
Title: MarginMatch: Improving Semi-Supervised Learning with Pseudo-Margins Abstract: We introduce MarginMatch, a new SSL approach combining consistency regularization and pseudo-labeling, with its main novelty arising from the use of unlabeled data training dynamics to measure pseudo-label quality. Instead of using onl...
[]
Test
32,853
2
Title: A separation logic for sequences in pointer programs and its decidability Abstract: Separation logic and its variants can describe various properties on pointer programs. However, when it comes to properties on sequences, one may find it hard to formalize. To deal with properties on variable-length sequences and...
[]
Train
32,854
28
Title: Construction of Optimal Binary Z-Complementary Code Sets with New Lengths Using Generalized Boolean Function Abstract: nan
[ 7119 ]
Train
32,855
25
Title: A General Framework for Learning Procedural Audio Models of Environmental Sounds Abstract: This paper introduces the Procedural (audio) Variational autoEncoder (ProVE) framework as a general approach to learning Procedural Audio PA models of environmental sounds with an improvement to the realism of the synthesi...
[]
Train
32,856
6
Title: UbiPhysio: Support Daily Functioning, Fitness, and Rehabilitation with Action Understanding and Feedback in Natural Language Abstract: We introduce UbiPhysio, a milestone framework that delivers fine-grained action description and feedback in natural language to support people's daily functioning, fitness, and r...
[ 36774, 29049, 32213, 43641, 17178, 44858, 21215 ]
Train
32,857
16
Title: Multiclass Confidence and Localization Calibration for Object Detection Abstract: Albeit achieving high predictive accuracy across many challenging computer vision problems, recent studies suggest that deep neural networks (DNNs) tend to make over-confident predictions, rendering them poorly calibrated. Most of ...
[ 36102 ]
Validation
32,858
22
Title: The Usability of Advanced Type Systems: Rust as a Case Study Abstract: Advanced type systems that enforce various correctness and safety guarantees--such as linear and ownership types--have a long history in the Programming Languages research community. Despite this history, a human-centered evaluation of these ...
[]
Train
32,859
30
Title: Platypus: Quick, Cheap, and Powerful Refinement of LLMs Abstract: We present $\textbf{Platypus}$, a family of fine-tuned and merged Large Language Models (LLMs) that achieves the strongest performance and currently stands at first place in HuggingFace's Open LLM Leaderboard as of the release date of this work. I...
[ 12128, 14592, 43970, 2980, 12741, 10598, 13029, 13700, 15812, 6797, 36786, 33815, 45494, 5815, 6328, 13855 ]
Test
32,860
26
Title: A multiple k-means cluster ensemble framework for clustering citation trajectories Abstract: Citation maturity time varies for different articles. However, the impact of all articles is measured in a fixed window. Clustering their citation trajectories helps understand the knowledge diffusion process and reveals...
[]
Test
32,861
30
Title: WADER at SemEval-2023 Task 9: A Weak-labelling framework for Data augmentation in tExt Regression Tasks Abstract: Intimacy is an essential element of human relationships and language is a crucial means of conveying it. Textual intimacy analysis can reveal social norms in different contexts and serve as a benchma...
[]
Train
32,862
4
Title: A Review of Data-driven Approaches for Malicious Website Detection Abstract: The detection of malicious websites has become a critical issue in cybersecurity. Therefore, this paper offers a comprehensive review of data-driven methods for detecting malicious websites. Traditional approaches and their limitations ...
[]
Train
32,863
30
Title: LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors Abstract: Prompt-tuning has emerged as an attractive paradigm for deploying large-scale language models due to its strong downstream task performance and efficient multitask serving ability. Despite its wide adoption, we empirically show that p...
[]
Train
32,864
3
Title: Education 5.0: Requirements, Enabling Technologies, and Future Directions Abstract: We are currently in a post-pandemic era in which life has shifted to a digital world. This has affected many aspects of life, including education and learning. Education 5.0 refers to the fifth industrial revolution in education ...
[]
Test
32,865
24
Title: Tuning structure learning algorithms with out-of-sample and resampling strategies Abstract: One of the challenges practitioners face when applying structure learning algorithms to their data involves determining a set of hyperparameters; otherwise, a set of hyperparameter defaults is assumed. The optimal hyperpa...
[ 7403 ]
Test
32,866
23
Title: Specification Inference for Evolving Systems Abstract: In this paper, we propose an assertion-based approach to capture software evolution, through the notion of commit-relevant specification. A commit-relevant specification summarises the program properties that have changed as a consequence of a commit (unders...
[]
Train
32,867
30
Title: \`{I}r\`{o}y\`{i}nSpeech: A multi-purpose Yor\`{u}b\'{a} Speech Corpus Abstract: We introduce the \`{I}r\`{o}y\`{i}nSpeech corpus -- a new dataset influenced by a desire to increase the amount of high quality, freely available, contemporary Yor\`{u}b\'{a} speech. We release a multi-purpose dataset that can be us...
[]
Train
32,868
10
Title: What is a decision problem? Abstract: This paper presents a general framework about what is a decision problem. Our motivation is related to the fact that decision analysis and operational research are structured (as disciplines) around classes of methods, while instead we should first characterise the decision p...
[]
Validation
32,869
24
Title: A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection Abstract: Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series a...
[ 40192, 42114, 37507, 45828, 35597, 2969, 19996, 40348, 29857, 14628, 20263, 15529, 17331, 36791, 16965, 38734, 18511, 31696, 40272, 1876, 44122, 31215, 42353, 4210, 25970, 42867, 7670, 3575, 23805 ]
Test
32,870
2
Title: Engel’s Theorem in Mathlib Abstract: nan
[]
Validation
32,871
24
Title: Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study Abstract: Modeling and simulations of pandemic dynamics play an essential role in understanding and addressing the spreading of highly infectious diseases such as COVID-19. In this work, we propose a novel deep learning ...
[ 1888 ]
Train
32,872
30
Title: SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation Abstract: Scientific writing involves retrieving, summarizing, and citing relevant papers, which can be time-consuming processes. Although in many workflows these processes are serially linked, there are opportuni...
[]
Validation
32,873
25
Title: Sound-based drone fault classification using multitask learning Abstract: The drone has been used for various purposes, including military applications, aerial photography, and pesticide spraying. However, the drone is vulnerable to external disturbances, and malfunction in propellers and motors can easily occur...
[]
Test
32,874
16
Title: DUFormer: Solving Power Line Detection Task in Aerial Images using Semantic Segmentation Abstract: Unmanned aerial vehicles (UAVs) are frequently used for inspecting power lines and capturing high-resolution aerial images. However, detecting power lines in aerial images is difficult,as the foreground data(i.e, p...
[]
Test
32,875
16
Title: Leveraging the Edge and Cloud for V2X-Based Real-Time Object Detection in Autonomous Driving Abstract: Environmental perception is a key element of autonomous driving because the information received from the perception module influences core driving decisions. An outstanding challenge in real-time perception fo...
[ 31551 ]
Train
32,876
24
Title: Optimizing Offensive Gameplan in the National Basketball Association with Machine Learning Abstract: Throughout the analytical revolution that has occurred in the NBA, the development of specific metrics and formulas has given teams, coaches, and players a new way to see the game. However - the question arises -...
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Validation
32,877
16
Title: InpaintNeRF360: Text-Guided 3D Inpainting on Unbounded Neural Radiance Fields Abstract: Neural Radiance Fields (NeRF) can generate highly realistic novel views. However, editing 3D scenes represented by NeRF across 360-degree views, particularly removing objects while preserving geometric and photometric consist...
[ 12704, 19781, 541, 35263 ]
Validation