node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
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|---|---|---|---|---|
27,978 | 23 | Title: TypeScript’s Evolution: An Analysis of Feature Adoption Over Time
Abstract: TypeScript is a quickly evolving superset of JavaScript with active development of new features. Our paper seeks to understand how quickly these features are adopted by the developer community. Existing work in JavaScript shows the adopt... | [] | Test |
27,979 | 24 | Title: Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning
Abstract: This paper studies reward-agnostic exploration in reinforcement learning (RL) -- a scenario where the learner is unware of the reward functions during the exploration stage -- and designs an algorithm that improves over the state of ... | [
18008,
31960,
29926,
3287
] | Test |
27,980 | 23 | Title: Monitoring and Maintenance of Telecommunication Systems: Challenges and Research Perspectives
Abstract: nan | [] | Train |
27,981 | 16 | Title: Zero-shot Nuclei Detection via Visual-Language Pre-trained Models
Abstract: Large-scale visual-language pre-trained models (VLPM) have proven their excellent performance in downstream object detection for natural scenes. However, zero-shot nuclei detection on H\&E images via VLPMs remains underexplored. The larg... | [] | Validation |
27,982 | 16 | Title: Cross Architecture Distillation for Face Recognition
Abstract: Transformers have emerged as the superior choice for face recognition tasks, but their insufficient platform acceleration hinders their application on mobile devices. In contrast, Convolutional Neural Networks (CNNs) capitalize on hardware-compatible... | [
1451
] | Train |
27,983 | 30 | Title: Learning to Memorize Entailment and Discourse Relations for Persona-Consistent Dialogues
Abstract: Maintaining engagement and consistency is particularly important in dialogue systems. Existing works have improved the performance of dialogue systems by intentionally learning interlocutor personas with sophistica... | [] | Train |
27,984 | 30 | Title: Recursive Metropolis-Hastings Naming Game: Symbol Emergence in a Multi-agent System based on Probabilistic Generative Models
Abstract: In the studies on symbol emergence and emergent communication in a population of agents, a computational model was employed in which agents participate in various language games.... | [] | Train |
27,985 | 16 | Title: AICSD: Adaptive Inter-Class Similarity Distillation for Semantic Segmentation
Abstract: In recent years, deep neural networks have achieved remarkable accuracy in computer vision tasks. With inference time being a crucial factor, particularly in dense prediction tasks such as semantic segmentation, knowledge dis... | [] | Test |
27,986 | 16 | Title: CHAMP: Crowdsourced, History-Based Advisory of Mapped Pedestrians for Safer Driver Assistance Systems
Abstract: Vehicles are constantly approaching and sharing the road with pedestrians, and as a result it is critical for vehicles to prevent any collisions with pedestrians. Current methods for pedestrian collisi... | [] | Train |
27,987 | 30 | Title: Learning Translation Quality Evaluation on Low Resource Languages from Large Language Models
Abstract: Learned metrics such as BLEURT have in recent years become widely employed to evaluate the quality of machine translation systems. Training such metrics requires data which can be expensive and difficult to acq... | [
16822
] | Train |
27,988 | 24 | Title: PRIMO: Private Regression in Multiple Outcomes
Abstract: We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of $l$ regressions while preserving privacy, where the covariate... | [] | Validation |
27,989 | 23 | Title: CBIM: A Graph-based Approach to Enhance Interoperability Using Semantic Enrichment
Abstract: Interoperability remains a challenge in the construction industry. In this study, we propose a semantic enrichment approach to construct BIM knowledge graphs from pure building object geometries and demonstrate its poten... | [
17804
] | Train |
27,990 | 30 | Title: Data-efficient Active Learning for Structured Prediction with Partial Annotation and Self-Training
Abstract: In this work we propose a pragmatic method that reduces the annotation cost for structured label spaces using active learning. Our approach leverages partial annotation, which reduces labeling costs for s... | [] | Train |
27,991 | 27 | Title: Motion Capture Benchmark of Real Industrial Tasks and Traditional Crafts for Human Movement Analysis
Abstract: Human movement analysis is a key area of research in robotics, biomechanics, and data science. It encompasses tracking, posture estimation, and movement synthesis. While numerous methodologies have evol... | [
20448
] | Test |
27,992 | 2 | Title: A Formal Proof of the Strong Normalization Theorem for System T in Agda
Abstract: We present a framework for the formal meta-theory of lambda calculi in first-order syntax, with two sorts of names, one to represent both free and bound variables, and the other for constants, and by using Stoughton's multiple subs... | [] | Train |
27,993 | 28 | Title: Localization-based OFDM framework for RIS-aided systems
Abstract: Efficient integration of reconfigurable intelligent surfaces (RISs) into the current wireless network standard is not a trivial task due to the overhead generated by performing channel estimation (CE) and phase-shift optimization. In this paper, w... | [
23173
] | Train |
27,994 | 30 | Title: Beyond Shared Vocabulary: Increasing Representational Word Similarities across Languages for Multilingual Machine Translation
Abstract: Using a shared vocabulary is common practice in Multilingual Neural Machine Translation (MNMT). In addition to its simple design, shared tokens play an important role in positiv... | [] | Train |
27,995 | 31 | Title: Query Understanding in the Age of Large Language Models
Abstract: Querying, conversing, and controlling search and information-seeking interfaces using natural language are fast becoming ubiquitous with the rise and adoption of large-language models (LLM). In this position paper, we describe a generic framework ... | [
19068,
13569,
67,
13700,
105,
6062,
12851,
15004
] | Train |
27,996 | 24 | Title: Exploiting Generalization in Offline Reinforcement Learning via Unseen State Augmentations
Abstract: Offline reinforcement learning (RL) methods strike a balance between exploration and exploitation by conservative value estimation -- penalizing values of unseen states and actions. Model-free methods penalize va... | [] | Train |
27,997 | 26 | Title: When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability
Abstract: Homophily principle, i.e. nodes with the same labels are more likely to be connected, has been believed to be the main reason for the performance superiority of Graph Neural Net... | [
269,
26023
] | Train |
27,998 | 16 | Title: Deformation Robust Text Spotting with Geometric Prior
Abstract: The goal of text spotting is to perform text detection and recognition in an end-to-end manner. Although the diversity of luminosity and orientation in scene texts has been widely studied, the font diversity and shape variance of the same character ... | [] | Train |
27,999 | 24 | Title: Stability Guarantees for Feature Attributions with Multiplicative Smoothing
Abstract: Explanation methods for machine learning models tend to not provide any formal guarantees and may not reflect the underlying decision-making process. In this work, we analyze stability as a property for reliable feature attribu... | [] | Train |
28,000 | 10 | Title: Semantic Compression With Large Language Models
Abstract: The rise of large language models (LLMs) is revolutionizing information retrieval, question answering, summarization, and code generation tasks. However, in addition to confidently presenting factually inaccurate information at times (known as"hallucinati... | [
13510,
1515,
43566,
43471,
33175,
35580
] | Test |
28,001 | 16 | Title: Latent Graph Attention for Enhanced Spatial Context
Abstract: Global contexts in images are quite valuable in image-to-image translation problems. Conventional attention-based and graph-based models capture the global context to a large extent, however, these are computationally expensive. Moreover, the existing... | [] | Train |
28,002 | 18 | Title: Dendritic Computation through Exploiting Resistive Memory as both Delays and Weights
Abstract: Biological neurons can detect complex spatio-temporal features in spiking patterns via their synapses spread across their dendritic branches. This is achieved by modulating the efficacy of the individual synapses, and ... | [
13511
] | Train |
28,003 | 30 | Title: Izindaba-Tindzaba: Machine learning news categorisation for Long and Short Text for isiZulu and Siswati
Abstract: Local/Native South African languages are classified as low-resource languages. As such, it is essential to build the resources for these languages so that they can benefit from advances in the field ... | [] | Train |
28,004 | 16 | Title: Robust Text-driven Image Editing Method that Adaptively Explores Directions in Latent Spaces of StyleGAN and CLIP
Abstract: Automatic image editing has great demands because of its numerous applications, and the use of natural language instructions is essential to achieving flexible and intuitive editing as the ... | [
20435
] | Train |
28,005 | 16 | Title: Noisy Image Segmentation With Soft-Dice
Abstract: This paper presents a study on the soft-Dice loss, one of the most popular loss functions in medical image segmentation, for situations where noise is present in target labels. In particular, the set of optimal solutions are characterized and sharp bounds on the ... | [
9454
] | Train |
28,006 | 16 | Title: Tranfer Learning of Semantic Segmentation Methods for Identifying Buried Archaeological Structures on LiDAR Data
Abstract: When applying deep learning to remote sensing data in archaeological research, a notable obstacle is the limited availability of suitable datasets for training models. The application of tra... | [
45218
] | Train |
28,007 | 26 | Title: Multiscale Transforms for Signals on Simplicial Complexes
Abstract: Our previous multiscale graph basis dictionaries/graph signal transforms -- Generalized Haar-Walsh Transform (GHWT); Hierarchical Graph Laplacian Eigen Transform (HGLET); Natural Graph Wavelet Packets (NGWPs); and their relatives -- were develop... | [] | Train |
28,008 | 30 | Title: Lived Experience Matters: Automatic Detection of Stigma on Social Media Toward People Who Use Substances
Abstract: Stigma toward people who use substances (PWUS) is a leading barrier to seeking treatment.Further, those in treatment are more likely to drop out if they experience higher levels of stigmatization. W... | [] | Validation |
28,009 | 31 | Title: Graph-based Alignment and Uniformity for Recommendation
Abstract: Collaborative filtering-based recommender systems (RecSys) rely on learning representations for users and items to predict preferences accurately. Representation learning on the hypersphere is a promising approach due to its desirable properties, ... | [] | Train |
28,010 | 24 | Title: Inferring networks from time series: a neural approach
Abstract: Network structures underlie the dynamics of many complex phenomena, from gene regulation and foodwebs to power grids and social media. Yet, as they often cannot be observed directly, their connectivities must be inferred from observations of their ... | [] | Train |
28,011 | 25 | Title: Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggers
Abstract: In this paper, we focus on Whisper, a recent automatic speech recognition model trained with a massive 680k hour labeled speech corpus recorded in diverse conditions. We first show an interesting finding t... | [
8558
] | Train |
28,012 | 24 | Title: ZhiJian: A Unifying and Rapidly Deployable Toolbox for Pre-trained Model Reuse
Abstract: The rapid expansion of foundation pre-trained models and their fine-tuned counterparts has significantly contributed to the advancement of machine learning. Leveraging pre-trained models to extract knowledge and expedite lea... | [
2979
] | Train |
28,013 | 28 | Title: Closed-Form Analysis of the α-Beaulieu-Xie Shadowed Fading Channel
Abstract: The presented research proposes the $\alpha $ -modification of the Beaulieu-Xie shadowed fading channel for wireless communications. For the assumed model the closed-form analytical description of the basic statistical characteristics i... | [] | Train |
28,014 | 16 | Title: Part Aware Contrastive Learning for Self-Supervised Action Recognition
Abstract: In recent years, remarkable results have been achieved in self-supervised action recognition using skeleton sequences with contrastive learning. It has been observed that the semantic distinction of human action features is often re... | [
37632,
8554,
5317
] | Train |
28,015 | 34 | Title: Quantitative Comparison of Nearest Neighbor Search Algorithms
Abstract: We compare the performance of three nearest neighbor search algorithms: the Orchard, ball tree, and VP-tree algorithms. These algorithms are commonly used for nearest-neighbor searches and are known for their efficiency in large datasets. We... | [] | Train |
28,016 | 16 | Title: Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images
Abstract: We propose a novel transformer-based framework that reconstructs two high fidelity hands from multi-view RGB images. Unlike existing hand pose estimation methods, where one typical... | [
16136,
1388
] | Train |
28,017 | 2 | Title: Recursive First-order Syntactic Unification Modulo Variable Classes
Abstract: We present a generalization of first-order syntactic unification to a term algebra where variable indexing is part of the object language. Unlike first-order syntactic unification, the number of variables within a given problem is not ... | [
2155
] | Validation |
28,018 | 27 | Title: Synthesizing Dexterous Nonprehensile Pregrasp for Ungraspable Objects
Abstract: Daily objects embedded in a contextual environment are often ungraspable initially. Whether it is a book sandwiched by other books on a fully packed bookshelf or a piece of paper lying flat on the desk, a series of nonprehensile preg... | [
35770,
16070
] | Test |
28,019 | 18 | Title: SPICE Modeling of Memcomputing Logic Gates
Abstract: Memcomputing logic gates generalize the traditional Boolean logic gates for operation in the reverse direction. According to the literature, this functionality enables the efficient solution of computationally-intensive problems including factorization and NP-... | [] | Train |
28,020 | 24 | Title: Machine Learning Techniques for Predicting the Short-Term Outcome of Resective Surgery in Lesional-Drug Resistance Epilepsy
Abstract: In this study, we developed and tested machine learning models to predict epilepsy surgical outcome using noninvasive clinical and demographic data from patients. Methods: Seven d... | [] | Train |
28,021 | 24 | Title: Adaptive Bernstein Change Detector for High-Dimensional Data Streams
Abstract: Change detection is of fundamental importance when analyzing data streams. Detecting changes both quickly and accurately enables monitoring and prediction systems to react, e.g., by issuing an alarm or by updating a learning algorithm... | [] | Test |
28,022 | 4 | Title: DCM: A Developers Certification Model for Mobile Ecosystems
Abstract: This article introduces a distributed model of trust for app developers in Android and iOS mobile ecosystems. The model aims to allow the co-existence of multiple app stores and distribution channels while retaining a high level of safety for ... | [] | Train |
28,023 | 27 | Title: Learning Sparse Control Tasks from Pixels by Latent Nearest-Neighbor-Guided Explorations
Abstract: Recent progress in deep reinforcement learning (RL) and computer vision enables artificial agents to solve complex tasks, including locomotion, manipulation and video games from high-dimensional pixel observations.... | [
40547
] | Train |
28,024 | 4 | Title: Recent Advances in the Internet-of-Medical-Things (IoMT) Systems Security
Abstract: The rapid evolutions in microcomputing, mini-hardware manufacturing, and machine-to-machine (M2M) communications have enabled novel Internet-of-Things (IoT) solutions to reshape many networking applications. Healthcare systems ar... | [
2763
] | Validation |
28,025 | 25 | Title: Onsets and Velocities: Affordable Real-Time Piano Transcription Using Convolutional Neural Networks
Abstract: Polyphonic Piano Transcription has recently experienced substantial progress, driven by the use of sophisticated Deep Learning approaches and the introduction of new subtasks such as note onset, offset, ... | [] | Test |
28,026 | 27 | Title: AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms
Abstract: The behaviours of a swarm are not explicitly engineered. Instead, they are an emergent consequence of the interactions of individual agents with each other and their environment. This emergent functionality poses a challenge to safety ... | [] | Validation |
28,027 | 10 | Title: ConvFormer: Revisiting Transformer for Sequential User Modeling
Abstract: Sequential user modeling, a critical task in personalized recommender systems, focuses on predicting the next item a user would prefer, requiring a deep understanding of user behavior sequences. Despite the remarkable success of Transforme... | [
36660
] | Validation |
28,028 | 4 | Title: A Comprehensive Analysis of the Role of Artificial Intelligence and Machine Learning in Modern Digital Forensics and Incident Response
Abstract: In the dynamic landscape of digital forensics, the integration of Artificial Intelligence (AI) and Machine Learning (ML) stands as a transformative technology, poised t... | [] | Train |
28,029 | 6 | Title: Expanding Targets in Virtual Reality Environments: A Fitts' Law Study
Abstract: Target pointing selection is a fundamental task. According to Fitts' law, users need more time to select targets with smaller sizes. Expanding the target to a larger size is a practical approach that can facilitate pointing selection... | [] | Train |
28,030 | 24 | Title: Graph Inductive Biases in Transformers without Message Passing
Abstract: Transformers for graph data are increasingly widely studied and successful in numerous learning tasks. Graph inductive biases are crucial for Graph Transformers, and previous works incorporate them using message-passing modules and/or posit... | [
8660,
32301,
11062
] | Test |
28,031 | 6 | Title: Applications of Voice User Interfaces in Clinical Settings
Abstract: The adoption of modern technologies for use in healthcare has become an inevitable change. The emergence of artificial intelligence drives this digital disruption. Artificial intelligence has augmented machine capabilities to act like and inter... | [] | Validation |
28,032 | 25 | Title: EE-TTS: Emphatic Expressive TTS with Linguistic Information
Abstract: While Current TTS systems perform well in synthesizing high-quality speech, producing highly expressive speech remains a challenge. Emphasis, as a critical factor in determining the expressiveness of speech, has attracted more attention nowada... | [] | Train |
28,033 | 30 | Title: IMAD: IMage-Augmented multi-modal Dialogue
Abstract: Currently, dialogue systems have achieved high performance in processing text-based communication. However, they have not yet effectively incorporated visual information, which poses a significant challenge. Furthermore, existing models that incorporate images... | [
10624,
30243,
28435
] | Validation |
28,034 | 30 | Title: Measuring Variety, Balance, and Disparity: An Analysis of Media Coverage of the 2021 German Federal Election
Abstract: Determining and measuring diversity in news articles is important for a number of reasons, including preventing filter bubbles and fueling public discourse, especially before elections. So far, ... | [] | Train |
28,035 | 22 | Title: MAGπ: Types for Failure-Prone Communication
Abstract: Multiparty Session Types (MPST) are a typing discipline for communication-centric systems, guaranteeing communication safety, deadlock freedom and protocol compliance. Several works have emerged which model failures and introduce fault-tolerance techniques. H... | [
35029
] | Test |
28,036 | 8 | Title: Safe Routing Approach by Identifying and Subsequently Eliminating the Attacks in MANET
Abstract: Wireless networks that are decentralized and communicate without using existing infrastructure are known as mobile ad-hoc networks. The most common sorts of threats and attacks can affect MANETs. Therefore, it is adv... | [
24065,
5154,
25547,
42860,
44207,
10838,
30199,
35578
] | Validation |
28,037 | 34 | Title: Fully Scalable Massively Parallel Algorithms for Embedded Planar Graphs
Abstract: We consider the \emph{massively parallel computation} (MPC) model, which is a theoretical abstraction of large-scale parallel processing models such as MapReduce. In this model, assuming the widely believed 1-vs-2-cycles conjecture... | [] | Train |
28,038 | 24 | Title: Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective
Abstract: We investigate the question of whether the knowledge learned by graph neural networks (GNNs) from small graphs is generalizable to large graphs in the same domain. Prior works suggest... | [
27757
] | Validation |
28,039 | 16 | Title: Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking
Abstract: In many applications of advanced robotic manipulation, six degrees of freedom (6DoF) object pose estimates are continuously required. In this work, we develop a multi-modality tracker that fuses information from visual appear... | [] | Test |
28,040 | 8 | Title: Synergies Between Federated Learning and O-RAN: Towards an Elastic Virtualized Architecture for Multiple Distributed Machine Learning Services
Abstract: Federated learning (FL) is the most popular distributed machine learning technique. However, implementation of FL over modern wireless networks faces key challe... | [] | Validation |
28,041 | 26 | Title: Will Admins Cope? Decentralized Moderation in the Fediverse
Abstract: As an alternative to Twitter and other centralized social networks, the Fediverse is growing in popularity. The recent, and polemical, takeover of Twitter by Elon Musk has exacerbated this trend. The Fediverse includes a growing number of dece... | [
12952,
32977,
20651
] | Train |
28,042 | 16 | Title: Blending-NeRF: Text-Driven Localized Editing in Neural Radiance Fields
Abstract: Text-driven localized editing of 3D objects is particularly difficult as locally mixing the original 3D object with the intended new object and style effects without distorting the object's form is not a straightforward process. To ... | [] | Test |
28,043 | 26 | Title: Zoo Guide to Network Embedding
Abstract: Networks have provided extremely successful models of data and complex systems. Yet, as combinatorial objects, networks do not have in general intrinsic coordinates and do not typically lie in an ambient space. The process of assigning an embedding space to a network has ... | [
26479
] | Train |
28,044 | 24 | Title: Blockchain Transaction Fee Forecasting: A Comparison of Machine Learning Methods
Abstract: Gas is the transaction-fee metering system of the Ethereum network. Users of the network are required to select a gas price for submission with their transaction, creating a risk of overpaying or delayed/unprocessed transa... | [] | Train |
28,045 | 10 | Title: Evolve Path Tracer: Early Detection of Malicious Addresses in Cryptocurrency
Abstract: With the boom of cryptocurrency and its concomitant financial risk concerns, detecting fraudulent behaviors and associated malicious addresses has been drawing significant research effort. Most existing studies, however, rely ... | [
21562
] | Validation |
28,046 | 17 | Title: Merge Tree Geodesics and Barycenters with Path Mappings
Abstract: Comparative visualization of scalar fields is often facilitated using similarity measures such as edit distances. In this paper, we describe a novel approach for similarity analysis of scalar fields that combines two recently introduced techniques... | [] | Train |
28,047 | 16 | Title: HGDNet: A Height-Hierarchy Guided Dual-Decoder Network for Single View Building Extraction and Height Estimation
Abstract: Unifying the correlative single-view satellite image building extraction and height estimation tasks indicates a promising way to share representations and acquire generalist model for large... | [
29873
] | Validation |
28,048 | 26 | Title: Edge Ranking of Graphs in Transportation Networks using a Graph Neural Network (GNN)
Abstract: Many networks, such as transportation, power, and water distribution, can be represented as graphs. Crucial challenge in graph representations is identifying the importance of graph edges and their influence on overall... | [] | Train |
28,049 | 16 | Title: Domain Adaptation for Efficiently Fine-tuning Vision Transformer with Encrypted Images
Abstract: In recent years, deep neural networks (DNNs) trained with transformed data have been applied to various applications such as privacy-preserving learning, access control, and adversarial defenses. However, the use of ... | [
33265
] | Train |
28,050 | 16 | Title: Point-and-Shoot All-in-Focus Photo Synthesis From Smartphone Camera Pair
Abstract: All-in-Focus (AIF) photography is expected to be a commercial selling point for modern smartphones. Standard AIF synthesis requires manual, time-consuming operations such as focal stack compositing, which is unfriendly to ordinary... | [
3166
] | Train |
28,051 | 30 | Title: Cross-functional Analysis of Generalization in Behavioral Learning
Abstract: Abstract In behavioral testing, system functionalities underrepresented in the standard evaluation setting (with a held-out test set) are validated through controlled input-output pairs. Optimizing performance on the behavioral tests du... | [] | Validation |
28,052 | 24 | Title: GBM-based Bregman Proximal Algorithms for Constrained Learning
Abstract: As the complexity of learning tasks surges, modern machine learning encounters a new constrained learning paradigm characterized by more intricate and data-driven function constraints. Prominent applications include Neyman-Pearson classific... | [] | Train |
28,053 | 16 | Title: WDiscOOD: Out-of-Distribution Detection via Whitened Linear Discriminant Analysis
Abstract: Deep neural networks are susceptible to generating overconfident yet erroneous predictions when presented with data beyond known concepts. This challenge underscores the importance of detecting out-of-distribution (OOD) s... | [
31248
] | Train |
28,054 | 30 | Title: Systematic Evaluation of GPT-3 for Zero-Shot Personality Estimation
Abstract: Very large language models (LLMs) perform extremely well on a spectrum of NLP tasks in a zero-shot setting. However, little is known about their performance on human-level NLP problems which rely on understanding psychological concepts... | [
14026
] | Test |
28,055 | 25 | Title: GTN-Bailando: Genre Consistent Long-Term 3D Dance Generation based on Pre-trained Genre Token Network
Abstract: Music-driven 3D dance generation has become an intensive research topic in recent years with great potential for real-world applications. Most existing methods lack the consideration of genre, which re... | [
27642,
36214
] | Train |
28,056 | 30 | Title: RaTE: a Reproducible automatic Taxonomy Evaluation by Filling the Gap
Abstract: Taxonomies are an essential knowledge representation, yet most studies on automatic taxonomy construction (ATC) resort to manual evaluation to score proposed algorithms. We argue that automatic taxonomy evaluation (ATE) is just as im... | [] | Train |
28,057 | 16 | Title: DLGSANet: Lightweight Dynamic Local and Global Self-Attention Networks for Image Super-Resolution
Abstract: We propose an effective lightweight dynamic local and global self-attention network (DLGSANet) to solve image super-resolution. Our method explores the properties of Transformers while having low computati... | [] | Train |
28,058 | 16 | Title: M3D-NCA: Robust 3D Segmentation with Built-in Quality Control
Abstract: Medical image segmentation relies heavily on large-scale deep learning models, such as UNet-based architectures. However, the real-world utility of such models is limited by their high computational requirements, which makes them impractical... | [] | Train |
28,059 | 24 | Title: Self-Supervised Transformer Architecture for Change Detection in Radio Access Networks
Abstract: Radio Access Networks (RANs) for telecommunications represent large agglomerations of interconnected hardware consisting of hundreds of thousands of transmitting devices (cells). Such networks undergo frequent and of... | [] | Test |
28,060 | 16 | Title: Cyclic-Bootstrap Labeling for Weakly Supervised Object Detection
Abstract: Recent progress in weakly supervised object detection is featured by a combination of multiple instance detection networks (MIDN) and ordinal online refinement. However, with only image-level annotation, MIDN inevitably assigns high score... | [] | Train |
28,061 | 16 | Title: Unsupervised Mutual Transformer Learning for Multi-Gigapixel Whole Slide Image Classification
Abstract: Classification of gigapixel Whole Slide Images (WSIs) is an important prediction task in the emerging area of computational pathology. There has been a surge of research in deep learning models for WSI classif... | [] | Train |
28,062 | 31 | Title: Creating Synthetic Datasets for Collaborative Filtering Recommender Systems using Generative Adversarial Networks
Abstract: Research and education in machine learning needs diverse, representative, and open datasets that contain sufficient samples to handle the necessary training, validation, and testing tasks. ... | [] | Validation |
28,063 | 30 | Title: Memorization for Good: Encryption with Autoregressive Language Models
Abstract: Over-parameterized neural language models (LMs) can memorize and recite long sequences of training data. While such memorization is normally associated with undesired properties such as overfitting and information leaking, our work c... | [
2347
] | Train |
28,064 | 16 | Title: Joint Hierarchical Priors and Adaptive Spatial Resolution for Efficient Neural Image Compression
Abstract: Recently, the performance of neural image compression (NIC) has steadily improved thanks to the last line of study, reaching or outperforming state-of-the-art conventional codecs. Despite significant progre... | [] | Train |
28,065 | 13 | Title: Modularity Based Linkage Model For Neuroevolution
Abstract: Crossover between neural networks is considered disruptive due to the strong functional dependency between connection weights. We propose a modularity-based linkage model at the weight level to preserve functionally dependent communities (building block... | [] | Test |
28,066 | 28 | Title: Transformer-aided Wireless Image Transmission with Channel Feedback
Abstract: This paper presents a novel wireless image transmission paradigm that can exploit feedback from the receiver, called DeepJSCC-ViT-f. We consider a block feedback channel model, where the transmitter receives noiseless/noisy channel out... | [] | Validation |
28,067 | 27 | Title: Exploring the Boundaries: Thorough Software Testing for Safety-Critical Driving Scenarios Based on Kinematics in the Context of Autonomous Driving
Abstract: This scientific publication focuses on the efficient application of boundary value analysis in the testing of corner cases for kinematic-based safety-critic... | [
1957
] | Train |
28,068 | 24 | Title: Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions
Abstract: How to properly set the privacy parameter in differential privacy (DP) has been an open question in DP research since it was first proposed in 2006. In this work, we demonstrate the ability of influence function... | [] | Test |
28,069 | 4 | Title: PUF for the Commons: Enhancing Embedded Security on the OS Level
Abstract: Security is essential for the Internet of Things (IoT). Cryptographic operations for authentication and encryption commonly rely on random input of high entropy and secure, tamper-resistant identities, which are difficult to obtain on con... | [
21954,
31965
] | Train |
28,070 | 27 | Title: Exploiting Redundancy for UWB Anomaly Detection in Infrastructure-Free Multi-Robot Relative Localization
Abstract: Ultra-wideband (UWB) localization methods have emerged as a cost-effective and accurate solution for GNSS-denied environments. There is a significant amount of previous research in terms of resilien... | [
2621
] | Test |
28,071 | 16 | Title: ADDSL: Hand Gesture Detection and Sign Language Recognition on Annotated Danish Sign Language
Abstract: For a long time, detecting hand gestures and recognizing them as letters or numbers has been a challenging task. This creates communication barriers for individuals with disabilities. This paper introduces a n... | [] | Train |
28,072 | 24 | Title: Learning Vortex Dynamics for Fluid Inference and Prediction
Abstract: We propose a novel differentiable vortex particle (DVP) method to infer and predict fluid dynamics from a single video. Lying at its core is a particle-based latent space to encapsulate the hidden, Lagrangian vortical evolution underpinning th... | [] | Validation |
28,073 | 6 | Title: A Case for VR Briefings: Comparing Communication in Daily Audio and VR Mission Control in a Simulated Lunar Mission
Abstract: Alpha-XR Mission conducted by XR Lab PJAIT focused on research related to individual and crew well-being and participatory team collaboration in ICE (isolated, confined and extreme) condi... | [] | Train |
28,074 | 6 | Title: Altruistic and Profit-oriented: Making Sense of Roles in Web3 Community from Airdrop Perspective
Abstract: Regardless of which community, incentivizing users is a necessity for well-sustainable operations. In the blockchain-backed Web3 communities, known for their transparency and security, airdrop serves as a w... | [
12723
] | Validation |
28,075 | 16 | Title: AICT: An Adaptive Image Compression Transformer
Abstract: Motivated by the efficiency investigation of the Tranformer-based transform coding framework, namely SwinT-ChARM, we propose to enhance the latter, as first, with a more straightforward yet effective Tranformer-based channel-wise auto-regressive prior mod... | [] | Test |
28,076 | 16 | Title: Distributional Modeling for Location-Aware Adversarial Patches
Abstract: Adversarial patch is one of the important forms of performing adversarial attacks in the physical world. To improve the naturalness and aggressiveness of existing adversarial patches, location-aware patches are proposed, where the patch's l... | [
8586
] | Validation |
28,077 | 24 | Title: When Fair Classification Meets Noisy Protected Attributes
Abstract: The operationalization of algorithmic fairness comes with several practical challenges, not the least of which is the availability or reliability of protected attributes in datasets. In real-world contexts, practical and legal impediments may pr... | [] | Test |
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