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
42,178	27	Title: Adaptive Graduated Non-Convexity for Pose Graph Optimization Abstract: We present a novel approach to robust pose graph optimization based on Graduated Non-Convexity (GNC). Unlike traditional GNC-based methods, the proposed approach employs an adaptive shape function using B-spline to optimize the shape of the r...	[]	Test
42,179	28	Title: On the Relationship Between Information-Theoretic Privacy Metrics And Probabilistic Information Privacy Abstract: Information-theoretic (IT) measures based on $f$-divergences have recently gained interest as a measure of privacy leakage as they allow for trading off privacy against utility using only a single-va...	[]	Test
42,180	30	Title: BIG-C: a Multimodal Multi-Purpose Dataset for Bemba Abstract: We present BIG-C (Bemba Image Grounded Conversations), a large multimodal dataset for Bemba. While Bemba is the most populous language of Zambia, it exhibits a dearth of resources which render the development of language technologies or language proce...	[ 5004 ]	Train
42,181	4	Title: A One-way Secret Key Agreement with Security Against Active Adversaries Abstract: In a one-way secret key agreement (OW-SKA) protocol in source model, Alice and Bob have private samples of two correlated variables X and Y that are partially leaked to Eve through the variable Z, and use a single message from Alic...	[]	Validation
42,182	34	Title: Tightest Admissible Shortest Path Abstract: The shortest path problem in graphs is fundamental to AI. Nearly all variants of the problem and relevant algorithms that solve them ignore edge-weight computation time and its common relation to weight uncertainty. This implies that taking these factors into considera...	[]	Test
42,183	5	Title: Efficient Coded Multi-Party Computation at Edge Networks Abstract: Multi-party computation (MPC) is promising for designing privacy-preserving machine learning algorithms at edge networks. An emerging approach is coded-MPC (CMPC), which advocates the use of coded computation to improve the performance of MPC in ...	[]	Train
42,184	16	Title: High-order Spatial Interactions Enhanced Lightweight Model for Optical Remote Sensing Image-based Small Ship Detection Abstract: Accurate and reliable optical remote sensing image-based small-ship detection is crucial for maritime surveillance systems, but existing methods often struggle with balancing detection...	[]	Validation
42,185	24	Title: Meta-Calibration Regularized Neural Networks Abstract: Miscalibration-the mismatch between predicted probability and the true correctness likelihood-has been frequently identified in modern deep neural networks. Recent work in the field aims to address this problem by training calibrated models directly by optim...	[]	Test
42,186	24	Title: DRGCN: Dynamic Evolving Initial Residual for Deep Graph Convolutional Networks Abstract: Graph convolutional networks (GCNs) have been proved to be very practical to handle various graph-related tasks. It has attracted considerable research interest to study deep GCNs, due to their potential superior performance...	[ 31375 ]	Train
42,187	26	Title: Analyzing large scale political discussions on Twitter: the use case of the Greek wiretapping scandal (#ypoklopes) Abstract: In this paper, we study the Greek wiretappings scandal, which has been revealed in 2022 and attracted a lot of attention by press and citizens. Specifically, we propose a methodology for c...	[ 35456 ]	Validation
42,188	16	Title: Robotic Scene Segmentation with Memory Network for Runtime Surgical Context Inference Abstract: Surgical context inference has recently garnered significant attention in robot-assisted surgery as it can facilitate workflow analysis, skill assessment, and error detection. However, runtime context inference is cha...	[ 25449 ]	Train
42,189	6	Title: Fused Spectatorship: Designing Bodily Experiences Where Spectators Become Players Abstract: Spectating digital games can be exciting. However, due to its vicarious nature, spectators often wish to engage in the gameplay beyond just watching and cheering. To blur the boundaries between spectators and players, we ...	[]	Train
42,190	16	Title: GeNAS: Neural Architecture Search with Better Generalization Abstract: Neural Architecture Search (NAS) aims to automatically excavate the optimal network architecture with superior test performance. Recent neural architecture search (NAS) approaches rely on validation loss or accuracy to find the superior netwo...	[]	Test
42,191	16	Title: PlaneRecTR: Unified Query learning for 3D Plane Recovery from a Single View Abstract: 3D plane recovery from a single image can usually be divided into several subtasks of plane detection, segmentation, parameter estimation and possibly depth estimation. Previous works tend to solve this task by either extending...	[ 33422 ]	Test
42,192	24	Title: Generalization error bounds for iterative learning algorithms with bounded updates Abstract: This paper explores the generalization characteristics of iterative learning algorithms with bounded updates for non-convex loss functions, employing information-theoretic techniques. Our key contribution is a novel boun...	[ 44855, 16911 ]	Validation
42,193	22	Title: FreeCHR: An Algebraic Framework for CHR-Embeddings Abstract: We introduce the framework FreeCHR, which formalizes the embedding of Constraint Handling Rules (CHR) into a host-language, using the concept of initial algebra semantics from category theory, to establish a high-level implementation scheme for CHR, as...	[]	Train
42,194	16	Title: Towards High-Quality Specular Highlight Removal by Leveraging Large-Scale Synthetic Data Abstract: This paper aims to remove specular highlights from a single object-level image. Although previous methods have made some progresses, their performance remains somewhat limited, particularly for real images with com...	[]	Train
42,195	16	Title: PixMIM: Rethinking Pixel Reconstruction in Masked Image Modeling Abstract: Masked Image Modeling (MIM) has achieved promising progress with the advent of Masked Autoencoders (MAE) and BEiT. However, subsequent works have complicated the framework with new auxiliary tasks or extra pre-trained models, inevitably i...	[ 28104 ]	Train
42,196	6	Title: Towards Prototyping Driverless Vehicle Behaviors, City Design, and Policies Simultaneously Abstract: Autonomous Vehicles (AVs) can potentially improve urban living by reducing accidents, increasing transportation accessibility and equity, and decreasing emissions. Realizing these promises requires the innovation...	[]	Train
42,197	24	Title: GiPH: Generalizable Placement Learning for Adaptive Heterogeneous Computing Abstract: Careful placement of a computational application within a target device cluster is critical for achieving low application completion time. The problem is challenging due to its NP-hardness and combinatorial nature. In recent ye...	[]	Train
42,198	16	Title: NeRFLiX: High-Quality Neural View Synthesis by Learning a Degradation-Driven Inter-viewpoint MiXer Abstract: Neural radiance fields (NeRF) show great success in novel view synthesis. However, in real-world scenes, recovering high-quality details from the source images is still challenging for the existing NeRF-b...	[ 7076, 2950, 32562, 30457, 14491 ]	Train
42,199	30	Title: Controllable Data Augmentation for Context-Dependent Text-to-SQL Abstract: The limited scale of annotated data constraints existing context-dependent text-to-SQL models because of the complexity of labeling. The data augmentation method is a commonly used method to solve this problem. However, the data generated...	[]	Train
42,200	30	Title: AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web Abstract: Existing datasets for automated fact-checking have substantial limitations, such as relying on artificial claims, lacking annotations for evidence and intermediate reasoning, or including evidence published after the claim...	[ 40787 ]	Test
42,201	24	Title: Explainable Representations for Relation Prediction in Knowledge Graphs Abstract: Knowledge graphs represent real-world entities and their relations in a semantically-rich structure supported by ontologies. Exploring this data with machine learning methods often relies on knowledge graph embeddings, which produc...	[]	Train
42,202	31	Title: printf: Preference Modeling Based on User Reviews with Item Images and Textual Information via Graph Learning Abstract: Nowadays, modern recommender systems usually leverage textual and visual contents as auxiliary information to predict user preference. For textual information, review texts are one of the most ...	[ 35746 ]	Train
42,203	39	Title: Sparse dynamic discretization discovery via arc-dependent time discretizations Abstract: While many time-dependent network design problems can be formulated as time-indexed formulations with strong relaxations, the size of these formulations depends on the discretization of the time horizon and can become prohib...	[ 41608 ]	Test
42,204	24	Title: Multi-market Energy Optimization with Renewables via Reinforcement Learning Abstract: This paper introduces a deep reinforcement learning (RL) framework for optimizing the operations of power plants pairing renewable energy with storage. The objective is to maximize revenue from energy markets while minimizing s...	[]	Test
42,205	16	Title: Trap-Based Pest Counting: Multiscale and Deformable Attention CenterNet Integrating Internal LR and HR Joint Feature Learning Abstract: Pest counting, which predicts the number of pests in the early stage, is very important because it enables rapid pest control, reduces damage to crops, and improves productivity...	[]	Train
42,206	11	Title: Multi-Agent Reinforcement Learning for Cooperative Air Transportation Services in City-Wide Autonomous Urban Air Mobility Abstract: The development of urban-air-mobility (UAM) is rapidly progressing with spurs, and the demand for efficient transportation management systems is a rising need due to the multifacete...	[ 8412 ]	Train
42,207	27	Title: Deep Reinforcement Learning for Flipper Control of Tracked Robots Abstract: The autonomous control of flippers plays an important role in enhancing the intelligent operation of tracked robots within complex environments. While existing methods mainly rely on hand-crafted control models, in this paper, we introdu...	[]	Train
42,208	16	Title: TinyHD: Efficient Video Saliency Prediction with Heterogeneous Decoders using Hierarchical Maps Distillation Abstract: Video saliency prediction has recently attracted attention of the research community, as it is an upstream task for several practical applications. However, current solutions are particurly comp...	[]	Train
42,209	9	Title: Find a witness or shatter: the landscape of computable PAC learning Abstract: This paper contributes to the study of CPAC learnability -- a computable version of PAC learning -- by solving three open questions from recent papers. Firstly, we prove that every improperly CPAC learnable class is contained in a clas...	[ 9250 ]	Test
42,210	30	Title: Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks Abstract: Large Language Models (LLMs) have shown promising performance in knowledge-intensive reasoning tasks that require a compound understanding of knowledge. However, deployment of the LLMs in real-world applic...	[ 13700, 15301, 12741, 33220, 6353, 21880 ]	Train
42,211	28	Title: Non-Orthogonal Multiplexing in the FBL Regime Enhances Physical Layer Security with Deception Abstract: We propose a new security framework for physical layer security (PLS) in the finite blocklength (FBL) regime that incorporates deception technology, allowing for active countermeasures against potential eavesd...	[]	Train
42,212	25	Title: Cross-domain Sound Recognition for Efficient Underwater Data Analysis Abstract: This paper presents a novel deep learning approach for analyzing massive underwater acoustic data by leveraging a model trained on a broad spectrum of non-underwater (aerial) sounds. Recognizing the challenge in labeling vast amounts...	[]	Train
42,213	10	Title: LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot Detection Abstract: As malicious actors employ increasingly advanced and widespread bots to disseminate misinformation and manipulate public opinion, the detection of Twitter bots has become a crucial task. Though grap...	[ 4784, 7742 ]	Train
42,214	16	Title: Motion-Conditioned Diffusion Model for Controllable Video Synthesis Abstract: Recent advancements in diffusion models have greatly improved the quality and diversity of synthesized content. To harness the expressive power of diffusion models, researchers have explored various controllable mechanisms that allow u...	[ 42272, 25057, 30566, 12841, 7993, 36286, 40985 ]	Test
42,215	30	Title: Hybrid lemmatization in HuSpaCy Abstract: Lemmatization is still not a trivial task for morphologically rich languages. Previous studies showed that hybrid architectures usually work better for these languages and can yield great results. This paper presents a hybrid lemmatizer utilizing both a neural model, dic...	[]	Train
42,216	24	Title: SEEDS: Emulation of Weather Forecast Ensembles with Diffusion Models Abstract: Uncertainty quantification is crucial to decision-making. A prominent example is probabilistic forecasting in numerical weather prediction. The dominant approach to representing uncertainty in weather forecasting is to generate an ens...	[ 1116 ]	Train
42,217	8	Title: Green UAV-enabled Internet-of-Things Network with AI-assisted NOMA for Disaster Management Abstract: Unmanned aerial vehicle (UAV)-assisted communication is becoming a streamlined technology in providing improved coverage to the internet-of-things (IoT) based devices. Rapid deployment, portability, and flexibili...	[ 42 ]	Test
42,218	24	Title: Getting from Generative AI to Trustworthy AI: What LLMs might learn from Cyc Abstract: Generative AI, the most popular current approach to AI, consists of large language models (LLMs) that are trained to produce outputs that are plausible, but not necessarily correct. Although their abilities are often uncanny, ...	[ 17606, 17295 ]	Validation
42,219	31	Title: Graph-guided Personalization for Federated Recommendation Abstract: Federated Recommendation is a new service architecture providing recommendations without sharing user data with the server. Existing methods deploy a recommendation model on each client and coordinate their training by synchronizing and aggregat...	[]	Validation
42,220	24	Title: Does Noise Affect Housing Prices? A Case Study in the Urban Area of Thessaloniki Abstract: Real estate markets depend on various methods to predict housing prices, including models that have been trained on datasets of residential or commercial properties. Most studies endeavor to create more accurate machine le...	[]	Train
42,221	16	Title: DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models Abstract: Collecting and annotating images with pixel-wise labels is time-consuming and laborious. In contrast, synthetic data can be freely available using a generative model (e.g., DALL-E, Stable Diffus...	[ 31617, 16291, 3524, 44197, 34184, 2985, 31913, 32587, 4716, 19948, 5807, 17839, 42100, 27032, 33944 ]	Validation
42,222	30	Title: Hindi as a Second Language: Improving Visually Grounded Speech with Semantically Similar Samples Abstract: The objective of this work is to explore the learning of visually grounded speech models (VGS) from multilingual perspective. Bilingual VGS models are generally trained with an equal number of spoken captio...	[]	Validation
42,223	11	Title: An Efficient Distributed Multi-Agent Reinforcement Learning for EV Charging Network Control Abstract: The increasing trend in adopting electric vehicles (EVs) will significantly impact the residential electricity demand, which results in an increased risk of transformer overload in the distribution grid. To miti...	[]	Train
42,224	24	Title: Label Distribution Learning from Logical Label Abstract: Label distribution learning (LDL) is an effective method to predict the label description degree (a.k.a. label distribution) of a sample. However, annotating label distribution (LD) for training samples is extremely costly. So recent studies often first us...	[]	Train
42,225	27	Title: The Hybrid Extended Bicycle: A Simple Model for High Dynamic Vehicle Trajectory Planning Abstract: While highly automated driving relies most of the time on a smooth driving assumption, the possibility of a vehicle performing harsh maneuvers with high dynamic driving to face unexpected events is very likely. The...	[]	Train
42,226	24	Title: Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization Abstract: Federated Learning (FL) is a distributed learning scheme to train a shared model across clients. One common and fundamental challenge in FL is that the sets of dnta across clients could be non-identically distribu...	[]	Test
42,227	31	Title: BioCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrieval Abstract: Information retrieval (IR) is essential in biomedical knowledge acquisition and clinical decision support. While recent progress has shown that language model encoders perform...	[ 7936 ]	Train
42,228	16	Title: Towards Scene-Text to Scene-Text Translation Abstract: In this work, we study the task of ``visually"translating scene text from a source language (e.g., English) to a target language (e.g., Chinese). Visual translation involves not just the recognition and translation of scene text but also the generation of th...	[]	Validation
42,229	16	Title: Cycle Consistency Driven Object Discovery Abstract: Developing deep learning models that effectively learn object-centric representations, akin to human cognition, remains a challenging task. Existing approaches have explored slot-based methods utilizing architectural priors or auxiliary information such as dept...	[ 5463 ]	Train
42,230	30	Title: LeTI: Learning to Generate from Textual Interactions Abstract: Finetuning pre-trained language models (LMs) enhances the models' capabilities. Prior techniques fine-tune a pre-trained LM on input-output pairs (e.g., instruction fine-tuning), or with numerical rewards that gauge the quality of its outputs (e.g., ...	[ 9314, 33220, 34820, 13700, 6353, 4658, 22578, 23159, 17789 ]	Train
42,231	16	Title: RSGPT: A Remote Sensing Vision Language Model and Benchmark Abstract: The emergence of large-scale large language models, with GPT-4 as a prominent example, has significantly propelled the rapid advancement of artificial general intelligence and sparked the revolution of Artificial Intelligence 2.0. In the realm...	[ 10624, 9890, 30243, 13700, 33220, 37987, 38637, 41104, 15413, 27454 ]	Test
42,232	27	Title: 3D Printed Graded Porous Sensors for Soft Sensorized Insoles with Gait Phase & Ground Reaction Forces Estimation Abstract: Sensorized insoles provide a tool to perform gait studies and health monitoring during daily life. These sensorized insoles need to be comfortable and lightweight to be accepted. Previous wo...	[ 26514 ]	Validation
42,233	15	Title: An Efficient FPGA-Based Accelerator for Swin Transformer Abstract: Since introduced, Swin Transformer has achieved remarkable results in the field of computer vision, it has sparked the need for dedicated hardware accelerators, specifically catering to edge computing demands. For the advantages of flexibility, l...	[ 36213 ]	Train
42,234	8	Title: An Efficient Mobile Gateway Selection and Discovery Based-Routing Protocol in Heterogeneous LTE-VANET Networks Abstract: Coupling cellular communication networks with vehicular ad hoc networks (VANET) can be a very interesting way out for providing Internet access to vehicles in the road. However, due to the sev...	[]	Train
42,235	8	Title: Joint 3D Deployment and Resource Allocation for UAV-assisted Integrated Communication and Localization Abstract: In this paper, we investigate an unmanned aerial vehicle (UAV)-assisted integrated communication and localization network in emergency scenarios where a single UAV is deployed as both an airborne base...	[]	Train
42,236	16	Title: k-SALSA: k-Anonymous Synthetic Averaging of Retinal Images via Local Style Alignment Abstract: nan	[ 24823 ]	Test
42,237	27	Title: A Multiplicative Value Function for Safe and Efficient Reinforcement Learning Abstract: An emerging field of sequential decision problems is safe Reinforcement Learning (RL), where the objective is to maximize the reward while obeying safety constraints. Being able to handle constraints is essential for deployin...	[]	Train
42,238	30	Title: BERT Based Clinical Knowledge Extraction for Biomedical Knowledge Graph Construction and Analysis Abstract: nan	[ 12260, 21930, 20235, 10128, 31984, 44691, 5850 ]	Train
42,239	16	Title: Noisy Universal Domain Adaptation via Divergence Optimization for Visual Recognition Abstract: To transfer the knowledge learned from a labeled source domain to an unlabeled target domain, many studies have worked on universal domain adaptation (UniDA), where there is no constraint on the label sets of the sourc...	[]	Train
42,240	33	Title: Primitive Automata that are Synchronizing Abstract: A deterministic finite (semi)automaton is primitive if its transition monoid (semigroup) acting on the set of states has no non-trivial congruences. It is synchronizing if it contains a constant map (transformation). In analogy to synchronizing groups, we study...	[ 23191 ]	Validation
42,241	16	Title: USAGE: A Unified Seed Area Generation Paradigm for Weakly Supervised Semantic Segmentation Abstract: Seed area generation is usually the starting point of weakly supervised semantic segmentation (WSSS). Computing the Class Activation Map (CAM) from a multi-label classification network is the de facto paradigm fo...	[]	Test
42,242	24	Title: Provably Convergent Subgraph-wise Sampling for Fast GNN Training Abstract: Subgraph-wise sampling -- a promising class of mini-batch training techniques for graph neural networks (GNNs -- is critical for real-world applications. During the message passing (MP) in GNNs, subgraph-wise sampling methods discard mess...	[ 5292 ]	Train
42,243	30	Title: Company classification using zero-shot learning Abstract: In recent years, natural language processing (NLP) has become increasingly important in a variety of business applications, including sentiment analysis, text classification, and named entity recognition. In this paper, we propose an approach for company ...	[]	Train
42,244	16	Title: SCTracker: Multi-object tracking with shape and confidence constraints Abstract: Detection-based tracking is one of the main methods of multi-object tracking. It can obtain good tracking results when using excellent detectors but it may associate wrong targets when facing overlapping and low-confidence detection...	[]	Train
42,245	10	Title: LAMBO: Large Language Model Empowered Edge Intelligence Abstract: Next-generation edge intelligence is anticipated to bring huge benefits to various applications, e.g., offloading systems. However, traditional deep offloading architectures face several issues, including heterogeneous constraints, partial percept...	[]	Test
42,246	30	Title: A Multi-Task Multi-Stage Transitional Training Framework for Neural Chat Translation Abstract: Neural chat translation (NCT) aims to translate a cross-lingual chat between speakers of different languages. Existing context-aware NMT models cannot achieve satisfactory performances due to the following inherent pro...	[ 1240 ]	Train
42,247	24	Title: Multi-representations Space Separation based Graph-level Anomaly-aware Detection Abstract: Graph structure patterns are widely used to model different area data recently. How to detect anomalous graph information on these graph data has become a popular research problem. The objective of this research is centere...	[]	Train
42,248	5	Title: TangleSim: An Agent-based, Modular Simulator for DAG-based Distributed Ledger Technologies Abstract: DAG-based DLTs allow for parallel, asynchronous writing access to a ledger. Consequently, the perception of the most recent blocks may differ considerably between nodes, and the underlying network properties of t...	[]	Test
42,249	24	Title: Sig-Splines: universal approximation and convex calibration of time series generative models Abstract: We propose a novel generative model for multivariate discrete-time time series data. Drawing inspiration from the construction of neural spline flows, our algorithm incorporates linear transformations and the s...	[]	Train
42,250	24	Title: ReLU soothes the NTK condition number and accelerates optimization for wide neural networks Abstract: Rectified linear unit (ReLU), as a non-linear activation function, is well known to improve the expressivity of neural networks such that any continuous function can be approximated to arbitrary precision by a s...	[]	Train
42,251	16	Title: Cancer-Net BCa-S: Breast Cancer Grade Prediction using Volumetric Deep Radiomic Features from Synthetic Correlated Diffusion Imaging Abstract: The prevalence of breast cancer continues to grow, affecting about 300,000 females in the United States in 2023. However, there are different levels of severity of breast...	[]	Test
42,252	16	Title: Hamming Similarity and Graph Laplacians for Class Partitioning and Adversarial Image Detection Abstract: Researchers typically investigate neural network representations by examining activation outputs for one or more layers of a network. Here, we investigate the potential for ReLU activation patterns (encoded a...	[]	Train
42,253	6	Title: A Semi-supervised Sensing Rate Learning based CMAB scheme to combat COVID-19 by trustful data collection in the crowd Abstract: nan	[]	Test
42,254	16	Title: FEDD - Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy Classification Abstract: Skin diseases affect millions of people worldwide, across all ethnicities. Increasing diagnosis accessibility requires fair and accurate segmentation and classification of dermatology images. However, ...	[]	Train
42,255	27	Title: METAVerse: Meta-Learning Traversability Cost Map for Off-Road Navigation Abstract: Autonomous navigation in off-road conditions requires an accurate estimation of terrain traversability. However, traversability estimation in unstructured environments is subject to high uncertainty due to the variability of numer...	[ 33400, 32783 ]	Train
42,256	23	Title: Towards Fair Machine Learning Software: Understanding and Addressing Model Bias Through Counterfactual Thinking Abstract: The increasing use of Machine Learning (ML) software can lead to unfair and unethical decisions, thus fairness bugs in software are becoming a growing concern. Addressing these fairness bugs ...	[ 41899, 13997, 46165, 22649, 37565, 46111 ]	Train
42,257	24	Title: Probabilistic Regular Tree Priors for Scientific Symbolic Reasoning Abstract: Symbolic Regression (SR) allows for the discovery of scientific equations from data. To limit the large search space of possible equations, prior knowledge has been expressed in terms of formal grammars that characterize subsets of arb...	[]	Test
42,258	10	Title: Machine Love Abstract: While ML generates much economic value, many of us have problematic relationships with social media and other ML-powered applications. One reason is that ML often optimizes for what we want in the moment, which is easy to quantify but at odds with what is known scientifically about human f...	[ 40304, 44173 ]	Train
42,259	16	Title: Automated Static Camera Calibration with Intelligent Vehicles Abstract: Connected and cooperative driving requires precise calibration of the roadside infrastructure for having a reliable perception system. To solve this requirement in an automated manner, we present a robust extrinsic calibration method for aut...	[]	Test
42,260	4	Title: Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection Abstract: Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve c...	[ 7801, 2354, 27670 ]	Train
42,261	24	Title: InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs Abstract: With the rapid development of Graph Neural Networks (GNNs), more and more studies focus on system design to improve training efficiency while ignoring the efficiency of GNN inference. Actually, GNN ...	[]	Test
42,262	16	Title: Deep Metric Learning for Unsupervised Remote Sensing Change Detection Abstract: Remote Sensing Change Detection (RS-CD) aims to detect relevant changes from Multi-Temporal Remote Sensing Images (MT-RSIs), which aids in various RS applications such as land cover, land use, human development analysis, and disaster...	[]	Train
42,263	16	Title: Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification Abstract: We introduce Meta-Album, an image classification meta-dataset designed to facilitate few-shot learning, transfer learning, meta-learning, among other tasks. It includes 40 open datasets, each having at least 20 classes with 40 exam...	[ 33799, 22247, 34444, 13522, 39703, 12795 ]	Train
42,264	24	Title: Representation Disentaglement via Regularization by Identification Abstract: This work focuses on the problem of learning disentangled representations from observational data. Given observations ${\mathbf{x}^{(i)}}$ for $i=1,...,N $ drawn from $p(\mathbf{x}\|\mathbf{y})$ with generative variables $\mathbf{y}$ adm...	[]	Validation
42,265	16	Title: A New Low-Rank Learning Robust Quaternion Tensor Completion Method for Color Video Inpainting Problem and Fast Algorithms Abstract: The color video inpainting problem is one of the most challenging problem in the modern imaging science. It aims to recover a color video from a small part of pixels that may contai...	[]	Test
42,266	6	Title: Measuring Perceived Trust in XAI-Assisted Decision-Making by Eliciting a Mental Model Abstract: This empirical study proposes a novel methodology to measure users' perceived trust in an Explainable Artificial Intelligence (XAI) model. To do so, users' mental models are elicited using Fuzzy Cognitive Maps (FCMs)....	[ 4184 ]	Train
42,267	16	Title: Segment Anything Meets Semantic Communication Abstract: In light of the diminishing returns of traditional methods for enhancing transmission rates, the domain of semantic communication presents promising new frontiers. Focusing on image transmission, this paper explores the application of foundation models, par...	[ 27232, 1899, 25368, 30518, 16728, 16697, 3066, 35263 ]	Train
42,268	30	Title: Out-of-Distribution Generalization in Text Classification: Past, Present, and Future Abstract: Machine learning (ML) systems in natural language processing (NLP) face significant challenges in generalizing to out-of-distribution (OOD) data, where the test distribution differs from the training data distribution....	[ 30026, 13700, 39583 ]	Train
42,269	30	Title: Pay More Attention to Relation Exploration for Knowledge Base Question Answering Abstract: Knowledge base question answering (KBQA) is a challenging task that aims to retrieve correct answers from large-scale knowledge bases. Existing attempts primarily focus on entity representation and final answer reasoning, ...	[ 35440 ]	Validation
42,270	16	Title: InternGPT: Solving Vision-Centric Tasks by Interacting with Chatbots Beyond Language Abstract: We present an interactive visual framework named InternGPT, or iGPT for short. The framework integrates chatbots that have planning and reasoning capabilities, such as ChatGPT, with non-verbal instructions like pointin...	[ 10624, 13700, 37765, 14086, 34314, 45452, 41104, 3609, 15258, 34074, 4643, 19747, 25892, 17328, 45362, 18621, 1854, 35263, 33220, 41183, 37987, 1900, 20588, 17390, 38894, 5104, 41336, 23545, 2811, 381, 3967 ]	Test
42,271	16	Title: Looking and Listening: Audio Guided Text Recognition Abstract: Text recognition in the wild is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest vision and language processing are effective for scene text recognition. Yet, solving edit errors such as add, dele...	[]	Train
42,272	16	Title: Structure and Content-Guided Video Synthesis with Diffusion Models Abstract: Text-guided generative diffusion models unlock powerful image creation and editing tools. While these have been extended to video generation, current approaches that edit the content of existing footage while retaining structure require...	[ 44549, 11655, 43911, 23563, 40979, 9364, 14105, 40985, 42907, 7709, 4765, 40606, 13474, 1318, 38696, 18731, 1836, 7597, 25006, 39340, 19378, 39603, 14132, 39730, 7993, 20666, 9276, 26429, 43328, 11841, 25666, 28482, 1860, 35394, 8390, 39759, 32...	Validation
42,273	17	Title: Neural Intersection Function Abstract: The ray casting operation in the Monte Carlo ray tracing algorithm usually adopts a bounding volume hierarchy (BVH) to accelerate the process of finding intersections to evaluate visibility. However, its characteristics are irregular, with divergence in memory access and br...	[]	Validation
42,274	30	Title: SmartProbe: A Virtual Moderator for Market Research Surveys Abstract: Market research surveys are a powerful methodology for understanding consumer perspectives at scale, but are limited by depth of understanding and insights. A virtual moderator can introduce elements of qualitative research into surveys, devel...	[]	Train
42,275	4	Title: faulTPM: Exposing AMD fTPMs’ Deepest Secrets Abstract: Trusted Platform Modules (TPMs) constitute an integral building block of modern security features. Moreover, as Windows 11 made a TPM 2.0 mandatory, they are subject to an ever-increasing academic challenge. While discrete TPMs (dTPMs) – as found in higher-e...	[]	Train
42,276	30	Title: Towards A Unified View of Sparse Feed-Forward Network in Pretraining Large Language Model Abstract: Large and sparse feed-forward networks (S-FFN) such as Mixture-of-Experts (MoE) have demonstrated to be an efficient approach for scaling up Transformers model size for pretraining large language models. By only a...	[]	Train
42,277	16	Title: When Hyperspectral Image Classification Meets Diffusion Models: An Unsupervised Feature Learning Framework Abstract: Learning effective spectral-spatial features is important for the hyperspectral image (HSI) classification task, but the majority of existing HSI classification methods still suffer from modeling ...	[ 4220 ]	Test

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