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
1612.00369	New Ideas for Brain Modelling 3	This paper considers a process for the creation and subsequent firing of sequences of neuronal patterns, as might be found in the human brain. The scale is one of larger patterns emerging from an ensemble mass, possibly through some type of energy equation and a reduction procedure. The links between the patterns can b...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	64,867
2208.14863	Style-Agnostic Reinforcement Learning	We present a novel method of learning style-agnostic representation using both style transfer and adversarial learning in the reinforcement learning framework. The style, here, refers to task-irrelevant details such as the color of the background in the images, where generalizing the learned policy across environments ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	315,440
2404.16250	Semgrex and Ssurgeon, Searching and Manipulating Dependency Graphs	Searching dependency graphs and manipulating them can be a time consuming and challenging task to get right. We document Semgrex, a system for searching dependency graphs, and introduce Ssurgeon, a system for manipulating the output of Semgrex. The compact language used by these systems allows for easy command line or ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	449,409
2408.11434	Near-Field Signal Processing: Unleashing the Power of Proximity	After nearly a century of specialized applications in optics, remote sensing, and acoustics, the near-field (NF) electromagnetic propagation zone is experiencing a resurgence in research interest. This renewed attention is fueled by the emergence of promising applications in various fields such as wireless communicatio...	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	482,292
2409.07032	From optimal score matching to optimal sampling	The recent, impressive advances in algorithmic generation of high-fidelity image, audio, and video are largely due to great successes in score-based diffusion models. A key implementing step is score matching, that is, the estimation of the score function of the forward diffusion process from training data. As shown in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	487,361
2111.15278	Bilingual Topic Models for Comparable Corpora	Probabilistic topic models like Latent Dirichlet Allocation (LDA) have been previously extended to the bilingual setting. A fundamental modeling assumption in several of these extensions is that the input corpora are in the form of document pairs whose constituent documents share a single topic distribution. However, t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	268,880
2211.00168	Improving Fairness in Image Classification via Sketching	Fairness is a fundamental requirement for trustworthy and human-centered Artificial Intelligence (AI) system. However, deep neural networks (DNNs) tend to make unfair predictions when the training data are collected from different sub-populations with different attributes (i.e. color, sex, age), leading to biased DNN p...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	327,773
2303.08778	Fully neuromorphic vision and control for autonomous drone flight	Biological sensing and processing is asynchronous and sparse, leading to low-latency and energy-efficient perception and action. In robotics, neuromorphic hardware for event-based vision and spiking neural networks promises to exhibit similar characteristics. However, robotic implementations have been limited to basic ...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	true	false	false	351,773
2106.00677	Bootstrap Your Own Correspondences	Geometric feature extraction is a crucial component of point cloud registration pipelines. Recent work has demonstrated how supervised learning can be leveraged to learn better and more compact 3D features. However, those approaches' reliance on ground-truth annotation limits their scalability. We propose BYOC: a self-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	238,216
2409.00215	Constraint-Aware Intent Estimation for Dynamic Human-Robot Object Co-Manipulation	Constraint-aware estimation of human intent is essential for robots to physically collaborate and interact with humans. Further, to achieve fluid collaboration in dynamic tasks intent estimation should be achieved in real-time. In this paper, we present a framework that combines online estimation and control to facilit...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	484,828
2406.04882	InstructNav: Zero-shot System for Generic Instruction Navigation in Unexplored Environment	Enabling robots to navigate following diverse language instructions in unexplored environments is an attractive goal for human-robot interaction. However, this goal is challenging because different navigation tasks require different strategies. The scarcity of instruction navigation data hinders training an instruction...	false	false	false	false	true	false	false	true	true	false	false	true	false	false	false	false	false	false	461,894
2501.00480	Lyapunov-based Resilient Secondary Synchronization Strategy of AC Microgrids Under Exponentially Energy-Unbounded FDI Attacks	This article presents fully distributed Lyapunov-based attack-resilient secondary control strategies for islanded inverter-based AC microgrids, designed to counter a broad spectrum of energy-unbounded False Data Injection (FDI) attacks, including exponential attacks, targeting control input channels. While distributed ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	521,679
2303.13364	Reevaluating Data Partitioning for Emotion Detection in EmoWOZ	This paper focuses on the EmoWoz dataset, an extension of MultiWOZ that provides emotion labels for the dialogues. MultiWOZ was partitioned initially for another purpose, resulting in a distributional shift when considering the new purpose of emotion recognition. The emotion tags in EmoWoz are highly imbalanced and une...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	353,635
2002.01862	If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills	Interview chatbots engage users in a text-based conversation to draw out their views and opinions. It is, however, challenging to build effective interview chatbots that can handle user free-text responses to open-ended questions and deliver engaging user experience. As the first step, we are investigating the feasibil...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	162,759
1106.3498	On the expressive power of unit resolution	This preliminary report addresses the expressive power of unit resolution regarding input data encoded with partial truth assignments of propositional variables. A characterization of the functions that are computable in this way, which we propose to call propagatable functions, is given. By establishing that propagata...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	10,886
2410.00242	Quantized and Asynchronous Federated Learning	Recent advances in federated learning have shown that asynchronous variants can be faster and more scalable than their synchronous counterparts. However, their design does not include quantization, which is necessary in practice to deal with the communication bottleneck. To bridge this gap, we develop a novel algorithm...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	493,281
1210.7659	The Objective Indefiniteness Interpretation of Quantum Mechanics	The common-sense view of reality is expressed logically in Boolean subset logic (each element is either definitely in or not in a subset, i.e., either definitely has or does not have a property). But quantum mechanics does not agree with this "properties all the way down" picture of micro-reality. Are there other coher...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,451
2007.01160	Tight Bounds on Minimax Regret under Logarithmic Loss via Self-Concordance	We consider the classical problem of sequential probability assignment under logarithmic loss while competing against an arbitrary, potentially nonparametric class of experts. We obtain tight bounds on the minimax regret via a new approach that exploits the self-concordance property of the logarithmic loss. We show tha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	185,342
1708.02501	Covert Communication with Channel-State Information at the Transmitter	We consider the problem of covert communication over a state-dependent channel, where the transmitter has causal or noncausal knowledge of the channel states. Here, "covert" means that a warden on the channel should observe similar statistics when the transmitter is sending a message and when it is not. When a sufficie...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	78,600
1707.09416	Vision-Based Assessment of Parkinsonism and Levodopa-Induced Dyskinesia with Deep Learning Pose Estimation	Objective: To apply deep learning pose estimation algorithms for vision-based assessment of parkinsonism and levodopa-induced dyskinesia (LID). Methods: Nine participants with Parkinson's disease (PD) and LID completed a levodopa infusion protocol, where symptoms were assessed at regular intervals using the Unified Dys...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	77,997
1506.07257	A Novel Feature Extraction Method for Scene Recognition Based on Centered Convolutional Restricted Boltzmann Machines	Scene recognition is an important research topic in computer vision, while feature extraction is a key step of object recognition. Although classical Restricted Boltzmann machines (RBM) can efficiently represent complicated data, it is hard to handle large images due to its complexity in computation. In this paper, a n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	44,500
2110.12052	A Taxonomy for Inference in Causal Model Families	Neurally-parameterized Structural Causal Models in the Pearlian notion to causality, referred to as NCM, were recently introduced as a step towards next-generation learning systems. However, said NCM are only concerned with the learning aspect of causal inference but totally miss out on the architecture aspect. That is...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	262,691
2501.12156	Characterization of Invariance, Periodic Solutions and Optimization of Dynamic Financial Networks	Cascading failures, such as bankruptcies and defaults, pose a serious threat for the resilience of the global financial system. Indeed, because of the complex investment and cross-holding relations within the system, failures can occur as a result of the propagation of a financial collapse from one organization to anot...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	526,184
2412.12801	Multi-View Incremental Learning with Structured Hebbian Plasticity for Enhanced Fusion Efficiency	The rapid evolution of multimedia technology has revolutionized human perception, paving the way for multi-view learning. However, traditional multi-view learning approaches are tailored for scenarios with fixed data views, falling short of emulating the intricate cognitive procedures of the human brain processing sign...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	518,038
2201.09976	Novel Blood Pressure Waveform Reconstruction from Photoplethysmography using Cycle Generative Adversarial Networks	Continuous monitoring of blood pressure (BP)can help individuals manage their chronic diseases such as hypertension, requiring non-invasive measurement methods in free-living conditions. Recent approaches fuse Photoplethysmograph (PPG) and electrocardiographic (ECG) signals using different machine and deep learning app...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	276,835
2111.03976	CubeLearn: End-to-end Learning for Human Motion Recognition from Raw mmWave Radar Signals	mmWave FMCW radar has attracted huge amount of research interest for human-centered applications in recent years, such as human gesture/activity recognition. Most existing pipelines are built upon conventional Discrete Fourier Transform (DFT) pre-processing and deep neural network classifier hybrid methods, with a majo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,335
2212.12649	Hyperspherical Loss-Aware Ternary Quantization	Most of the existing works use projection functions for ternary quantization in discrete space. Scaling factors and thresholds are used in some cases to improve the model accuracy. However, the gradients used for optimization are inaccurate and result in a notable accuracy gap between the full precision and ternary mod...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	338,085
1507.08449	One model, two languages: training bilingual parsers with harmonized treebanks	We introduce an approach to train lexicalized parsers using bilingual corpora obtained by merging harmonized treebanks of different languages, producing parsers that can analyze sentences in either of the learned languages, or even sentences that mix both. We test the approach on the Universal Dependency Treebanks, tra...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	45,571
2008.11784	Output Feedback Control of Coupled Linear Parabolic ODE-PDE-ODE Systems	This paper deals with the backstepping design of observer-based compensators for parabolic ODE-PDE-ODE systems. The latter consist of n coupled parabolic PDEs with distinct diffusion coefficients and spatially-varying coefficients, that are bidirectionally coupled to ODEs at both boundaries. The actuation and sensing a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	193,371
2309.12444	Foundation Metrics for Evaluating Effectiveness of Healthcare Conversations Powered by Generative AI	Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process. Chatbots, serving as interactive conversational models, will probably drive this patient-centered transformation in healthcare. Through the ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	393,798
2108.07472	Is Nash Equilibrium Approximator Learnable?	In this paper, we investigate the learnability of the function approximator that approximates Nash equilibrium (NE) for games generated from a distribution. First, we offer a generalization bound using the Probably Approximately Correct (PAC) learning model. The bound describes the gap between the expected loss and emp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	250,925
2109.07252	Modeling Ice Friction for Vehicle Dynamics of a Bobsled with Application in Driver Evaluation and Driving Simulation	We provide an ice friction model for vehicle dynamics of a two-man bobsled which can be used for driver evaluation and in a driver-in-the-loop simulator. Longitudinal friction is modeled by combining experimental results with finite element simulations to yield a correlation between contact pressure and friction. To mo...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	255,452
2404.07575	An Effective Automated Speaking Assessment Approach to Mitigating Data Scarcity and Imbalanced Distribution	Automated speaking assessment (ASA) typically involves automatic speech recognition (ASR) and hand-crafted feature extraction from the ASR transcript of a learner's speech. Recently, self-supervised learning (SSL) has shown stellar performance compared to traditional methods. However, SSL-based ASA systems are faced wi...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	445,893
1911.01485	Assessing Social and Intersectional Biases in Contextualized Word Representations	Social bias in machine learning has drawn significant attention, with work ranging from demonstrations of bias in a multitude of applications, curating definitions of fairness for different contexts, to developing algorithms to mitigate bias. In natural language processing, gender bias has been shown to exist in contex...	false	false	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	152,109
2102.00663	Densely Connected Recurrent Residual (Dense R2UNet) Convolutional Neural Network for Segmentation of Lung CT Images	Deep Learning networks have established themselves as providing state of art performance for semantic segmentation. These techniques are widely applied specifically to medical detection, segmentation and classification. The advent of the U-Net based architecture has become particularly popular for this application. In ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	217,868
1901.07446	Use of First and Third Person Views for Deep Intersection Classification	We explore the problem of intersection classification using monocular on-board passive vision, with the goal of classifying traffic scenes with respect to road topology. We divide the existing approaches into two broad categories according to the type of input data: (a) first person vision (FPV) approaches, which use a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	119,218
2007.03581	Expressiveness of SETAFs and Support-Free ADFs under 3-valued Semantics	Generalizing the attack structure in argumentation frameworks (AFs) has been studied in different ways. Most prominently, the binary attack relation of Dung frameworks has been extended to the notion of collective attacks. The resulting formalism is often termed SETAFs. Another approach is provided via abstract dialect...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	186,101
2411.06550	A Practical Validation of RIS Detection and Identification	Reconfigurable intelligent surface (RIS)-assisted communication is a key enabling technology for next-generation wireless communication networks, allowing for the reshaping of wireless channels without requiring traditional radio frequency (RF) active components. While their passive nature makes RISs highly attractive,...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	507,159
1712.07316	A Flexible Approach to Automated RNN Architecture Generation	The process of designing neural architectures requires expert knowledge and extensive trial and error. While automated architecture search may simplify these requirements, the recurrent neural network (RNN) architectures generated by existing methods are limited in both flexibility and components. We propose a domain-s...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	87,030
2411.00920	Comparative Evaluation of Applicability Domain Definition Methods for Regression Models	The applicability domain refers to the range of data for which the prediction of the predictive model is expected to be reliable and accurate and using a model outside its applicability domain can lead to incorrect results. The ability to define the regions in data space where a predictive model can be safely used is a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	504,838
2407.08187	ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimation	Estimating depth from a single image is a challenging visual task. Compared to relative depth estimation, metric depth estimation attracts more attention due to its practical physical significance and critical applications in real-life scenarios. However, existing metric depth estimation methods are typically trained o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,054
2302.01928	Aligning Robot and Human Representations	To act in the world, robots rely on a representation of salient task aspects: for example, to carry a coffee mug, a robot may consider movement efficiency or mug orientation in its behavior. However, if we want robots to act for and with people, their representations must not be just functional but also reflective of w...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	343,788
2112.03321	Noether Networks: Meta-Learning Useful Conserved Quantities	Progress in machine learning (ML) stems from a combination of data availability, computational resources, and an appropriate encoding of inductive biases. Useful biases often exploit symmetries in the prediction problem, such as convolutional networks relying on translation equivariance. Automatically discovering these...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	270,155
2105.14184	E2ETag: An End-to-End Trainable Method for Generating and Detecting Fiducial Markers	Existing fiducial markers solutions are designed for efficient detection and decoding, however, their ability to stand out in natural environments is difficult to infer from relatively limited analysis. Furthermore, worsening performance in challenging image capture scenarios - such as poor exposure, motion blur, and o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	237,564
2102.03327	Symbolic Models for Infinite Networks of Control Systems: A Compositional Approach	This paper presents a compositional framework for the construction of symbolic models for a network composed of a countably infinite number of finite-dimensional discrete-time control subsystems. We refer to such a network as infinite network. The proposed approach is based on the notion of alternating simulation funct...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	218,710
2304.03691	Feature Mining for Encrypted Malicious Traffic Detection with Deep Learning and Other Machine Learning Algorithms	The popularity of encryption mechanisms poses a great challenge to malicious traffic detection. The reason is traditional detection techniques cannot work without the decryption of encrypted traffic. Currently, research on encrypted malicious traffic detection without decryption has focused on feature extraction and th...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	356,907
2410.05183	Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics	Machine Translation (MT) evaluation metrics assess translation quality automatically. Recently, researchers have employed MT metrics for various new use cases, such as data filtering and translation re-ranking. However, most MT metrics return assessments as scalar scores that are difficult to interpret, posing a challe...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	495,607
1902.01480	What is the dimension of your binary data?	Many 0/1 datasets have a very large number of variables; on the other hand, they are sparse and the dependency structure of the variables is simpler than the number of variables would suggest. Defining the effective dimensionality of such a dataset is a nontrivial problem. We consider the problem of defining a robust m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,665
1202.5597	Hybrid Batch Bayesian Optimization	Bayesian Optimization aims at optimizing an unknown non-convex/concave function that is costly to evaluate. We are interested in application scenarios where concurrent function evaluations are possible. Under such a setting, BO could choose to either sequentially evaluate the function, one input at a time and wait for ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	14,566
1401.4221	Distortion-driven Turbulence Effect Removal using Variational Model	It remains a challenge to simultaneously remove geometric distortion and space-time-varying blur in frames captured through a turbulent atmospheric medium. To solve, or at least reduce these effects, we propose a new scheme to recover a latent image from observed frames by integrating a new variational model and distor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	30,050
2501.05414	LongProc: Benchmarking Long-Context Language Models on Long Procedural Generation	Existing benchmarks for evaluating long-context language models (LCLMs) primarily focus on long-context recall, requiring models to produce short responses based on a few critical snippets while processing thousands of irrelevant tokens. We introduce LongProc (Long Procedural Generation), a new benchmark that requires ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	523,570
2303.13912	The generation and regulation of public opinion on multiplex social networks	The dissemination of information and the development of public opinion are essential elements of most social media platforms and are often described as distinct, man-made occurrences. However, what is often disregarded is the interdependence between these two phenomena. Information dissemination serves as the foundatio...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	353,879
2405.02030	Obstacle Avoidance of Autonomous Vehicles: An LPVMPC with Scheduling Trust Region	Reference tracking and obstacle avoidance rank among the foremost challenging aspects of autonomous driving. This paper proposes control designs for solving reference tracking problems in autonomous driving tasks while considering static obstacles. We suggest a model predictive control (MPC) strategy that evades the co...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	451,600
2210.05770	Deep Active Ensemble Sampling For Image Classification	Conventional active learning (AL) frameworks aim to reduce the cost of data annotation by actively requesting the labeling for the most informative data points. However, introducing AL to data hungry deep learning algorithms has been a challenge. Some proposed approaches include uncertainty-based techniques, geometric ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	322,991
2002.09084	On the impressive performance of randomly weighted encoders in summarization tasks	In this work, we investigate the performance of untrained randomly initialized encoders in a general class of sequence to sequence models and compare their performance with that of fully-trained encoders on the task of abstractive summarization. We hypothesize that random projections of an input text have enough repres...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	164,962
2410.22899	Wormhole Loss for Partial Shape Matching	When matching parts of a surface to its whole, a fundamental question arises: Which points should be included in the matching process? The issue is intensified when using isometry to measure similarity, as it requires the validation of whether distances measured between pairs of surface points should influence the matc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	503,818
0901.0317	Design of a P System based Artificial Graph Chemistry	Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the origin of life. In this work we define a P system based artificial graph chemistry to understand the principles leading to the evolution of life-like structures in an AC set up and to develop ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	2,882
1812.01288	FaceFeat-GAN: a Two-Stage Approach for Identity-Preserving Face Synthesis	The advance of Generative Adversarial Networks (GANs) enables realistic face image synthesis. However, synthesizing face images that preserve facial identity as well as have high diversity within each identity remains challenging. To address this problem, we present FaceFeat-GAN, a novel generative model that improves ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	115,494
2111.14160	Learning To Segment Dominant Object Motion From Watching Videos	Existing deep learning based unsupervised video object segmentation methods still rely on ground-truth segmentation masks to train. Unsupervised in this context only means that no annotated frames are used during inference. As obtaining ground-truth segmentation masks for real image scenes is a laborious task, we envis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	268,511
2109.12788	Multiplicative Position-aware Transformer Models for Language Understanding	Transformer models, which leverage architectural improvements like self-attention, perform remarkably well on Natural Language Processing (NLP) tasks. The self-attention mechanism is position agnostic. In order to capture positional ordering information, various flavors of absolute and relative position embeddings have...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	257,417
2502.04353	CognArtive: Large Language Models for Automating Art Analysis and Decoding Aesthetic Elements	Art, as a universal language, can be interpreted in diverse ways, with artworks embodying profound meanings and nuances. The advent of Large Language Models (LLMs) and the availability of Multimodal Large Language Models (MLLMs) raise the question of how these transformative models can be used to assess and interpret t...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	531,097
2212.08568	Biomedical image analysis competitions: The state of current participation practice	The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the community in tackling the research questions posed. To shed light on the status qu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	336,794
2001.04174	Testing Database Engines via Pivoted Query Synthesis	Relational databases are used ubiquitously. They are managed by database management systems (DBMS), which allow inserting, modifying, and querying data using a domain-specific language called Structured Query Language (SQL). Popular DBMS have been extensively tested by fuzzers, which have been successful in finding cra...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	160,170
2305.12083	High Dimensional Geometry and Limitations in System Identification	We study the problem of identification of linear dynamical system from a single trajectory, via excitations of isotropic Gaussian. In stark contrast with previously reported results, Ordinary Least Squares (OLS) estimator for even \emph{stable} dynamical system contains non-vanishing error in \emph{high dimensions}; wh...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	365,826
1906.12087	ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network	In recent years, memory-augmented neural networks(MANNs) have shown promising power to enhance the memory ability of neural networks for sequential processing tasks. However, previous MANNs suffer from complex memory addressing mechanism, making them relatively hard to train and causing computational overheads. Moreove...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	136,840
1811.11606	Escaping Plato's Cave: 3D Shape From Adversarial Rendering	We introduce PlatonicGAN to discover the 3D structure of an object class from an unstructured collection of 2D images, i.e., where no relation between photos is known, except that they are showing instances of the same category. The key idea is to train a deep neural network to generate 3D shapes which, when rendered t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	114,816
1903.04049	Exploration of Interesting Dense Regions in Spatial Data	Nowadays, spatial data are ubiquitous in various fields of science, such as transportation and the social Web. A recent research direction in analyzing spatial data is to provide means for "exploratory analysis" of such data where analysts are guided towards interesting options in consecutive analysis iterations. Typic...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	123,887
1903.09878	Expanding the Text Classification Toolbox with Cross-Lingual Embeddings	Most work in text classification and Natural Language Processing (NLP) focuses on English or a handful of other languages that have text corpora of hundreds of millions of words. This is creating a new version of the digital divide: the artificial intelligence (AI) divide. Transfer-based approaches, such as Cross-Lingu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	125,156
1810.02525	Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods	Recent analyses of certain gradient descent optimization methods have shown that performance can degrade in some settings - such as with stochasticity or implicit momentum. In deep reinforcement learning (Deep RL), such optimization methods are often used for training neural networks via the temporal difference error o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	109,609
1802.02212	Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach	Analysis of histopathology slides is a critical step for many diagnoses, and in particular in oncology where it defines the gold standard. In the case of digital histopathological analysis, highly trained pathologists must review vast whole-slide-images of extreme digital resolution ($100,000^2$ pixels) across multiple...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	89,732
2309.01340	MDSC: Towards Evaluating the Style Consistency Between Music and Dance	We propose MDSC(Music-Dance-Style Consistency), the first evaluation metric that assesses to what degree the dance moves and music match. Existing metrics can only evaluate the motion fidelity and diversity and the degree of rhythmic matching between music and dance. MDSC measures how stylistically correlated the gener...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	389,647
2412.19944	Zero-shot Hazard Identification in Autonomous Driving: A Case Study on the COOOL Benchmark	This paper presents our submission to the COOOL competition, a novel benchmark for detecting and classifying out-of-label hazards in autonomous driving. Our approach integrates diverse methods across three core tasks: (i) driver reaction detection, (ii) hazard object identification, and (iii) hazard captioning. We prop...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	521,030
2305.05883	Level-line Guided Edge Drawing for Robust Line Segment Detection	Line segment detection plays a cornerstone role in computer vision tasks. Among numerous detection methods that have been recently proposed, the ones based on edge drawing attract increasing attention owing to their excellent detection efficiency. However, the existing methods are not robust enough due to the inadequat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	363,322
2211.09388	Data-Efficient Autoregressive Document Retrieval for Fact Verification	Document retrieval is a core component of many knowledge-intensive natural language processing task formulations such as fact verification and question answering. Sources of textual knowledge, such as Wikipedia articles, condition the generation of answers from the models. Recent advances in retrieval use sequence-to-s...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	330,959
2302.13114	Sequential Query Encoding For Complex Query Answering on Knowledge Graphs	Complex Query Answering (CQA) is an important and fundamental task for knowledge graph (KG) reasoning. Query encoding (QE) is proposed as a fast and robust solution to CQA. In the encoding process, most existing QE methods first parse the logical query into an executable computational direct-acyclic graph (DAG), then u...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	347,817
2006.06704	End-to-end Sinkhorn Autoencoder with Noise Generator	In this work, we propose a novel end-to-end sinkhorn autoencoder with noise generator for efficient data collection simulation. Simulating processes that aim at collecting experimental data is crucial for multiple real-life applications, including nuclear medicine, astronomy and high energy physics. Contemporary method...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,525
1902.03346	Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data	Connected vehicle and driver's assistance applications are greatly facilitated by Enhanced Digital Maps (EDMs) that represent roadway features (e.g., lane edges or centerlines, stop bars). Due to the large number of signalized intersections and miles of roadway, manual development of EDMs on a global basis is not feasi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	121,076
2406.14308	FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation	Single-source domain generalization (SDG) in medical image segmentation (MIS) aims to generalize a model using data from only one source domain to segment data from an unseen target domain. Despite substantial advances in SDG with data augmentation, existing methods often fail to fully consider the details and uncertai...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	466,252
1212.4507	Variational Optimization	We discuss a general technique that can be used to form a differentiable bound on the optima of non-differentiable or discrete objective functions. We form a unified description of these methods and consider under which circumstances the bound is concave. In particular we consider two concrete applications of the metho...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	20,467
2105.05080	ANDREAS: Artificial intelligence traiNing scheDuler foR accElerAted resource clusterS	Artificial Intelligence (AI) and Deep Learning (DL) algorithms are currently applied to a wide range of products and solutions. DL training jobs are highly resource demanding and they experience great benefits when exploiting AI accelerators (e.g., GPUs). However, the effective management of GPU-powered clusters comes ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	234,711
2201.03110	Towards the Next 1000 Languages in Multilingual Machine Translation: Exploring the Synergy Between Supervised and Self-Supervised Learning	Achieving universal translation between all human language pairs is the holy-grail of machine translation (MT) research. While recent progress in massively multilingual MT is one step closer to reaching this goal, it is becoming evident that extending a multilingual MT system simply by training on more parallel data is...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	274,750
2111.11986	HERO: Hessian-Enhanced Robust Optimization for Unifying and Improving Generalization and Quantization Performance	With the recent demand of deploying neural network models on mobile and edge devices, it is desired to improve the model's generalizability on unseen testing data, as well as enhance the model's robustness under fixed-point quantization for efficient deployment. Minimizing the training loss, however, provides few guara...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	267,838
2204.11524	Multi-UE Multi-AP Beam Alignment in User-Centric Cell-Free Massive MIMO Systems Operating at mmWave	This paper considers the problem of beam alignment in a cell-free massive MIMO deployment with multiple access points (APs) and multiple user equipments (UEs) simultaneously operating in the same millimeter wave frequency band. Assuming the availability of a control channel at sub-6 GHz frequencies, a protocol is devel...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	293,181
1906.10068	Is It Worth the Attention? A Comparative Evaluation of Attention Layers for Argument Unit Segmentation	Attention mechanisms have seen some success for natural language processing downstream tasks in recent years and generated new State-of-the-Art results. A thorough evaluation of the attention mechanism for the task of Argumentation Mining is missing, though. With this paper, we report a comparative evaluation of attent...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	136,347
2410.03335	Audio-Agent: Leveraging LLMs For Audio Generation, Editing and Composition	We introduce Audio-Agent, a multimodal framework for audio generation, editing and composition based on text or video inputs. Conventional approaches for text-to-audio (TTA) tasks often make single-pass inferences from text descriptions. While straightforward, this design struggles to produce high-quality audio when gi...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	494,737
1210.4900	Probability and Asset Updating using Bayesian Networks for Combinatorial Prediction Markets	A market-maker-based prediction market lets forecasters aggregate information by editing a consensus probability distribution either directly or by trading securities that pay off contingent on an event of interest. Combinatorial prediction markets allow trading on any event that can be specified as a combination of a ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	19,224
2309.09947	Deep Visual Odometry with Events and Frames	Visual Odometry (VO) is crucial for autonomous robotic navigation, especially in GPS-denied environments like planetary terrains. To improve robustness, recent model-based VO systems have begun combining standard and event-based cameras. While event cameras excel in low-light and high-speed motion, standard cameras pro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	392,803
1305.1221	Construction of two SD Codes	SD codes are erasure codes that address the mixed failure mode of current RAID systems. Rather than dedicate entire disks to erasure coding, as done in RAID-5, RAID-6 and Reed-Solomon coding, an SD code dedicates entire disks, plus individual sectors to erasure coding. The code then tolerates combinations of disk and s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	24,418
1612.04718	A Survey on Forced Oscillations in Power System	Oscillations in a power system can be categorized into free oscillations and forced oscillations. Many algorithms have been developed to estimate the modes of free oscillations in a power system. Recently, forced oscillations caught many attentions. Techniques are proposed to detect forced oscillations and locate their...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	65,563
2203.02392	Beyond Plain Toxic: Detection of Inappropriate Statements on Flammable Topics for the Russian Language	Toxicity on the Internet, such as hate speech, offenses towards particular users or groups of people, or the use of obscene words, is an acknowledged problem. However, there also exist other types of inappropriate messages which are usually not viewed as toxic, e.g. as they do not contain explicit offences. Such messag...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	283,731
2412.01527	Traversing the Subspace of Adversarial Patches	Despite ongoing research on the topic of adversarial examples in deep learning for computer vision, some fundamentals of the nature of these attacks remain unclear. As the manifold hypothesis posits, high-dimensional data tends to be part of a low-dimensional manifold. To verify the thesis with adversarial patches, thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,155
1910.07467	Root Mean Square Layer Normalization	Layer normalization (LayerNorm) has been successfully applied to various deep neural networks to help stabilize training and boost model convergence because of its capability in handling re-centering and re-scaling of both inputs and weight matrix. However, the computational overhead introduced by LayerNorm makes these...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	149,617
1804.06219	Application of the Ranking Relative Principal Component Attributes Network Model (REL-PCANet) for the Inclusive Development Index Estimation	In 2018, at the World Economic Forum in Davos it was presented a new countries' economic performance metric named the Inclusive Development Index (IDI) composed of 12 indicators. The new metric implies that countries might need to realize structural reforms for improving both economic expansion and social inclusion per...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	95,252
1408.6723	An MPC approach to output-feedback control of stochastic linear discrete-time systems	In this paper we propose an output-feedback Model Predictive Control (MPC) algorithm for linear discrete-time systems affected by a possibly unbounded additive noise and subject to probabilistic constraints. In case the noise distribution is unknown, the chance constraints on the input and state variables are reformula...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	35,652
2106.03236	Graph2Graph Learning with Conditional Autoregressive Models	We present a graph neural network model for solving graph-to-graph learning problems. Most deep learning on graphs considers ``simple'' problems such as graph classification or regressing real-valued graph properties. For such tasks, the main requirement for intermediate representations of the data is to maintain the s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	239,238
2410.14086	In-context learning and Occam's razor	A central goal of machine learning is generalization. While the No Free Lunch Theorem states that we cannot obtain theoretical guarantees for generalization without further assumptions, in practice we observe that simple models which explain the training data generalize best: a principle called Occam's razor. Despite t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	499,859
2409.10328	Fuse4Seg: Image-Level Fusion Based Multi-Modality Medical Image Segmentation	Although multi-modality medical image segmentation holds significant potential for enhancing the diagnosis and understanding of complex diseases by integrating diverse imaging modalities, existing methods predominantly rely on feature-level fusion strategies. We argue the current feature-level fusion strategy is prone ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	488,704
1310.1822	Error Rate Analysis of Cognitive Radio Transmissions with Imperfect Channel Sensing	This paper studies the symbol error rate performance of cognitive radio transmissions in the presence of imperfect sensing decisions. Two different transmission schemes, namely sensing-based spectrum sharing (SSS) and opportunistic spectrum access (OSA), are considered. In both schemes, secondary users first perform ch...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	27,601
2112.10609	An ensemble deep learning technique for detecting suicidal ideation from posts in social media platforms	Suicidal ideation detection from social media is an evolving research with great challenges. Many of the people who have the tendency to suicide share their thoughts and opinions through social media platforms. As part of many researches it is observed that the publicly available posts from social media contain valuabl...	false	false	false	true	false	true	true	false	true	false	false	false	false	false	false	false	false	false	272,485
2406.00551	Strategic Linear Contextual Bandits	Motivated by the phenomenon of strategic agents gaming a recommender system to maximize the number of times they are recommended to users, we study a strategic variant of the linear contextual bandit problem, where the arms can strategically misreport privately observed contexts to the learner. We treat the algorithm d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	459,912

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