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
19,778	30	Title: Topical-Chat: Towards Knowledge-Grounded Open-Domain Conversations Abstract: Building socialbots that can have deep, engaging open-domain conversations with humans is one of the grand challenges of artificial intelligence (AI). To this end, bots need to be able to leverage world knowledge spanning several domain...	[ 36097, 41350, 29832, 8713, 5131, 29206, 4641, 21032, 13231, 37684, 45239, 22842, 2622, 7246, 31836, 734, 45935, 8817, 6775 ]	Train
19,779	28	Title: Spatial Modulation with Energy Detection: Diversity Analysis and Experimental Evaluation Abstract: In this paper, we present a non-coherent energy detection scheme for spatial modulation (SM) systems. In particular, the use of SM is motivated by its low-complexity implementation in comparison to multiple-input m...	[]	Train
19,780	30	Title: Improving the Generalization Ability in Essay Coherence Evaluation through Monotonic Constraints Abstract: Coherence is a crucial aspect of evaluating text readability and can be assessed through two primary factors when evaluating an essay in a scoring scenario. The first factor is logical coherence, characteri...	[]	Train
19,781	16	Title: Nerfstudio: A Modular Framework for Neural Radiance Field Development Abstract: Neural Radiance Fields (NeRF) are a rapidly growing area of research with wide-ranging applications in computer vision, graphics, robotics, and more. In order to streamline the development and deployment of NeRF research, we propose ...	[ 27264, 28673, 44288, 2950, 13319, 36871, 23051, 28557, 541, 8606, 39587, 9515, 14892, 45356, 38959, 32433, 21170, 28851, 35000, 41400, 9276, 10313, 3277, 35030, 21846, 18012, 41055, 23392, 39653, 37352, 32877, 30835, 30457, 32762, 13565 ]	Validation
19,782	4	Title: SF-IDS: An Imbalanced Semi-Supervised Learning Framework for Fine-grained Intrusion Detection Abstract: Deep learning-based fine-grained network intrusion detection systems (NIDS) enable different attacks to be responded to in a fast and targeted manner with the help of large-scale labels. However, the cost of l...	[]	Validation
19,783	24	Title: Semi-Supervised Machine Learning: a Homological Approach Abstract: A BSTRACT . In this paper we describe the mathematical foundations of a new approach to semi-supervised Machine Learning. Using techniques of Symbolic Computation and Computer Algebra, we apply the concept of persistent homology to obtain a new s...	[ 33822 ]	Test
19,784	24	Title: DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting Abstract: While diffusion models can successfully generate data and make predictions, they are predominantly designed for static images. We propose an approach for training diffusion models for dynamics forecasting that leverages the t...	[ 37545, 878, 30169, 37402, 1116 ]	Train
19,785	2	Title: Characterising Modal Formulas with Examples Abstract: We study the existence of finite characterisations for modal formulas. A finite characterisation of a modal formula $\varphi$ is a finite collection of positive and negative examples that distinguishes $\varphi$ from every other, non-equivalent modal formula,...	[ 20259, 31092 ]	Test
19,786	22	Title: Generalizing Hierarchical Parallelism Abstract: nan	[]	Train
19,787	16	Title: What Do Self-Supervised Vision Transformers Learn? Abstract: We present a comparative study on how and why contrastive learning (CL) and masked image modeling (MIM) differ in their representations and in their performance of downstream tasks. In particular, we demonstrate that self-supervised Vision Transformers...	[ 26498, 5892, 15269, 40868, 27622, 9609, 18058, 35370, 25654, 26491 ]	Train
19,788	24	Title: Towards the Characterization of Representations Learned via Capsule-based Network Architectures Abstract: Capsule Networks (CapsNets) have been re-introduced as a more compact and interpretable alternative to standard deep neural networks. While recent efforts have proved their compression capabilities, to date,...	[ 27092 ]	Validation
19,789	16	Title: FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofing Abstract: The availability of handy multi-modal (i.e., RGB-D) sensors has brought about a surge of face anti-spoofing research. However, the current multi-modal face presentation attack detection (PAD) has two defects: (1) The framework based on m...	[ 19977, 18995, 19246 ]	Validation
19,790	24	Title: CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data Abstract: This study presents a novel constraint-based causal discovery approach for autocorrelated and non-stationary time series data (CDANs). Our proposed method addresses several limitations of existing causal discovery ...	[ 34570 ]	Validation
19,791	36	Title: Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions Abstract: We study the design of loss functions for click-through rates (CTR) to optimize (social) welfare in advertising auctions. Existing works either only focus on CTR predictions without consideration of busine...	[]	Train
19,792	16	Title: A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos Abstract: Detecting breast lesion in videos is crucial for computer-aided diagnosis. Existing video-based breast lesion detection approaches typically perform temporal feature aggregation of deep backbone features based...	[]	Validation
19,793	30	Title: How to Distill your BERT: An Empirical Study on the Impact of Weight Initialisation and Distillation Objectives Abstract: Recently, various intermediate layer distillation (ILD) objectives have been shown to improve compression of BERT models via Knowledge Distillation (KD). However, a comprehensive evaluation o...	[]	Test
19,794	26	Title: Effective Graph-Neural-Network based Models for Discovering Structural Hole Spanners in Large-Scale and Diverse Networks Abstract: A Structural Hole Spanner (SHS) is a set of nodes in a network that act as a bridge among different otherwise disconnected communities. Numerous solutions have been proposed to disco...	[]	Validation
19,795	27	Title: Factorization of Multi-Agent Sampling-Based Motion Planning Abstract: Modern robotics often involves multiple embodied agents operating within a shared environment. Path planning in these cases is considerably more challenging than in single-agent scenarios. Although standard Sampling-based Algorithms (SBAs) can...	[]	Validation
19,796	26	Title: Attributed Stream Hypergraphs: temporal modeling of node-attributed high-order interactions Abstract: nan	[]	Validation
19,797	27	Title: MOVESe: MOVablE and Moving LiDAR Scene Segmentation with Improved Navigation in Seg-label free settings Abstract: Accurate detection of movable and moving objects in LiDAR is of vital importance for navigation. Most existing works focus on extracting and removing moving objects during navigation. Movable objects...	[]	Train
19,798	16	Title: LivePose: Online 3D Reconstruction from Monocular Video with Dynamic Camera Poses Abstract: Dense 3D reconstruction from RGB images traditionally assumes static camera pose estimates. This assumption has endured, even as recent works have increasingly focused on real-time methods for mobile devices. However, the...	[ 30238 ]	Test
19,799	24	Title: Deep Learning and Geometric Deep Learning: an introduction for mathematicians and physicists Abstract: In this expository paper we want to give a brief introduction, with few key references for further reading, to the inner functioning of the new and successfull algorithms of Deep Learning and Geometric Deep Lea...	[]	Train
19,800	16	Title: AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset Abstract: It is a long-term vision for Autonomous Driving (AD) community that the perception models can learn from a large-scale point cloud dataset, to obtain unified representations that can achieve promising results on different tasks...	[ 26137, 14062, 40999 ]	Train
19,801	24	Title: Scaling Survival Analysis in Healthcare with Federated Survival Forests: A Comparative Study on Heart Failure and Breast Cancer Genomics Abstract: nan	[ 45304, 41058 ]	Train
19,802	3	Title: Applications of educational data mining and learning analytics on data from cybersecurity training Abstract: nan	[]	Train
19,803	24	Title: BayesFlow: Amortized Bayesian Workflows With Neural Networks Abstract: Modern Bayesian inference involves a mixture of computational techniques for estimating, validating, and drawing conclusions from probabilistic models as part of principled workflows for data analysis. Typical problems in Bayesian workflows a...	[ 24045 ]	Validation
19,804	30	Title: Graph-based Keyword Planning for Legal Clause Generation from Topics Abstract: Generating domain-specific content such as legal clauses based on minimal user-provided information can be of significant benefit in automating legal contract generation. In this paper, we propose a controllable graph-based mechanism ...	[]	Train
19,805	2	Title: Compositional Separation of Control Flow and Data Flow Abstract: Every constructive model of computation (CMC) has an underlying composition mechanism for combining simple computation devices into more complex ones. Composition can be done by (explicitly or implicitly) defining control flow, data flow or any com...	[]	Test
19,806	24	Title: The noise level in linear regression with dependent data Abstract: We derive upper bounds for random design linear regression with dependent ($\beta$-mixing) data absent any realizability assumptions. In contrast to the strictly realizable martingale noise regime, no sharp instance-optimal non-asymptotics are av...	[]	Train
19,807	28	Title: Mutual Information Analysis for Factor Graph-based MIMO Iterative Detections through Error Functions Abstract: The factor graph (FG) based iterative detection is considered an effective and practical method for multiple-input and multiple-out (MIMO), particularly massive MIMO (m-MIMO) systems. However, the conve...	[]	Test
19,808	6	Title: Needs, Passions and Loot Boxes - Exploring Reasons for Problem Behaviour in Relation to Loot Box Engagement Abstract: Research on the convergence of gaming and gambling has been around since the 1990s. The emergence of loot boxes in video games in the mid 2010s, a game mechanic with a chance-based outcome that s...	[]	Validation
19,809	31	Title: Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders Abstract: Sequential recommenders have been widely used in industry due to their strength in modeling user preferences. While these models excel at learning a user’s positive interests, less attention has been paid to l...	[]	Test
19,810	10	Title: An Application of Neutrosophic Sets to Decision Making Abstract: Maji et al. introduced in 2002 a method of parametric decision making using soft sets as tools and representing their tabular form as a binary matrix. In cases, however, where some or all of the parameters used for the characterization of the eleme...	[]	Train
19,811	27	Title: Refining Obstacle Perception Safety Zones via Maneuver-Based Decomposition Abstract: A critical task for developing safe autonomous driving stacks is to determine whether an obstacle is safety-critical, i.e., poses an imminent threat to the autonomous vehicle. Our previous work showed that Hamilton Jacobi reacha...	[]	Train
19,812	24	Title: GCI: A (G)raph (C)oncept (I)nterpretation Framework Abstract: Explainable AI (XAI) underwent a recent surge in research on concept extraction, focusing on extracting human-interpretable concepts from Deep Neural Networks. An important challenge facing concept extraction approaches is the difficulty of interpreti...	[]	Validation
19,813	4	Title: Interpreting GNN-based IDS Detections Using Provenance Graph Structural Features Abstract: The black-box nature of complex Neural Network (NN)-based models has hindered their widespread adoption in security domains due to the lack of logical explanations and actionable follow-ups for their predictions. To enhanc...	[]	Train
19,814	24	Title: A Framework for Learning From Demonstration With Minimal Human Effort Abstract: We consider robot learning in the context of shared autonomy, where control of the system can switch between a human teleoperator and autonomous control. In this setting we address reinforcement learning, and learning from demonstrat...	[ 29643 ]	Train
19,815	16	Title: Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities Abstract: Decoding visual stimuli from neural responses recorded by functional Magnetic Resonance Imaging (fMRI) presents an intriguing intersection between cognitive neuroscience and machine learning, promising advancements in u...	[ 34074, 15983 ]	Train
19,816	9	Title: A Fine-Grained Classification of the Complexity of Evaluating the Tutte Polynomial on Integer Points Parameterized by Treewidth and Cutwidth Abstract: We give a fine-grained classification of evaluating the Tutte polynomial $T(G;x,y)$ on all integer points on graphs with small treewidth and cutwidth. Specificall...	[]	Validation
19,817	24	Title: G-CEALS: Gaussian Cluster Embedding in Autoencoder Latent Space for Tabular Data Representation Abstract: The latent space of autoencoders has been improved for clustering image data by jointly learning a t-distributed embedding with a clustering algorithm inspired by the neighborhood embedding concept proposed ...	[]	Train
19,818	16	Title: Temporal Sentence Grounding in Streaming Videos Abstract: This paper aims to tackle a novel task - Temporal Sentence Grounding in Streaming Videos (TSGSV). The goal of TSGSV is to evaluate the relevance between a video stream and a given sentence query. Unlike regular videos, streaming videos are acquired contin...	[ 18490, 20203, 8813 ]	Train
19,819	38	Title: Using citation networks to evaluate the impact of text length on the identification of relevant concepts Abstract: ,	[]	Train
19,820	27	Title: An Efficient Multi-solution Solver for the Inverse Kinematics of 3-Section Constant-Curvature Robots Abstract: Piecewise constant curvature is a popular kinematics framework for continuum robots. Computing the model parameters from the desired end pose, known as the inverse kinematics problem, is fundamental in ...	[]	Test
19,821	25	Title: Learning Local to Global Feature Aggregation for Speech Emotion Recognition Abstract: Transformer has emerged in speech emotion recognition (SER) at present. However, its equal patch division not only damages frequency information but also ignores local emotion correlations across frames, which are key cues to r...	[]	Test
19,822	16	Title: Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging Abstract: Snapshot compressive imaging emerges as a promising technology for acquiring real-world hyperspectral signals. It uses an optical encoder and compressively produces the 2D measurement, followed by which the 3D hyperspectral data can ...	[ 29111 ]	Train
19,823	30	Title: Cost-efficient Crowdsourcing for Span-based Sequence Labeling: Worker Selection and Data Augmentation Abstract: This paper introduces a novel worker selection algorithm, enhancing annotation quality and reducing costs in challenging span-based sequence labeling tasks in Natural Language Processing (NLP). Unlike ...	[]	Train
19,824	30	Title: Time to Embrace Natural Language Processing (NLP)-based Digital Pathology: Benchmarking NLP- and Convolutional Neural Network-based Deep Learning Pipelines Abstract: NLP-based computer vision models, particularly vision transformers, have been shown to outperform CNN models in many imaging tasks. However, most d...	[]	Train
19,825	5	Title: Coded Distributed Image Classification Abstract: In this paper, we present a coded computation (CC) scheme for distributed computation of the inference phase of machine learning (ML) tasks, specifically, the task of image classification. Building upon Agrawal et al.~2022, the proposed scheme combines the strengt...	[]	Train
19,826	24	Title: Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention Abstract: Recent years have witnessed the great potential of attention mechanism in graph representation learning. However, while variants of attention-based GNNs are setting new benchmarks for n...	[ 2450 ]	Train
19,827	34	Title: Tight Lower Bound on Equivalence Testing in Conditional Sampling Model Abstract: We study the equivalence testing problem where the goal is to determine if the given two unknown distributions on $[n]$ are equal or $\epsilon$-far in the total variation distance in the conditional sampling model (CFGM, SICOMP16; C...	[]	Train
19,828	16	Title: Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks Abstract: Change detection, as an important application for high-resolution remote sensing images, aims to monitor and analyze changes in the land surface over time. With the rapid growth in...	[ 16470 ]	Train
19,829	37	Title: Probabilistic Reasoning at Scale: Trigger Graphs to the Rescue Abstract: The role of uncertainty in data management has become more prominent than ever before, especially because of the growing importance of machine learning-driven applications that produce large uncertain databases. A well-known approach to que...	[]	Test
19,830	37	Title: DataVinci: Learning Syntactic and Semantic String Repairs Abstract: String data is common in real-world datasets: 67.6% of values in a sample of 1.8 million real Excel spreadsheets from the web were represented as text. Systems that successfully clean such string data can have a significant impact on real users....	[ 392 ]	Test
19,831	24	Title: Adiabatic replay for continual learning Abstract: Conventional replay-based approaches to continual learning (CL) require, for each learning phase with new data, the replay of samples representing all of the previously learned knowledge in order to avoid catastrophic forgetting. Since the amount of learned knowl...	[]	Train
19,832	16	Title: Rapid building damage assessment workflow: An implementation for the 2023 Rolling Fork, Mississippi tornado event Abstract: Rapid and accurate building damage assessments from high-resolution satellite imagery following a natural disaster is essential to inform and optimize first responder efforts. However, perf...	[]	Train
19,833	10	Title: Concept Extrapolation: A Conceptual Primer Abstract: This article is a primer on concept extrapolation - the ability to take a concept, a feature, or a goal that is defined in one context and extrapolate it safely to a more general context. Concept extrapolation aims to solve model splintering - a ubiquitous occ...	[ 16098 ]	Test
19,834	23	Title: On the Effect of Transitivity and Granularity on Vulnerability Propagation in the Maven Ecosystem Abstract: Reusing software libraries is a pillar of modern software engineering. In 2022, the average Java application depends on 40 third-party libraries. Relying on such libraries exposes a project to potential vu...	[ 25537, 40871 ]	Train
19,835	16	Title: Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects Abstract: Camouflaged object detection (COD) is the challenging task of identifying camouflaged objects visually blended into surroundings. Albeit achieving remarkable success, existing COD detectors st...	[ 23266 ]	Test
19,836	27	Title: Near Field iToF LIDAR Depth Improvement from Limited Number of Shots Abstract: Indirect Time of Flight LiDARs can indirectly calculate the scene’s depth from the phase shift angle between transmitted and received laser signals with amplitudes modulated at a predefined frequency. Unfortunately, this method genera...	[]	Train
19,837	27	Title: Graph-based SLAM-Aware Exploration with Prior Topo-Metric Information Abstract: Autonomous exploration requires the robot to explore an unknown environment while constructing an accurate map with the SLAM (Simultaneous Localization and Mapping) techniques. Without prior information, the exploratory performance i...	[ 35587 ]	Validation
19,838	37	Title: Learned Query Superoptimization Abstract: Traditional query optimizers are designed to be fast and stateless: each query is quickly optimized using approximate statistics, sent off to the execution engine, and promptly forgotten. Recent work on learned query optimization have shown that it is possible for a quer...	[ 3311 ]	Train
19,839	4	Title: Boosting Model Inversion Attacks with Adversarial Examples Abstract: Model inversion attacks involve reconstructing the training data of a target model, which raises serious privacy concerns for machine learning models. However, these attacks, especially learning-based methods, are likely to suffer from low atta...	[]	Train
19,840	4	Title: A Study of Different Awareness Campaigns in a Company Abstract: Phishing is a major cyber threat to organizations that can cause financial and reputational damage, threatening their existence. The technical measures against phishing should be complemented by awareness training for employees. However, there is li...	[]	Train
19,841	6	Title: GeoExplainer: A Visual Analytics Framework for Spatial Modeling Contextualization and Report Generation Abstract: Geographic regression models of various descriptions are often applied to identify patterns and anomalies in the determinants of spatially distributed observations. These types of analyses focus on a...	[]	Test
19,842	24	Title: PEOPL: Characterizing Privately Encoded Open Datasets with Public Labels Abstract: Allowing organizations to share their data for training of machine learning (ML) models without unintended information leakage is an open problem in practice. A promising technique for this still-open problem is to train models on...	[]	Train
19,843	30	Title: Unsupervised Calibration through Prior Adaptation for Text Classification using Large Language Models Abstract: A wide variety of natural language tasks are currently being addressed with large-scale language models (LLMs). These models are usually trained with a very large amount of unsupervised text data and a...	[ 13700 ]	Train
19,844	25	Title: BigVSAN: Enhancing GAN-based Neural Vocoders with Slicing Adversarial Network Abstract: Generative adversarial network (GAN)-based vocoders have been intensively studied because they can synthesize high-fidelity audio waveforms faster than real-time. However, it has been reported that most GANs fail to obtain th...	[ 5284 ]	Train
19,845	37	Title: Discovering Sound Free-Choice Workflow Nets with Non-block Structures Abstract: nan	[ 15189 ]	Validation
19,846	24	Title: Deep reinforcement learning for process design: Review and perspective Abstract: The transformation towards renewable energy and feedstock supply in the chemical industry requires new conceptual process design approaches. Recently, breakthroughs in artificial intelligence offer opportunities to accelerate this t...	[ 36558 ]	Train
19,847	16	Title: Zero-TPrune: Zero-Shot Token Pruning through Leveraging of the Attention Graph in Pre-Trained Transformers Abstract: Deployment of Transformer models on the edge is increasingly challenging due to the exponentially growing model size and inference cost that scales quadratically with the number of tokens in the i...	[]	Validation
19,848	16	Title: Transfer: Cross Modality Knowledge Transfer using Adversarial Networks - A Study on Gesture Recognition Abstract: Knowledge transfer across sensing technology is a novel concept that has been recently explored in many application domains, including gesture-based human computer interaction. The main aim is to gat...	[ 13322, 11092, 36293 ]	Validation
19,849	16	Title: Under-Display Camera Image Restoration with Scattering Effect Abstract: The under-display camera (UDC) provides consumers with a full-screen visual experience without any obstruction due to notches or punched holes. However, the semi-transparent nature of the display inevitably introduces the severe degradation ...	[]	Train
19,850	16	Title: 4DHumanOutfit: a multi-subject 4D dataset of human motion sequences in varying outfits exhibiting large displacements Abstract: This work presents 4DHumanOutfit, a new dataset of densely sampled spatio-temporal 4D human motion data of different actors, outfits and motions. The dataset is designed to contain diff...	[ 5512 ]	Validation
19,851	24	Title: TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification Abstract: Encrypted traffic classification is receiving widespread attention from researchers and industrial companies. However, the existing methods only extract flow-level features, failing to handl...	[]	Test
19,852	24	Title: LU-Net: Invertible Neural Networks Based on Matrix Factorization Abstract: LU-Net is a simple and fast architecture for invertible neural networks (INN) that is based on the factorization of quadratic weight matrices A=LU, where L is a lower triangular matrix with ones on the diagonal and U an upper triangular m...	[]	Test
19,853	24	Title: A modern look at the relationship between sharpness and generalization Abstract: Sharpness of minima is a promising quantity that can correlate with generalization in deep networks and, when optimized during training, can improve generalization. However, standard sharpness is not invariant under reparametrizatio...	[ 29794, 6307, 4326, 33831, 43378 ]	Train
19,854	24	Title: A Meta-learning based Stacked Regression Approach for Customer Lifetime Value Prediction Abstract: Companies across the globe are keen on targeting potential high-value customers in an attempt to expand revenue and this could be achieved only by understanding the customers more. Customer Lifetime Value (CLV) is ...	[ 6747 ]	Test
19,855	16	Title: Context-Aware Change Detection With Semi-Supervised Learning Abstract: Change detection using earth observation data plays a vital role in quantifying the impact of disasters in affected areas. While data sources like Sentinel-2 provide rich optical information, they are often hindered by cloud cover, limiting t...	[]	Train
19,856	16	Title: Racial Bias within Face Recognition: A Survey Abstract: Facial recognition is one of the most academically studied and industrially developed areas within computer vision where we readily find associated applications deployed globally. This widespread adoption has uncovered significant performance variation acro...	[]	Train
19,857	24	Title: Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal Abstract: Multi-task learning has the potential to improve generalization by maximizing positive transfer between tasks while reducing task interference. Fully achieving this potential is hindered by manually designed ...	[]	Train
19,858	24	Title: Multi-Fidelity Active Learning with GFlowNets Abstract: In the last decades, the capacity to generate large amounts of data in science and engineering applications has been growing steadily. Meanwhile, the progress in machine learning has turned it into a suitable tool to process and utilise the available data. ...	[ 21081, 15438 ]	Train
19,859	24	Title: Automatically identifying ordinary differential equations from data Abstract: Discovering nonlinear differential equations that describe system dynamics from empirical data is a fundamental challenge in contemporary science. Here, we propose a methodology to identify dynamical laws by integrating denoising techn...	[]	Train
19,860	11	Title: Capacity ATL Abstract: Model checking strategic abilities was successfully developed and applied since the early 2000s to ensure properties in Multi-Agent System. In this paper, we introduce the notion of capacities giving different abilities to an agent. This applies naturally to systems where multiple entities...	[]	Train
19,861	31	Title: Temporal Interest Network for Click-Through Rate Prediction Abstract: The history of user behaviors constitutes one of the most significant characteristics in predicting the click-through rate (CTR), owing to their strong semantic and temporal correlation with the target item. While the literature has individual...	[]	Train
19,862	24	Title: Towards One-Shot Learning for Text Classification using Inductive Logic Programming Abstract: With the ever-increasing potential of AI to perform personalised tasks, it is becoming essential to develop new machine learning techniques which are data-efficient and do not require hundreds or thousands of training d...	[]	Test
19,863	16	Title: Semantify: Simplifying the Control of 3D Morphable Models using CLIP Abstract: We present Semantify: a self-supervised method that utilizes the semantic power of CLIP language-vision foundation model to simplify the control of 3D morphable models. Given a parametric model, training data is created by randomly sa...	[]	Train
19,864	30	Title: Factify 2: A Multimodal Fake News and Satire News Dataset Abstract: The internet gives the world an open platform to express their views and share their stories. While this is very valuable, it makes fake news one of our society's most pressing problems. Manual fact checking process is time consuming, which make...	[ 24048, 38915, 18692 ]	Train
19,865	16	Title: Boosting Verified Training for Robust Image Classifications via Abstraction Abstract: This paper proposes a novel, abstraction-based, certified training method for robust image classifiers. Via abstraction, all perturbed images are mapped into intervals before feeding into neural networks for training. By traini...	[ 3266 ]	Train
19,866	24	Title: Survey of Federated Learning Models for Spatial-Temporal Mobility Applications Abstract: Federated learning involves training statistical models over edge devices such as mobile phones such that the training data is kept local. Federated Learning (FL) can serve as an ideal candidate for training spatial temporal...	[ 19461 ]	Train
19,867	24	Title: Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPs Abstract: In many real-life reinforcement learning (RL) problems, deploying new policies is costly. In those scenarios, algorithms must solve exploration (which requires adaptivity) while switching the deployed policy sparsely (which limits ...	[ 18008 ]	Train
19,868	24	Title: CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training Abstract: Recent research on online Gradient Balancing (GraB) has revealed that there exist permutation-based example orderings that are guaranteed to outperform random reshuffling (RR). Whereas RR arbitrarily permutes training ex...	[ 26333 ]	Train
19,869	27	Title: Communicating human intent to a robotic companion by multi-type gesture sentences Abstract: Human-Robot collaboration in home and industrial workspaces is on the rise. However, the communication between robots and humans is a bottleneck. Although people use a combination of different types of gestures to complem...	[ 30171 ]	Validation
19,870	24	Title: Analyzing And Editing Inner Mechanisms Of Backdoored Language Models Abstract: Recent advancements in interpretability research made transformer language models more transparent. This progress led to a better understanding of their inner workings for toy and naturally occurring models. However, how these models ...	[ 3601, 38834, 30331 ]	Train
19,871	16	Title: Context De-Confounded Emotion Recognition Abstract: Context-Aware Emotion Recognition (CAER) is a crucial and challenging task that aims to perceive the emotional states of the target person with contextual information. Recent approaches invariably focus on designing sophisticated architectures or mechanisms to ...	[ 41185, 23110, 45414, 5619, 42771, 14677, 2453, 17878, 13272 ]	Validation
19,872	16	Title: From slides (through tiles) to pixels: an explainability framework for weakly supervised models in pre-clinical pathology Abstract: In pre-clinical pathology, there is a paradox between the abundance of raw data (whole slide images from many organs of many individual animals) and the lack of pixel-level slide an...	[]	Validation
19,873	20	Title: Sparse Higher Order \v{C}ech Filtrations Abstract: For a finite set of balls of radius $r$, the $k$-fold cover is the space covered by at least $k$ balls. Fixing the ball centers and varying the radius, we obtain a nested sequence of spaces that is called the $k$-fold filtration of the centers. For $k=1$, the co...	[]	Train
19,874	16	Title: Super-Resolution Information Enhancement For Crowd Counting Abstract: Crowd counting is a challenging task due to the heavy occlusions, scales, and density variations. Existing methods handle these challenges effectively while ignoring low-resolution (LR) circumstances. The LR circumstances weaken the counting p...	[ 15093 ]	Validation
19,875	23	Title: Test Adequacy Evaluation for the User-database Interaction: A Specification-Based Approach Abstract: Testing a database application is a challenging process where both the database and the user interaction have to be considered in the design of test cases. This paper describes a specification-based approach to g...	[]	Train
19,876	10	Title: Empowering LLM to use Smartphone for Intelligent Task Automation Abstract: Mobile task automation is an attractive technique that aims to enable voice-based hands-free user interaction with smartphones. However, existing approaches suffer from poor scalability due to the limited language understanding ability an...	[ 7936, 40610, 1379, 13700, 12741, 22023, 14920, 33228, 6963, 1401, 4635, 19485 ]	Test
19,877	4	Title: Exposing Hidden Attackers in Industrial Control Systems using Micro-distortions Abstract: For industrial control systems (ICS), many existing defense solutions focus on detecting attacks only when they make the system behave anomalously. Instead, in this work, we study how to detect attackers who are still in th...	[]	Train

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