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
2409.18169	Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey	Recent research demonstrates that the nascent fine-tuning-as-a-service business model exposes serious safety concerns -- fine-tuning over a few harmful data uploaded by the users can compromise the safety alignment of the model. The attack, known as harmful fine-tuning attack, has raised a broad research interest among...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	492,133
2306.12545	Neural Multigrid Memory For Computational Fluid Dynamics	Turbulent flow simulation plays a crucial role in various applications, including aircraft and ship design, industrial process optimization, and weather prediction. In this paper, we propose an advanced data-driven method for simulating turbulent flow, representing a significant improvement over existing approaches. Ou...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	374,968
2409.17335	Non-asymptotic Convergence of Training Transformers for Next-token Prediction	Transformers have achieved extraordinary success in modern machine learning due to their excellent ability to handle sequential data, especially in next-token prediction (NTP) tasks. However, the theoretical understanding of their performance in NTP is limited, with existing studies focusing mainly on asymptotic perfor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	491,745
1807.08905	Pilot Spoofing Attack by Multiple Eavesdroppers	In this paper, we investigate the design of a pilot spoofing attack (PSA) carried out by multiple single-antenna eavesdroppers (Eves) in a downlink time-division duplex (TDD) system, where a multiple antenna base station (BS) transmits confidential information to a single-antenna legitimate user (LU). During the uplink...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	103,623
2104.10834	DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation	Semantic segmentation of nighttime images plays an equally important role as that of daytime images in autonomous driving, but the former is much more challenging due to poor illuminations and arduous human annotations. In this paper, we propose a novel domain adaptation network (DANNet) for nighttime semantic segmenta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	231,730
1904.03870	Streamlined Dense Video Captioning	Dense video captioning is an extremely challenging task since accurate and coherent description of events in a video requires holistic understanding of video contents as well as contextual reasoning of individual events. Most existing approaches handle this problem by first detecting event proposals from a video and th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,866
2112.04177	VISOLO: Grid-Based Space-Time Aggregation for Efficient Online Video Instance Segmentation	For online video instance segmentation (VIS), fully utilizing the information from previous frames in an efficient manner is essential for real-time applications. Most previous methods follow a two-stage approach requiring additional computations such as RPN and RoIAlign, and do not fully exploit the available informat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	270,445
2302.06885	Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations	Knowledge tracing (KT) is a crucial technique to predict students' future performance by observing their historical learning processes. Due to the powerful representation ability of deep neural networks, remarkable progress has been made by using deep learning techniques to solve the KT problem. The majority of existin...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	345,566
1806.02660	Analyzing Traffic Delay at Unmanaged Intersections	At an unmanaged intersection, it is important to understand how much traffic delay may be caused as a result of microscopic vehicle interactions. Conventional traffic simulations that explicitly track these interactions are time-consuming. Prior work introduced an analytical traffic model for unmanaged intersections. T...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	99,830
2404.08264	Guided Masked Self-Distillation Modeling for Distributed Multimedia Sensor Event Analysis	Observations with distributed sensors are essential in analyzing a series of human and machine activities (referred to as 'events' in this paper) in complex and extensive real-world environments. This is because the information obtained from a single sensor is often missing or fragmented in such an environment; observa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	446,171
2205.12394	MaskEval: Weighted MLM-Based Evaluation for Text Summarization and Simplification	In text summarization and simplification, system outputs must be evaluated along multiple dimensions such as relevance, factual consistency, fluency, and grammaticality, and a wide range of possible outputs could be of high quality. These properties make the development of an adaptable, reference-less evaluation metric...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	298,510
2412.20632	EVOLVE: Emotion and Visual Output Learning via LLM Evaluation	Human acceptance of social robots is greatly effected by empathy and perceived understanding. This necessitates accurate and flexible responses to various input data from the user. While systems such as this can become increasingly complex as more states or response types are included, new research in the application o...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	521,291
1810.01270	META-DES: A Dynamic Ensemble Selection Framework using Meta-Learning	Dynamic ensemble selection systems work by estimating the level of competence of each classifier from a pool of classifiers. Only the most competent ones are selected to classify a given test sample. This is achieved by defining a criterion to measure the level of competence of a base classifier, such as, its accuracy ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	109,365
2008.04581	Using Network Embeddings for Improving Network Alignment	Network (or Graph) Alignment Algorithms aims to reveal structural similarities among graphs. In particular Local Network Alignment Algorithms (LNAs) finds local regions of similarity among two or more networks. Such algorithms are in general based on a set of seed nodes that are used to grow an alignment. Almost all LN...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	191,269
1803.04836	3D Video Quality Assessment	A key factor in designing 3D systems is to understand how different visual cues and distortions affect the perceptual quality of 3D video. The ultimate way to assess video quality is through subjective tests. However, subjective evaluation is time consuming, expensive, and in most cases not even possible. An alternativ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,526
1910.09644	ConEx: Efficient Exploration of Big-Data System Configurations for Better Performance	Configuration space complexity makes the big-data software systems hard to configure well. Consider Hadoop, with over nine hundred parameters, developers often just use the default configurations provided with Hadoop distributions. The opportunity costs in lost performance are significant. Popular learning-based approa...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	150,250
1704.02819	Flags of almost affine codes	We describe a two-party wire-tap channel of type II in the framework of almost affine codes. Its cryptological performance is related to some relative profiles of a pair of almost affine codes. These profiles are analogues of relative generalized Hamming weights in the linear case.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	71,519
2411.11693	From Spectra to Geography: Intelligent Mapping of RRUFF Mineral Data	Accurately determining the geographic origin of mineral samples is pivotal for applications in geology, mineralogy, and material science. Leveraging the comprehensive Raman spectral data from the RRUFF database, this study introduces a novel machine learning framework aimed at geolocating mineral specimens at the count...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,142
2209.12278	Neural inhibition during speech planning contributes to contrastive hyperarticulation	Previous work has demonstrated that words are hyperarticulated on dimensions of speech that differentiate them from a minimal pair competitor. This phenomenon has been termed contrastive hyperarticulation (CH). We present a dynamic neural field (DNF) model of voice onset time (VOT) planning that derives CH from an inhi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	319,475
2301.12129	Decentralized Energy Market Integrating Carbon Allowance Trade and Uncertainty Balance in Energy Communities	With the sustained attention on carbon neutrality, the personal carbon trading (PCT) scheme has been embraced as an auspicious paradigm for scaling down carbon emissions. To facilitate the simultaneous clearance of energy and carbon allowance inside the energy community while hedging against uncertainty, a joint tradin...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	342,406
2002.01441	A Generalized Flow for B2B Sales Predictive Modeling: An Azure Machine Learning Approach	Predicting the outcome of sales opportunities is a core part of successful business management. Conventionally, making this prediction has relied mostly on subjective human evaluations in the process of sales decision making. In this paper, we addressed the problem of forecasting the outcome of business to business (B2...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,650
1909.12778	Global Sparse Momentum SGD for Pruning Very Deep Neural Networks	Deep Neural Network (DNN) is powerful but computationally expensive and memory intensive, thus impeding its practical usage on resource-constrained front-end devices. DNN pruning is an approach for deep model compression, which aims at eliminating some parameters with tolerable performance degradation. In this paper, w...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	147,215
2402.01605	A Lyapunov theory demonstrating a fundamental limit on the speed of systems consolidation	The nervous system reorganizes memories from an early site to a late site, a commonly observed feature of learning and memory systems known as systems consolidation. Previous work has suggested learning rules by which consolidation may occur. Here, we provide conditions under which such rules are guaranteed to lead to ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	426,095
2401.04578	Effective pruning of web-scale datasets based on complexity of concept clusters	Utilizing massive web-scale datasets has led to unprecedented performance gains in machine learning models, but also imposes outlandish compute requirements for their training. In order to improve training and data efficiency, we here push the limits of pruning large-scale multimodal datasets for training CLIP-style mo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	420,476
2111.11023	Multi-Channel Multi-Speaker ASR Using 3D Spatial Feature	Automatic speech recognition (ASR) of multi-channel multi-speaker overlapped speech remains one of the most challenging tasks to the speech community. In this paper, we look into this challenge by utilizing the location information of target speakers in the 3D space for the first time. To explore the strength of propos...	true	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	267,524
2305.08802	Multi-Cluster Aggregative Games: A Linearly Convergent Nash Equilibrium Seeking Algorithm and its Applications in Energy Management	We propose a type of non-cooperative game, termed multi-cluster aggregative game, which is composed of clusters as players, where each cluster consists of collaborative agents with cost functions depending on their own decisions and the aggregate quantity of each participant cluster to modeling large-scale and hierarch...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	364,413
2308.00703	A Backend Platform for Supporting the Reproducibility of Computational Experiments	In recent years, the research community has raised serious questions about the reproducibility of scientific work. In particular, since many studies include some kind of computing work, reproducibility is also a technological challenge, not only in computer science, but in most research domains. Replicability and com...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	383,021
2203.00663	Iterative Residual Policy: for Goal-Conditioned Dynamic Manipulation of Deformable Objects	This paper tackles the task of goal-conditioned dynamic manipulation of deformable objects. This task is highly challenging due to its complex dynamics (introduced by object deformation and high-speed action) and strict task requirements (defined by a precise goal specification). To address these challenges, we present...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	283,080
2412.05313	{\lambda}: A Benchmark for Data-Efficiency in Long-Horizon Indoor Mobile Manipulation Robotics	Efficiently learning and executing long-horizon mobile manipulation (MoMa) tasks is crucial for advancing robotics in household and workplace settings. However, current MoMa models are data-inefficient, underscoring the need for improved models that require realistic-sized benchmarks to evaluate their efficiency, which...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	514,782
1709.03424	Constant-Weight Array Codes	Binary constant-weight codes have been extensively studied, due to both their numerous applications and to their theoretical significance. In particular, constant-weight codes have been proposed for error correction in store and forward. In this paper, we introduce constant-weight array codes (CWACs), which offer a tra...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	80,459
1208.4656	Capacity of Compound MIMO Gaussian Channels with Additive Uncertainty	This paper considers reliable communications over a multiple-input multiple-output (MIMO) Gaussian channel, where the channel matrix is within a bounded channel uncertainty region around a nominal channel matrix, i.e., an instance of the compound MIMO Gaussian channel. We study the optimal transmit covariance matrix de...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,225
2209.02200	Task-wise Sampling Convolutions for Arbitrary-Oriented Object Detection in Aerial Images	Arbitrary-oriented object detection (AOOD) has been widely applied to locate and classify objects with diverse orientations in remote sensing images. However, the inconsistent features for the localization and classification tasks in AOOD models may lead to ambiguity and low-quality object predictions, which constrains...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	316,131
1906.03973	E-LPIPS: Robust Perceptual Image Similarity via Random Transformation Ensembles	It has been recently shown that the hidden variables of convolutional neural networks make for an efficient perceptual similarity metric that accurately predicts human judgment on relative image similarity assessment. First, we show that such learned perceptual similarity metrics (LPIPS) are susceptible to adversarial ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	134,556
2408.02651	Can Reinforcement Learning Unlock the Hidden Dangers in Aligned Large Language Models?	Large Language Models (LLMs) have demonstrated impressive capabilities in natural language tasks, but their safety and morality remain contentious due to their training on internet text corpora. To address these concerns, alignment techniques have been developed to improve the public usability and safety of LLMs. Yet, ...	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	false	false	false	478,704
1905.07470	A semantic-aided particle filter approach for AUV localization	This paper presents a novel approach to AUV localization, based on a semantic-aided particle filter. Particle filters have been used successfully for robotics localization since many years. Most of the approaches are however based on geometric measurements and geometric information and simulations. In the past years mo...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	131,241
1304.1527	Decision under Uncertainty	We derive axiomatically the probability function that should be used to make decisions given any form of underlying uncertainty.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,560
2104.01284	A GPU Implementation of a Look-Ahead Optimal Controller for Eco-Driving Based on Dynamic Programming	Predictive energy management of Connected and Automated Vehicles (CAVs), in particular those with multiple power sources, has the potential to significantly improve energy savings in real-world driving conditions. In particular, the eco-driving problem seeks to design optimal speed and power usage profiles based upon a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	228,289
1301.7404	Resolving Conflicting Arguments under Uncertainties	Distributed knowledge based applications in open domain rely on common sense information which is bound to be uncertain and incomplete. To draw the useful conclusions from ambiguous data, one must address uncertainties and conflicts incurred in a holistic view. No integrated frameworks are viable without an in-depth an...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,637
2106.00050	Continual 3D Convolutional Neural Networks for Real-time Processing of Videos	We introduce Continual 3D Convolutional Neural Networks (Co3D CNNs), a new computational formulation of spatio-temporal 3D CNNs, in which videos are processed frame-by-frame rather than by clip. In online tasks demanding frame-wise predictions, Co3D CNNs dispense with the computational redundancies of regular 3D CNNs, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	237,963
2502.05497	DeepThink: Aligning Language Models with Domain-Specific User Intents	Supervised fine-tuning with synthesized instructions has been a common practice for adapting LLMs to domain-specific QA tasks. However, the synthesized instructions deviate from real user questions and expected answers. This study proposes a novel framework called DeepThink to generate high-quality instructions. DeepTh...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	531,641
1901.01347	Learning to Remember More with Less Memorization	Memory-augmented neural networks consisting of a neural controller and an external memory have shown potentials in long-term sequential learning. Current RAM-like memory models maintain memory accessing every timesteps, thus they do not effectively leverage the short-term memory held in the controller. We hypothesize t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	117,954
2112.14705	Lane Change Decision-Making through Deep Reinforcement Learning	Due to the complexity and volatility of the traffic environment, decision-making in autonomous driving is a significantly hard problem. In this project, we use a Deep Q-Network, along with rule-based constraints to make lane-changing decision. A safe and efficient lane change behavior may be obtained by combining high-...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	273,591
1808.07243	Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally	Finding regions for which there is higher controversy among different classifiers is insightful with regards to the domain and our models. Such evaluation can falsify assumptions, assert some, or also, bring to the attention unknown phenomena. The present work describes an algorithm, which is based on the Exceptional M...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	105,696
2005.10957	Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer Learning	Ovarian cancer is the most lethal cancer of the female reproductive organs. There are $5$ major histological subtypes of epithelial ovarian cancer, each with distinct morphological, genetic, and clinical features. Currently, these histotypes are determined by a pathologist's microscopic examination of tumor whole-slide...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	178,331
1712.05404	SEE: Towards Semi-Supervised End-to-End Scene Text Recognition	Detecting and recognizing text in natural scene images is a challenging, yet not completely solved task. In recent years several new systems that try to solve at least one of the two sub-tasks (text detection and text recognition) have been proposed. In this paper we present SEE, a step towards semi-supervised neural n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	86,728
1811.08564	Feature Selection Convolutional Neural Networks for Visual Tracking	Most of the existing tracking methods based on CNN(convolutional neural networks) are too slow for real-time application despite the excellent tracking precision compared with the traditional ones. Moreover, neural networks are memory intensive which will take up lots of hardware resources. In this paper, a feature sel...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,064
2203.13086	HiFi++: a Unified Framework for Bandwidth Extension and Speech Enhancement	Generative adversarial networks have recently demonstrated outstanding performance in neural vocoding outperforming best autoregressive and flow-based models. In this paper, we show that this success can be extended to other tasks of conditional audio generation. In particular, building upon HiFi vocoders, we propose a...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	287,502
1904.07735	A Graph Theory Approach for Regional Controllability of Boolean Cellular Automata	Controllability is one of the central concepts of modern control theory that allows a good understanding of a system's behaviour. It consists in constraining a system to reach the desired state from an initial state within a given time interval. When the desired objective affects only a sub-region of the domain, the co...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	127,873
2002.08616	Diversity sampling is an implicit regularization for kernel methods	Kernel methods have achieved very good performance on large scale regression and classification problems, by using the Nystr\"om method and preconditioning techniques. The Nystr\"om approximation -- based on a subset of landmarks -- gives a low rank approximation of the kernel matrix, and is known to provide a form of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	164,818
2501.03939	Visual question answering: from early developments to recent advances -- a survey	Visual Question Answering (VQA) is an evolving research field aimed at enabling machines to answer questions about visual content by integrating image and language processing techniques such as feature extraction, object detection, text embedding, natural language understanding, and language generation. With the growth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	523,048
2005.14140	Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection	Anomaly Detection (AD) in images is a fundamental computer vision problem and refers to identifying images and image substructures that deviate significantly from the norm. Popular AD algorithms commonly try to learn a model of normality from scratch using task specific datasets, but are limited to semi-supervised appr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	179,194
1804.02628	Clustering and Retrieval Method of Immunological Memory Cell in Clonal Selection Algorithm	The clonal selection principle explains the basic features of an adaptive immune response to a antigenic stimulus. It established the idea that only those cells that recognize the antigens are selected to proliferate and differentiate. This paper explains a computational implementation of the clonal selection principle...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	94,449
2311.16108	Picogrid: An experimental platform for prosumer microgrids	The Microgrid paradigm is gaining momentum as one of the key pieces of technology for expanding clean energy access and improving energy resilience. Most of the interest in this pertains to distinct entities that either generate electricity or act as loads, i.e., distinct producers and consumers. Remote community micro...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	410,761
2203.05123	Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials	Estimating treatment effects from observational data provides insights about causality guiding many real-world applications such as different clinical study designs, which are the formulations of trials, experiments, and observational studies in medical, clinical, and other types of research. In this paper, we describe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	284,712
2203.13977	Exploring Self-Attention for Visual Intersection Classification	In robot vision, self-attention has recently emerged as a technique for capturing non-local contexts. In this study, we introduced a self-attention mechanism into the intersection recognition system as a method to capture the non-local contexts behind the scenes. An intersection classification system comprises two dist...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,832
2112.08688	Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks	Retrieval-augmented generation models have shown state-of-the-art performance across many knowledge-intensive NLP tasks such as open question answering and fact verification. These models are trained to generate the final output given the retrieved passages, which can be irrelevant to the original query, leading to lea...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,898
2311.09500	Pseudo-keypoint RKHS Learning for Self-supervised 6DoF Pose Estimation	We address the simulation-to-real domain gap in six degree-of-freedom pose estimation (6DoF PE), and propose a novel self-supervised keypoint voting-based 6DoF PE framework, effectively narrowing this gap using a learnable kernel in RKHS. We formulate this domain gap as a distance in high-dimensional feature space, dis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,153
2003.10306	Safe Crossover of Neural Networks Through Neuron Alignment	One of the main and largely unexplored challenges in evolving the weights of neural networks using genetic algorithms is to find a sensible crossover operation between parent networks. Indeed, naive crossover leads to functionally damaged offspring that do not retain information from the parents. This is because neural...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	169,299
2408.03356	RayGauss: Volumetric Gaussian-Based Ray Casting for Photorealistic Novel View Synthesis	Differentiable volumetric rendering-based methods made significant progress in novel view synthesis. On one hand, innovative methods have replaced the Neural Radiance Fields (NeRF) network with locally parameterized structures, enabling high-quality renderings in a reasonable time. On the other hand, approaches have us...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	478,988
2107.08661	Translatotron 2: High-quality direct speech-to-speech translation with voice preservation	We present Translatotron 2, a neural direct speech-to-speech translation model that can be trained end-to-end. Translatotron 2 consists of a speech encoder, a linguistic decoder, an acoustic synthesizer, and a single attention module that connects them together. Experimental results on three datasets consistently show ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	246,797
2406.12560	Towards Bayesian Data Selection	A wide range of machine learning algorithms iteratively add data to the training sample. Examples include semi-supervised learning, active learning, multi-armed bandits, and Bayesian optimization. We embed this kind of data addition into decision theory by framing data selection as a decision problem. This paves the wa...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	465,462
1208.2976	Discriminating different classes of biological networks by analyzing the graphs spectra distribution	The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network a...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	18,077
1908.01057	Proposition d'un mod\`ele pour l'optimisation automatique de boucles dans le compilateur Tiramisu : cas d'optimisation de d\'eroulage	Computer architectures become more and more complex. It requires more effort to develop techniques that improve the programs of performance and allow to exploit material resources efficiently. As a result, many transformations are applied on various levels of code abstraction. The first level is the high level, where t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	140,661
2501.05309	Private Selection with Heterogeneous Sensitivities	Differentially private (DP) selection involves choosing a high-scoring candidate from a finite candidate pool, where each score depends on a sensitive dataset. This problem arises naturally in a variety of contexts including model selection, hypothesis testing, and within many DP algorithms. Classical methods, such as ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	523,538
1510.06469	Optimal Temporal Logic Planning in Probabilistic Semantic Maps	This paper considers robot motion planning under temporal logic constraints in probabilistic maps obtained by semantic simultaneous localization and mapping (SLAM). The uncertainty in a map distribution presents a great challenge for obtaining correctness guarantees with respect to the linear temporal logic (LTL) speci...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	48,110
1612.02255	Knowledge Representation in Graphs using Convolutional Neural Networks	Knowledge Graphs (KG) constitute a flexible representation of complex relationships between entities particularly useful for biomedical data. These KG, however, are very sparse with many missing edges (facts) and the visualisation of the mesh of interactions nontrivial. Here we apply a compositional model to embed node...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	65,214
2401.14469	Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels	Recent advances in depthwise-separable convolutional neural networks (DS-CNNs) have led to novel architectures, that surpass the performance of classical CNNs, by a considerable scalability and accuracy margin. This paper reveals another striking property of DS-CNN architectures: discernible and explainable patterns em...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	424,101
2302.07393	Spectral Clustering for Crowdsourcing with Inherently Distinct Task Types	The Dawid-Skene model is the most widely assumed model in the analysis of crowdsourcing algorithms that estimate ground-truth labels from noisy worker responses. In this work, we are motivated by crowdsourcing applications where workers have distinct skill sets and their accuracy additionally depends on a task's type. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	345,712
2407.16031	An Exponential Mixing Condition for Quantum Channels	Quantum channels, pivotal in information processing, describe transformations within quantum systems and enable secure communication and error correction. Ergodic and mixing properties elucidate their behavior. In this paper, we establish a sufficient condition for mixing based on a quantum Markov-Dobrushin inequality....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	475,428
1811.04491	Multiple Subspace Alignment Improves Domain Adaptation	We present a novel unsupervised domain adaptation (DA) method for cross-domain visual recognition. Though subspace methods have found success in DA, their performance is often limited due to the assumption of approximating an entire dataset using a single low-dimensional subspace. Instead, we develop a method to effect...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,104
2402.15959	Towards Robust Image Stitching: An Adaptive Resistance Learning against Compatible Attacks	Image stitching seamlessly integrates images captured from varying perspectives into a single wide field-of-view image. Such integration not only broadens the captured scene but also augments holistic perception in computer vision applications. Given a pair of captured images, subtle perturbations and distortions which...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	432,353
1504.07225	Correlational Neural Networks	Common Representation Learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, is receiving a lot of attention recently. Two popular paradigms here are Canonical Correlation Analysis (CCA) based approaches and Autoencoder (AE) based approaches. CCA based approaches learn ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	42,510
2402.17246	SDR-Former: A Siamese Dual-Resolution Transformer for Liver Lesion Classification Using 3D Multi-Phase Imaging	Automated classification of liver lesions in multi-phase CT and MR scans is of clinical significance but challenging. This study proposes a novel Siamese Dual-Resolution Transformer (SDR-Former) framework, specifically designed for liver lesion classification in 3D multi-phase CT and MR imaging with varying phase count...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	432,911
2501.09283	Free-Knots Kolmogorov-Arnold Network: On the Analysis of Spline Knots and Advancing Stability	Kolmogorov-Arnold Neural Networks (KANs) have gained significant attention in the machine learning community. However, their implementation often suffers from poor training stability and heavy trainable parameter. Furthermore, there is limited understanding of the behavior of the learned activation functions derived fr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	525,080
2306.17249	A Hybrid System for Systematic Generalization in Simple Arithmetic Problems	Solving symbolic reasoning problems that require compositionality and systematicity is considered one of the key ingredients of human intelligence. However, symbolic reasoning is still a great challenge for deep learning models, which often cannot generalize the reasoning pattern to out-of-distribution test cases. In t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	376,645
1402.3144	A Robust Ensemble Approach to Learn From Positive and Unlabeled Data Using SVM Base Models	We present a novel approach to learn binary classifiers when only positive and unlabeled instances are available (PU learning). This problem is routinely cast as a supervised task with label noise in the negative set. We use an ensemble of SVM models trained on bootstrap resamples of the training data for increased rob...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	30,844
2106.01151	Towards Deeper Deep Reinforcement Learning with Spectral Normalization	In computer vision and natural language processing, innovations in model architecture that increase model capacity have reliably translated into gains in performance. In stark contrast with this trend, state-of-the-art reinforcement learning (RL) algorithms often use small MLPs, and gains in performance typically origi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	238,408
2109.00530	A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis	We introduce a novel gradient descent algorithm extending the well-known Gradient Sampling methodology to the class of stratifiably smooth objective functions, which are defined as locally Lipschitz functions that are smooth on some regular pieces-called the strata-of the ambient Euclidean space. For this class of func...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	253,130
2209.06673	Fault-Tolerant Preparation of Quantum Polar Codes Encoding One Logical Qubit	This paper explores a new approach to fault-tolerant quantum computing (FTQC), relying on quantum polar codes. We consider quantum polar codes of Calderbank-Shor-Steane type, encoding one logical qubit, which we refer to as $\mathcal{Q}_1$ codes. First, we show that a subfamily of $\mathcal{Q}_1$ codes is equivalent to...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	317,477
2107.02839	Toward Robotically Automated Femoral Vascular Access	Advanced resuscitative technologies, such as Extra Corporeal Membrane Oxygenation (ECMO) cannulation or Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA), are technically difficult even for skilled medical personnel. This paper describes the core technologies that comprise a teleoperated system capable ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	244,955
2404.03200	Future-Proofing Class Incremental Learning	Exemplar-Free Class Incremental Learning is a highly challenging setting where replay memory is unavailable. Methods relying on frozen feature extractors have drawn attention recently in this setting due to their impressive performances and lower computational costs. However, those methods are highly dependent on the d...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	444,162
2010.05856	Exemplar-Controllable Paraphrasing and Translation using Bitext	Most prior work on exemplar-based syntactically controlled paraphrase generation relies on automatically-constructed large-scale paraphrase datasets, which are costly to create. We sidestep this prerequisite by adapting models from prior work to be able to learn solely from bilingual text (bitext). Despite only using b...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	200,277
1701.03937	Hedera: Scalable Indexing and Exploring Entities in Wikipedia Revision History	Much of work in semantic web relying on Wikipedia as the main source of knowledge often work on static snapshots of the dataset. The full history of Wikipedia revisions, while contains much more useful information, is still difficult to access due to its exceptional volume. To enable further research on this collection...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	66,780
2401.15458	A New Method for Vehicle Logo Recognition Based on Swin Transformer	Intelligent Transportation Systems (ITS) utilize sensors, cameras, and big data analysis to monitor real-time traffic conditions, aiming to improve traffic efficiency and safety. Accurate vehicle recognition is crucial in this process, and Vehicle Logo Recognition (VLR) stands as a key method. VLR enables effective man...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,452
1811.06458	Psychophysical evaluation of individual low-level feature influences on visual attention	In this study we provide the analysis of eye movement behavior elicited by low-level feature distinctiveness with a dataset of synthetically-generated image patterns. Design of visual stimuli was inspired by the ones used in previous psychophysical experiments, namely in free-viewing and visual searching tasks, to prov...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,532
2007.10629	CSLNSpeech: solving extended speech separation problem with the help of Chinese sign language	Previous audio-visual speech separation methods use the synchronization of the speaker's facial movement and speech in the video to supervise the speech separation in a self-supervised way. In this paper, we propose a model to solve the speech separation problem assisted by both face and sign language, which we call th...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,327
1905.12712	Path-Augmented Graph Transformer Network	Much of the recent work on learning molecular representations has been based on Graph Convolution Networks (GCN). These models rely on local aggregation operations and can therefore miss higher-order graph properties. To remedy this, we propose Path-Augmented Graph Transformer Networks (PAGTN) that are explicitly built...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,848
1002.2928	Reconstruction of signals with unknown spectra in information field theory with parameter uncertainty	The optimal reconstruction of cosmic metric perturbations and other signals requires knowledge of their power spectra and other parameters. If these are not known a priori, they have to be measured simultaneously from the same data used for the signal reconstruction. We formulate the general problem of signal inference...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,704
1906.07851	Key Instance Selection for Unsupervised Video Object Segmentation	This paper proposes key instance selection based on video saliency covering objectness and dynamics for unsupervised video object segmentation (UVOS). Our method takes frames sequentially and extracts object proposals with corresponding masks for each frame. We link objects according to their similarity until the M-th ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	135,701
2203.12899	Facial Expression Classification using Fusion of Deep Neural Network in Video for the 3rd ABAW3 Competition	For computers to recognize human emotions, expression classification is an equally important problem in the human-computer interaction area. In the 3rd Affective Behavior Analysis In-The-Wild competition, the task of expression classification includes eight classes with six basic expressions of human faces from videos....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,437
2303.15065	Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations	Clinical routine and retrospective cohorts commonly include multi-parametric Magnetic Resonance Imaging; however, they are mostly acquired in different anisotropic 2D views due to signal-to-noise-ratio and scan-time constraints. Thus acquired views suffer from poor out-of-plane resolution and affect downstream volumetr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,347
1507.05875	Efficient Dodgson-Score Calculation Using Heuristics and Parallel Computing	Conflict of interest is the permanent companion of any population of agents (computational or biological). For that reason, the ability to compromise is of paramount importance, making voting a key element of societal mechanisms. One of the voting procedures most often discussed in the literature and, due to its intuit...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	45,330
2204.08194	Phishing Fraud Detection on Ethereum using Graph Neural Network	Blockchain has widespread applications in the financial field but has also attracted increasing cybercrimes. Recently, phishing fraud has emerged as a major threat to blockchain security, calling for the development of effective regulatory strategies. Nowadays network science has been widely used in modeling Ethereum t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	292,002
2010.00950	Regularized K-means through hard-thresholding	We study a framework of regularized $K$-means methods based on direct penalization of the size of the cluster centers. Different penalization strategies are considered and compared through simulation and theoretical analysis. Based on the results, we propose HT $K$-means, which uses an $\ell_0$ penalty to induce sparsi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	198,453
2306.14587	Near-Field Beamforming for STAR-RIS Networks	Recently, simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have received significant research interest. The employment of large STAR-RIS and high-frequency signaling inevitably make the near-field propagation dominant in wireless communications. In this work, a STAR-RIS aided n...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	375,735
1805.10970	A Generative Model For Electron Paths	Chemical reactions can be described as the stepwise redistribution of electrons in molecules. As such, reactions are often depicted using `arrow-pushing' diagrams which show this movement as a sequence of arrows. We propose an electron path prediction model (ELECTRO) to learn these sequences directly from raw reaction ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	98,812
2406.19803	Scalable and Domain-General Abstractive Proposition Segmentation	Segmenting text into fine-grained units of meaning is important to a wide range of NLP applications. The default approach of segmenting text into sentences is often insufficient, especially since sentences are usually complex enough to include multiple units of meaning that merit separate treatment in the downstream ta...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	468,571
2501.10639	Latent-space adversarial training with post-aware calibration for defending large language models against jailbreak attacks	Ensuring safety alignment has become a critical requirement for large language models (LLMs), particularly given their widespread deployment in real-world applications. However, LLMs remain susceptible to jailbreak attacks, which exploit system vulnerabilities to bypass safety measures and generate harmful outputs. Alt...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	525,598
1205.3993	Diffusion Strategies Outperform Consensus Strategies for Distributed Estimation over Adaptive Networks	Adaptive networks consist of a collection of nodes with adaptation and learning abilities. The nodes interact with each other on a local level and diffuse information across the network to solve estimation and inference tasks in a distributed manner. In this work, we compare the mean-square performance of two main stra...	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,057
0903.5066	Modified-CS: Modifying Compressive Sensing for Problems with Partially Known Support	We study the problem of reconstructing a sparse signal from a limited number of its linear projections when a part of its support is known, although the known part may contain some errors. The ``known" part of the support, denoted T, may be available from prior knowledge. Alternatively, in a problem of recursively reco...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,436

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