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
29,078	20	Title: Kernelization for Spreading Points Abstract: We consider the following problem about dispersing points. Given a set of points in the plane, the task is to identify whether by moving a small number of points by small distance, we can obtain an arrangement of points such that no pair of points is ``close"to each o...	[]	Train
29,079	24	Title: Speeding up Fourier Neural Operators via Mixed Precision Abstract: The Fourier neural operator (FNO) is a powerful technique for learning surrogate maps for partial differential equation (PDE) solution operators. For many real-world applications, which often require high-resolution data points, training time and...	[ 11681, 878 ]	Train
29,080	27	Title: Learning Pedestrian Actions to Ensure Safe Autonomous Driving Abstract: To ensure safe autonomous driving in urban environments with complex vehicle-pedestrian interactions, it is critical for Autonomous Vehicles (AVs) to have the ability to predict pedestrians’ short-term and immediate actions in real-time. In ...	[]	Train
29,081	16	Title: Domain Reduction Strategy for Non Line of Sight Imaging Abstract: This paper presents a novel optimization-based method for non-line-of-sight (NLOS) imaging that aims to reconstruct hidden scenes under various setups. Our method is built upon the observation that photons returning from each point in hidden volum...	[]	Test
29,082	24	Title: Generative Diffusions in Augmented Spaces: A Complete Recipe Abstract: Score-based Generative Models (SGMs) have achieved state-of-the-art synthesis results on diverse tasks. However, the current design space of the forward diffusion process is largely unexplored and often relies on physical intuition or simplif...	[ 43955 ]	Test
29,083	24	Title: Sparse Partitioning Around Medoids Abstract: Hierarchical Agglomerative Clustering (HAC) is likely the earliest and most flexible clustering method, because it can be used with many distances, similarities, and various linkage strategies. It is often used when the number of clusters the data set forms is unknown...	[]	Train
29,084	27	Title: A Universal Semantic-Geometric Representation for Robotic Manipulation Abstract: Robots rely heavily on sensors, especially RGB and depth cameras, to perceive and interact with the world. RGB cameras record 2D images with rich semantic information while missing precise spatial information. On the other side, dep...	[ 4385, 34215, 19271, 23385, 6042 ]	Train
29,085	23	Title: A Requirements-Driven Platform for Validating Field Operations of Small Uncrewed Aerial Vehicles Abstract: Flight-time failures of small Uncrewed Aerial Systems (sUAS) can have a severe impact on people or the environment. Therefore, sUAS applications must be thoroughly evaluated and tested to ensure their adher...	[]	Train
29,086	24	Title: Multi-Start Team Orienteering Problem for UAS Mission Re-Planning with Data-Efficient Deep Reinforcement Learning Abstract: In this paper, we study the Multi-Start Team Orienteering Problem (MSTOP), a mission re-planning problem where vehicles are initially located away from the depot and have different amounts ...	[]	Test
29,087	24	Title: Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery Abstract: The strength of modern generative models lies in their ability to be controlled through text-based prompts. Typical"hard"prompts are made from interpretable words and tokens, and must be hand-crafted by humans....	[ 10252, 17295, 39439, 6801, 14610, 2168, 42020, 549, 45476, 34987, 27059, 44481, 33610, 3918, 16846, 18767, 30034, 30041, 34912, 29536, 1767, 17647, 20852, 14581, 17400, 1916 ]	Train
29,088	10	Title: Development of a Trust-Aware User Simulator for Statistical Proactive Dialog Modeling in Human-AI Teams Abstract: The concept of a Human-AI team has gained increasing attention in recent years. For effective collaboration between humans and AI teammates, proactivity is crucial for close coordination and effectiv...	[]	Train
29,089	24	Title: Solving Attention Kernel Regression Problem via Pre-conditioner Abstract: Large language models have shown impressive performance in many tasks. One of the major features from the computation perspective is computing the attention matrix. Previous works [Zandieh, Han, Daliri, and Karba 2023, Alman and Song 2023]...	[ 32416, 12898, 34404, 29739, 13100, 4909, 40301, 8436, 16949, 39573, 7767, 11128, 12825, 7643 ]	Train
29,090	23	Title: A Meta-Learning Approach for Software Refactoring Abstract: Software refactoring is the process of changing the structure of software without any alteration in its behavior and functionality. Presuming it is carried out in appropriate opportunities, refactoring enhances software quality characteristics such as m...	[]	Train
29,091	5	Title: Improving Blockchain Scalability with the Setchain Data-type Abstract: Blockchain technologies are facing a scalability challenge, which must be overcome to guarantee a wider adoption of the technology. This scalability issue is due to the use of consensus algorithms to guarantee the total order of the chain of ...	[]	Train
29,092	22	Title: Effect Handlers for Programmable Inference Abstract: Inference algorithms for probabilistic programming are complex imperative programs with many moving parts. Efficient inference often requires customising an algorithm to a particular probabilistic model or problem, sometimes called inference programming. Most ...	[]	Test
29,093	26	Title: Entity graphs for exploring online discourse Abstract: nan	[]	Validation
29,094	16	Title: GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models Abstract: This paper introduces GenCorres, a novel unsupervised joint shape matching (JSM) approach. The basic idea of GenCorres is to learn a parametric mesh generator to fit an unorganized deformable shape collection whi...	[]	Train
29,095	24	Title: Physics Informed Recurrent Neural Networks for Seismic Response Evaluation of Nonlinear Systems Abstract: Dynamic response evaluation in structural engineering is the process of determining the response of a structure, such as member forces, node displacements, etc when subjected to dynamic loads such as earthqu...	[]	Train
29,096	24	Title: Understanding Programs by Exploiting (Fuzzing) Test Cases Abstract: Semantic understanding of programs has attracted great attention in the community. Inspired by recent successes of large language models (LLMs) in natural language understanding, tremendous progress has been made by treating programming language...	[ 39826, 11190 ]	Train
29,097	4	Title: Optimizing Linear Correctors: A Tight Output Min-Entropy Bound and Selection Technique Abstract: Post-processing of the raw bits produced by a true random number generator (TRNG) is always necessary when the entropy per bit is insufficient for security applications. In this paper, we derive a tight bound on the ...	[]	Test
29,098	23	Title: Automate migration to microservices architecture using Machine Learning techniques Abstract: The microservice architectural style has many advantages such as scalability, reusability, and easy maintainability. Microservices have therefore become a popular architectural choice when developing new applications. Re...	[]	Test
29,099	24	Title: A Knowledge Graph Perspective on Supply Chain Resilience Abstract: Global crises and regulatory developments require increased supply chain transparency and resilience. Companies do not only need to react to a dynamic environment but have to act proactively and implement measures to prevent production delays and...	[]	Train
29,100	30	Title: nanoT5: A PyTorch Framework for Pre-training and Fine-tuning T5-style Models with Limited Resources Abstract: State-of-the-art language models like T5 have revolutionized the NLP landscape, but their computational demands hinder a large portion of the research community. To address this challenge, we present nan...	[ 39628, 5447 ]	Validation
29,101	16	Title: Towards Continual Egocentric Activity Recognition: A Multi-modal Egocentric Activity Dataset for Continual Learning Abstract: With the rapid development of wearable cameras, a massive collection of egocentric video for first-person visual perception becomes available. Using egocentric videos to predict first-per...	[ 38937 ]	Train
29,102	24	Title: FedEBA+: Towards Fair and Effective Federated Learning via Entropy-Based Model Abstract: Ensuring fairness is a crucial aspect of Federated Learning (FL), which enables the model to perform consistently across all clients. However, designing an FL algorithm that simultaneously improves global model performance a...	[ 24485 ]	Train
29,103	4	Title: Privacy Amplification via Importance Sampling Abstract: We examine the privacy-enhancing properties of subsampling a data set via importance sampling as a pre-processing step for differentially private mechanisms. This extends the established privacy amplification by subsampling result to importance sampling whe...	[]	Test
29,104	28	Title: Reversible cyclic codes over finite chain rings Abstract: In this paper, necessary and sufficient conditions for the reversibility of a cyclic code of arbitrary length over a finite commutative chain ring have been derived. MDS reversible cyclic codes having length p^s over a finite chain ring with nilpotency in...	[ 9122 ]	Train
29,105	38	Title: A Checklist to Publish Collections as Data in GLAM Institutions Abstract: Large-scale digitization in Galleries, Libraries, Archives and Museums (GLAM) created the conditions for providing access to collections as data. It opened new opportunities to explore, use and reuse digital collections. Strong proponents ...	[]	Validation
29,106	16	Title: Neural Field Conditioning Strategies for 2D Semantic Segmentation Abstract: Neural fields are neural networks which map coordinates to a desired signal. When a neural field should jointly model multiple signals, and not memorize only one, it needs to be conditioned on a latent code which describes the signal at ...	[]	Test
29,107	6	Title: Beyond Screens: Supporting Co-located Augmented Reality Experiences with Smart Home Devices Abstract: We introduce Spooky Spirits, an AR game that makes novel use of everyday smart home devices to support co-located play. Recent exploration of co-located AR experiences consists mainly of digital visual augmentat...	[]	Validation
29,108	10	Title: MLOps with enhanced performance control and observability Abstract: The explosion of data and its ever increasing complexity in the last few years, has made MLOps systems more prone to failure, and new tools need to be embedded in such systems to avoid such failure. In this demo, we will introduce crucial tools ...	[]	Test
29,109	31	Title: Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search? Abstract: Systematic reviews are comprehensive literature reviews for a highly focused research question. These reviews are considered the highest form of evidence in medicine. Complex Boolean queries are developed as part of the sys...	[ 45760, 37762, 23239, 40903, 16713, 11273, 1899, 30026, 27161, 43566, 25203, 35545, 30775, 17913, 3931, 4892, 44733 ]	Train
29,110	24	Title: Cooperative Multi-Agent Reinforcement Learning for Inventory Management Abstract: With Reinforcement Learning (RL) for inventory management (IM) being a nascent field of research, approaches tend to be limited to simple, linear environments with implementations that are minor modifications of off-the-shelf RL al...	[]	Validation
29,111	24	Title: FedExP: Speeding up Federated Averaging Via Extrapolation Abstract: Federated Averaging (FedAvg) remains the most popular algorithm for Federated Learning (FL) optimization due to its simple implementation, stateless nature, and privacy guarantees combined with secure aggregation. Recent work has sought to gener...	[ 26962, 1100, 19822, 2687 ]	Test
29,112	16	Title: Boosting Semantic Segmentation by Conditioning the Backbone with Semantic Boundaries Abstract: In this paper, we propose the Semantic-Boundary-Conditioned Backbone (SBCB) framework, an effective approach to enhancing semantic segmentation performance, particularly around mask boundaries, while maintaining compat...	[ 17633, 43394, 28141 ]	Validation
29,113	30	Title: The Pipeline System of ASR and NLU with MLM-based Data Augmentation toward STOP Low-resource Challenge Abstract: This paper describes our system for the low-resource domain adaptation track (Track 3) in Spoken Language Understanding Grand Challenge, which is a part of ICASSP Signal Processing Grand Challenge 202...	[]	Train
29,114	16	Title: SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution Detection Abstract: Building up reliable Out-of-Distribution (OOD) detectors is challenging, often requiring the use of OOD data during training. In this work, we develop a data-driven approach which is distinct and complementary to existing works:...	[]	Test
29,115	30	Title: Scaling Relationship on Learning Mathematical Reasoning with Large Language Models Abstract: Mathematical reasoning is a challenging task for large language models (LLMs), while the scaling relationship of it with respect to LLM capacity is under-explored. In this paper, we investigate how the pre-training loss,...	[ 3745, 40610, 13700, 15812, 21190, 38505, 22444, 25772, 40155, 6353, 43641, 4119, 29396, 35445, 9975, 22201, 1595 ]	Test
29,116	24	Title: Interpretable Outlier Summarization Abstract: Outlier detection is critical in real applications to prevent financial fraud, defend network intrusions, or detecting imminent device failures. To reduce the human effort in evaluating outlier detection results and effectively turn the outliers into actionable insig...	[]	Train
29,117	4	Title: McFIL: Model Counting Functionality-Inherent Leakage Abstract: Protecting the confidentiality of private data and using it for useful collaboration have long been at odds. Modern cryptography is bridging this gap through rapid growth in secure protocols such as multi-party computation, fully-homomorphic encrypti...	[]	Validation
29,118	24	Title: Planning with Sequence Models through Iterative Energy Minimization Abstract: Recent works have shown that sequence modeling can be effectively used to train reinforcement learning (RL) policies. However, the success of applying existing sequence models to planning, in which we wish to obtain a trajectory of act...	[ 40602, 35541 ]	Train
29,119	28	Title: Machine Learning-Aided Efficient Decoding of Reed–Muller Subcodes Abstract: Reed-Muller (RM) codes achieve the capacity of general binary-input memoryless symmetric channels and are conjectured to have a comparable performance to that of random codes in terms of scaling laws. However, such results are establishe...	[ 40649 ]	Train
29,120	7	Title: DOT: A flexible multi-objective optimization framework for transferring features across single-cell and spatial omics Abstract: Single-cell RNA sequencing (scRNA-seq) and spatially-resolved imaging/sequencing technologies have revolutionized biomedical research. On one hand, scRNA-seq provides information about ...	[]	Train
29,121	27	Title: Simulation-based Bayesian inference for robotic grasping Abstract: General robotic grippers are challenging to control because of their rich nonsmooth contact dynamics and the many sources of uncertainties due to the environment or sensor noise. In this work, we demonstrate how to compute 6-DoF grasp poses using...	[ 3200 ]	Test
29,122	23	Title: Fully Autonomous Programming with Large Language Models Abstract: Current approaches to program synthesis with Large Language Models (LLMs) exhibit a "near miss syndrome": they tend to generate programs that semantically resemble the correct answer (as measured by text similarity metrics or human evaluation), bu...	[ 12107, 25227, 29781 ]	Test
29,123	24	Title: Evaluation of self-supervised pre-training for automatic infant movement classification using wearable movement sensors Abstract: The recently-developed infant wearable MAIJU provides a means to automatically evaluate infants' motor performance in an objective and scalable manner in out-of-hospital settings. Thi...	[]	Validation
29,124	6	Title: Continuous Reinforcement Learning-based Dynamic Difficulty Adjustment in a Visual Working Memory Game Abstract: Dynamic Difficulty Adjustment (DDA) is a viable approach to enhance a player's experience in video games. Recently, Reinforcement Learning (RL) methods have been employed for DDA in non-competitive gam...	[]	Validation
29,125	16	Title: ProbVLM: Probabilistic Adapter for Frozen Vison-Language Models Abstract: Large-scale vision-language models (VLMs) like CLIP successfully find correspondences between images and text. Through the standard deterministic mapping process, an image or a text sample is mapped to a single vector in the embedding spac...	[ 10624, 30914, 1875 ]	Train
29,126	24	Title: Improved Online Conformal Prediction via Strongly Adaptive Online Learning Abstract: We study the problem of uncertainty quantification via prediction sets, in an online setting where the data distribution may vary arbitrarily over time. Recent work develops online conformal prediction techniques that leverage r...	[ 99, 3500 ]	Train
29,127	10	Title: Fact-Checking of AI-Generated Reports Abstract: With advances in generative artificial intelligence (AI), it is now possible to produce realistic-looking automated reports for preliminary reads of radiology images. This can expedite clinical workflows, improve accuracy and reduce overall costs. However, it is al...	[ 38102 ]	Test
29,128	16	Title: SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data Abstract: State-of-the-art face recognition networks are often computationally expensive and cannot be used for mobile applications. Training lightweight face recognition models also requires large identity-labeled datasets. Meanwhile...	[ 28216, 22834, 41429 ]	Train
29,129	16	Title: Boosting Crop Classification by Hierarchically Fusing Satellite, Rotational, and Contextual Data Abstract: Accurate in-season crop type classification is crucial for the crop production estimation and monitoring of agricultural parcels. However, the complexity of the plant growth patterns and their spatio-tempor...	[]	Validation
29,130	30	Title: 3D-Speaker: A Large-Scale Multi-Device, Multi-Distance, and Multi-Dialect Corpus for Speech Representation Disentanglement Abstract: Disentangling uncorrelated information in speech utterances is a crucial research topic within speech community. Different speech-related tasks focus on extracting distinct speech ...	[ 23532 ]	Validation
29,131	34	Title: Correcting matrix products over the ring of integers Abstract: Let $A$, $B$, and $C$ be three $n\times n$ matrices. We investigate the problem of verifying whether $AB=C$ over the ring of integers and finding the correct product $AB$. Given that $C$ is different from $AB$ by at most $k$ entries, we propose an al...	[]	Train
29,132	24	Title: On Differentially Private Federated Linear Contextual Bandits Abstract: We consider cross-silo federated linear contextual bandit (LCB) problem under differential privacy, where multiple silos (agents) interact with the local users and communicate via a central server to realize collaboration while without sacri...	[ 38101, 28337, 28749, 16373 ]	Test
29,133	24	Title: Fair Minimum Representation Clustering Abstract: Clustering is an unsupervised learning task that aims to partition data into a set of clusters. In many applications, these clusters correspond to real-world constructs (e.g. electoral districts) whose benefit can only be attained by groups when they reach a minim...	[]	Train
29,134	23	Title: Human-in-the-loop online just-in-time software defect prediction Abstract: Online Just-In-Time Software Defect Prediction (O-JIT-SDP) uses an online model to predict whether a new software change will introduce a bug or not. However, existing studies neglect the interaction of Software Quality Assurance (SQA) st...	[]	Validation
29,135	16	Title: Diffusion-based Target Sampler for Unsupervised Domain Adaptation Abstract: Limited transferability hinders the performance of deep learning models when applied to new application scenarios. Recently, unsupervised domain adaptation (UDA) has achieved significant progress in addressing this issue via learning dom...	[ 20371, 20941 ]	Validation
29,136	27	Title: Data-Driven Batch Localization and SLAM Using Koopman Linearization Abstract: We present a framework for model-free batch localization and SLAM. We use lifting functions to map a control-affine system into a high-dimensional space, where both the process model and the measurement model are rendered bilinear. Dur...	[]	Test
29,137	16	Title: Meta-Optimization for Higher Model Generalizability in Single-Image Depth Prediction Abstract: Model generalizability to unseen datasets, concerned with in-the-wild robustness, is less studied for indoor single-image depth prediction. We leverage gradient-based meta-learning for higher generalizability on zero-s...	[ 33936, 3938 ]	Validation
29,138	24	Title: A2CiD2: Accelerating Asynchronous Communication in Decentralized Deep Learning Abstract: Distributed training of Deep Learning models has been critical to many recent successes in the field. Current standard methods primarily rely on synchronous centralized algorithms which induce major communication bottlenecks...	[]	Test
29,139	24	Title: Contrastive Graph Clustering in Curvature Spaces Abstract: Graph clustering is a longstanding research topic, and has achieved remarkable success with the deep learning methods in recent years. Nevertheless, we observe that several important issues largely remain open. On the one hand, graph clustering from the ...	[]	Validation
29,140	27	Title: Spiking based Cellular Learning Automata (SCLA) algorithm for mobile robot motion formulation Abstract: In this paper a new method called SCLA which stands for Spiking based Cellular Learning Automata is proposed for a mobile robot to get to the target from any random initial point. The proposed method is a resu...	[]	Train
29,141	37	Title: FASTAGEDS: Fast Approximate Graph Entity Dependency Discovery Abstract: This paper studies the discovery of approximate rules in property graphs. We propose a semantically meaningful measure of error for mining graph entity dependencies (GEDs) at almost hold, to tolerate errors and inconsistencies that exist in ...	[ 29817 ]	Train
29,142	30	Title: Colexifications for Bootstrapping Cross-lingual Datasets: The Case of Phonology, Concreteness, and Affectiveness Abstract: Colexification refers to the linguistic phenomenon where a single lexical form is used to convey multiple meanings. By studying cross-lingual colexifications, researchers have gained valuabl...	[ 31520, 42001 ]	Train
29,143	30	Title: German CheXpert Chest X-ray Radiology Report Labeler Abstract: This study aimed to develop an algorithm to automatically extract annotations for chest X-ray classification models from German thoracic radiology reports. An automatic label extraction model was designed based on the CheXpert architecture, and a web...	[ 3732 ]	Validation
29,144	24	Title: An Exact Kernel Equivalence for Finite Classification Models Abstract: We explore the equivalence between neural networks and kernel methods by deriving the first exact representation of any finite-size parametric classification model trained with gradient descent as a kernel machine. We compare our exact repres...	[]	Validation
29,145	23	Title: Developing Responsible Chatbots for Financial Services: A Pattern-Oriented Responsible AI Engineering Approach Abstract: The recent release of ChatGPT has gained huge attention and discussion worldwide, with responsible AI being a key topic of discussion. How can we ensure that AI systems, including ChatGPT, are...	[]	Validation
29,146	7	Title: Designing architectured ceramics for transient thermal applications using finite element and deep learning Abstract: Topologically interlocking architectures can generate tough ceramics with attractive thermo-mechanical properties. This concept can make the material design pathway a challenging task, since model...	[]	Validation
29,147	24	Title: Robust Networked Federated Learning for Localization Abstract: This paper addresses the problem of localization, which is inherently non-convex and non-smooth in a federated setting where the data is distributed across a multitude of devices. Due to the decentralized nature of federated environments, distributed...	[]	Train
29,148	27	Title: Optimal Motion Generation of the Bipedal Under-Actuated Planar Robot for Stair Climbing Abstract: The importance of humanoid robots in today's world is undeniable, one of the most important features of humanoid robots is the ability to maneuver in environments such as stairs that other robots can not easily cros...	[]	Validation
29,149	27	Title: A Comprehensive Review on Ontologies for Scenario-based Testing in the Context of Autonomous Driving Abstract: The verification and validation of autonomous driving vehicles remains a major challenge due to the high complexity of autonomous driving functions. Scenario-based testing is a promising method for vali...	[]	Train
29,150	15	Title: A Chisel Framework for Flexible Design Space Exploration through a Functional Approach Abstract: As the need for efficient digital circuits is ever growing in the industry, the design of such systems remains daunting, requiring both expertise and time. In an attempt to close the gap between software development ...	[]	Test
29,151	30	Title: Federated Nearest Neighbor Machine Translation Abstract: To protect user privacy and meet legal regulations, federated learning (FL) is attracting significant attention. Training neural machine translation (NMT) models with traditional FL algorithm (e.g., FedAvg) typically relies on multi-round model-based inter...	[ 10401, 27500 ]	Test
29,152	24	Title: Towards Unsupervised Graph Completion Learning on Graphs with Features and Structure Missing Abstract: In recent years, graph neural networks (GNN) have achieved significant developments in a variety of graph analytical tasks. Nevertheless, GNN's superior performance will suffer from serious damage when the coll...	[]	Train
29,153	24	Title: Communication-Free Distributed GNN Training with Vertex Cut Abstract: Training Graph Neural Networks (GNNs) on real-world graphs consisting of billions of nodes and edges is quite challenging, primarily due to the substantial memory needed to store the graph and its intermediate node and edge features, and there...	[ 5000, 27583 ]	Train
29,154	6	Title: From ontology design to user-centred interfaces for music heritage Abstract: In this article we investigate the bridge between ontology design and UI/UX design methodologies to assist designers in prototyping web applications for information seeking purposes. We briefly review the state of the art in ontology de...	[]	Validation
29,155	11	Title: Opponent-aware Role-based Learning in Team Competitive Markov Games Abstract: Team competition in multi-agent Markov games is an increasingly important setting for multi-agent reinforcement learning, due to its general applicability in modeling many real-life situations. Multi-agent actor-critic methods are the ...	[]	Train
29,156	16	Title: Interpreting Vision and Language Generative Models with Semantic Visual Priors Abstract: When applied to Image-to-text models, interpretability methods often provide token-by-token explanations namely, they compute a visual explanation for each token of the generated sequence. Those explanations are expensive to...	[]	Train
29,157	16	Title: KS-APR: Keyframe Selection for Robust Absolute Pose Regression Abstract: Markerless Mobile Augmented Reality (AR) aims to anchor digital content in the physical world without using specific 2D or 3D objects. Absolute Pose Regressors (APR) are end-to-end machine learning solutions that infer the device's pose fro...	[ 41561, 32892 ]	Train
29,158	34	Title: $(1-\epsilon)$-Approximation of Knapsack in Nearly Quadratic Time Abstract: Knapsack is one of the most fundamental problems in theoretical computer science. In the $(1 - \epsilon)$-approximation setting, although there is a fine-grained lower bound of $(n + 1 / \epsilon) ^ {2 - o(1)}$ based on the $(\min, +)$-c...	[ 14314, 23227 ]	Train
29,159	16	Title: Image Moment Invariants to Rotational Motion Blur Abstract: Rotational motion blur caused by the circular motion of the camera or/and object is common in life. Identifying objects from images affected by rotational motion blur is challenging because this image degradation severely impacts image quality. Therefor...	[]	Train
29,160	24	Title: DeepVAT: A Self-Supervised Technique for Cluster Assessment in Image Datasets Abstract: Estimating the number of clusters and cluster structures in unlabeled, complex, and high-dimensional datasets (like images) is challenging for traditional clustering algorithms. In recent years, a matrix reordering-based algo...	[]	Train
29,161	24	Title: À-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting Abstract: We introduce À-la-carte Prompt Tuning (APT), a transformer-based scheme to tune prompts on distinct data so that they can be arbitrarily composed at inference time. The individual prompts can be trained in isolation, possi...	[ 5384, 23184, 11100, 13805 ]	Train
29,162	24	Title: Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective Abstract: Graph neural networks (GNNs) have pioneered advancements in graph representation learning, exhibiting superior feature learning and performance over multilayer perceptrons (MLPs) when handling graph input...	[ 13595, 33725 ]	Train
29,163	31	Title: MMRec: Simplifying Multimodal Recommendation Abstract: This paper presents an open-source toolbox, MMRec for multimodal recommendation. MMRec simplifies and canonicalizes the process of implementing and comparing multimodal recommendation models. The objective of MMRec is to provide a unified and configurable ar...	[ 185, 1434, 27018 ]	Validation
29,164	4	Title: A Controlled Experiment on the Impact of Intrusion Detection False Alarm Rate on Analyst Performance Abstract: Organizations use intrusion detection systems (IDSes) to identify harmful activity among millions of computer network events. Cybersecurity analysts review IDS alarms to verify whether malicious activit...	[]	Train
29,165	16	Title: DeblurSR: Event-Based Motion Deblurring Under the Spiking Representation Abstract: We present DeblurSR, a novel motion deblurring approach that converts a blurry image into a sharp video. DeblurSR utilizes event data to compensate for motion ambiguities and exploits the spiking representation to parameterize the...	[ 20292 ]	Train
29,166	37	Title: Quantifying Uncertainty in Aggregate Queries over Integrated Datasets Abstract: Data integration is a notoriously difficult and heuristic-driven process, especially when ground-truth data are not readily available. This paper presents a measure of uncertainty by providing maximal and minimal ranges of a query ou...	[]	Train
29,167	16	Title: Colo-SCRL: Self-Supervised Contrastive Representation Learning for Colonoscopic Video Retrieval Abstract: Colonoscopic video retrieval, which is a critical part of polyp treatment, has great clinical significance for the prevention and treatment of colorectal cancer. However, retrieval models trained on action r...	[ 14721, 18058, 1612 ]	Validation
29,168	24	Title: Infomaxformer: Maximum Entropy Transformer for Long Time-Series Forecasting Problem Abstract: The Transformer architecture yields state-of-the-art results in many tasks such as natural language processing (NLP) and computer vision (CV), since the ability to efficiently capture the precise long-range dependency c...	[]	Train
29,169	24	Title: Locally Adaptive Federated Learning via Stochastic Polyak Stepsizes Abstract: State-of-the-art federated learning algorithms such as FedAvg require carefully tuned stepsizes to achieve their best performance. The improvements proposed by existing adaptive federated methods involve tuning of additional hyperparam...	[ 15816, 26901 ]	Train
29,170	6	Title: On the Interdependence of Reliance Behavior and Accuracy in AI-Assisted Decision-Making Abstract: In AI-assisted decision-making, a central promise of putting a human in the loop is that they should be able to complement the AI system by adhering to its correct and overriding its mistaken recommendations. In pra...	[ 6512, 44232, 14799 ]	Train
29,171	30	Title: SLTUNET: A Simple Unified Model for Sign Language Translation Abstract: Despite recent successes with neural models for sign language translation (SLT), translation quality still lags behind spoken languages because of the data scarcity and modality gap between sign video and text. To address both problems, we i...	[ 11822, 5358 ]	Train
29,172	10	Title: Hierarchical Time Series Forecasting with Bayesian Modeling Abstract: We encounter time series data in many domains such as finance, physics, business, and weather. One of the main tasks of time series analysis, one that helps to take informed decisions under uncertainty, is forecasting. Time series are often hi...	[]	Train
29,173	16	Title: MGMAE: Motion Guided Masking for Video Masked Autoencoding Abstract: Masked autoencoding has shown excellent performance on self-supervised video representation learning. Temporal redundancy has led to a high masking ratio and customized masking strategy in VideoMAE. In this paper, we aim to further improve the ...	[ 26484, 41183 ]	Train
29,174	24	Title: IronForge: An Open, Secure, Fair, Decentralized Federated Learning Abstract: Federated learning (FL) provides an effective machine learning (ML) architecture to protect data privacy in a distributed manner. However, the inevitable network asynchrony, the over-dependence on a central coordinator, and the lack of ...	[ 26993, 45348, 24061, 1335 ]	Train
29,175	25	Title: LP-MusicCaps: LLM-Based Pseudo Music Captioning Abstract: Automatic music captioning, which generates natural language descriptions for given music tracks, holds significant potential for enhancing the understanding and organization of large volumes of musical data. Despite its importance, researchers face chall...	[ 11904, 13186, 11877, 33241, 39642, 42747 ]	Test
29,176	24	Title: Privacy in Multimodal Federated Human Activity Recognition Abstract: Human Activity Recognition (HAR) training data is often privacy-sensitive or held by non-cooperative entities. Federated Learning (FL) addresses such concerns by training ML models on edge clients. This work studies the impact of privacy in fed...	[]	Validation
29,177	2	Title: Satisfiability Checking of Multi-Variable TPTL with Unilateral Intervals Is PSPACE-Complete Abstract: We investigate the decidability of the ${0,\infty}$ fragment of Timed Propositional Temporal Logic (TPTL). We show that the satisfiability checking of TPTL$^{0,\infty}$ is PSPACE-complete. Moreover, even its 1-v...	[]	Test

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