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
33,278	31	Title: Metric Search for Rank List Compatibility Matching with Applications Abstract: As online dating has become more popular in the past few years, an efficient and effective algorithm to match users is needed. In this project, we proposed a new dating matching algorithm that uses Kendall-Tau distance to measure the ...	[]	Test
33,279	24	Title: Dissecting Chain-of-Thought: A Study on Compositional In-Context Learning of MLPs Abstract: Chain-of-thought (CoT) is a method that enables language models to handle complex reasoning tasks by decomposing them into simpler steps. Despite its success, the underlying mechanics of CoT are not yet fully understood. ...	[ 35488, 40099, 25833, 3795, 6261, 5078, 2518, 45529 ]	Test
33,280	30	Title: Few Shot Rationale Generation using Self-Training with Dual Teachers Abstract: Self-rationalizing models that also generate a free-text explanation for their predicted labels are an important tool to build trustworthy AI applications. Since generating explanations for annotated labels is a laborious and costly p...	[]	Test
33,281	24	Title: Verification against in-situ observations for Data-Driven Weather Prediction Abstract: Data-driven weather prediction models (DDWPs) have made rapid strides in recent years, demonstrating an ability to approximate Numerical Weather Prediction (NWP) models to a high degree of accuracy. The fast, accurate, and low...	[]	Test
33,282	8	Title: Semantic Communications for Image Recovery and Classification via Deep Joint Source and Channel Coding Abstract: With the recent advancements in edge artificial intelligence (AI), future sixth-generation (6G) networks need to support new AI tasks such as classification and clustering apart from data recovery. Mo...	[ 30505 ]	Train
33,283	16	Title: Regular Splitting Graph Network for 3D Human Pose Estimation Abstract: In human pose estimation methods based on graph convolutional architectures, the human skeleton is usually modeled as an undirected graph whose nodes are body joints and edges are connections between neighboring joints. However, most of these...	[ 24126 ]	Test
33,284	30	Title: Query Rewriting for Retrieval-Augmented Large Language Models Abstract: Large Language Models (LLMs) play a powerful \textit{Reader} of the \textit{Retrieve-then-Read} pipeline, making great progress in knowledge-based open-domain tasks. This work introduces a new framework, \textit{Rewrite-Retrieve-Read} that i...	[ 31905, 397, 7695, 27669, 35580 ]	Validation
33,285	10	Title: Optimized Vectorizing of Building Structures with Swap: High-Efficiency Convolutional Channel-Swap Hybridization Strategy Abstract: The building planar graph reconstruction, a.k.a. footprint reconstruction, which lies in the domain of computer vision and geoinformatics, has been long afflicted with the challenge...	[]	Train
33,286	27	Title: Mixed Integer Programming for Time-Optimal Multi-Robot Coverage Path Planning With Efficient Heuristics Abstract: We investigate time-optimal Multi-Robot Coverage Path Planning (MCPP) for both unweighted and weighted terrains, which aims to minimize the coverage time, defined as the maximum travel time of all ro...	[]	Train
33,287	16	Title: Text-To-Concept (and Back) via Cross-Model Alignment Abstract: We observe that the mapping between an image's representation in one model to its representation in another can be learned surprisingly well with just a linear layer, even across diverse models. Building on this observation, we propose $\textit{text-...	[ 45080 ]	Train
33,288	16	Title: DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices Abstract: Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent works mostly focus on learning a deep f...	[]	Train
33,289	24	Title: Energy Modelling and Forecasting for an Underground Agricultural Farm using a Higher Order Dynamic Mode Decomposition Approach Abstract: This paper presents an approach based on higher order dynamic mode decomposition (HODMD) to model, analyse, and forecast energy behaviour in an urban agriculture farm situated ...	[]	Validation
33,290	28	Title: Characteristics of Channel Eigenvalues and Mutual Coupling Effects for Holographic Reconfigurable Intelligent Surfaces Abstract: As a prospective key technology for the next-generation wireless communications, reconfigurable intelligent surfaces (RISs) have gained tremendous research interest in both the academi...	[ 27596, 262 ]	Train
33,291	25	Title: TrustSER: On the Trustworthiness of Fine-tuning Pre-trained Speech Embeddings For Speech Emotion Recognition Abstract: Recent studies have explored the use of pre-trained embeddings for speech emotion recognition (SER), achieving comparable performance to conventional methods that rely on low-level knowledge-ins...	[]	Test
33,292	4	Title: FedBlockHealth: A Synergistic Approach to Privacy and Security in IoT-Enabled Healthcare through Federated Learning and Blockchain Abstract: The rapid adoption of Internet of Things (IoT) devices in healthcare has introduced new challenges in preserving data privacy, security and patient safety. Traditional appr...	[]	Test
33,293	24	Title: FLAG: Fast Label-Adaptive Aggregation for Multi-label Classification in Federated Learning Abstract: Federated learning aims to share private data to maximize the data utility without privacy leakage. Previous federated learning research mainly focuses on multi-class classification problems. However, multi-label...	[]	Test
33,294	31	Title: Knowledge is Power, Understanding is Impact: Utility and Beyond Goals, Explanation Quality, and Fairness in Path Reasoning Recommendation Abstract: Path reasoning is a notable recommendation approach that models high-order user-product relations, based on a Knowledge Graph (KG). This approach can extract reasoni...	[]	Validation
33,295	16	Title: An Adaptive Plug-and-Play Network for Few-Shot Learning Abstract: Few-shot learning (FSL) requires a model to classify new samples after learning from only a few samples. While remarkable results are achieved in existing methods, the performance of embedding and metrics determines the upper limit of classificati...	[]	Test
33,296	24	Title: Min-Max Optimization under Delays Abstract: Delays and asynchrony are inevitable in large-scale machine-learning problems where communication plays a key role. As such, several works have extensively analyzed stochastic optimization with delayed gradients. However, as far as we are aware, no analogous theory is ...	[]	Train
33,297	16	Title: Single Image LDR to HDR Conversion using Conditional Diffusion Abstract: Digital imaging aims to replicate realistic scenes, but Low Dynamic Range (LDR) cameras cannot represent the wide dynamic range of real scenes, resulting in under-/overexposed images. This paper presents a deep learning-based approach for r...	[ 10872 ]	Test
33,298	16	Title: Referenceless User Controllable Semantic Image Synthesis Abstract: Despite recent progress in semantic image synthesis, complete control over image style remains a challenging problem. Existing methods require reference images to feed style information into semantic layouts, which indicates that the style is con...	[]	Train
33,299	16	Title: Q-HyViT: Post-Training Quantization for Hybrid Vision Transformer with Bridge Block Reconstruction Abstract: Recently, vision transformers (ViTs) have superseded convolutional neural networks in numerous applications, including classification, detection, and segmentation. However, the high computational requirem...	[]	Validation
33,300	30	Title: Retrieval-Augmented Meta Learning for Low-Resource Text Classification Abstract: Meta learning have achieved promising performance in low-resource text classification which aims to identify target classes with knowledge transferred from source classes with sets of small tasks named episodes. However, due to the ...	[ 45300 ]	Train
33,301	23	Title: DAT: Data Architecture Modeling Tool for Data-Driven Applications Abstract: Data is the key to success for any Data-Driven Organization, and managing it is considered the most challenging task. Data Architecture (DA) focuses on describing, collecting, storing, processing, and analyzing the data to meet business ...	[ 10539 ]	Validation
33,302	30	Title: Linguistic ambiguity analysis in ChatGPT Abstract: Linguistic ambiguity is and has always been one of the main challenges in Natural Language Processing (NLP) systems. Modern Transformer architectures like BERT, T5 or more recently InstructGPT have achieved some impressive improvements in many NLP fields, but th...	[ 11273, 44173, 23252, 26357, 13239, 3518 ]	Train
33,303	24	Title: A Unified View of Long-Sequence Models towards Modeling Million-Scale Dependencies Abstract: Ever since their conception, Transformers have taken over traditional sequence models in many tasks, such as NLP, image classification, and video/audio processing, for their fast training and superior performance. Much o...	[]	Validation
33,304	16	Title: A Hyper-pixel-wise Contrastive Learning Augmented Segmentation Network for Old Landslide Detection Using High-Resolution Remote Sensing Images and Digital Elevation Model Data Abstract: As a harzard disaster, landslide often brings tremendous losses to humanity, so it's necessary to achieve reliable detection of...	[]	Train
33,305	30	Title: Taxonomy Completion with Probabilistic Scorer via Box Embedding Abstract: Taxonomy completion, a task aimed at automatically enriching an existing taxonomy with new concepts, has gained significant interest in recent years. Previous works have introduced complex modules, external information, and pseudo-leaves t...	[]	Validation
33,306	24	Title: Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach Abstract: Accurate time series forecasting is critical for a wide range of problems with temporal data. Ensemble modeling is a well-established technique for leveraging multiple predictive models to increase accuracy and robu...	[ 12722, 16991 ]	Train
33,307	24	Title: Chasing Low-Carbon Electricity for Practical and Sustainable DNN Training Abstract: Deep learning has experienced significant growth in recent years, resulting in increased energy consumption and carbon emission from the use of GPUs for training deep neural networks (DNNs). Answering the call for sustainability,...	[]	Validation
33,308	24	Title: Reconciling High Accuracy, Cost-Efficiency, and Low Latency of Inference Serving Systems Abstract: The use of machine learning (ML) inference for various applications is growing drastically. ML inference services engage with users directly, requiring fast and accurate responses. Moreover, these services face dyn...	[ 11347 ]	Test
33,309	24	Title: Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning Abstract: Many real-world domains require safe decision making in the presence of uncertainty. In this work, we propose a deep reinforcement learning framework for approaching this important problem. We consider a risk-averse p...	[ 35591 ]	Train
33,310	27	Title: Visual-Policy Learning through Multi-Camera View to Single-Camera View Knowledge Distillation for Robot Manipulation Tasks Abstract: The use of multi-camera views simultaneously has been shown to improve the generalization capabilities and performance of visual policies. However, the hardware cost and design con...	[]	Test
33,311	30	Title: Can large language models generate salient negative statements? Abstract: We examine the ability of large language models (LLMs) to generate salient (interesting) negative statements about real-world entities; an emerging research topic of the last few years. We probe the LLMs using zero- and k-shot unconstraine...	[ 40810, 38886 ]	Test
33,312	16	Title: GDDS: Pulmonary Bronchioles Segmentation with Group Deep Dense Supervision Abstract: Airway segmentation, especially bronchioles segmentation, is an important but challenging task because distal bronchus are sparsely distributed and of a fine scale. Existing neural networks usually exploit sparse topology to lea...	[]	Train
33,313	27	Title: Distributed Consistent Multi-robot Cooperative Localization: A Coordinate Transformation Approach Abstract: This paper considers the problem of distributed cooperative localization (CL) via robot-to-robot measurements for a multi-robot system. We propose a distributed consistent CL algorithm. The key idea is to ...	[]	Test
33,314	16	Title: Graph-Collaborated Auto-Encoder Hashing for Multi-view Binary Clustering Abstract: Unsupervised hashing methods have attracted widespread attention with the explosive growth of large-scale data, which can greatly reduce storage and computation by learning compact binary codes. Existing unsupervised hashing metho...	[]	Test
33,315	30	Title: A Frustratingly Easy Improvement for Position Embeddings via Random Padding Abstract: Position embeddings, encoding the positional relationships among tokens in text sequences, make great contributions to modeling local context features in Transformer-based pre-trained language models. However, in Extractive Que...	[ 9470 ]	Validation
33,316	24	Title: Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms Abstract: The goal of this paper is to revisit Kernel Principal Component Analysis (KPCA) through dualization of a difference of convex functions. This allows to naturally extend KPCA to multiple objective functions and leads to e...	[]	Train
33,317	31	Title: Toward a Better Understanding of Loss Functions for Collaborative Filtering Abstract: Collaborative filtering (CF) is a pivotal technique in modern recommender systems. The learning process of CF models typically consists of three components: interaction encoder, loss function, and negative sampling. Although ma...	[ 31085, 25391 ]	Train
33,318	24	Title: Learning Horn Envelopes via Queries from Large Language Models Abstract: We investigate an approach for extracting knowledge from trained neural networks based on Angluin's exact learning model with membership and equivalence queries to an oracle. In this approach, the oracle is a trained neural network. We cons...	[]	Test
33,319	24	Title: Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations Abstract: We introduce a data-driven learning framework that assimilates two powerful ideas: ideal large eddy simulation (LES) from turbulence closure modeling and neural stochastic differential equations (SDE) ...	[]	Test
33,320	6	Title: Co-designing Community-based Sharing of Smarthome Devices for the Purpose of Co-monitoring In-home Emergencies Abstract: We conducted 26 co-design interviews with 50 smarthome device owners to understand the perceived benefits, drawbacks, and design considerations for developing a smarthome system that facilitat...	[]	Train
33,321	16	Title: ConvoWaste: An Automatic Waste Segregation Machine Using Deep Learning Abstract: Nowadays, proper urban waste management is one the biggest concerns for maintaining a green and clean environment. An automatic waste segregation system can be a viable solution to improve the sustainability of the country and to bo...	[ 10408 ]	Train
33,322	30	Title: CoLaDa: A Collaborative Label Denoising Framework for Cross-lingual Named Entity Recognition Abstract: Cross-lingual named entity recognition (NER) aims to train an NER system that generalizes well to a target language by leveraging labeled data in a given source language. Previous work alleviates the data scarc...	[ 19288 ]	Train
33,323	25	Title: Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation Abstract: Large diffusion models have been successful in text-to-audio (T2A) synthesis tasks, but they often suffer from common issues such as semantic misalignment and poor temporal consistency due to limited natural language understanding and data sca...	[ 4481, 39170, 15628, 14966, 7351, 4088 ]	Train
33,324	30	Title: "Is the Pope Catholic?" Applying Chain-of-Thought Reasoning to Understanding Conversational Implicatures Abstract: Conversational implicatures are pragmatic inferences that require listeners to deduce the intended meaning conveyed by a speaker from their explicit utterances. Although such inferential reasoning i...	[ 13510 ]	Train
33,325	6	Title: Can Voice Assistants Sound Cute? Towards a Model of Kawaii Vocalics Abstract: The Japanese notion of “kawaii” or expressions of cuteness, vulnerability, and/or charm is a global cultural export. Work has explored kawaii-ness as a design feature and factor of user experience in the visual appearance, nonverbal be...	[]	Train
33,326	25	Title: Intelligible Lip-to-Speech Synthesis with Speech Units Abstract: In this paper, we propose a novel Lip-to-Speech synthesis (L2S) framework, for synthesizing intelligible speech from a silent lip movement video. Specifically, to complement the insufficient supervisory signal of the previous L2S model, we propose ...	[ 22602, 28234, 36618, 19637, 118, 8186 ]	Validation
33,327	24	Title: Leveraging Importance Weights in Subset Selection Abstract: We present a subset selection algorithm designed to work with arbitrary model families in a practical batch setting. In such a setting, an algorithm can sample examples one at a time but, in order to limit overhead costs, is only able to update its stat...	[]	Train
33,328	24	Title: Enhancing Event Sequence Modeling with Contrastive Relational Inference Abstract: Neural temporal point processes(TPPs) have shown promise for modeling continuous-time event sequences. However, capturing the interactions between events is challenging yet critical for performing inference tasks like forecasting o...	[ 30854, 29454, 13583, 1437, 45406 ]	Train
33,329	24	Title: Anomaly detection with semi-supervised classification based on risk estimators Abstract: A significant limitation of one-class classification anomaly detection methods is their reliance on the assumption that unlabeled training data only contains normal instances. To overcome this impractical assumption, we prop...	[]	Train
33,330	24	Title: Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model Market Abstract: The emerging availability of trained machine learning models has put forward the novel concept of Machine Learning Model Market in which one can harness the collective intelligence of multiple ...	[ 32955 ]	Test
33,331	16	Title: Open-TransMind: A New Baseline and Benchmark for 1st Foundation Model Challenge of Intelligent Transportation Abstract: With the continuous improvement of computing power and deep learning algorithms in recent years, the foundation model has grown in popularity. Because of its powerful capabilities and excellent...	[]	Validation
33,332	4	Title: Securing Blockchain Systems: A Novel Collaborative Learning Framework to Detect Attacks in Transactions and Smart Contracts Abstract: With the escalating prevalence of malicious activities exploiting vulnerabilities in blockchain systems, there is an urgent requirement for robust attack detection mechanisms. To ...	[ 26959 ]	Test
33,333	27	Title: Assistive Robot Teleoperation Using Behavior Trees Abstract: Robotic assistance in robot arm teleoperation tasks has recently gained a lot of traction in industrial and domestic environment. A wide variety of input devices is used in such setups. Due to the noise in the input signals (e.g., Brain Computer Interf...	[]	Validation
33,334	24	Title: Securing Biomedical Images from Unauthorized Training with Anti-Learning Perturbation Abstract: The volume of open-source biomedical data has been essential to the development of various spheres of the healthcare community since more `free' data can provide individual researchers more chances to contribute. Howe...	[ 6942 ]	Test
33,335	24	Title: STEF-DHNet: Spatiotemporal External Factors Based Deep Hybrid Network for Enhanced Long-Term Taxi Demand Prediction Abstract: Accurately predicting the demand for ride-hailing services can result in significant benefits such as more effective surge pricing strategies, improved driver positioning, and enhanced cu...	[]	Test
33,336	23	Title: Parsing Fortran-77 with proprietary extensions Abstract: Far from the latest innovations in software development, many organizations still rely on old code written in"obsolete"programming languages. Because this source code is old and proven it often contributes significantly to the continuing success of these o...	[]	Validation
33,337	24	Title: Optimizing Sparse Linear Algebra Through Automatic Format Selection and Machine Learning Abstract: Sparse matrices are an integral part of scientific simulations. As hardware evolves new sparse matrix storage formats are proposed aiming to exploit optimizations specific to the new hardware. In the era of heterog...	[ 20848 ]	Validation
33,338	27	Title: KGNv2: Separating Scale and Pose Prediction for Keypoint-based 6-DoF Grasp Synthesis on RGB-D input Abstract: We propose a new 6-DoF grasp pose synthesis approach from 2D/2.5D input based on keypoints. Keypoint-based grasp detector from image input has demonstrated promising results in the previous study, where ...	[ 38786, 34074, 34167 ]	Train
33,339	24	Title: Predicting Molecule-Target Interaction by Learning Biomedical Network and Molecule Representations Abstract: The study of molecule-target interaction is quite important for drug discovery in terms of target identification, hit identification, pathway study, drug-drug interaction, etc. Most existing methodologies...	[]	Test
33,340	30	Title: DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI Abstract: Despite advancements in conversational AI, language models encounter challenges to handle diverse conversational tasks, and existing dialogue dataset collections often lack diversity and comprehensiveness. T...	[ 42756, 13700, 25892, 33363, 2197, 29206, 35580 ]	Train
33,341	25	Title: Enrollment-stage Backdoor Attacks on Speaker Recognition Systems via Adversarial Ultrasound Abstract: Automatic Speaker Recognition Systems (SRSs) have been widely used in voice applications for personal identification and access control. A typical SRS consists of three stages, i.e., training, enrollment, and re...	[]	Train
33,342	24	Title: Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing Abstract: Most graph neural networks follow the message passing mechanism. However, it faces the over-smoothing problem when multiple times of message passing is applied to a graph, causing indistinguishable node representations an...	[ 39650 ]	Train
33,343	4	Title: Facing Unknown: Open-World Encrypted Traffic Classification Based on Contrastive Pre-Training Abstract: Traditional Encrypted Traffic Classification (ETC) methods face a significant challenge in classifying large volumes of encrypted traffic in the open-world assumption, i.e., simultaneously classifying the know...	[ 36063 ]	Train
33,344	2	Title: Expressivity Landscape for Logics with Probabilistic Interventionist Counterfactuals Abstract: Causal multiteam semantics is a framework where probabilistic dependencies arising from data and causation between variables can be together formalized and studied logically. We consider several logics in the setting o...	[ 10531, 37519 ]	Train
33,345	24	Title: Finding Regions of Counterfactual Explanations via Robust Optimization Abstract: Counterfactual explanations play an important role in detecting bias and improving the explainability of data-driven classification models. A counterfactual explanation (CE) is a minimal perturbed data point for which the decision o...	[ 44432, 42315 ]	Train
33,346	24	Title: Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power Abstract: The ability of graph neural networks (GNNs) to count certain graph substructures, especially cycles, is important for the success of GNNs on a wide range of tasks. It has been recently used as a popular metric for eva...	[ 26191 ]	Train
33,347	16	Title: Contextual Affinity Distillation for Image Anomaly Detection Abstract: Previous works on unsupervised industrial anomaly detection mainly focus on local structural anomalies such as cracks and color contamination. While achieving significantly high detection performance on this kind of anomaly, they are faced wi...	[]	Validation
33,348	16	Title: Joint Modeling of Feature, Correspondence, and a Compressed Memory for Video Object Segmentation Abstract: Current prevailing Video Object Segmentation (VOS) methods usually perform dense matching between the current and reference frames after extracting their features. One on hand, the decoupled modeling restri...	[ 15675, 26484 ]	Validation
33,349	24	Title: GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent Abstract: Decision Trees (DTs) are commonly used for many machine learning tasks due to their high degree of interpretability. However, learning a DT from data is a difficult optimization problem, as it is non-convex and non-differentiable. The...	[]	Train
33,350	10	Title: Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems Abstract: We study the multi-objective minimum weight base problem, an abstraction of classical NP-hard combinatorial problems such as the multi-objective minimum spanning tree problem. We prove some important properties...	[ 39607 ]	Validation
33,351	5	Title: FaaSwap: SLO-Aware, GPU-Efficient Serverless Inference via Model Swapping Abstract: The dynamic request patterns of machine learning (ML) inference workloads have driven an increasing trend towards exploiting serverless computing for scalable ML model serving. However, today's serverless platforms lack efficient...	[ 40953 ]	Validation
33,352	16	Title: Topology-aware MLP for Skeleton-based Action Recognition Abstract: Graph convolution networks (GCNs) have achieved remarkable performance in skeleton-based action recognition. However, existing previous GCN-based methods have relied excessively on elaborate human body priors and constructed complex feature aggre...	[]	Train
33,353	16	Title: Prior based Sampling for Adaptive LiDAR Abstract: We propose SampleDepth, a Convolutional Neural Network (CNN), that is suited for an adaptive LiDAR. Typically,LiDAR sampling strategy is pre-defined, constant and independent of the observed scene. Instead of letting a LiDAR sample the scene in this agnostic fash...	[]	Train
33,354	20	Title: Improved Algorithms for Distance Selection and Related Problems Abstract: In this paper, we propose new techniques for solving geometric optimization problems involving interpoint distances of a point set in the plane. Given a set $P$ of $n$ points in the plane and an integer $1 \leq k \leq \binom{n}{2}$, the di...	[]	Test
33,355	22	Title: Defunctionalization with Dependent Types Abstract: The defunctionalization translation that eliminates higher-order functions from programs forms a key part of many compilers. However, defunctionalization for dependently-typed languages has not been formally studied. We present the first formally-specified defun...	[]	Validation
33,356	24	Title: Effective Medical Code Prediction via Label Internal Alignment Abstract: The clinical notes are usually typed into the system by physicians. They are typically required to be marked by standard medical codes, and each code represents a diagnosis or medical treatment procedure. Annotating these notes is time cons...	[]	Test
33,357	28	Title: Rate-Distortion Analysis for Semantic-Aware Multi-Terminal Source Coding Problem Abstract: A novel distributed source coding model which named semantic-aware multi-terminal source coding problem is proposed and studied in the paper. This is motivated by the new communication paradigm being aware of semantic info...	[ 33408, 7636 ]	Train
33,358	27	Title: Improving Extrinsics between RADAR and LIDAR using Learning Abstract: LIDAR and RADAR are two commonly used sensors in autonomous driving systems. The extrinsic calibration between the two is crucial for effective sensor fusion. The challenge arises due to the low accuracy and sparse information in RADAR measure...	[]	Test
33,359	16	Title: Towards Anytime Optical Flow Estimation with Event Cameras Abstract: Event cameras are capable of responding to log-brightness changes in microseconds. Its characteristic of producing responses only to the changing region is particularly suitable for optical flow estimation. In contrast to the super low-latency ...	[ 9784, 30294 ]	Train
33,360	31	Title: Implicit ZCA Whitening Effects of Linear Autoencoders for Recommendation Abstract: Recently, in the field of recommendation systems, linear regression (autoencoder) models have been investigated as a way to learn item similarity. In this paper, we show a connection between a linear autoencoder model and ZCA whit...	[ 45265 ]	Train
33,361	24	Title: Predicting Listing Prices In Dynamic Short Term Rental Markets Using Machine Learning Models Abstract: Our research group wanted to take on the difficult task of predicting prices in a dynamic market. And short term rentals such as Airbnb listings seemed to be the perfect proving ground to do such a thing. Airbn...	[]	Train
33,362	38	Title: An Approach to Evaluate User Interfaces in a Scholarly Knowledge Communication Domain Abstract: nan	[]	Train
33,363	30	Title: Efficient Benchmarking (of Language Models) Abstract: The increasing versatility of language models LMs has given rise to a new class of benchmarks that comprehensively assess a broad range of capabilities. Such benchmarks are associated with massive computational costs reaching thousands of GPU hours per model....	[ 30018, 43906, 44482, 2197, 31256, 21401, 12602, 33340, 32350 ]	Test
33,364	24	Title: Revolutionizing Wireless Networks with Federated Learning: A Comprehensive Review Abstract: These days with the rising computational capabilities of wireless user equipment such as smart phones, tablets, and vehicles, along with growing concerns about sharing private data, a novel machine learning model called f...	[]	Train
33,365	30	Title: Dissecting Recall of Factual Associations in Auto-Regressive Language Models Abstract: Transformer-based language models (LMs) are known to capture factual knowledge in their parameters. While previous work looked into where factual associations are stored, only little is known about how they are retrieved inter...	[ 13955, 24134, 41766, 31851, 33933, 40719, 22801, 38834, 40691, 41683, 14581, 9685, 382 ]	Train
33,366	23	Title: CGui Toolchain for Highly Customized GUI Development for Multiple Platforms Abstract: Highly customized graphical user interfaces play a major role in today's software applications. There exist many technologies that support developing them. But these technologies demand writing a significant amount of unintuiti...	[]	Train
33,367	25	Title: Beyond-Voice: Towards Continuous 3D Hand Pose Tracking on Commercial Home Assistant Devices Abstract: Increasingly popular home assistants are widely utilized as the central controller for smart home devices. However, current designs heavily rely on voice interfaces with accessibility and usability issues; some ...	[]	Train
33,368	30	Title: Evade ChatGPT Detectors via A Single Space Abstract: ChatGPT brings revolutionary social value but also raises concerns about the misuse of AI-generated content. Consequently, an important question is how to detect whether content is generated by ChatGPT or by human. Existing detectors are built upon the assumpt...	[ 14592, 13345, 41122, 45347, 18758, 43974, 13801, 846, 14133, 35415, 43930, 38235 ]	Train
33,369	30	Title: When the Majority is Wrong: Modeling Annotator Disagreement for Subjective Tasks Abstract: Though majority vote among annotators is typically used for ground truth labels in natural language processing, annotator disagreement in tasks such as hate speech detection may reflect differences in opinion across groups...	[ 24841, 25470 ]	Test
33,370	7	Title: A Blockchain based Fund Management System for Construction Projects - A Comprehensive Case Study in Xiong'an New Area China Abstract: As large scale construction projects become increasingly complex, the use and integration of advanced technologies are being emphasized more and more. However, the construction in...	[]	Test
33,371	17	Title: Perception of Human Motion With Different Geometric Models Abstract: Human figures have been animated using a variety of geometric models, including stick figures, polygonal models and NURBS-based models with muscles, flexible skin or clothing. This paper reports on experimental results indicating that a viewer'...	[ 45122 ]	Train
33,372	16	Title: Top-Down Visual Attention from Analysis by Synthesis Abstract: Current attention algorithms (e.g., self-attention) are stimulus-driven and highlight all the salient objects in an image. However, intelligent agents like humans often guide their attention based on the high-level task at hand, focusing only on task...	[ 16621 ]	Train
33,373	24	Title: Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare Abstract: Many reinforcement learning (RL) applications have combinatorial action spaces, where each action is a composition of sub-actions. A standard RL approach ignores this inherent factorization structure, resulting...	[ 28949, 10067, 31508, 3461 ]	Train
33,374	24	Title: AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks Abstract: Sharpness aware minimization (SAM) optimizer has been extensively explored as it can generalize better for training deep neural networks via introducing extra perturbation steps to f...	[ 6241, 41253, 16201, 6222, 2194, 18682, 5212 ]	Test
33,375	24	Title: Enhancing Adversarial Training via Reweighting Optimization Trajectory Abstract: Despite the fact that adversarial training has become the de facto method for improving the robustness of deep neural networks, it is well-known that vanilla adversarial training suffers from daunting robust overfitting, resulting i...	[]	Train
33,376	27	Title: Fusion of Visual-Inertial Odometry with LiDAR Relative Localization for Cooperative Guidance of a Micro-Scale Aerial Vehicle Abstract: A novel relative localization approach for cooperative guidance of a micro-scale Unmanned Aerial Vehicle (UAV) fusing Visual-Inertial Odometry (VIO) with Light Detection and Rang...	[ 27877, 34378, 33675, 45306, 22714 ]	Train
33,377	30	Title: Towards Populating Generalizable Engineering Design Knowledge Abstract: Aiming to populate generalizable engineering design knowledge, we propose a method to extract facts of the formfrom sentences found in patent documents. These facts could be combined within and across patent documents to form knowledge graph...	[]	Train

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