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46,078
30
Title: Analyzing FOMC Minutes: Accuracy and Constraints of Language Models Abstract: This research article analyzes the language used in the official statements released by the Federal Open Market Committee (FOMC) after its scheduled meetings to gain insights into the impact of FOMC official statements on financial mar...
[]
Train
46,079
30
Title: Zero-Shot Generalizable End-to-End Task-Oriented Dialog System using Context Summarization and Domain Schema Abstract: Task-oriented dialog systems empower users to accom-plish their goals by facilitating intuitive and expres-sive natural language interactions. State-of-the-art ap-proaches in task-oriented dialo...
[]
Test
46,080
16
Title: The Potential of Visual ChatGPT For Remote Sensing Abstract: Recent advancements in Natural Language Processing (NLP), particularly in Large Language Models (LLMs), associated with deep learning-based computer vision techniques, have shown substantial potential for automating a variety of tasks. These are known ...
[ 7936, 40192, 12546, 11273, 41109, 3609, 34074 ]
Validation
46,081
16
Title: Adaptively Clustering Neighbor Elements for Image Captioning Abstract: We design a novel global-local Transformer named \textbf{Ada-ClustFormer} (\textbf{ACF}) to generate captions. We use this name since each layer of ACF can adaptively cluster input elements to carry self-attention (Self-ATT) for learning loca...
[]
Test
46,082
16
Title: Zero-Shot Noise2Noise: Efficient Image Denoising without any Data Abstract: Recently, self-supervised neural networks have shown excellent image denoising performance. How-ever, current dataset free methods are either computationally expensive, require a noise model, or have inad-equate image quality. In this wo...
[]
Validation
46,083
16
Title: NIFTY: Neural Object Interaction Fields for Guided Human Motion Synthesis Abstract: We address the problem of generating realistic 3D motions of humans interacting with objects in a scene. Our key idea is to create a neural interaction field attached to a specific object, which outputs the distance to the valid ...
[ 38181, 27782, 27849, 14197, 15230 ]
Train
46,084
27
Title: A RL-based Policy Optimization Method Guided by Adaptive Stability Certification Abstract: In contrast to the control-theoretic methods, the lack of stability guarantee remains a significant problem for model-free reinforcement learning (RL) methods. Jointly learning a policy and a Lyapunov function has recently ...
[ 13143 ]
Train
46,085
16
Title: Semi-supervised Road Updating Network (SRUNet): A Deep Learning Method for Road Updating from Remote Sensing Imagery and Historical Vector Maps Abstract: A road is the skeleton of a city and is a fundamental and important geographical component. Currently, many countries have built geo-information databases and ...
[]
Train
46,086
16
Title: Multi-Branch Context-Aware Network for Person Re-Identification Abstract: Most existing methods on person re-identification pay redundant attention to global features or local features which ignore contextual dependencies which are equally important in representing pedestrian images. In this paper, we propose a ...
[ 16784, 45849, 43048 ]
Train
46,087
24
Title: Low Rank Optimization for Efficient Deep Learning: Making A Balance between Compact Architecture and Fast Training Abstract: Deep neural networks have achieved great success in many data processing applications. However, the high computational complexity and storage cost makes deep learning hard to be used on re...
[]
Test
46,088
2
Title: On Singleton Self-Loop Removal for Termination of LCTRSs with Bit-Vector Arithmetic Abstract: As for term rewrite systems, the dependency pair (DP, for short) framework with several kinds of DP processors is useful for proving termination of logically constrained term rewrite systems (LCTRSs, for short). However...
[]
Test
46,089
24
Title: Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression Abstract: Communication compression is an essential strategy for alleviating communication overhead by reducing the volume of information exchanged between computing nodes in large-scale distributed stoc...
[ 36857, 22738 ]
Train
46,090
2
Title: Nominal Recursors as Epi-Recursors Abstract: We study nominal recursors from the literature on syntax with bindings and compare them with respect to expressiveness. The term"nominal"refers to the fact that these recursors operate on a syntax representation where the names of bound variables appear explicitly, as...
[]
Test
46,091
6
Title: Computer Anxiety: Supporting the Transition from Desktop to Mobile Abstract: Computer Anxiety is a phenomenon studied in multiple contexts and, in the actual COVID-19 scenario, it is gaining more and more importance as it impacts technology adoption and autonomy. People with Computer Anxiety (PwCA) might feel in...
[]
Train
46,092
22
Title: A Grounded Conceptual Model for Ownership Types in Rust Abstract: Programmers learning Rust struggle to understand ownership types, Rust's core mechanism for ensuring memory safety without garbage collection. This paper describes our attempt to systematically design a pedagogy for ownership types. First, we stud...
[]
Train
46,093
24
Title: Do We Need an Encoder-Decoder to Model Dynamical Systems on Networks? Abstract: As deep learning gains popularity in modelling dynamical systems, we expose an underappreciated misunderstanding relevant to modelling dynamics on networks. Strongly influenced by graph neural networks, latent vertex embeddings are n...
[]
Train
46,094
27
Title: Path and Trajectory Planning of a Tethered UAV-UGV Marsupial Robotic System Abstract: This letter addresses the problem of trajectory planning in a marsupial robotic system consisting of an unmanned aerial vehicle (UAV) linked to an unmanned ground vehicle (UGV) through a non-taut tether with controllable length...
[]
Test
46,095
27
Title: Action-conditioned Deep Visual Prediction with RoAM, a new Indoor Human Motion Dataset for Autonomous Robots Abstract: With the increasing adoption of robots across industries, it is crucial to focus on developing advanced algorithms that enable robots to anticipate, comprehend, and plan their actions effectivel...
[]
Train
46,096
30
Title: Biomedical Named Entity Recognition via Dictionary-based Synonym Generalization Abstract: Biomedical named entity recognition is one of the core tasks in biomedical natural language processing (BioNLP). To tackle this task, numerous supervised/distantly supervised approaches have been proposed. Despite their rem...
[]
Test
46,097
30
Title: PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation Abstract: Controllable text generation is a challenging and meaningful field in natural language generation (NLG). Especially, poetry generation is a typical one with well-defined and strict conditions for text generation whic...
[ 5346, 6075, 32252 ]
Train
46,098
4
Title: Security Evaluation of Compressible and Learnable Image Encryption Against Jigsaw Puzzle Solver Attacks Abstract: Several learnable image encryption schemes have been developed for privacy-preserving image classification. This paper focuses on the security block-based image encryption methods that are learnable ...
[]
Train
46,099
24
Title: SuperFed: Weight Shared Federated Learning Abstract: Federated Learning (FL) is a well-established technique for privacy preserving distributed training. Much attention has been given to various aspects of FL training. A growing number of applications that consume FL-trained models, however, increasingly operate...
[]
Train
46,100
27
Title: Decentralised construction of a global coordinate system in a large swarm of minimalistic robots Abstract: Collective intelligence and autonomy of robot swarms can be improved by enabling the individual robots to become aware they are the constituent units of a larger whole and what is their role. In this study,...
[]
Validation
46,101
16
Title: Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models Abstract: Continual learning (CL) can help pre-trained vision-language models efficiently adapt to new or under-trained data distributions without re-training. Nevertheless, during the continual training of the Contrastive ...
[ 30243, 31523, 14501, 30472, 25417, 37070, 1167, 17406 ]
Train
46,102
6
Title: “It’s Weird That it Knows What I Want”: Usability and Interactions with Copilot for Novice Programmers Abstract: Recent developments in deep learning have resulted in code-generation models that produce source code from natural language and code-based prompts with high accuracy. This is likely to have profound e...
[ 41537, 3586, 100, 40036, 8265, 36778, 21487, 4976, 593, 3314, 37424 ]
Test
46,103
24
Title: Benchmarking Algorithms for Federated Domain Generalization Abstract: While prior domain generalization (DG) benchmarks consider train-test dataset heterogeneity, we evaluate Federated DG which introduces federated learning (FL) specific challenges. Additionally, we explore domain-based heterogeneity in clients'...
[]
Train
46,104
24
Title: Match-And-Deform: Time Series Domain Adaptation through Optimal Transport and Temporal Alignment Abstract: While large volumes of unlabeled data are usually available, associated labels are often scarce. The unsupervised domain adaptation problem aims at exploiting labels from a source domain to classify data fr...
[]
Test
46,105
16
Title: Empirical study of the modulus as activation function in computer vision applications Abstract: In this work we propose a new non-monotonic activation function: the modulus. The majority of the reported research on nonlinearities is focused on monotonic functions. We empirically demonstrate how by using the modu...
[]
Train
46,106
16
Title: A Low-rank Matching Attention based Cross-modal Feature Fusion Method for Conversational Emotion Recognition Abstract: Conversational emotion recognition (CER) is an important research topic in human-computer interactions. Although deep learning (DL) based CER approaches have achieved excellent performance, exis...
[]
Train
46,107
10
Title: Expanding Frozen Vision-Language Models without Retraining: Towards Improved Robot Perception Abstract: Vision-language models (VLMs) have shown powerful capabilities in visual question answering and reasoning tasks by combining visual representations with the abstract skill set large language models (LLMs) lear...
[ 10624, 3398, 41318, 4618, 41104, 15413, 25558, 34455, 5720, 23545, 13564, 39613 ]
Test
46,108
4
Title: A Cyber Threat Intelligence Management Platform for Industrial Environments Abstract: Developing intelligent, interoperable Cyber Threat Information (CTI) sharing technologies can help build strong defences against modern cyber threats. CTIs allow the community to share information about cybercriminals' threats ...
[]
Test
46,109
24
Title: Localizing Model Behavior with Path Patching Abstract: Localizing behaviors of neural networks to a subset of the network's components or a subset of interactions between components is a natural first step towards analyzing network mechanisms and possible failure modes. Existing work is often qualitative and ad-...
[ 36769, 13349, 43560, 7758, 29583, 11633, 4434, 6932, 45275 ]
Validation
46,110
27
Title: Multi-Session, Localization-oriented and Lightweight LiDAR Mapping Using Semantic Lines and Planes Abstract: In this paper, we present a centralized framework for multi-session LiDAR mapping in urban environments, by utilizing lightweight line and plane map representations instead of widely used point clouds. Th...
[]
Train
46,111
4
Title: FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis Abstract: Deep learning classifiers achieve state-of-the-art performance in various risk detection applications. They explore rich semantic representations and are supposed to automatically discover risk behavi...
[ 42256 ]
Train
46,112
36
Title: Platform Equilibrium: Analayzing Social Welfare in Online Market Places Abstract: We introduce the theoretical study of a Platform Equilibrium. There are unit-demand buyers and unit-supply sellers. Each seller chooses to join or remain off a trading platform, and each buyer can transact with any on-platform sell...
[]
Test
46,113
24
Title: From Sparse to Soft Mixtures of Experts Abstract: Sparse mixture of expert architectures (MoEs) scale model capacity without large increases in training or inference costs. Despite their success, MoEs suffer from a number of issues: training instability, token dropping, inability to scale the number of experts, ...
[ 20996 ]
Validation
46,114
24
Title: Model-Agnostic Federated Learning Abstract: Since its debut in 2016, Federated Learning (FL) has been tied to the inner workings of Deep Neural Networks (DNNs). On the one hand, this allowed its development and widespread use as DNNs proliferated. On the other hand, it neglected all those scenarios in which usin...
[ 1668 ]
Validation
46,115
24
Title: Solving Richly Constrained Reinforcement Learning through State Augmentation and Reward Penalties Abstract: Constrained Reinforcement Learning has been employed to enforce safety constraints on policy through the use of expected cost constraints. The key challenge is in handling expected cost accumulated using t...
[]
Train
46,116
16
Title: Spatial Gated Multi-Layer Perceptron for Land Use and Land Cover Mapping Abstract: Convolutional Neural Networks (CNNs) are models that are utilized extensively for the hierarchical extraction of features. Vision transformers (ViTs), through the use of a self-attention mechanism, have recently achieved superior ...
[]
Train
46,117
27
Title: Marker-based Visual SLAM leveraging Hierarchical Representations Abstract: Fiducial markers can encode rich information about the environment and can aid Visual SLAM (VSLAM) approaches in reconstructing maps with practical semantic information. Current marker-based VSLAM approaches mainly utilize markers for imp...
[]
Test
46,118
28
Title: Doppler-Resilient Universal Filtered MultiCarrier (DR-UFMC): A Beyond-OTFS Modulation Abstract: In the past few years, some alternatives to the Orthogonal Frequency Division Multiplexing (OFDM) modulation have been considered to improve its spectral containment and its performance level in the presence of heavy ...
[]
Train
46,119
6
Title: Supporting Construction and Architectural Visualization through BIM and AR/VR: A Systematic Literature Review Abstract: The Architecture, Engineering, Construction, and Facility Management (AEC/FM) industry deals with the design, construction, and operation of complex buildings. Today, Building Information Model...
[]
Train
46,120
23
Title: Towards Using Gameplay Videos for Detecting Issues in Video Games Abstract: Context. The game industry is increasingly growing in recent years. Every day, millions of people play video games, not only as a hobby, but also for professional competitions (e.g., e-sports or speed-running) or for making business by e...
[]
Train
46,121
16
Title: Teeth and Root Canals Segmentation using Zxyformer with Uncertainty Guidance and Weight Transfer Abstract: This study attempts to segment teeth and root-canals simultaneously from CBCT images, but there are very challenging problems in this process. First, the clinical CBCT image data is very large (e.g., 672 × ...
[]
Train
46,122
8
Title: QualityBLE: A QoS Aware Implementation for BLE Mesh Networks Abstract: Bluetooth Low Energy (BLE) Mesh is widely recognized as a driver technology for IoT applications. However, the lack of quality of service (QoS) in BLE Mesh, represented by packet prioritization, significantly limits its potential. This work i...
[]
Validation
46,123
22
Title: EXPRESSing Session Types Abstract: To celebrate the 30th edition of EXPRESS and the 20th edition of SOS we overview how session types can be expressed in a type theory for the standard $\pi$-calculus by means of a suitable encoding. The encoding allows one to reuse results about the $\pi$-calculus in the context...
[]
Train
46,124
37
Title: A Critical Re-evaluation of Benchmark Datasets for (Deep) Learning-Based Matching Algorithms Abstract: Entity resolution (ER) is the process of identifying records that refer to the same entities within one or across multiple databases. Numerous techniques have been developed to tackle ER challenges over the yea...
[]
Test
46,125
38
Title: Data inaccuracy quantification and uncertainty propagation for bibliometric indicators Abstract: This study introduces an approach to estimate the uncertainty in bibliometric indicator values that is caused by data errors. This approach utilizes Bayesian regression models, estimated from empirical data samples, ...
[]
Train
46,126
24
Title: Online Prototype Alignment for Few-shot Policy Transfer Abstract: Domain adaptation in reinforcement learning (RL) mainly deals with the changes of observation when transferring the policy to a new environment. Many traditional approaches of domain adaptation in RL manage to learn a mapping function between the ...
[ 26374 ]
Train
46,127
23
Title: Challenges and practices in aligning requirements with verification and validation: a case study of six companies Abstract: nan
[ 30214, 38475, 33008, 10714, 30906, 7357 ]
Train
46,128
30
Title: Exploring the Effectiveness of GPT Models in Test-Taking: A Case Study of the Driver's License Knowledge Test Abstract: Large language models such as Open AI's Generative Pre-trained Transformer (GPT) models are proficient at answering questions, but their knowledge is confined to the information present in thei...
[ 15301 ]
Train
46,129
24
Title: Learning Multi-Object Positional Relationships via Emergent Communication Abstract: The study of emergent communication has been dedicated to interactive artificial intelligence. While existing work focuses on communication about single objects or complex image scenes, we argue that communicating relationships b...
[]
Train
46,130
16
Title: PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection Abstract: Recently, polar-based representation has shown promising properties in perceptual tasks. In addition to Cartesian-based approaches, which separate point clouds unevenly, representing point clouds as polar grids has been recognized...
[]
Train
46,131
23
Title: Systematic Review on Privacy Categorization Abstract: In the modern digital world users need to make privacy and security choices that have far-reaching consequences. Researchers are increasingly studying people's decisions when facing with privacy and security trade-offs, the pressing and time consuming disince...
[]
Test
46,132
16
Title: Curriculum Knowledge Switching for Pancreas Segmentation Abstract: Pancreas segmentation is challenging due to the small proportion and highly changeable anatomical structure. It motivates us to propose a novel segmentation framework, namely Curriculum Knowledge Switching (CKS) framework, which decomposes detect...
[]
Train
46,133
30
Title: Structured Pruning of Self-Supervised Pre-trained Models for Speech Recognition and Understanding Abstract: Self-supervised speech representation learning (SSL) has shown to be effective in various downstream tasks, but SSL models are usually large and slow. Model compression techniques such as pruning aim to re...
[ 32480, 37122, 476 ]
Train
46,134
16
Title: Exploring Efficient Few-shot Adaptation for Vision Transformers Abstract: The task of Few-shot Learning (FSL) aims to do the inference on novel categories containing only few labeled examples, with the help of knowledge learned from base categories containing abundant labeled training samples. While there are nu...
[ 35784, 40863, 13805, 33799 ]
Validation
46,135
24
Title: Fast Diffusion Sampler for Inverse Problems by Geometric Decomposition Abstract: Diffusion models have shown exceptional performance in solving inverse problems. However, one major limitation is the slow inference time. While faster diffusion samplers have been developed for unconditional sampling, there has bee...
[ 24640, 41216, 30151, 11982, 26866, 27197 ]
Train
46,136
16
Title: Towards Grounded Visual Spatial Reasoning in Multi-Modal Vision Language Models Abstract: With the advances in large scale vision-and-language models (VLMs) it is of interest to assess their performance on various visual reasoning tasks such as counting, referring expressions and general visual question answerin...
[]
Validation
46,137
16
Title: Embrace Limited and Imperfect Training Datasets: Opportunities and Challenges in Plant Disease Recognition Using Deep Learning Abstract: Recent advancements in deep learning have brought significant improvements to plant disease recognition. However, achieving satisfactory performance often requires high-quality...
[]
Test
46,138
16
Title: Revisiting Temporal Modeling for CLIP-Based Image-to-Video Knowledge Transferring Abstract: Image-text pretrained models, e.g., CLIP, have shown impressive general multi-modal knowledge learned from large-scale image-text data pairs, thus attracting increasing attention for their potential to improve visual repr...
[]
Validation
46,139
3
Title: A User-Driven Framework for Regulating and Auditing Social Media Abstract: People form judgments and make decisions based on the information that they observe. A growing portion of that information is not only provided, but carefully curated by social media platforms. Although lawmakers largely agree that platfo...
[]
Validation
46,140
27
Title: Multi-Visual-Inertial System: Analysis, Calibration and Estimation Abstract: In this paper, we study state estimation of multi-visual-inertial systems (MVIS) and develop sensor fusion algorithms to optimally fuse an arbitrary number of asynchronous inertial measurement units (IMUs) or gyroscopes and global and(o...
[]
Train
46,141
10
Title: Generative Semantic Communication: Diffusion Models Beyond Bit Recovery Abstract: Semantic communication is expected to be one of the cores of next-generation AI-based communications. One of the possibilities offered by semantic communication is the capability to regenerate, at the destination side, images or vi...
[ 29187, 41892, 42503, 38408, 15628, 19954 ]
Test
46,142
24
Title: The Score-Difference Flow for Implicit Generative Modeling Abstract: Implicit generative modeling (IGM) aims to produce samples of synthetic data matching the characteristics of a target data distribution. Recent work (e.g. score-matching networks, diffusion models) has approached the IGM problem from the perspe...
[]
Test
46,143
24
Title: Learning to Count Isomorphisms with Graph Neural Networks Abstract: Subgraph isomorphism counting is an important problem on graphs, as many graph-based tasks exploit recurring subgraph patterns. Classical methods usually boil down to a backtracking framework that needs to navigate a huge search space with prohi...
[ 33488, 4110, 26191 ]
Validation
46,144
4
Title: Autonomous Intelligent Cyber-defense Agent: Introduction and Overview Abstract: This chapter introduces the concept of Autonomous Intelligent Cyber-defense Agents (AICAs), and briefly explains the importance of this field and the motivation for its emergence. AICA is a software agent that resides on a system, an...
[]
Train
46,145
15
Title: By-Software Branch Prediction in Loops Abstract: Load-Dependent Branches (LDB) often do not exhibit regular patterns in their local or global history and thus are inherently hard to predict correctly by conventional branch predictors. We propose a software-to-hardware branch pre-resolution mechanism that allows ...
[]
Train
46,146
2
Title: Extensions of K5: Proof Theory and Uniform Lyndon Interpolation Abstract: We introduce a Gentzen-style framework, called layered sequent calculi, for modal logic K5 and its extensions KD5, K45, KD45, KB5, and S5 with the goal to investigate the uniform Lyndon interpolation property (ULIP), which implies both the...
[]
Test
46,147
16
Title: Pointless Global Bundle Adjustment With Relative Motions Hessians Abstract: Bundle adjustment (BA) is the standard way to optimise camera poses and to produce sparse representations of a scene. However, as the number of camera poses and features grows, refinement through bundle adjustment becomes inefficient. In...
[]
Validation
46,148
10
Title: A clustering and graph deep learning-based framework for COVID-19 drug repurposing Abstract: Drug repurposing (or repositioning) is the process of finding new therapeutic uses for drugs already approved by drug regulatory authorities (e.g., the Food and Drug Administration (FDA) and Therapeutic Goods Administrat...
[]
Train
46,149
24
Title: Benchmarks and Algorithms for Offline Preference-Based Reward Learning Abstract: Learning a reward function from human preferences is challenging as it typically requires having a high-fidelity simulator or using expensive and potentially unsafe actual physical rollouts in the environment. However, in many tasks...
[ 12481, 28106, 42581, 35767 ]
Train
46,150
4
Title: Robustness for Spectral Clustering of General Graphs under Local Differential Privacy Abstract: Spectral clustering is a widely used algorithm to find clusters in networks. Several researchers have studied the stability of spectral clustering under local differential privacy with the additional assumption that t...
[ 31083 ]
Validation
46,151
16
Title: CCL: Continual Contrastive Learning for LiDAR Place Recognition Abstract: Place recognition is an essential and challenging task in loop closing and global localization for robotics and autonomous driving applications. Benefiting from the recent advances in deep learning techniques, the performance of LiDAR plac...
[ 36298 ]
Train
46,152
4
Title: Front-running Attack in Sharded Blockchains and Fair Cross-shard Consensus Abstract: Sharding is a prominent technique for scaling blockchains. By dividing the network into smaller components known as shards, a sharded blockchain can process transactions in parallel without introducing inconsistencies through th...
[ 22992 ]
Train
46,153
27
Title: Immersive Virtual Reality Platform for Robot-Assisted Antenatal Ultrasound Scanning Abstract: Maternal health remains a pervasive challenge in developing and underdeveloped countries. Inadequate access to basic antenatal Ultrasound (US) examinations, limited resources such as primary health services and infrastr...
[]
Train
46,154
16
Title: Visual Prompt Multi-Modal Tracking Abstract: Visible-modal object tracking gives rise to a series of downstream multi-modal tracking tributaries. To inherit the powerful representations of the foundation model, a natural modus operandi for multi-modal tracking is full fine-tuning on the RGB-based parameters. Alb...
[ 21989, 28103, 21193, 13521, 18995, 11927, 28124, 27100, 1151 ]
Train
46,155
30
Title: Dynamic Strategy Chain: Dynamic Zero-Shot CoT for Long Mental Health Support Generation Abstract: Long counseling Text Generation for Mental health support (LTGM), an innovative and challenging task, aims to provide help-seekers with mental health support through a comprehensive and more acceptable response. The...
[ 40610, 9907, 13700 ]
Test
46,156
16
Title: Towards Unified Scene Text Spotting Based on Sequence Generation Abstract: Sequence generation models have recently made significant progress in unifying various vision tasks. Although some auto-regressive models have demonstrated promising results in end-to-end text spotting, they use specific detection formats...
[]
Validation
46,157
23
Title: Implementing a Model-based Engineering Tool as Web Application Abstract: This paper reports on a study of transferring a desktop-based model-based engineering tool to a web application. The study has been conducted in the WEBMODEL project where the well-established technology stack around the Eclipse platform an...
[]
Test
46,158
30
Title: Exploiting Language Relatedness in Machine Translation Through Domain Adaptation Techniques Abstract: One of the significant challenges of Machine Translation (MT) is the scarcity of large amounts of data, mainly parallel sentence aligned corpora. If the evaluation is as rigorous as resource-rich languages, both...
[]
Train
46,159
28
Title: Multiuser Communications with Movable-Antenna Base Station: Joint Antenna Positioning, Receive Combining, and Power Control Abstract: Movable antenna (MA) is an emerging technology which enables a local movement of the antenna in the transmitter/receiver region for improving the channel condition and communicati...
[ 10887, 15346, 6199, 6616, 10461 ]
Train
46,160
16
Title: Multi-view Feature Extraction based on Dual Contrastive Head Abstract: Multi-view feature extraction is an efficient approach for alleviating the issue of dimensionality in highdimensional multi-view data. Contrastive learning (CL), which is a popular self-supervised learning method, has recently attracted consi...
[]
Train
46,161
30
Title: Math Word Problem Solving by Generating Linguistic Variants of Problem Statements Abstract: The art of mathematical reasoning stands as a fundamental pillar of intellectual progress and is a central catalyst in cultivating human ingenuity. Researchers have recently published a plethora of works centered around t...
[ 35388, 13510, 33207 ]
Train
46,162
26
Title: Exploring Diverse Coping Mechanisms in 2023: A Comprehensive Survey Across Backgrounds and Cultures Abstract: This study presents a pioneering investigation into the wide array of coping mechanisms employed by individuals in the year 2023, with a focus on data collected through the popular social media platform ...
[]
Train
46,163
30
Title: Learning and Leveraging Verifiers to Improve Planning Capabilities of Pre-trained Language Models Abstract: There have been wide spread claims in the literature about the emergent reasoning capabilities of Pretrained Large Language Models. However, recent studies, have found that their ability to plan remains qu...
[]
Train
46,164
10
Title: Extensions to Generalized Annotated Logic and an Equivalent Neural Architecture Abstract: While deep neural networks have led to major advances in image recognition, language translation, data mining, and game playing, there are well-known limits to the paradigm such as lack of explainability, difficulty of inco...
[ 14035 ]
Test
46,165
24
Title: Preventing Discriminatory Decision-making in Evolving Data Streams Abstract: Bias in machine learning has rightly received significant attention over the past decade. However, most fair machine learning (fair-ML) works to address bias in decision-making systems has focused solely on the offline setting. Despite ...
[ 42256, 41899, 13997 ]
Test
46,166
16
Title: Overlap Bias Matching is Necessary for Point Cloud Registration Abstract: Point cloud registration is a fundamental problem in many domains. Practically, the overlap between point clouds to be registered may be relatively small. Most unsupervised methods lack effective initial evaluation of overlap, leading to s...
[]
Train
46,167
5
Title: SMOTEC: An Edge Computing Testbed for Adaptive Smart Mobility Experimentation Abstract: Smart mobility becomes paramount for meeting net-zero targets. However, autonomous, self-driving and electric vehicles require more than ever before an efficient, resilient and trustworthy computational offloading backbone th...
[]
Train
46,168
4
Title: A Comprehensive Overview of Backdoor Attacks in Large Language Models within Communication Networks Abstract: The Large Language Models (LLMs) are poised to offer efficient and intelligent services for future mobile communication networks, owing to their exceptional capabilities in language comprehension and gen...
[ 9248, 7345, 22515, 13510 ]
Train
46,169
6
Title: HistoColAi: An Open-Source Web Platform for Collaborative Digital Histology Image Annotation with AI-Driven Predictive Integration Abstract: Digital pathology has become a standard in the pathology workflow due to its many benefits. These include the level of detail of the whole slide images generated and the po...
[]
Train
46,170
24
Title: MimiC: Combating Client Dropouts in Federated Learning by Mimicking Central Updates Abstract: Federated learning (FL) is a promising framework for privacy-preserving collaborative learning, where model training tasks are distributed to clients and only the model updates need to be collected at a server. However,...
[]
Train
46,171
16
Title: Random Word Data Augmentation with CLIP for Zero-Shot Anomaly Detection Abstract: This paper presents a novel method that leverages a visual-language model, CLIP, as a data source for zero-shot anomaly detection. Tremendous efforts have been put towards developing anomaly detectors due to their potential industr...
[ 12907, 37029 ]
Train
46,172
16
Title: In-context Cross-Density Adaptation on Noisy Mammogram Abnormalities Detection Abstract: This paper investigates the impact of breast density distribution on the generalization performance of deep-learning models on mammography images using the VinDr-Mammo dataset. We explore the use of domain adaptation techniq...
[ 42431, 19087 ]
Train
46,173
24
Title: Identifying Adversarially Attackable and Robust Samples Abstract: Adversarial attacks insert small, imperceptible perturbations to input samples that cause large, undesired changes to the output of deep learning models. Despite extensive research on generating adversarial attacks and building defense systems, th...
[ 38450, 17876 ]
Train
46,174
30
Title: Examining the Causal Impact of First Names on Language Models: The Case of Social Commonsense Reasoning Abstract: As language models continue to be integrated into applications of personal and societal relevance, ensuring these models’ trustworthiness is crucial, particularly with respect to producing consistent...
[]
Train
46,175
30
Title: Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extraction Abstract: Aspect Sentiment Triplet Extraction (ASTE) is widely used in various applications. However, existing ASTE datasets are limited in their ability to represent real-world scenarios, hindering...
[ 22525 ]
Validation
46,176
24
Title: Practical Policy Optimization with Personalized Experimentation Abstract: Many organizations measure treatment effects via an experimentation platform to evaluate the casual effect of product variations prior to full-scale deployment. However, standard experimentation platforms do not perform optimally for end u...
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Test
46,177
16
Title: Noisy-label Learning with Sample Selection based on Noise Rate Estimate Abstract: Noisy-labels are challenging for deep learning due to the high capacity of the deep models that can overfit noisy-label training samples. Arguably the most realistic and coincidentally challenging type of label noise is the instanc...
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Validation