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
1806.07420	Improved Image Selection for Stack-Based HDR Imaging	Stack-based high dynamic range (HDR) imaging is a technique for achieving a larger dynamic range in an image by combining several low dynamic range images acquired at different exposures. Minimizing the set of images to combine, while ensuring that the resulting HDR image fully captures the scene's irradiance, is impor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	100,924
2404.16413	Asking and Answering Questions to Extract Event-Argument Structures	This paper presents a question-answering approach to extract document-level event-argument structures. We automatically ask and answer questions for each argument type an event may have. Questions are generated using manually defined templates and generative transformers. Template-based questions are generated using pr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	449,486
2111.08947	Fast Yet Effective Machine Unlearning	Unlearning the data observed during the training of a machine learning (ML) model is an important task that can play a pivotal role in fortifying the privacy and security of ML-based applications. This paper raises the following questions: (i) can we unlearn a single or multiple class(es) of data from a ML model withou...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,860
1304.8029	Cooperative Synchronization in Wireless Networks	Synchronization is a key functionality in wireless network, enabling a wide variety of services. We consider a Bayesian inference framework whereby network nodes can achieve phase and skew synchronization in a fully distributed way. In particular, under the assumption of Gaussian measurement noise, we derive two messag...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	24,307
2102.06761	MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset	The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications. However, due to the nature of such deep black-boxed models, concerns about interpretability, fairness, and biases in healthcare scenarios where human lives are at sta...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	219,864
cmp-lg/9705009	Charts, Interaction-Free Grammars, and the Compact Representation of Ambiguity	Recently researchers working in the LFG framework have proposed algorithms for taking advantage of the implicit context-free components of a unification grammar [Maxwell 96]. This paper clarifies the mathematical foundations of these techniques, provides a uniform framework in which they can be formally studied and eli...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,731
2410.08188	DifFRelight: Diffusion-Based Facial Performance Relighting	We present a novel framework for free-viewpoint facial performance relighting using diffusion-based image-to-image translation. Leveraging a subject-specific dataset containing diverse facial expressions captured under various lighting conditions, including flat-lit and one-light-at-a-time (OLAT) scenarios, we train a ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	496,992
2207.11166	METER-ML: A Multi-Sensor Earth Observation Benchmark for Automated Methane Source Mapping	Reducing methane emissions is essential for mitigating global warming. To attribute methane emissions to their sources, a comprehensive dataset of methane source infrastructure is necessary. Recent advancements with deep learning on remotely sensed imagery have the potential to identify the locations and characteristic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,527
2405.02357	Large Language Models for Mobility in Transportation Systems: A Survey on Forecasting Tasks	Mobility analysis is a crucial element in the research area of transportation systems. Forecasting traffic information offers a viable solution to address the conflict between increasing transportation demands and the limitations of transportation infrastructure. Predicting human travel is significant in aiding various...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	451,737
2304.06037	Quantitative Trading using Deep Q Learning	Reinforcement learning (RL) is a branch of machine learning that has been used in a variety of applications such as robotics, game playing, and autonomous systems. In recent years, there has been growing interest in applying RL to quantitative trading, where the goal is to make profitable trades in financial markets. T...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	357,832
1301.0167	Classifier Fusion Method to Recognize Handwritten Kannada Numerals	Optical Character Recognition (OCR) is one of the important fields in image processing and pattern recognition domain. Handwritten character recognition has always been a challenging task. Only a little work can be traced towards the recognition of handwritten characters for the south Indian languages. Kannada is one s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	20,704
2412.01919	Diffusion models learn distributions generated by complex Langevin dynamics	The probability distribution effectively sampled by a complex Langevin process for theories with a sign problem is not known a priori and notoriously hard to understand. Diffusion models, a class of generative AI, can learn distributions from data. In this contribution, we explore the ability of diffusion models to lea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	513,304
2401.11740	Multi-level Cross-modal Alignment for Image Clustering	Recently, the cross-modal pretraining model has been employed to produce meaningful pseudo-labels to supervise the training of an image clustering model. However, numerous erroneous alignments in a cross-modal pre-training model could produce poor-quality pseudo-labels and degrade clustering performance. To solve the a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	423,133
2201.13100	Adversarial Masking for Self-Supervised Learning	We propose ADIOS, a masked image model (MIM) framework for self-supervised learning, which simultaneously learns a masking function and an image encoder using an adversarial objective. The image encoder is trained to minimise the distance between representations of the original and that of a masked image. The masking f...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	277,883
2101.12154	Reinforcement Learning based Per-antenna Discrete Power Control for Massive MIMO Systems	Power consumption is one of the major issues in massive MIMO (multiple input multiple output) systems, causing increased long-term operational cost and overheating issues. In this paper, we consider per-antenna power allocation with a given finite set of power levels towards maximizing the long-term energy efficiency o...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	217,501
1503.00269	Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification	Improvement guarantees for semi-supervised classifiers can currently only be given under restrictive conditions on the data. We propose a general way to perform semi-supervised parameter estimation for likelihood-based classifiers for which, on the full training set, the estimates are never worse than the supervised so...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	40,685
2409.09816	Fast Shortest Path Polyline Smoothing With G1 Continuity and Bounded Curvature	In this work, we propose a novel and efficient method for smoothing polylines in motion planning tasks. The algorithm applies to motion planning of vehicles with bounded curvature. In the paper, we show that the generated path: 1) has minimal length, 2) is $G^1$ continuous, and 3) is collision-free by construction, if ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	488,487
1605.02495	Capacity and Degree-of-Freedom of OFDM Channels with Amplitude Constraint	In this paper, we study the capacity and degree-of-freedom (DoF) scaling for the continuous-time amplitude limited AWGN channels in radio frequency (RF) and intensity modulated optical communication (OC) channels. More precisely, we study how the capacity varies in terms of the OFDM block transmission time $T$, bandwid...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,639
2210.00208	Summing free unitary Brownian motions with applications to quantum information	Motivated by quantum information theory, we introduce a dynamical random state built out of the sum of $k \geq 2$ independent unitary Brownian motions. In the large size limit, its spectral distribution equals, up to a normalising factor, that of the free Jacobi process associated with a single self-adjoint projection ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	320,780
2303.06018	Hierarchical Neural Program Synthesis	Program synthesis aims to automatically construct human-readable programs that satisfy given task specifications, such as input/output pairs or demonstrations. Recent works have demonstrated encouraging results in a variety of domains, such as string transformation, tensor manipulation, and describing behaviors of embo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	350,663
1810.05440	An algebraic-geometric approach for linear regression without correspondences	Linear regression without correspondences is the problem of performing a linear regression fit to a dataset for which the correspondences between the independent samples and the observations are unknown. Such a problem naturally arises in diverse domains such as computer vision, data mining, communications and biology....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,230
2103.05321	User Association in Scalable Cell-Free Massive MIMO Systems	In this work, we consider the uplink of a scalable cell-free massive MIMO system where the users are served only by a subset of access points (APs) in the network. The APs are physically grouped into predetermined "cell-centric clusters", which are connected to different cooperative central processing units (CPUs). Giv...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	223,939
2304.03104	Constrained Exploration in Reinforcement Learning with Optimality Preservation	We consider a class of reinforcement-learning systems in which the agent follows a behavior policy to explore a discrete state-action space to find an optimal policy while adhering to some restriction on its behavior. Such restriction may prevent the agent from visiting some state-action pairs, possibly leading to the ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	356,669
2205.12628	Are Large Pre-Trained Language Models Leaking Your Personal Information?	Are Large Pre-Trained Language Models Leaking Your Personal Information? In this paper, we analyze whether Pre-Trained Language Models (PLMs) are prone to leaking personal information. Specifically, we query PLMs for email addresses with contexts of the email address or prompts containing the owner's name. We find that...	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	false	false	false	298,636
2008.03231	Dissipativity verification with guarantees for polynomial systems from noisy input-state data	In this paper, we investigate the verification of dissipativity properties for polynomial systems without an explicitly identified model but directly from noise-corrupted measurements. Contrary to most data-driven approaches for nonlinear systems, we determine dissipativity properties over all finite time horizons usin...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	190,844
2310.10878	Eco-Driving Control of Connected and Automated Vehicles using Neural Network based Rollout	Connected and autonomous vehicles have the potential to minimize energy consumption by optimizing the vehicle velocity and powertrain dynamics with Vehicle-to-Everything info en route. Existing deterministic and stochastic methods created to solve the eco-driving problem generally suffer from high computational and mem...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	400,419
2304.08013	CLIP-Lung: Textual Knowledge-Guided Lung Nodule Malignancy Prediction	Lung nodule malignancy prediction has been enhanced by advanced deep-learning techniques and effective tricks. Nevertheless, current methods are mainly trained with cross-entropy loss using one-hot categorical labels, which results in difficulty in distinguishing those nodules with closer progression labels. Interestin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	358,560
2011.08106	Recovering and Simulating Pedestrians in the Wild	Sensor simulation is a key component for testing the performance of self-driving vehicles and for data augmentation to better train perception systems. Typical approaches rely on artists to create both 3D assets and their animations to generate a new scenario. This, however, does not scale. In contrast, we propose to r...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	206,782
1809.09761	PhotoShape: Photorealistic Materials for Large-Scale Shape Collections	Existing online 3D shape repositories contain thousands of 3D models but lack photorealistic appearance. We present an approach to automatically assign high-quality, realistic appearance models to large scale 3D shape collections. The key idea is to jointly leverage three types of online data -- shape collections, mate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	108,768
2411.01807	Can Language Models Enable In-Context Database?	Large language models (LLMs) are emerging as few-shot learners capable of handling a variety of tasks, including comprehension, planning, reasoning, question answering, arithmetic calculations, and more. At the core of these capabilities is LLMs' proficiency in representing and understanding structural or semi-structur...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	505,235
2303.17080	Mole Recruitment: Poisoning of Image Classifiers via Selective Batch Sampling	In this work, we present a data poisoning attack that confounds machine learning models without any manipulation of the image or label. This is achieved by simply leveraging the most confounding natural samples found within the training data itself, in a new form of a targeted attack coined "Mole Recruitment." We defin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	355,099
1701.02377	The principle of cognitive action - Preliminary experimental analysis	In this document we shows a first implementation and some preliminary results of a new theory, facing Machine Learning problems in the frameworks of Classical Mechanics and Variational Calculus. We give a general formulation of the problem and then we studies basic behaviors of the model on simple practical implementat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	66,543
2206.08496	Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency	Pre-training on time series poses a unique challenge due to the potential mismatch between pre-training and target domains, such as shifts in temporal dynamics, fast-evolving trends, and long-range and short-cyclic effects, which can lead to poor downstream performance. While domain adaptation methods can mitigate thes...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	303,166
2304.13827	Multicast Transmission Design with Enhanced DoF for MIMO Coded Caching Systems	Integrating coded caching (CC) into multi-input multi-output (MIMO) setups significantly enhances the achievable degrees of freedom (DoF). We consider a cache-aided MIMO configuration with a CC gain $t$, where a server with $L$ Tx-antennas communicates with $K$ users, each equipped with $G$ Rx-antennas. Similar to exis...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	360,718
2312.09885	Simple Weak Coresets for Non-Decomposable Classification Measures	While coresets have been growing in terms of their application, barring few exceptions, they have mostly been limited to unsupervised settings. We consider supervised classification problems, and non-decomposable evaluation measures in such settings. We show that stratified uniform sampling based coresets have excellen...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	415,918
1507.04401	Humanoid Momentum Estimation Using Sensed Contact Wrenches	This work presents approaches for the estimation of quantities important for the control of the momentum of a humanoid robot. In contrast to previous approaches which use simplified models such as the Linear Inverted Pendulum Model, we present estimators based on the momentum dynamics of the robot. By using this simple...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	45,169
2311.14904	LLM-Assisted Code Cleaning For Training Accurate Code Generators	Natural language to code generation is an important application area of LLMs and has received wide attention from the community. The majority of relevant studies have exclusively concentrated on increasing the quantity and functional correctness of training sets while disregarding other stylistic elements of programs. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	410,299
2203.14005	Learn to Adapt for Monocular Depth Estimation	Monocular depth estimation is one of the fundamental tasks in environmental perception and has achieved tremendous progress in virtue of deep learning. However, the performance of trained models tends to degrade or deteriorate when employed on other new datasets due to the gap between different datasets. Though some me...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	287,842
2411.14438	Agent-Based Modeling for Multimodal Transportation of $CO_2$ for Carbon Capture, Utilization, and Storage: CCUS-Agent	To understand the system-level interactions between the entities in Carbon Capture, Utilization, and Storage (CCUS), an agent-based foundational modeling tool, CCUS-Agent, is developed for a large-scale study of transportation flows and infrastructure in the United States. Key features of the tool include (i) modular d...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	510,160
2404.17466	FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings via Deep Neural Networks	Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity for building efficient models to identify plasma i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	449,864
2502.14471	Integrating Extra Modality Helps Segmentor Find Camouflaged Objects Well	Camouflaged Object Segmentation (COS) remains a challenging problem due to the subtle visual differences between camouflaged objects and backgrounds. Owing to the exceedingly limited visual cues available from visible spectrum, previous RGB single-modality approaches often struggle to achieve satisfactory results, prom...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	535,846
2210.01743	Covariance Steering of Discrete-Time Linear Systems with Mixed Multiplicative and Additive Noise	In this paper, we study the covariance steering (CS) problem for discrete-time linear systems subject to multiplicative and additive noise. Specifically, we consider two variants of the so-called CS problem. The goal of the first problem, which is called the exact CS problem, is to steer the mean and the covariance of ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	321,373
2304.04122	Estimation and Fault Detection on Hydraulic System with Adaptive-Scaling Kalman and Consensus Filtering	The area of fault detection is becoming more interesting since there have been many unique designs to detect or even compensate the faults, either from sensor or actuator. This paper applies the hydraulic system with interconnected tanks by implementing a leakage on one of the three tanks. The mathematical model along ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	357,085
2409.15226	Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach	Traffic routing is vital for the proper functioning of the Internet. As users and network traffic increase, researchers try to develop adaptive and intelligent routing algorithms that can fulfill various QoS requirements. Reinforcement Learning (RL) based routing algorithms have shown better performance than traditiona...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	490,811
2405.01611	Unifying and extending Precision Recall metrics for assessing generative models	With the recent success of generative models in image and text, the evaluation of generative models has gained a lot of attention. Whereas most generative models are compared in terms of scalar values such as Frechet Inception Distance (FID) or Inception Score (IS), in the last years (Sajjadi et al., 2018) proposed a d...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	451,435
2107.11703	One-Leg Stance of Humanoid Robot using Active Balance Control	The task of self-balancing is one of the most important tasks when developing humanoid robots. This paper proposes a novel external balance mechanism for humanoid robot to maintain sideway balance. First, a dynamic model of the humanoid robot with balance mechanism and its simplified model are introduced. Secondly, a b...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	247,663
2212.10428	HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios	Estimating 6D object poses is a major challenge in 3D computer vision. Building on successful instance-level approaches, research is shifting towards category-level pose estimation for practical applications. Current category-level datasets, however, fall short in annotation quality and pose variety. Addressing this, w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	337,456
2209.15146	Ensemble Machine Learning Model Trained on a New Synthesized Dataset Generalizes Well for Stress Prediction Using Wearable Devices	Introduction. We investigate the generalization ability of models built on datasets containing a small number of subjects, recorded in single study protocols. Next, we propose and evaluate methods combining these datasets into a single, large dataset. Finally, we propose and evaluate the use of ensemble techniques by c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	320,480
1309.7455	From sparse to dense and from assortative to disassortative in online social networks	Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable prop...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	27,377
2108.07555	Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays	Several real-world scenarios, such as remote control and sensing, are comprised of action and observation delays. The presence of delays degrades the performance of reinforcement learning (RL) algorithms, often to such an extent that algorithms fail to learn anything substantial. This paper formally describes the notio...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	250,953
2004.12083	Non-Linear Trajectory Optimization for Large Step-Ups: Application to the Humanoid Robot Atlas	Performing large step-ups is a challenging task for a humanoid robot. It requires the robot to perform motions at the limit of its reachable workspace while straining to move its body upon the obstacle. This paper presents a non-linear trajectory optimization method for generating step-up motions. We adopt a simplified...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	174,122
1702.04789	Achievable information rates estimates in optically-amplified transmission systems using nonlinearity compensation and probabilistic shaping	Achievable information rates (AIRs) of wideband optical communication systems using ~40 nm (~5 THz) EDFA and ~100 nm (~12.5 THz) distributed Raman amplification are estimated based on a first-order perturbation analysis. The AIRs of each individual channel have been evaluated for DP-64QAM, DP-256QAM, and DP-1024QAM mod...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,309
2105.14107	Data Acquisition for Improving Machine Learning Models	The vast advances in Machine Learning over the last ten years have been powered by the availability of suitably prepared data for training purposes. The future of ML-enabled enterprise hinges on data. As such, there is already a vibrant market offering data annotation services to tailor sophisticated ML models. In this...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	237,528
2004.03092	Spectral Efficiency and Energy Efficiency Tradeoff in Massive MIMO Downlink Transmission with Statistical CSIT	As a key technology for future wireless networks, massive multiple-input multiple-output (MIMO) can significantly improve the energy efficiency (EE) and spectral efficiency (SE), and the performance is highly dependant on the degree of the available channel state information (CSI). While most existing works on massive ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	171,444
2212.00638	Finetune like you pretrain: Improved finetuning of zero-shot vision models	Finetuning image-text models such as CLIP achieves state-of-the-art accuracies on a variety of benchmarks. However, recent works like WiseFT (Wortsman et al., 2021) and LP-FT (Kumar et al., 2022) have shown that even subtle differences in the finetuning process can lead to surprisingly large differences in the final pe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	334,135
2407.08411	CLEO: Continual Learning of Evolving Ontologies	Continual learning (CL) addresses the problem of catastrophic forgetting in neural networks, which occurs when a trained model tends to overwrite previously learned information, when presented with a new task. CL aims to instill the lifelong learning characteristic of humans in intelligent systems, making them capable ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,154
2002.11593	Appending Atomically in Byzantine Distributed Ledgers	A Distributed Ledger Object (DLO) is a concurrent object that maintains a totally ordered sequence of records, and supports two basic operations: append, which appends a record at the end of the sequence, and get, which returns the sequence of records. In this work we provide a proper formalization of a Byzantine-toler...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	165,763
1908.08563	Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics	In [1], we have explored the theoretical aspects of feature selection and evolutionary algorithms. In this chapter, we focus on optimization algorithms for enhancing data analytic process, i.e., we propose to explore applications of nature-inspired algorithms in data science. Feature selection optimization is a hybrid ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	142,582
2401.15103	PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression	Symbolic regression aims to derive interpretable symbolic expressions from data in order to better understand and interpret data. %which plays an important role in knowledge discovery and interpretable machine learning. In this study, a symbolic network called PruneSymNet is proposed for symbolic regression. This is ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	424,319
1912.00937	Lambada: Interactive Data Analytics on Cold Data using Serverless Cloud Infrastructure	The promise of ultimate elasticity and operational simplicity of serverless computing has recently lead to an explosion of research in this area. In the context of data analytics, the concept sounds appealing, but due to the limitations of current offerings, there is no consensus yet on whether or not this approach is ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	155,934
2407.04346	MobileFlow: A Multimodal LLM For Mobile GUI Agent	Currently, the integration of mobile Graphical User Interfaces (GUIs) is ubiquitous in most people's daily lives. And the ongoing evolution of multimodal large-scale models, such as GPT-4v, Qwen-VL-Max, has significantly bolstered the capabilities of GUI comprehension and user action analysis, showcasing the potentiali...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,528
2212.13504	DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation	Transformers have recently gained attention in the computer vision domain due to their ability to model long-range dependencies. However, the self-attention mechanism, which is the core part of the Transformer model, usually suffers from quadratic computational complexity with respect to the number of tokens. Many arch...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	338,322
1911.02989	Cross-Lingual Relevance Transfer for Document Retrieval	Recent work has shown the surprising ability of multi-lingual BERT to serve as a zero-shot cross-lingual transfer model for a number of language processing tasks. We combine this finding with a similarly-recently proposal on sentence-level relevance modeling for document retrieval to demonstrate the ability of multi-li...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	152,513
2304.14679	Social Media Harms as a Trilemma: Asymmetry, Algorithms, and Audacious Design Choices	Social media has expanded in its use, and reach, since the inception of early social networks in the early 2000s. Increasingly, users turn to social media for keeping up to date with current affairs and information. However, social media is increasingly used to promote disinformation and cause harm. In this contributio...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	361,063
2202.07183	A Survey of Neural Trojan Attacks and Defenses in Deep Learning	Artificial Intelligence (AI) relies heavily on deep learning - a technology that is becoming increasingly popular in real-life applications of AI, even in the safety-critical and high-risk domains. However, it is recently discovered that deep learning can be manipulated by embedding Trojans inside it. Unfortunately, pr...	false	false	false	false	true	false	false	false	false	false	false	true	true	false	false	false	false	false	280,463
2108.01518	Non-local Graph Convolutional Network for joint Activity Recognition and Motion Prediction	3D skeleton-based motion prediction and activity recognition are two interwoven tasks in human behaviour analysis. In this work, we propose a motion context modeling methodology that provides a new way to combine the advantages of both graph convolutional neural networks and recurrent neural networks for joint human mo...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	249,053
1902.10514	RESTful or RESTless -- Current State of Today's Top Web APIs	Recent developments in the world of services on the Web show that both the number of available Web APIs as well as the applications built on top is constantly increasing. This trend is commonly attributed to the wide adoption of the REST architectural principles. Still, the development of Web APIs is rather autonomous ...	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	true	122,702
2303.00673	Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness	Mitigating algorithmic bias is a critical task in the development and deployment of machine learning models. While several toolkits exist to aid machine learning practitioners in addressing fairness issues, little is known about the strategies practitioners employ to evaluate model fairness and what factors influence t...	true	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	348,678
1807.03046	Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners	This paper summarizes some recent advances on a set of tasks related to the processing of singing using state-of-the-art deep learning techniques. We discuss their achievements in terms of accuracy and sound quality, and the current challenges, such as availability of data and computing resources. We also discuss the i...	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	102,413
2411.04372	Benchmarking Large Language Models with Integer Sequence Generation Tasks	This paper presents a novel benchmark where the large language model (LLM) must write code that computes integer sequences from the Online Encyclopedia of Integer Sequences (OEIS), a widely-used resource for mathematical sequences. The benchmark is designed to evaluate both the correctness of the generated code and its...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	506,243
2003.00780	Risk-Averse Learning by Temporal Difference Methods	We consider reinforcement learning with performance evaluated by a dynamic risk measure. We construct a projected risk-averse dynamic programming equation and study its properties. Then we propose risk-averse counterparts of the methods of temporal differences and we prove their convergence with probability one. We als...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	166,416
0806.1806	Perfect Derived Propagators	When implementing a propagator for a constraint, one must decide about variants: When implementing min, should one also implement max? Should one implement linear equations both with and without coefficients? Constraint variants are ubiquitous: implementing them requires considerable (if not prohibitive) effort and dec...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	1,903
2210.15287	Learned Inertial Odometry for Autonomous Drone Racing	Inertial odometry is an attractive solution to the problem of state estimation for agile quadrotor flight. It is inexpensive, lightweight, and it is not affected by perceptual degradation. However, only relying on the integration of the inertial measurements for state estimation is infeasible. The errors and time-varyi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	326,891
2102.05179	Structure-preserving Model Reduction of Parametric Power Networks	We develop a structure-preserving parametric model reduction approach for linearized swing equations where parametrization corresponds to variations in operating conditions. We employ a global basis approach to develop the parametric reduced model in which we concatenate the local bases obtained via $\mathcal{H}_2$-bas...	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	219,347
2405.06143	Perceptual Crack Detection for Rendered 3D Textured Meshes	Recent years have witnessed many advancements in the applications of 3D textured meshes. As the demand continues to rise, evaluating the perceptual quality of this new type of media content becomes crucial for quality assurance and optimization purposes. Different from traditional image quality assessment, crack is an ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	453,185
1705.07112	Fast Singular Value Shrinkage with Chebyshev Polynomial Approximation Based on Signal Sparsity	We propose an approximation method for thresholding of singular values using Chebyshev polynomial approximation (CPA). Many signal processing problems require iterative application of singular value decomposition (SVD) for minimizing the rank of a given data matrix with other cost functions and/or constraints, which is...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	73,749
2405.10135	Self-supervised feature distillation and design of experiments for efficient training of micromechanical deep learning surrogates	Machine learning surrogate emulators are needed in engineering design and optimization tasks to rapidly emulate computationally expensive physics-based models. In micromechanics problems the local full-field response variables are desired at microstructural length scales. While there has been a great deal of work on es...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	454,657
1412.6622	Deep metric learning using Triplet network	Deep learning has proven itself as a successful set of models for learning useful semantic representations of data. These, however, are mostly implicitly learned as part of a classification task. In this paper we propose the triplet network model, which aims to learn useful representations by distance comparisons. A si...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	38,682
2411.04016	Multi-Scale and Multimodal Species Distribution Modeling	Species distribution models (SDMs) aim to predict the distribution of species by relating occurrence data with environmental variables. Recent applications of deep learning to SDMs have enabled new avenues, specifically the inclusion of spatial data (environmental rasters, satellite images) as model predictors, allowin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	506,122
2405.21040	Direct Alignment of Language Models via Quality-Aware Self-Refinement	Reinforcement Learning from Human Feedback (RLHF) has been commonly used to align the behaviors of Large Language Models (LLMs) with human preferences. Recently, a popular alternative is Direct Policy Optimization (DPO), which replaces an LLM-based reward model with the policy itself, thus obviating the need for extra ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	459,620
1804.05170	Model-Free Information Extraction in Enriched Nonlinear Phase-Space	Detecting anomalies and discovering driving signals is an essential component of scientific research and industrial practice. Often the underlying mechanism is highly complex, involving hidden evolving nonlinear dynamics and noise contamination. When representative physical models and large labeled data sets are unavai...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	95,011
2409.06720	Evolutionary Game Dynamics Applied to Strategic Adoption of Immersive Technologies in Cultural Heritage and Tourism	Immersive technologies such as Metaverse, AR, and VR are at a crossroads, with many actors pondering their adoption and potential sectors interested in integration. The cultural and tourism industries are particularly impacted, facing significant pressure to make decisions that could shape their future landscapes. Stak...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	487,245
2410.08431	oRetrieval Augmented Generation for 10 Large Language Models and its Generalizability in Assessing Medical Fitness	Large Language Models (LLMs) show potential for medical applications but often lack specialized clinical knowledge. Retrieval Augmented Generation (RAG) allows customization with domain-specific information, making it suitable for healthcare. This study evaluates the accuracy, consistency, and safety of RAG models in d...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	497,106
2410.14008	From Distributional Robustness to Robust Statistics: A Confidence Sets Perspective	We establish a connection between distributionally robust optimization (DRO) and classical robust statistics. We demonstrate that this connection arises naturally in the context of estimation under data corruption, where the goal is to construct ``minimal'' confidence sets for the unknown data-generating distribution. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	499,812
2312.11752	Learning a Diffusion Model Policy from Rewards via Q-Score Matching	Diffusion models have become a popular choice for representing actor policies in behavior cloning and offline reinforcement learning. This is due to their natural ability to optimize an expressive class of distributions over a continuous space. However, previous works fail to exploit the score-based structure of diffus...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	416,697
2212.12137	Dubbing in Practice: A Large Scale Study of Human Localization With Insights for Automatic Dubbing	We investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319.57 hours of video from 54 professionally produced titles. This is the first such large-scale study we are aware of. The results challenge a number of assumptions commonly made in both qua...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,972
2306.07298	Referring to Screen Texts with Voice Assistants	Voice assistants help users make phone calls, send messages, create events, navigate, and do a lot more. However, assistants have limited capacity to understand their users' context. In this work, we aim to take a step in this direction. Our work dives into a new experience for users to refer to phone numbers, addresse...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	372,965
1912.02209	Leveraging Prior Knowledge Asymmetries in the Design of Location Privacy-Preserving Mechanisms	The prevalence of mobile devices and Location-Based Services (LBS) necessitate the study of Location Privacy-Preserving Mechanisms (LPPM). However, LPPMs reduce the utility of LBS due to the noise they add to users' locations. Here, we consider the remapping technique, which presumes the adversary has a perfect statist...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	156,284
2402.16090	Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis	This study provides a comprehensive benchmark framework for Source-Free Unsupervised Domain Adaptation (SF-UDA) in image classification, aiming to achieve a rigorous empirical understanding of the complex relationships between multiple key design factors in SF-UDA methods. The study empirically examines a diverse set o...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	432,420
2112.07224	Exploring Category-correlated Feature for Few-shot Image Classification	Few-shot classification aims to adapt classifiers to novel classes with a few training samples. However, the insufficiency of training data may cause a biased estimation of feature distribution in a certain class. To alleviate this problem, we present a simple yet effective feature rectification method by exploring the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	271,415
2110.04234	Extremum Seeking Tracking for Derivative-free Distributed Optimization	In this paper, we deal with a network of agents that want to cooperatively minimize the sum of local cost functions depending on a common decision variable. We consider the challenging scenario in which objective functions are unknown and agents have only access to local measurements of their local functions. We propos...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	259,806
2406.15784	Data Issues in Industrial AI System: A Meta-Review and Research Strategy	In the era of Industry 4.0, artificial intelligence (AI) is assuming an increasingly pivotal role within industrial systems. Despite the recent trend within various industries to adopt AI, the actual adoption of AI is not as developed as perceived. A significant factor contributing to this lag is the data issues in AI ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	466,864
2210.12755	LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers	Transformer with its underlying attention mechanism and the ability to capture long-range dependencies makes it become a natural choice for unordered point cloud data. However, separated local regions from the general sampling architecture corrupt the structural information of the instances, and the inherent relationsh...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	325,886
2110.04654	Complex Network-Based Approach for Feature Extraction and Classification of Musical Genres	Musical genre's classification has been a relevant research topic. The association between music and genres is fundamental for the media industry, which manages musical recommendation systems, and for music streaming services, which may appear classified by genres. In this context, this work presents a feature extracti...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	259,982
0907.3099	Graph Theory and Optimization Problems for Very Large Networks	Graph theory provides a primary tool for analyzing and designing computer communication networks. In the past few decades, Graph theory has been used to study various types of networks, including the Internet, wide Area Networks, Local Area Networks, and networking protocols such as border Gateway Protocol, Open shorte...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	4,121
2204.13741	On the Arithmetic and Geometric Fusion of Beliefs for Distributed Inference	We study the asymptotic learning rates under linear and log-linear combination rules of belief vectors in a distributed hypothesis testing problem. We show that under both combination strategies, agents are able to learn the truth exponentially fast, with a faster rate under log-linear fusion. We examine the gap betwee...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	293,919
2110.12296	Cybersecurity Misinformation Detection on Social Media: Case Studies on Phishing Reports and Zoom's Threats	Prior work has extensively studied misinformation related to news, politics, and health, however, misinformation can also be about technological topics. While less controversial, such misinformation can severely impact companies' reputations and revenues, and users' online experiences. Recently, social media has also b...	false	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	false	262,789
2411.04143	Software Design Pattern Model and Data Structure Algorithm Abilities on Microservices Architecture Design in High-tech Enterprises	This study investigates the impact of software design model capabilities and data structure algorithm abilities on microservices architecture design within enterprises. Utilizing a qualitative methodology, the research involved in-depth interviews with software architects and developers who possess extensive experience...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	506,167
1306.4774	Repair Locality with Multiple Erasure Tolerance	In distributed storage systems, erasure codes with locality $r$ is preferred because a coordinate can be recovered by accessing at most $r$ other coordinates which in turn greatly reduces the disk I/O complexity for small $r$. However, the local repair may be ineffective when some of the $r$ coordinates accessed for re...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	25,343
1301.7412	Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams)	One of the benefits of belief networks and influence diagrams is that so much knowledge is captured in the graphical structure. In particular, statements of conditional irrelevance (or independence) can be verified in time linear in the size of the graph. To resolve a particular inference query or decision problem, onl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,645

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