Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2404.17419	Multi-view Image Prompted Multi-view Diffusion for Improved 3D Generation	Using image as prompts for 3D generation demonstrate particularly strong performances compared to using text prompts alone, for images provide a more intuitive guidance for the 3D generation process. In this work, we delve into the potential of using multiple image prompts, instead of a single image prompt, for 3D gene...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	449,849
1703.04943	Matched bipartite block model with covariates	Community detection or clustering is a fundamental task in the analysis of network data. Many real networks have a bipartite structure which makes community detection challenging. In this paper, we consider a model which allows for matched communities in the bipartite setting, in addition to node covariates with inform...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	69,996
2105.07869	Fast and Accurate Camera Scene Detection on Smartphones	AI-powered automatic camera scene detection mode is nowadays available in nearly any modern smartphone, though the problem of accurate scene prediction has not yet been addressed by the research community. This paper for the first time carefully defines this problem and proposes a novel Camera Scene Detection Dataset (...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	235,581
2411.07729	Exploring the loss landscape of regularized neural networks via convex duality	We discuss several aspects of the loss landscape of regularized neural networks: the structure of stationary points, connectivity of optimal solutions, path with nonincreasing loss to arbitrary global optimum, and the nonuniqueness of optimal solutions, by casting the problem into an equivalent convex problem and consi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	507,658
2210.03205	Synthetic Dataset Generation for Privacy-Preserving Machine Learning	Machine Learning (ML) has achieved enormous success in solving a variety of problems in computer vision, speech recognition, object detection, to name a few. The principal reason for this success is the availability of huge datasets for training deep neural networks (DNNs). However, datasets can not be publicly release...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	false	false	false	false	321,936
2403.03455	Robust Control Lyapunov-Value Functions for Nonlinear Disturbed Systems	Control Lyapunov Functions (CLFs) have been extensively used in the control community. A well-known drawback is the absence of a systematic way to construct CLFs for general nonlinear systems, and the problem can become more complex with input or state constraints. Our preliminary work on constructing Control Lyapunov ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	435,199
2206.11321	An Application of a Modified Beta Factor Method for the Analysis of Software Common Cause Failures	This paper presents an approach for modeling software common cause failures (CCFs) within digital instrumentation and control (I&C) systems. CCFs consist of a concurrent failure between two or more components due to a shared failure cause and coupling mechanism. This work emphasizes the importance of identifying softwa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	304,226
2409.11410	Multilevel Verification on a Single Digital Decentralized Distributed (DDD) Ledger	This paper presents an approach to using decentralized distributed digital (DDD) ledgers like blockchain with multi-level verification. In regular DDD ledgers like Blockchain, only a single level of verification is available, which makes it not useful for those systems where there is a hierarchy and verification is req...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	489,147
2202.01857	Brain Cancer Survival Prediction on Treatment-na ive MRI using Deep Anchor Attention Learning with Vision Transformer	Image-based brain cancer prediction models, based on radiomics, quantify the radiologic phenotype from magnetic resonance imaging (MRI). However, these features are difficult to reproduce because of variability in acquisition and preprocessing pipelines. Despite evidence of intra-tumor phenotypic heterogeneity, the spa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	278,607
2201.08099	JEDI: These aren't the JSON documents you're looking for... (Extended Version*)	The JavaScript Object Notation (JSON) is a popular data format used in document stores to natively support semi-structured data. In this paper, we address the problem of JSON similarity lookup queries: given a query document and a distance threshold $\tau$, retrieve all JSON documents that are within $\tau$ from the qu...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	276,229
1204.4779	Paraiso : An Automated Tuning Framework for Explicit Solvers of Partial Differential Equations	We propose Paraiso, a domain specific language embedded in functional programming language Haskell, for automated tuning of explicit solvers of partial differential equations (PDEs) on GPUs as well as multicore CPUs. In Paraiso, one can describe PDE solving algorithms succinctly using tensor equations notation. Hydrody...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	15,612
2404.11993	Knowledge-Aware Multi-Intent Contrastive Learning for Multi-Behavior Recommendation	Multi-behavioral recommendation optimizes user experiences by providing users with more accurate choices based on their diverse behaviors, such as view, add to cart, and purchase. Current studies on multi-behavioral recommendation mainly explore the connections and differences between multi-behaviors from an implicit p...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	447,693
2406.14558	CooHOI: Learning Cooperative Human-Object Interaction with Manipulated Object Dynamics	Enabling humanoid robots to clean rooms has long been a pursued dream within humanoid research communities. However, many tasks require multi-humanoid collaboration, such as carrying large and heavy furniture together. Given the scarcity of motion capture data on multi-humanoid collaboration and the efficiency challeng...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	466,371
2402.05828	Discovering Temporally-Aware Reinforcement Learning Algorithms	Recent advancements in meta-learning have enabled the automatic discovery of novel reinforcement learning algorithms parameterized by surrogate objective functions. To improve upon manually designed algorithms, the parameterization of this learned objective function must be expressive enough to represent novel principl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	428,022
cs/0006011	Bagging and Boosting a Treebank Parser	Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these techniques with a trainable statistical parser are described. The best resulting system provides roughly as large of a gain in F-measure as doubling the corpus size. Error analysis of the re...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,123
1902.07602	Point cloud denoising based on tensor Tucker decomposition	In this paper, we propose a new algorithm for point cloud denoising based on the tensor Tucker decomposition. We first represent the local surface patches of a noisy point cloud to be matrices by their distances to a reference point, and stack the similar patch matrices to be a 3rd order tensor. Then we use the Tucker ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	122,018
2307.11308	DPM-OT: A New Diffusion Probabilistic Model Based on Optimal Transport	Sampling from diffusion probabilistic models (DPMs) can be viewed as a piecewise distribution transformation, which generally requires hundreds or thousands of steps of the inverse diffusion trajectory to get a high-quality image. Recent progress in designing fast samplers for DPMs achieves a trade-off between sampling...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	380,855
1703.01830	Decomposable Submodular Function Minimization: Discrete and Continuous	This paper investigates connections between discrete and continuous approaches for decomposable submodular function minimization. We provide improved running time estimates for the state-of-the-art continuous algorithms for the problem using combinatorial arguments. We also provide a systematic experimental comparison ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	69,438
1907.09504	Reservoir Computing Models for Patient-Adaptable ECG Monitoring in Wearable Devices	The reservoir computing paradigm is employed to classify heartbeat anomalies online based on electrocardiogram signals. Inspired by the principles of information processing in the brain, reservoir computing provides a framework to design, train, and analyze recurrent neural networks (RNNs) for processing time-dependent...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,378
1508.03765	SoftNull: Many-Antenna Full-Duplex Wireless via Digital Beamforming	In this paper, we present and study a digital-controlled method, called SoftNull, to enable full-duplex in many-antenna systems. Unlike most designs that rely on analog cancelers to suppress self-interference, SoftNull relies on digital transmit beamforming to reduce self-interference. SoftNull does not attempt to perf...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	46,038
2411.00121	I Can Hear You: Selective Robust Training for Deepfake Audio Detection	Recent advances in AI-generated voices have intensified the challenge of detecting deepfake audio, posing risks for scams and the spread of disinformation. To tackle this issue, we establish the largest public voice dataset to date, named DeepFakeVox-HQ, comprising 1.3 million samples, including 270,000 high-quality de...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	504,440
2205.15707	CALEB: A Conditional Adversarial Learning Framework to Enhance Bot Detection	The high growth of Online Social Networks (OSNs) over the last few years has allowed automated accounts, known as social bots, to gain ground. As highlighted by other researchers, most of these bots have malicious purposes and tend to mimic human behavior, posing high-level security threats on OSN platforms. Moreover, ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	299,838
2405.12299	Perturbing the Gradient for Alleviating Meta Overfitting	The reason for Meta Overfitting can be attributed to two factors: Mutual Non-exclusivity and the Lack of diversity, consequent to which a single global function can fit the support set data of all the meta-training tasks and fail to generalize to new unseen tasks. This issue is evidenced by low error rates on the meta-...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	455,469
1309.0790	SKYNET: an efficient and robust neural network training tool for machine learning in astronomy	We present the first public release of our generic neural network training algorithm, called SkyNet. This efficient and robust machine learning tool is able to train large and deep feed-forward neural networks, including autoencoders, for use in a wide range of supervised and unsupervised learning applications, such as...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	26,808
2008.09461	The paradox of productivity during quarantine: an agent-based simulation	Economies across the globe were brought to their knees due to lockdowns and social restriction measures to contain the spread of the SARS-CoV-2, despite the quick switch to remote working. This downfall may be partially explained by the "water cooler effect", which holds that higher levels of social interaction lead to...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	192,719
2208.04777	Learning Mean-Field Control for Delayed Information Load Balancing in Large Queuing Systems	Recent years have seen a great increase in the capacity and parallel processing power of data centers and cloud services. To fully utilize the said distributed systems, optimal load balancing for parallel queuing architectures must be realized. Existing state-of-the-art solutions fail to consider the effect of communic...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	true	312,223
2402.01456	Convolution kernel adaptation to calibrated fisheye	Convolution kernels are the basic structural component of convolutional neural networks (CNNs). In the last years there has been a growing interest in fisheye cameras for many applications. However, the radially symmetric projection model of these cameras produces high distortions that affect the performance of CNNs, e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	426,030
2010.12707	Learning to Recognize Dialect Features	Building NLP systems that serve everyone requires accounting for dialect differences. But dialects are not monolithic entities: rather, distinctions between and within dialects are captured by the presence, absence, and frequency of dozens of dialect features in speech and text, such as the deletion of the copula in "H...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	202,810
2403.18212	Preference-Based Planning in Stochastic Environments: From Partially-Ordered Temporal Goals to Most Preferred Policies	Human preferences are not always represented via complete linear orders: It is natural to employ partially-ordered preferences for expressing incomparable outcomes. In this work, we consider decision-making and probabilistic planning in stochastic systems modeled as Markov decision processes (MDPs), given a partially o...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	true	441,824
1907.00511	Automatic Real-time Anomaly Detection for Autonomous Aerial Vehicles	The recent increase in the use of aerial vehicles raises concerns about the safety and reliability of autonomous operations. There is a growing need for methods to monitor the status of these aircraft and report any faults and anomalies to the safety pilot or to the autopilot to deal with the emergency situation. In th...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	137,072
2104.01103	Semi-supervised Viewpoint Estimation with Geometry-aware Conditional Generation	There is a growing interest in developing computer vision methods that can learn from limited supervision. In this paper, we consider the problem of learning to predict camera viewpoints, where obtaining ground-truth annotations are expensive and require special equipment, from a limited number of labeled images. We pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	228,233
2309.17280	STRONG -- Structure Controllable Legal Opinion Summary Generation	We propose an approach for the structure controllable summarization of long legal opinions that considers the argument structure of the document. Our approach involves using predicted argument role information to guide the model in generating coherent summaries that follow a provided structure pattern. We demonstrate t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	395,711
2204.09280	Reinforced Structured State-Evolution for Vision-Language Navigation	Vision-and-language Navigation (VLN) task requires an embodied agent to navigate to a remote location following a natural language instruction. Previous methods usually adopt a sequence model (e.g., Transformer and LSTM) as the navigator. In such a paradigm, the sequence model predicts action at each step through a mai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	292,379
1710.04163	An Information Theoretic Framework for Active De-anonymization in Social Networks Based on Group Memberships	In this paper, a new mathematical formulation for the problem of de-anonymizing social network users by actively querying their membership in social network groups is introduced. In this formulation, the attacker has access to a noisy observation of the group membership of each user in the social network. When an unide...	false	false	false	true	false	false	false	false	false	true	false	false	true	false	false	false	false	false	82,442
2012.08662	Automated system to measure Tandem Gait to assess executive functions in children	As mobile technologies have become ubiquitous in recent years, computer-based cognitive tests have become more popular and efficient. In this work, we focus on assessing motor function in children by analyzing their gait movements. Although there has been a lot of research on designing automated assessment systems for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	211,823
2403.15407	X-AMR Annotation Tool	This paper presents a novel Cross-document Abstract Meaning Representation (X-AMR) annotation tool designed for annotating key corpus-level event semantics. Leveraging machine assistance through the Prodigy Annotation Tool, we enhance the user experience, ensuring ease and efficiency in the annotation process. Through ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	440,538
1310.8499	Deep AutoRegressive Networks	We introduce a deep, generative autoencoder capable of learning hierarchies of distributed representations from data. Successive deep stochastic hidden layers are equipped with autoregressive connections, which enable the model to be sampled from quickly and exactly via ancestral sampling. We derive an efficient approx...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	28,109
1912.02143	Landscape Complexity for the Empirical Risk of Generalized Linear Models	We present a method to obtain the average and the typical value of the number of critical points of the empirical risk landscape for generalized linear estimation problems and variants. This represents a substantial extension of previous applications of the Kac-Rice method since it allows to analyze the critical points...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,266
2204.02338	MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering	Graph Neural Networks (GNNs) have recently been utilized to build Collaborative Filtering (CF) models to predict user preferences based on historical user-item interactions. However, there is relatively little understanding of how GNN-based CF models relate to some traditional Network Representation Learning (NRL) appr...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	289,908
2005.04246	ConvoKit: A Toolkit for the Analysis of Conversations	This paper describes the design and functionality of ConvoKit, an open-source toolkit for analyzing conversations and the social interactions embedded within. ConvoKit provides an unified framework for representing and manipulating conversational data, as well as a large and diverse collection of conversational dataset...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	176,398
2404.00884	Self-Demos: Eliciting Out-of-Demonstration Generalizability in Large Language Models	Large language models (LLMs) have shown promising abilities of in-context learning (ICL), adapting swiftly to new tasks with only few-shot demonstrations. However, current few-shot methods heavily depend on high-quality, query-specific demos, which are often lacking. When faced with out-of-demonstration (OOD) queries, ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	443,147
2202.09363	Towards Digital Twin Oriented Modelling of Complex Networked Systems and Their Dynamics: A Comprehensive Survey	This paper aims to provide a comprehensive critical overview on how entities and their interactions in Complex Networked Systems (CNS) are modelled across disciplines as they approach their ultimate goal of creating a Digital Twin (DT) that perfectly matches the reality. We propose a new framework to conceptually compa...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	281,169
1905.00877	You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle	Deep learning achieves state-of-the-art results in many tasks in computer vision and natural language processing. However, recent works have shown that deep networks can be vulnerable to adversarial perturbations, which raised a serious robustness issue of deep networks. Adversarial training, typically formulated as a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	129,583
1704.04966	Larger is Better: The Effect of Learning Rates Enjoyed by Stochastic Optimization with Progressive Variance Reduction	In this paper, we propose a simple variant of the original stochastic variance reduction gradient (SVRG), where hereafter we refer to as the variance reduced stochastic gradient descent (VR-SGD). Different from the choices of the snapshot point and starting point in SVRG and its proximal variant, Prox-SVRG, the two vec...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	71,924
2305.06341	Non-Euclidean Motion Planning with Graphs of Geodesically-Convex Sets	Computing optimal, collision-free trajectories for high-dimensional systems is a challenging problem. Sampling-based planners struggle with the dimensionality, whereas trajectory optimizers may get stuck in local minima due to inherent nonconvexities in the optimization landscape. The use of mixed-integer programming t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	363,499
2203.00235	Beam Squint-Aware Integrated Sensing and Communications for Hybrid Massive MIMO LEO Satellite Systems	The space-air-ground-sea integrated network (SAGSIN) plays an important role in offering global coverage. To improve the efficient utilization of spectral and hardware resources in the SAGSIN, integrated sensing and communications (ISAC) has drawn extensive attention. Most existing ISAC works focus on terrestrial netwo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	282,923
2108.11523	SOMTimeS: Self Organizing Maps for Time Series Clustering and its Application to Serious Illness Conversations	There is an increasing demand for scalable algorithms capable of clustering and analyzing large time series datasets. The Kohonen self-organizing map (SOM) is a type of unsupervised artificial neural network for visualizing and clustering complex data, reducing the dimensionality of data, and selecting influential feat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	252,199
2309.00966	Compositional Diffusion-Based Continuous Constraint Solvers	This paper introduces an approach for learning to solve continuous constraint satisfaction problems (CCSP) in robotic reasoning and planning. Previous methods primarily rely on hand-engineering or learning generators for specific constraint types and then rejecting the value assignments when other constraints are viola...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	389,490
2108.06119	Effective semantic segmentation in Cataract Surgery: What matters most?	Our work proposes neural network design choices that set the state-of-the-art on a challenging public benchmark on cataract surgery, CaDIS. Our methodology achieves strong performance across three semantic segmentation tasks with increasingly granular surgical tool class sets by effectively handling class imbalance, an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	250,509
2201.08281	Symplectic Momentum Neural Networks -- Using Discrete Variational Mechanics as a prior in Deep Learning	With deep learning gaining attention from the research community for prediction and control of real physical systems, learning important representations is becoming now more than ever mandatory. It is of extreme importance that deep learning representations are coherent with physics. When learning from discrete data th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	276,290
2411.15800	PG-SLAM: Photo-realistic and Geometry-aware RGB-D SLAM in Dynamic Environments	Simultaneous localization and mapping (SLAM) has achieved impressive performance in static environments. However, SLAM in dynamic environments remains an open question. Many methods directly filter out dynamic objects, resulting in incomplete scene reconstruction and limited accuracy of camera localization. The other w...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	510,777
1106.5270	Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions	Auctions are becoming an increasingly popular method for transacting business, especially over the Internet. This article presents a general approach to building autonomous bidding agents to bid in multiple simultaneous auctions for interacting goods. A core component of our approach learns a model of the empirical pri...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	11,015
2501.06554	Hierarchical Reinforcement Learning for Optimal Agent Grouping in Cooperative Systems	This paper presents a hierarchical reinforcement learning (RL) approach to address the agent grouping or pairing problem in cooperative multi-agent systems. The goal is to simultaneously learn the optimal grouping and agent policy. By employing a hierarchical RL framework, we distinguish between high-level decisions of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	524,030
2102.00976	Can Predominant Credible Information Suppress Misinformation in Crises? Empirical Studies of Tweets Related to Prevention Measures during COVID-19	During COVID-19, misinformation on social media affects the adoption of appropriate prevention behaviors. It is urgent to suppress the misinformation to prevent negative public health consequences. Although an array of studies has proposed misinformation suppression strategies, few have investigated the role of predomi...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	217,971
2206.10608	Generating Diverse Indoor Furniture Arrangements	We present a method for generating arrangements of indoor furniture from human-designed furniture layout data. Our method creates arrangements that target specified diversity, such as the total price of all furniture in the room and the number of pieces placed. To generate realistic furniture arrangement, we train a ge...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	true	303,975
2211.12911	Data-driven approximation of control invariant set for linear system based on convex piecewise linear fitting	Control invariant set is critical for guaranteeing safe control and the problem of computing control invariant set for linear discrete-time system is revisited in this paper by using a data-driven approach. Specifically, sample points on convergent trajectories of linear MPC are recorded, of which the convex hull formu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	332,286
2109.04266	An objective function for order preserving hierarchical clustering	We present a theory and an objective function for similarity-based hierarchical clustering of probabilistic partial orders and directed acyclic graphs (DAGs). Specifically, given elements $x \le y$ in the partial order, and their respective clusters $[x]$ and $[y]$, the theory yields an order relation $\le'$ on the clu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	254,337
2502.02975	TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics	Future link prediction is a fundamental challenge in various real-world dynamic systems. To address this, numerous temporal graph neural networks (temporal GNNs) and benchmark datasets have been developed. However, these datasets often feature excessive repeated edges and lack complex sequential dynamics, a key charact...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	530,551
2410.08224	A Survey of Spatio-Temporal EEG data Analysis: from Models to Applications	In recent years, the field of electroencephalography (EEG) analysis has witnessed remarkable advancements, driven by the integration of machine learning and artificial intelligence. This survey aims to encapsulate the latest developments, focusing on emerging methods and technologies that are poised to transform our co...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	497,015
2206.14989	A Unified End-to-End Retriever-Reader Framework for Knowledge-based VQA	Knowledge-based Visual Question Answering (VQA) expects models to rely on external knowledge for robust answer prediction. Though significant it is, this paper discovers several leading factors impeding the advancement of current state-of-the-art methods. On the one hand, methods which exploit the explicit knowledge ta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	305,448
1401.1456	Using temporal IDF for efficient novelty detection in text streams	Novelty detection in text streams is a challenging task that emerges in quite a few different scenarios, ranging from email thread filtering to RSS news feed recommendation on a smartphone. An efficient novelty detection algorithm can save the user a great deal of time and resources when browsing through relevant yet u...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	29,652
2405.03060	Tree-based Ensemble Learning for Out-of-distribution Detection	Being able to successfully determine whether the testing samples has similar distribution as the training samples is a fundamental question to address before we can safely deploy most of the machine learning models into practice. In this paper, we propose TOOD detection, a simple yet effective tree-based out-of-distrib...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	452,031
2108.10810	Design and integration of end-effector for 3D printing of novel UV-curable shape memory polymers with a collaborative robotic system	This paper presents the initial development of a robotic additive manufacturing technology based on ultraviolet (UV)-curable thermoset polymers. This is designed to allow free-standing printing through partial UV curing and fiber reinforcement for structural applications. The proposed system integrates a collaborative ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	252,014
2409.12579	Sharp estimates for Gowers norms on discrete cubes	We study optimal dimensionless inequalities $$ \\|f\\|_{U^k} \leq \\|f\\|_{\ell^{p_{k,n}}} $$ that hold for all functions $f\colon\mathbb{Z}^d\to\mathbb{C}$ supported in $\{0,1,\ldots,n-1\}^d$ and estimates $$ \\|1_A\\|_{U^k}^{2^k}\leq \|A\|^{t_{k,n}} $$ that hold for all subsets $A$ of the same discrete cubes. A general theor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	489,645
2302.11982	A Plot is Worth a Thousand Words: Model Information Stealing Attacks via Scientific Plots	Building advanced machine learning (ML) models requires expert knowledge and many trials to discover the best architecture and hyperparameter settings. Previous work demonstrates that model information can be leveraged to assist other attacks, such as membership inference, generating adversarial examples. Therefore, su...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	347,388
2407.01559	Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data	Electrical impedance tomography (EIT) plays a crucial role in non-invasive imaging, with both medical and industrial applications. In this paper, we present three data-driven reconstruction methods for EIT imaging. These three approaches were originally submitted to the Kuopio tomography challenge 2023 (KTC2023). First...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	469,354
2312.01650	Adaptive Confidence Threshold for ByteTrack in Multi-Object Tracking	We investigate the application of ByteTrack in the realm of multiple object tracking. ByteTrack, a simple tracking algorithm, enables the simultaneous tracking of multiple objects by strategically incorporating detections with a low confidence threshold. Conventionally, objects are initially associated with high confid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,530
2305.17526	Computing a partition function of a generalized pattern-based energy over a semiring	Valued constraint satisfaction problems with ordered variables (VCSPO) are a special case of Valued CSPs in which variables are totally ordered and soft constraints are imposed on tuples of variables that do not violate the order. We study a restriction of VCSPO, in which soft constraints are imposed on a segment of ad...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	368,632
1810.09147	Summarizing User-generated Textual Content: Motivation and Methods for Fairness in Algorithmic Summaries	As the amount of user-generated textual content grows rapidly, text summarization algorithms are increasingly being used to provide users a quick overview of the information content. Traditionally, summarization algorithms have been evaluated only based on how well they match human-written summaries (e.g. as measured b...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	110,998
2107.01980	Gaze Estimation with an Ensemble of Four Architectures	This paper presents a method for gaze estimation according to face images. We train several gaze estimators adopting four different network architectures, including an architecture designed for gaze estimation (i.e.,iTracker-MHSA) and three originally designed for general computer vision tasks(i.e., BoTNet, HRNet, ResN...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	244,660
2409.18197	Autonomous Network Defence using Reinforcement Learning	In the network security arms race, the defender is significantly disadvantaged as they need to successfully detect and counter every malicious attack. In contrast, the attacker needs to succeed only once. To level the playing field, we investigate the effectiveness of autonomous agents in a realistic network defence sc...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	492,136
2403.11460	Fed3DGS: Scalable 3D Gaussian Splatting with Federated Learning	In this work, we present Fed3DGS, a scalable 3D reconstruction framework based on 3D Gaussian splatting (3DGS) with federated learning. Existing city-scale reconstruction methods typically adopt a centralized approach, which gathers all data in a central server and reconstructs scenes. The approach hampers scalability ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,709
2502.10868	NitiBench: A Comprehensive Studies of LLM Frameworks Capabilities for Thai Legal Question Answering	The application of large language models (LLMs) in the legal domain holds significant potential for information retrieval and question answering, yet Thai legal QA systems face challenges due to a lack of standardized evaluation benchmarks and the complexity of Thai legal structures. This paper introduces NitiBench, a ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	534,082
1610.03792	Decentralized Coded Caching with Distinct Cache Capacities	Decentralized coded caching is studied for a content server with $N$ files, each of size $F$ bits, serving $K$ active users, each equipped with a cache of distinct capacity. It is assumed that the users' caches are filled in advance during the off-peak traffic period without the knowledge of the number of active users,...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	62,301
2409.14316	MVPGS: Excavating Multi-view Priors for Gaussian Splatting from Sparse Input Views	Recently, the Neural Radiance Field (NeRF) advancement has facilitated few-shot Novel View Synthesis (NVS), which is a significant challenge in 3D vision applications. Despite numerous attempts to reduce the dense input requirement in NeRF, it still suffers from time-consumed training and rendering processes. More rece...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	490,419
2003.13027	Abstractive Text Summarization based on Language Model Conditioning and Locality Modeling	We explore to what extent knowledge about the pre-trained language model that is used is beneficial for the task of abstractive summarization. To this end, we experiment with conditioning the encoder and decoder of a Transformer-based neural model on the BERT language model. In addition, we propose a new method of BERT...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	170,082
1806.03740	Unsupervised Disambiguation of Syncretism in Inflected Lexicons	Lexical ambiguity makes it difficult to compute various useful statistics of a corpus. A given word form might represent any of several morphological feature bundles. One can, however, use unsupervised learning (as in EM) to fit a model that probabilistically disambiguates word forms. We present such an approach, which...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	100,073
2004.06101	Near-Optimal Distributed Band-Joins through Recursive Partitioning	We consider running-time optimization for band-joins in a distributed system, e.g., the cloud. To balance load across worker machines, input has to be partitioned, which causes duplication. We explore how to resolve this tension between maximum load per worker and input duplication for band-joins between two relations....	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	172,417
1804.06201	LCMR: Local and Centralized Memories for Collaborative Filtering with Unstructured Text	Collaborative filtering (CF) is the key technique for recommender systems. Pure CF approaches exploit the user-item interaction data (e.g., clicks, likes, and views) only and suffer from the sparsity issue. Items are usually associated with content information such as unstructured text (e.g., abstracts of articles and ...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	95,243
2404.05673	CoReS: Orchestrating the Dance of Reasoning and Segmentation	The reasoning segmentation task, which demands a nuanced comprehension of intricate queries to accurately pinpoint object regions, is attracting increasing attention. However, Multi-modal Large Language Models (MLLM) often find it difficult to accurately localize the objects described in complex reasoning contexts. We ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,168
1801.09496	Improving Active Learning in Systematic Reviews	Systematic reviews are essential to summarizing the results of different clinical and social science studies. The first step in a systematic review task is to identify all the studies relevant to the review. The task of identifying relevant studies for a given systematic review is usually performed manually, and as a r...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	true	89,123
2003.14204	Verification of Nonblockingness in Bounded Petri Nets With Minimax Basis Reachability Graphs	This paper proposes a semi-structural approach to verify the nonblockingness of a Petri net. We construct a structure, called minimax basis reachability graph (minimax-BRG): it provides an abstract description of the reachability set of a net while preserving all information needed to test if the net is blocking. We pr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	170,440
2401.04979	DualDynamics: Synergizing Implicit and Explicit Methods for Robust Irregular Time Series Analysis	Real-world time series analysis faces significant challenges when dealing with irregular and incomplete data. While Neural Differential Equation (NDE) based methods have shown promise, they struggle with limited expressiveness, scalability issues, and stability concerns. Conversely, Neural Flows offer stability but fal...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	420,611
1702.08033	Euclidean and Hermitian LCD MDS codes	Linear codes with complementary duals (abbreviated LCD) are linear codes whose intersection with their dual is trivial. When they are binary, they play an important role in armoring implementations against side-channel attacks and fault injection attacks. Non-binary LCD codes in characteristic 2 can be transformed into...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,899
2401.09496	Learning to Generalize over Subpartitions for Heterogeneity-aware Domain Adaptive Nuclei Segmentation	Annotation scarcity and cross-modality/stain data distribution shifts are two major obstacles hindering the application of deep learning models for nuclei analysis, which holds a broad spectrum of potential applications in digital pathology. Recently, unsupervised domain adaptation (UDA) methods have been proposed to m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	422,289
2008.00851	Planning to Score a Goal in Robotic Football with Heuristic Search	This paper considers a problem of planning an attack in robotic football (RoboCup). The problem is reduced to finding a trajectory of the ball from its current position to the opponents goals. Heuristic search algorithm, i.e. A*, is used to find such a trajectory. For this algorithm to be applicable we introduce a disc...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	190,135
2106.01499	Personalizing Pre-trained Models	Self-supervised or weakly supervised models trained on large-scale datasets have shown sample-efficient transfer to diverse datasets in few-shot settings. We consider how upstream pretrained models can be leveraged for downstream few-shot, multilabel, and continual learning tasks. Our model CLIPPER (CLIP PERsonalized) ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	238,516
2007.14634	Approximation Based Variance Reduction for Reparameterization Gradients	Flexible variational distributions improve variational inference but are harder to optimize. In this work we present a control variate that is applicable for any reparameterizable distribution with known mean and covariance matrix, e.g. Gaussians with any covariance structure. The control variate is based on a quadrati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	189,462
2104.11416	Predicting Distant Metastases in Soft-Tissue Sarcomas from PET-CT scans using Constrained Hierarchical Multi-Modality Feature Learning	Distant metastases (DM) refer to the dissemination of tumors, usually, beyond the organ where the tumor originated. They are the leading cause of death in patients with soft-tissue sarcomas (STSs). Positron emission tomography-computed tomography (PET-CT) is regarded as the imaging modality of choice for the management...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	231,903
2306.14067	UAlberta at SemEval-2023 Task 1: Context Augmentation and Translation for Multilingual Visual Word Sense Disambiguation	We describe the systems of the University of Alberta team for the SemEval-2023 Visual Word Sense Disambiguation (V-WSD) Task. We present a novel algorithm that leverages glosses retrieved from BabelNet, in combination with text and image encoders. Furthermore, we compare language-specific encoders against the applicati...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	375,527
1501.02620	Energy Harvesting Small Cell Networks: Feasibility, Deployment and Operation	Small cell networks (SCNs) have attracted great attention in recent years due to their potential to meet the exponential growth of mobile data traffic and the increasing demand for better quality of service and user experience in mobile applications. Nevertheless, a wide deployment of SCNs has not happened yet because ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,203
2309.10438	AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration	Diffusion models are emerging expressive generative models, in which a large number of time steps (inference steps) are required for a single image generation. To accelerate such tedious process, reducing steps uniformly is considered as an undisputed principle of diffusion models. We consider that such a uniform assum...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	393,013
2408.10482	Evaluation Framework for AI-driven Molecular Design of Multi-target Drugs: Brain Diseases as a Case Study	The widespread application of Artificial Intelligence (AI) techniques has significantly influenced the development of new therapeutic agents. These computational methods can be used to design and predict the properties of generated molecules. Multi-target Drug Discovery (MTDD) is an emerging paradigm for discovering dr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	481,867
1601.00595	Robust Non-linear Regression: A Greedy Approach Employing Kernels with Application to Image Denoising	We consider the task of robust non-linear regression in the presence of both inlier noise and outliers. Assuming that the unknown non-linear function belongs to a Reproducing Kernel Hilbert Space (RKHS), our goal is to estimate the set of the associated unknown parameters. Due to the presence of outliers, common techni...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	50,657
1912.00983	Quasi-factorization and Multiplicative Comparison of Subalgebra-Relative Entropy	Purely multiplicative comparisons of quantum relative entropy are desirable but challenging to prove. We show such comparisons for relative entropies between comparable densities, including the relative entropy of a density with respect to its subalgebraic restriction. These inequalities are asymptotically tight in app...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	155,951
1207.1408	Representation Policy Iteration	This paper addresses a fundamental issue central to approximation methods for solving large Markov decision processes (MDPs): how to automatically learn the underlying representation for value function approximation? A novel theoretically rigorous framework is proposed that automatically generates geometrically customi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	17,288
2112.14518	Mutual influence between language and perception in multi-agent communication games	Language interfaces with many other cognitive domains. This paper explores how interactions at these interfaces can be studied with deep learning methods, focusing on the relation between language emergence and visual perception. To model the emergence of language, a sender and a receiver agent are trained on a referen...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	273,554
1606.06439	Social-sparsity brain decoders: faster spatial sparsity	Spatially-sparse predictors are good models for brain decoding: they give accurate predictions and their weight maps are interpretable as they focus on a small number of regions. However, the state of the art, based on total variation or graph-net, is computationally costly. Here we introduce sparsity in the local neig...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	57,578
2308.09372	Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers	Self-attention in Transformers comes with a high computational cost because of their quadratic computational complexity, but their effectiveness in addressing problems in language and vision has sparked extensive research aimed at enhancing their efficiency. However, diverse experimental conditions, spanning multiple i...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	386,268
2202.12426	Analyzing Human Observer Ability in Morphing Attack Detection -- Where Do We Stand?	Few studies have focused on examining how people recognize morphing attacks, even as several publications have examined the susceptibility of automated FRS and offered morphing attack detection (MAD) approaches. MAD approaches base their decisions either on a single image with no reference to compare against (S-MAD) or...	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	282,233

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