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
31,578	30	Title: The 2022 n2c2/UW Shared Task on Extracting Social Determinants of Health Abstract: OBJECTIVE The n2c2/UW SDOH Challenge explores the extraction of social determinant of health (SDOH) information from clinical notes. The objectives include the advancement of natural language processing (NLP) information extractio...	[ 42060, 23421, 38454 ]	Test
31,579	4	Title: Earn While You Reveal: Private Set Intersection that Rewards Participants Abstract: In Private Set Intersection protocols (PSIs), a non-empty result always reveals something about the private input sets of the parties. Moreover, in various variants of PSI, not all parties necessarily receive or are interested in...	[]	Train
31,580	24	Title: Understanding the effect of varying amounts of replay per step Abstract: Model-based reinforcement learning uses models to plan, where the predictions and policies of an agent can be improved by using more computation without additional data from the environment, thereby improving sample efficiency. However, lea...	[]	Train
31,581	5	Title: ParaGraph: Weighted Graph Representation for Performance Optimization of HPC Kernels Abstract: GPU-based HPC clusters are attracting more scientific application developers due to their extensive parallelism and energy efficiency. In order to achieve portability among a variety of multi/many core architectures, a...	[ 18898, 6978 ]	Train
31,582	6	Title: Legal Obligation and Ethical Best Practice: Towards Meaningful Verbal Consent for Voice Assistants Abstract: To improve user experience, Alexa now allows users to consent to data sharing via voice rather than directing them to the companion smartphone app. While verbal consent mechanisms for voice assistants (VA...	[]	Validation
31,583	30	Title: Unleashing the Power of User Reviews: Exploring Airline Choices at Catania Airport, Italy Abstract: This study aims to investigate the possible relationship between the mechanisms of social influence and the choice of airline, through the use of new tools, with the aim of understanding whether they can contribut...	[]	Train
31,584	24	Title: Data-Based Design of Multi-Model Inferential Sensors Abstract: nan	[ 29610 ]	Train
31,585	24	Title: Bayesian Safety Validation for Black-Box Systems Abstract: Accurately estimating the probability of failure for safety-critical systems is important for certification. Estimation is often challenging due to high-dimensional input spaces, dangerous test scenarios, and computationally expensive simulators; thus, e...	[ 4647 ]	Test
31,586	16	Title: PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification Abstract: Existing approaches to system identification (estimating the physical parameters of an object) from videos assume known object geometries. This precludes their applicability in a vast majority of sc...	[ 37769, 34157, 19118 ]	Validation
31,587	24	Title: Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap Abstract: We show that convex-concave Lipschitz stochastic saddle point problems (also known as stochastic minimax optimization) can be solved under the constraint of $(\epsilon,\delta)$-differential p...	[]	Validation
31,588	16	Title: SDDM: Score-Decomposed Diffusion Models on Manifolds for Unpaired Image-to-Image Translation Abstract: Recent score-based diffusion models (SBDMs) show promising results in unpaired image-to-image translation (I2I). However, existing methods, either energy-based or statistically-based, provide no explicit form o...	[ 22995 ]	Test
31,589	24	Title: Bayesian Free Energy of Deep ReLU Neural Network in Overparametrized Cases Abstract: In many research fields in artificial intelligence, it has been shown that deep neural networks are useful to estimate unknown functions on high dimensional input spaces. However, their generalization performance is not yet comp...	[ 6639 ]	Validation
31,590	25	Title: Masked Autoencoders with Multi-Window Attention Are Better Audio Learners Abstract: Several recent works have adapted Masked Autoencoders (MAEs) for learning general-purpose audio representations. However, they do not address two key aspects of modelling multi-domain audio data: (i) real-world audio tasks consis...	[]	Train
31,591	6	Title: Artistic Strategies to Guide Neural Networks Abstract: Artificial Intelligence is present in the generation and distribution of culture. How do artists exploit neural networks? What impact do these algorithms have on artistic practice? Through a practice-based research methodology, this paper explores the potent...	[]	Validation
31,592	30	Title: Rediscovering Hashed Random Projections for Efficient Quantization of Contextualized Sentence Embeddings Abstract: Training and inference on edge devices often requires an efficient setup due to computational limitations. While pre-computing data representations and caching them on a server can mitigate extensiv...	[]	Train
31,593	24	Title: A Novel Method Combines Moving Fronts, Data Decomposition and Deep Learning to Forecast Intricate Time Series Abstract: A univariate time series with high variability can pose a challenge even to Deep Neural Network (DNN). To overcome this, a univariate time series is decomposed into simpler constituent series, ...	[]	Train
31,594	30	Title: Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection Abstract: This paper investigates the effectiveness of large language models (LLMs) in email spam detection by comparing prominent models from three distinct families: BERT-like, Sentence Transformers, and Seq2Seq. Additionally, we exa...	[]	Validation
31,595	24	Title: Loss and Reward Weighing for increased learning in Distributed Reinforcement Learning Abstract: This paper introduces two learning schemes for distributed agents in Reinforcement Learning (RL) environments, namely Reward-Weighted (R-Weighted) and Loss-Weighted (L-Weighted) gradient merger. The R/L weighted metho...	[]	Train
31,596	24	Title: Source Free Domain Adaptation of a DNN for SSVEP-based Brain-Computer Interfaces Abstract: This paper presents a source free domain adaptation method for steady-state visually evoked potential (SSVEP) based brain-computer interface (BCI) spellers. SSVEP-based BCI spellers help individuals experiencing speech dif...	[ 26803 ]	Train
31,597	27	Title: Nonlinear Controller Design for a Quadrotor with Inverted Pendulum Abstract: The quadrotor is a $6$ degrees-of-freedom (DoF) system with underactuation. Adding a spherical pendulum on top of a quadrotor further complicates the task of achieving any output tracking while stabilizing the rest. In this report, we p...	[]	Train
31,598	24	Title: Fourier Neural Operator Surrogate Model to Predict 3D Seismic Waves Propagation Abstract: With the recent rise of neural operators, scientific machine learning offers new solutions to quantify uncertainties associated with high-fidelity numerical simulations. Traditional neural networks, such as Convolutional Ne...	[ 13424 ]	Train
31,599	16	Title: Realistic Full-Body Tracking from Sparse Observations via Joint-Level Modeling Abstract: To bridge the physical and virtual worlds for rapidly developed VR/AR applications, the ability to realistically drive 3D full-body avatars is of great significance. Although real-time body tracking with only the head-mounte...	[]	Test
31,600	16	Title: Person Re-Identification without Identification via Event Anonymization Abstract: Wide-scale use of visual surveillance in public spaces puts individual privacy at stake while increasing resource consumption (energy, bandwidth, and computation). Neuromorphic vision sensors (event-cameras) have been recently cons...	[ 14441 ]	Test
31,601	2	Title: Synthesising Recursive Functions for First-Order Model Counting: Challenges, Progress, and Conjectures Abstract: First-order model counting (FOMC) is a computational problem that asks to count the models of a sentence in finite-domain first-order logic. In this paper, we argue that the capabilities of FOMC algor...	[]	Train
31,602	16	Title: Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art History Abstract: Throughout the history of art, the pose—as the holistic abstraction of the human body’s expression—has proven to be a constant in numerous studies. However, due to the enormous amount of data that so far had to be proce...	[]	Train
31,603	30	Title: INK: Injecting kNN Knowledge in Nearest Neighbor Machine Translation Abstract: Neural machine translation has achieved promising results on many translation tasks. However, previous studies have shown that neural models induce a non-smooth representation space, which harms its generalization results. Recently, k...	[]	Train
31,604	30	Title: Linear Classifier: An Often-Forgotten Baseline for Text Classification Abstract: Large-scale pre-trained language models such as BERT are popular solutions for text classification.Due to the superior performance of these advanced methods, nowadays, people often directly train them for a few epochs and deploy the...	[]	Test
31,605	16	Title: A Simple Baseline for Supervised Surround-view Depth Estimation Abstract: Depth estimation has been widely studied and serves as the fundamental step of 3D perception for autonomous driving. Though significant progress has been made for monocular depth estimation in the past decades, these attempts are mainly co...	[ 39577, 3938 ]	Train
31,606	24	Title: Fast and Robust State Estimation and Tracking via Hierarchical Learning Abstract: Fully distributed estimation and tracking solutions to large-scale multi-agent networks suffer slow convergence and are vulnerable to network failures. In this paper, we aim to speed up the convergence and enhance the resilience of...	[]	Validation
31,607	37	Title: WiscSort: External Sorting For Byte-Addressable Storage Abstract: We present WiscSort, a new approach to high-performance concurrent sorting for existing and future byte-addressable storage (BAS) devices. WiscSort carefully reduces writes, exploits random reads by splitting keys and values during sorting, and ...	[]	Train
31,608	24	Title: Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization Abstract: In this paper, we propose REASON, a novel framework that enables the automatic discovery of both intra-level (i.e., within-network) and inter-level (i.e., across-network) causal relationships for root cause localization...	[ 18232, 22232 ]	Train
31,609	5	Title: MadEye: Boosting Live Video Analytics Accuracy with Adaptive Camera Configurations Abstract: Camera orientations (i.e., rotation and zoom) govern the content that a camera captures in a given scene, which in turn heavily influences the accuracy of live video analytics pipelines. However, existing analytics appro...	[]	Test
31,610	30	Title: Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos Abstract: To realize human-robot collaboration, robots need to execute actions for new tasks according to human instructions given finite prior knowledge. Human experts can share their knowledge of ...	[]	Train
31,611	6	Title: Towards User-Centric Guidelines for Chatbot Conversational Design Abstract: The conversational nature of chatbots poses challenges to designers since their development is different from other software and requires investigating new practices in the context of human-AI interaction and their impact on user experie...	[]	Train
31,612	30	Title: ClArTTS: An Open-Source Classical Arabic Text-to-Speech Corpus Abstract: At present, Text-to-speech (TTS) systems that are trained with high-quality transcribed speech data using end-to-end neural models can generate speech that is intelligible, natural, and closely resembles human speech. These models are train...	[ 1090 ]	Test
31,613	30	Title: AxomiyaBERTa: A Phonologically-aware Transformer Model for Assamese Abstract: Despite their successes in NLP, Transformer-based language models still require extensive computing resources and suffer in low-resource or low-compute settings. In this paper, we present AxomiyaBERTa, a novel BERT model for Assamese, ...	[ 31259 ]	Test
31,614	30	Title: Text vectorization via transformer-based language models and n-gram perplexities Abstract: As the probability (and thus perplexity) of a text is calculated based on the product of the probabilities of individual tokens, it may happen that one unlikely token significantly reduces the probability (i.e., increase t...	[]	Test
31,615	24	Title: Circumventing Concept Erasure Methods For Text-to-Image Generative Models Abstract: Text-to-image generative models can produce photo-realistic images for an extremely broad range of concepts, and their usage has proliferated widely among the general public. On the flip side, these models have numerous drawbacks...	[]	Train
31,616	26	Title: Reviewing War: Unconventional User Reviews as a Side Channel to Circumvent Information Controls Abstract: During the first days of the 2022 Russian invasion of Ukraine, Russia's media regulator blocked access to many global social media platforms and news sites, including Twitter, Facebook, and the BBC. To bypas...	[]	Train
31,617	16	Title: Generative Prompt Model for Weakly Supervised Object Localization Abstract: Weakly supervised object localization (WSOL) remains challenging when learning object localization models from image category labels. Conventional methods that discriminatively train activation models ignore representative yet less discr...	[ 12177, 30922, 42221 ]	Train
31,618	24	Title: Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift Abstract: Bayesian deep learning (BDL) is a promising approach to achieve well-calibrated predictions on distribution-shifted data. Nevertheless, there exists no large-scale survey that evaluates recent SOTA method...	[]	Validation
31,619	24	Title: FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning Abstract: LLMs have demonstrated great capabilities in various NLP tasks. Different entities can further improve the performance of those LLMs on their specific downstream tasks by fine-tuning LLMs. When sever...	[ 40192, 30243, 13700, 33220, 14920, 35224, 3609, 9499, 13564 ]	Test
31,620	16	Title: Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature Abstract: Visual Question Answering (VQA) is an emerging area of interest for researches, being a recent problem in natural language processing and image prediction. In this area, an algorithm needs to answer questions about...	[]	Train
31,621	8	Title: Deadline Aware Two-Timescale Resource Allocation for VR Video Streaming Abstract: In this paper, we investigate resource allocation problem in the context of multiple virtual reality (VR) video flows sharing a certain link, considering specific deadline of each video frame and the impact of different frames on v...	[]	Train
31,622	16	Title: Collision Avoidance Detour for Multi-Agent Trajectory Forecasting Abstract: We present our approach, Collision Avoidance Detour (CAD), which won the 3rd place award in the 2023 Waymo Open Dataset Challenge - Sim Agents, held at the 2023 CVPR Workshop on Autonomous Driving. To satisfy the motion prediction factor...	[]	Train
31,623	24	Title: Machine learning for potion development at Hogwarts Abstract: Objective: To determine whether machine learning methods can generate useful potion recipes for research and teaching at Hogwarts School of Witchcraft and Wizardry. Design: Using deep neural networks to classify generated recipes into a standard drug ...	[]	Validation
31,624	25	Title: Cross-modal Audio-visual Co-learning for Text-independent Speaker Verification Abstract: Visual speech (i.e., lip motion) is highly related to auditory speech due to the co-occurrence and synchronization in speech production. This paper investigates this correlation and proposes a cross-modal speech co-learning ...	[]	Train
31,625	16	Title: Multiscale Global and Regional Feature Learning Using Co-Tuplet Loss for Offline Handwritten Signature Verification Abstract: Handwritten signature verification is a significant biometric verification method widely acknowledged by legal and financial institutions. However, the development of automatic signature ...	[]	Train
31,626	24	Title: AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network Abstract: Many real-world data can be modeled as heterogeneous graphs that contain multiple types of nodes and edges. Meanwhile, due to excellent performance, heterogeneous graph neural networks (GNNs) have received more and mo...	[]	Train
31,627	16	Title: Simple Parameter-free Self-attention Approximation Abstract: The hybrid model of self-attention and convolution is one of the methods to lighten ViT. The quadratic computational complexity of self-attention with respect to token length limits the efficiency of ViT on edge devices. We propose a self-attention app...	[]	Validation
31,628	27	Title: An Active Learning Based Robot Kinematic Calibration Framework Using Gaussian Processes Abstract: Future NASA lander missions to icy moons will require completely automated, accurate, and data efficient calibration methods for the robot manipulator arms that sample icy terrains in the lander's vicinity. To suppo...	[]	Validation
31,629	16	Title: Test-time Detection and Repair of Adversarial Samples via Masked Autoencoder Abstract: Training-time defenses, known as adversarial training, incur high training costs and do not generalize to unseen attacks. Test-time defenses solve these issues but most existing test-time defenses require adapting the model we...	[ 26113 ]	Validation
31,630	23	Title: Benchmarking Robustness of AI-enabled Multi-sensor Fusion Systems: Challenges and Opportunities Abstract: Multi-Sensor Fusion (MSF) based perception systems have been the foundation in supporting many industrial applications and domains, such as self-driving cars, robotic arms, and unmanned aerial vehicles. Over...	[]	Validation
31,631	31	Title: Representation Sparsification with Hybrid Thresholding for Fast SPLADE-based Document Retrieval Abstract: Learned sparse document representations using a transformer-based neural model has been found to be attractive in both relevance effectiveness and time efficiency. This paper describes a representation spars...	[ 39821 ]	Train
31,632	16	Title: FSNet: Redesign Self-Supervised MonoDepth for Full-Scale Depth Prediction for Autonomous Driving Abstract: Predicting accurate depth with monocular images is important for low-cost robotic applications and autonomous driving. This study proposes a comprehensive self-supervised framework for accurate scale-aware ...	[]	Test
31,633	30	Title: A Cheaper and Better Diffusion Language Model with Soft-Masked Noise Abstract: Diffusion models that are based on iterative denoising have been recently proposed and leveraged in various generation tasks like image generation. Whereas, as a way inherently built for continuous data, existing diffusion models stil...	[ 23120, 8939, 10317 ]	Test
31,634	16	Title: CLUSTSEG: Clustering for Universal Segmentation Abstract: We present CLUSTSEG, a general, transformer-based framework that tackles different image segmentation tasks (i.e., superpixel, semantic, instance, and panoptic) through a unified neural clustering scheme. Regarding queries as cluster centers, CLUSTSEG is ...	[ 5921, 21058, 43042, 27405, 37038, 29585, 41109, 27032, 12286 ]	Validation
31,635	27	Title: Estimation and early prediction of grip force based on sEMG signals and deep recurrent neural networks Abstract: nan	[]	Train
31,636	10	Title: Chebyshev Particles Abstract: Markov chain Monte Carlo (MCMC) provides a feasible method for inferring Hidden Markov models, however, it is often computationally prohibitive, especially constrained by the curse of dimensionality, as the Monte Carlo sampler traverses randomly taking small steps within uncertain r...	[]	Validation
31,637	22	Title: Demonstrating (Hybrid) Active Logic Documents and the Ciao Prolog Playground, and an Application to Verification Tutorials Abstract: Active Logic Documents (ALD) are web pages which incorporate embedded Prolog engines that run locally within the browser. ALD offers both a very easy way to add click-to-run capabi...	[]	Test
31,638	27	Title: Addressing Non-IID Problem in Federated Autonomous Driving with Contrastive Divergence Loss Abstract: Federated learning has been widely applied in autonomous driving since it enables training a learning model among vehicles without sharing users' data. However, data from autonomous vehicles usually suffer from ...	[ 834, 45031 ]	Train
31,639	2	Title: Craig Interpolation for Guarded Fragments Abstract: We show that the guarded-negation fragment (GNFO) is, in a precise sense, the smallest extension of the guarded fragment (GFO) with Craig interpolation. In contrast, %we show that the smallest extension of the two-variable fragment (FO2) with Craig interpolatio...	[]	Train
31,640	16	Title: MultiScale Probability Map guided Index Pooling with Attention-based learning for Road and Building Segmentation Abstract: Efficient road and building footprint extraction from satellite images are predominant in many remote sensing applications. However, precise segmentation map extraction is quite challenging ...	[]	Train
31,641	4	Title: DAXiot: A Decentralized Authentication and Authorization Scheme for Dynamic IoT Networks Abstract: Federated and decentralized networks supporting frequently changing system participants are a requirement for future Internet of Things (IoT) use cases. IoT devices and networks often lack adequate authentication a...	[]	Train
31,642	27	Title: Autonomous Search of Semantic Objects in Unknown Environments Abstract: This paper addresses the problem of enabling a robot to search for a semantic object in an unknown and GPS-denied environment. For the robot in the unknown environment to detect and find the target object, it must perform simultaneous locali...	[ 16503 ]	Train
31,643	4	Title: Vulnerabilities in AI Code Generators: Exploring Targeted Data Poisoning Attacks Abstract: In this work, we assess the security of AI code generators via data poisoning, i.e., an attack that injects malicious samples into the training data to generate vulnerable code. We poison the training data by injecting inc...	[ 43714, 12170, 2219, 2510, 31153, 33490, 6328, 42649 ]	Train
31,644	24	Title: Global-QSGD: Practical Floatless Quantization for Distributed Learning with Theoretical Guarantees Abstract: Efficient distributed training is a principal driver of recent advances in deep learning. However, communication often proves costly and becomes the primary bottleneck in these systems. As a result, there...	[]	Test
31,645	23	Title: Characterizing and Detecting WebAssembly Runtime Bugs Abstract: WebAssembly (abbreviated WASM) has emerged as a promising language of the Web and also been used for a wide spectrum of software applications such as mobile applications and desktop applications. These applications, named as WASM applications, commo...	[ 1774 ]	Train
31,646	8	Title: ns-O-RAN: Simulating O-RAN 5G Systems in ns-3 Abstract: O-RAN is radically shifting how cellular networks are designed, deployed and optimized through network programmability, disaggregation, and virtualization. Specifically, RAN Intelligent Controllers (RICs) can orchestrate and optimize the Radio Access Networ...	[]	Test
31,647	30	Title: UnScientify: Detecting Scientific Uncertainty in Scholarly Full Text Abstract: This demo paper presents UnScientify, an interactive system designed to detect scientific uncertainty in scholarly full text. The system utilizes a weakly supervised technique that employs a fine-grained annotation scheme to identify ...	[]	Validation
31,648	30	Title: Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline Abstract: Large language models (LLMs) have revolutionized the field of AI, demonstrating unprecedented capacity across various tasks. However, the inference process for LLMs comes with significant computational costs. In...	[ 13700, 35117, 12015, 28151, 40953, 38780, 40413 ]	Train
31,649	24	Title: Mean Field Theory in Deep Metric Learning Abstract: In this paper, we explore the application of mean field theory, a technique from statistical physics, to deep metric learning and address the high training complexity commonly associated with conventional metric learning loss functions. By adapting mean field t...	[]	Test
31,650	24	Title: Predicting malaria dynamics in Burundi using deep Learning Models Abstract: Malaria continues to be a major public health problem on the African continent, particularly in Sub-Saharan Africa. Nonetheless, efforts are ongoing, and significant progress has been made. In Burundi, malaria is among the main public he...	[]	Validation
31,651	4	Title: Schooling to Exploit Foolish Contracts Abstract: We introduce SCooLS, our Smart Contract Learning (Semi-supervised) engine. SCooLS uses neural networks to analyze Ethereum contract bytecode and identifies specific vulnerable functions. SCooLS incorporates two key elements: semi-supervised learning and graph neur...	[ 4820 ]	Train
31,652	23	Title: Evaluating AIGC Detectors on Code Content Abstract: Artificial Intelligence Generated Content (AIGC) has garnered considerable attention for its impressive performance, with ChatGPT emerging as a leading AIGC model that produces high-quality responses across various applications, including software development a...	[ 13224, 25227, 43930, 38235, 35580 ]	Train
31,653	30	Title: Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models Abstract: Considerable research efforts have been devoted to ensuring that large language models (LLMs) align with human values and generate safe text. However, an excessive focus on sensitivity to certain top...	[ 35170, 13510, 17606, 14536, 45821, 18764, 36911, 10800, 8853, 729, 10749 ]	Train
31,654	23	Title: Personalized First Issue Recommender for Newcomers in Open Source Projects Abstract: Many open source projects provide good first issues (GFIs) to attract and retain newcomers. Although several automated GFI recommenders have been proposed, existing recommenders are limited to recommending generic GFIs without c...	[ 44400, 33773 ]	Train
31,655	16	Title: Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving Abstract: Deep neural networks (DNNs) have proven their capabilities in the past years and play a significant role in environment perception for the challenging application of automated driving. They are...	[ 6275, 44670 ]	Validation
31,656	31	Title: Evolution of the online rating platform data structures and its implications for recommender systems Abstract: Online rating platform represents the new trend of online cultural and commercial goods consumption. The user rating data on such platforms are foods for recommender system algorithms. Understanding the...	[ 14763 ]	Test
31,657	16	Title: Large-scale Detection of Marine Debris in Coastal Areas with Sentinel-2 Abstract: Detecting and quantifying marine pollution and macro-plastics is an increasingly pressing ecological issue that directly impacts ecology and human health. Efforts to quantify marine pollution are often conducted with sparse and exp...	[]	Train
31,658	10	Title: FastDiagP: An Algorithm for Parallelized Direct Diagnosis Abstract: Constraint-based applications attempt to identify a solution that meets all defined user requirements. If the requirements are inconsistent with the underlying constraint set, algorithms that compute diagnoses for inconsistent constraints should...	[]	Train
31,659	2	Title: A Symbolic Algorithm for the Case-Split Rule in Solving Word Constraints with Extensions (Technical Report) Abstract: Case split is a core proof rule in current decision procedures for the theory of string constraints. Its use is the primary cause of the state space explosion in string constraint solving, since ...	[]	Train
31,660	23	Title: U Owns the Code That Changes and How Marginal Owners Resolve Issues Slower in Low-Quality Source Code Abstract: [Context] Accurate time estimation is a critical aspect of predictable software engineering. Previous work shows that low source code quality increases the uncertainty in issue resolution times. [Objec...	[]	Train
31,661	38	Title: Who should I Collaborate with? A Comparative Study of Academia and Industry Research Collaboration in NLP Abstract: The goal of our research was to investigate the effects of collaboration between academia and industry on Natural Language Processing (NLP). To do this, we created a pipeline to extract affiliation...	[]	Train
31,662	30	Title: DUMB: A Benchmark for Smart Evaluation of Dutch Models Abstract: We introduce the Dutch Model Benchmark: DUMB. The benchmark includes a diverse set of datasets for low-, medium- and high-resource tasks. The total set of eight tasks include three tasks that were previously not available in Dutch. Instead of relyi...	[]	Test
31,663	30	Title: Text Encoders Lack Knowledge: Leveraging Generative LLMs for Domain-Specific Semantic Textual Similarity Abstract: Amidst the sharp rise in the evaluation of large language models (LLMs) on various tasks, we find that semantic textual similarity (STS) has been under-explored. In this study, we show that STS can ...	[ 6744, 15049, 43641, 35388 ]	Validation
31,664	16	Title: You Only Need One Thing One Click: Self-Training for Weakly Supervised 3D Scene Understanding Abstract: 3D scene understanding, e.g., point cloud semantic and instance segmentation, often requires large-scale annotated training data, but clearly, point-wise labels are too tedious to prepare. While some recent me...	[]	Validation
31,665	27	Title: Development of a Voice Controlled Robotic Arm Abstract: This paper describes a robotic arm with 5 degrees-of-freedom (DOF) which is controlled by human voice and has been developed in the Mechatronics Laboratory, CUET. This robotic arm is interfaced with a PC by serial communication (RS-232). Users' voice comman...	[]	Train
31,666	30	Title: MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain Abstract: This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million German medical documents and has been shown to achieve new...	[ 21574, 23127 ]	Test
31,667	6	Title: Characterizing Usability Issue Discussions in OSS Projects Abstract: Usability is a crucial factor but one of the most neglected concerns in open source software (OSS). While far from an ideal approach, a common practice that OSS communities adopt to collaboratively address usability is through discussions on is...	[]	Validation
31,668	16	Title: SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs Abstract: In this work, we introduce Semantic Pyramid AutoEncoder (SPAE) for enabling frozen LLMs to perform both understanding and generation tasks involving non-linguistic modalities such as images or videos. SPAE converts between ra...	[ 33220, 29396, 19509, 28532, 3609, 11229 ]	Test
31,669	16	Title: General-Purpose Multi-Modal OOD Detection Framework Abstract: Out-of-distribution (OOD) detection identifies test samples that differ from the training data, which is critical to ensuring the safety and reliability of machine learning (ML) systems. While a plethora of methods have been developed to detect uni-mo...	[]	Train
31,670	24	Title: Personalized Event Prediction for Electronic Health Records Abstract: nan	[]	Train
31,671	23	Title: On the Suitability of Hugging Face Hub for Empirical Studies Abstract: Background. The development of empirical studies in software engineering mainly relies on the data available on code hosting platforms, being GitHub the most representative. Nevertheless, in the last years, the emergence of Machine Learning (...	[]	Train
31,672	24	Title: Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker Abstract: Finding classifiers robust to adversarial examples is critical for their safe deployment. Determining the robustness of the best possible classifier under a given threat model for a given data distribution and ...	[]	Train
31,673	31	Title: An OPC UA-based industrial Big Data architecture Abstract: Industry 4.0 factories are complex and data-driven. Data is yielded from many sources, including sensors, PLCs, and other devices, but also from IT, like ERP or CRM systems. We ask how to collect and process this data in a way, such that it includes meta...	[]	Train
31,674	8	Title: Adaptive Scheduling for Edge-Assisted DNN Serving Abstract: Deep neural networks (DNNs) have been widely used in various video analytic tasks. These tasks demand real-time responses. Due to the limited processing power on mobile devices, a common way to support such real-time analytics is to offload the processi...	[]	Train
31,675	24	Title: Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds Abstract: The privacy preserving properties of Langevin dynamics with additive isotropic noise have been extensively studied. However, the isotropic noise assumption is very restrictive: (a) when adding noise to existing learning algori...	[]	Validation
31,676	28	Title: A Gaussian Copula Approach to the Performance Analysis of Fluid Antenna Systems Abstract: This paper investigates the performance of a singleuser fluid antenna system (FAS), by exploiting a class of elliptical copulas to describe the structure of dependency amongst the fluid antenna ports. By expressing Jakes' m...	[ 14765 ]	Train
31,677	13	Title: Modularizing and Assembling Cognitive Map Learners via Hyperdimensional Computing Abstract: Biological organisms must learn how to control their own bodies to achieve deliberate locomotion, that is, predict their next body position based on their current position and selected action. Such learning is goal-agnost...	[]	Train

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.