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
2403.14120	Advancing IIoT with Over-the-Air Federated Learning: The Role of Iterative Magnitude Pruning	The industrial Internet of Things (IIoT) under Industry 4.0 heralds an era of interconnected smart devices where data-driven insights and machine learning (ML) fuse to revolutionize manufacturing. A noteworthy development in IIoT is the integration of federated learning (FL), which addresses data privacy and security a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	439,921
2405.02478	Continuous Learned Primal Dual	Neural ordinary differential equations (Neural ODEs) propose the idea that a sequence of layers in a neural network is just a discretisation of an ODE, and thus can instead be directly modelled by a parameterised ODE. This idea has had resounding success in the deep learning literature, with direct or indirect influenc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	451,775
2311.18241	LLVMs4Protest: Harnessing the Power of Large Language and Vision Models for Deciphering Protests in the News	Large language and vision models have transformed how social movements scholars identify protest and extract key protest attributes from multi-modal data such as texts, images, and videos. This article documents how we fine-tuned two large pretrained transformer models, including longformer and swin-transformer v2, to ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	411,610
2109.09354	CUNI systems for WMT21: Multilingual Low-Resource Translation for Indo-European Languages Shared Task	This paper describes Charles University submission for Multilingual Low-Resource Translation for Indo-European Languages shared task at WMT21. We competed in translation from Catalan into Romanian, Italian and Occitan. Our systems are based on shared multilingual model. We show that using joint model for multiple simil...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	256,246
2306.00223	Customized Co-Simulation Environment for Autonomous Driving Algorithm Development and Evaluation	Increasing the implemented SAE level of autonomy in road vehicles requires extensive simulations and verifications in a realistic simulation environment before proving ground and public road testing. The level of detail in the simulation environment helps ensure the safety of a real-world implementation and reduces alg...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	369,919
1701.00056	Compressed sensing and optimal denoising of monotone signals	We consider the problems of compressed sensing and optimal denoising for signals $\mathbf{x_0}\in\mathbb{R}^N$ that are monotone, i.e., $\mathbf{x_0}(i+1) \geq \mathbf{x_0}(i)$, and sparsely varying, i.e., $\mathbf{x_0}(i+1) > \mathbf{x_0}(i)$ only for a small number $k$ of indices $i$. We approach the compressed sensi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	66,219
2309.06739	MCNS: Mining Causal Natural Structures Inside Time Series via A Novel Internal Causality Scheme	Causal inference permits us to discover covert relationships of various variables in time series. However, in most existing works, the variables mentioned above are the dimensions. The causality between dimensions could be cursory, which hinders the comprehension of the internal relationship and the benefit of the caus...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	391,529
2405.18035	Instruction Tuning with Retrieval-based Examples Ranking for Aspect-based Sentiment Analysis	Aspect-based sentiment analysis (ABSA) identifies sentiment information related to specific aspects and provides deeper market insights to businesses and organizations. With the emergence of large language models (LMs), recent studies have proposed using fixed examples for instruction tuning to reformulate ABSA as a ge...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	458,246
2402.05160	What's documented in AI? Systematic Analysis of 32K AI Model Cards	The rapid proliferation of AI models has underscored the importance of thorough documentation, as it enables users to understand, trust, and effectively utilize these models in various applications. Although developers are encouraged to produce model cards, it's not clear how much information or what information these ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	427,762
2408.06818	Personalized Dynamic Difficulty Adjustment -- Imitation Learning Meets Reinforcement Learning	Balancing game difficulty in video games is a key task to create interesting gaming experiences for players. Mismatching the game difficulty and a player's skill or commitment results in frustration or boredom on the player's side, and hence reduces time spent playing the game. In this work, we explore balancing game d...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	480,358
2110.06865	Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments	Semantic role labeling (SRL) is a fundamental yet challenging task in the NLP community. Recent works of SRL mainly fall into two lines: 1) BIO-based; 2) span-based. Despite ubiquity, they share some intrinsic drawbacks of not considering internal argument structures, potentially hindering the model's expressiveness. T...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	260,769
2406.01623	WebSuite: Systematically Evaluating Why Web Agents Fail	We describe WebSuite, the first diagnostic benchmark for generalist web agents, designed to systematically evaluate why agents fail. Advances in AI have led to the rise of numerous web agents that autonomously operate a browser to complete tasks. However, most existing benchmarks focus on strictly measuring whether an ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	460,403
2402.10617	Multitask Kernel-based Learning with Logic Constraints	This paper presents a general framework to integrate prior knowledge in the form of logic constraints among a set of task functions into kernel machines. The logic propositions provide a partial representation of the environment, in which the learner operates, that is exploited by the learning algorithm together with t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	430,036
0805.0697	Stochastic Optimization Approaches for Solving Sudoku	In this paper the Sudoku problem is solved using stochastic search techniques and these are: Cultural Genetic Algorithm (CGA), Repulsive Particle Swarm Optimization (RPSO), Quantum Simulated Annealing (QSA) and the Hybrid method that combines Genetic Algorithm with Simulated Annealing (HGASA). The results obtained show...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	1,722
2405.08603	A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicine	Since the release of ChatGPT and GPT-4, large language models (LLMs) and multimodal large language models (MLLMs) have attracted widespread attention for their exceptional capabilities in understanding, reasoning, and generation, introducing transformative paradigms for integrating artificial intelligence into medicine...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	454,154
1208.0959	Recklessly Approximate Sparse Coding	It has recently been observed that certain extremely simple feature encoding techniques are able to achieve state of the art performance on several standard image classification benchmarks including deep belief networks, convolutional nets, factored RBMs, mcRBMs, convolutional RBMs, sparse autoencoders and several othe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	17,942
2007.01442	Multi-Agent Low-Dimensional Linear Bandits	We study a multi-agent stochastic linear bandit with side information, parameterized by an unknown vector $\theta^* \in \mathbb{R}^d$. The side information consists of a finite collection of low-dimensional subspaces, one of which contains $\theta^*$. In our setting, agents can collaborate to reduce regret by sending r...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	185,426
1806.04931	An image representation based convolutional network for DNA classification	The folding structure of the DNA molecule combined with helper molecules, also referred to as the chromatin, is highly relevant for the functional properties of DNA. The chromatin structure is largely determined by the underlying primary DNA sequence, though the interaction is not yet fully understood. In this paper we...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	100,351
2303.04571	A Categorical Framework of General Intelligence	Can machines think? Since Alan Turing asked this question in 1950, nobody is able to give a direct answer, due to the lack of solid mathematical foundations for general intelligence. In this paper, we introduce a categorical framework towards this goal, with two main results. First, we investigate object representation...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	350,139
cs/0702052	On Random Network Coding for Multicast	Random linear network coding is a particularly decentralized approach to the multicast problem. Use of random network codes introduces a non-zero probability however that some sinks will not be able to successfully decode the required sources. One of the main theoretical motivations for random network codes stems from ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,147
2408.05945	MV2DFusion: Leveraging Modality-Specific Object Semantics for Multi-Modal 3D Detection	The rise of autonomous vehicles has significantly increased the demand for robust 3D object detection systems. While cameras and LiDAR sensors each offer unique advantages--cameras provide rich texture information and LiDAR offers precise 3D spatial data--relying on a single modality often leads to performance limitati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	480,014
2012.12174	Fundamental Limits of Controlled Stochastic Dynamical Systems: An Information-Theoretic Approach	In this paper, we examine the fundamental performance limitations in the control of stochastic dynamical systems; more specifically, we derive generic $\mathcal{L}_p$ bounds that hold for any causal (stabilizing) controllers and any stochastic disturbances, by an information-theoretic analysis. We first consider the sc...	false	false	false	false	false	false	true	true	false	true	true	false	false	false	false	false	false	false	212,848
1111.1797	Analysis of Thompson Sampling for the multi-armed bandit problem	The multi-armed bandit problem is a popular model for studying exploration/exploitation trade-off in sequential decision problems. Many algorithms are now available for this well-studied problem. One of the earliest algorithms, given by W. R. Thompson, dates back to 1933. This algorithm, referred to as Thompson Samplin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	12,952
2309.16143	Generative Semi-supervised Learning with Meta-Optimized Synthetic Samples	Semi-supervised learning (SSL) is a promising approach for training deep classification models using labeled and unlabeled datasets. However, existing SSL methods rely on a large unlabeled dataset, which may not always be available in many real-world applications due to legal constraints (e.g., GDPR). In this paper, we...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	395,234
2204.00128	Perceptual Quality Assessment of UGC Gaming Videos	In recent years, with the vigorous development of the video game industry, the proportion of gaming videos on major video websites like YouTube has dramatically increased. However, relatively little research has been done on the automatic quality prediction of gaming videos, especially on those that fall in the categor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	289,143
1908.08074	DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer	Positron emission tomography (PET) imaging is an imaging modality for diagnosing a number of neurological diseases. In contrast to Magnetic Resonance Imaging (MRI), PET is costly and involves injecting a radioactive substance into the patient. Motivated by developments in modality transfer in vision, we study the gener...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	142,463
1912.02477	Love Me, Love Me, Say (and Write!) that You Love Me: Enriching the WASABI Song Corpus with Lyrics Annotations	We present the WASABI Song Corpus, a large corpus of songs enriched with metadata extracted from music databases on the Web, and resulting from the processing of song lyrics and from audio analysis. More specifically, given that lyrics encode an important part of the semantics of a song, we focus here on the descriptio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	156,358
2406.13301	ARDuP: Active Region Video Diffusion for Universal Policies	Sequential decision-making can be formulated as a text-conditioned video generation problem, where a video planner, guided by a text-defined goal, generates future frames visualizing planned actions, from which control actions are subsequently derived. In this work, we introduce Active Region Video Diffusion for Univer...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	465,794
1802.01159	Mining Twitter Conversations around E-commerce Promotional Events	With Social Media platforms establishing themselves as the de facto destinations for their customers views and opinions, brands around the World are investing heavily on invigorating their customer connects by utilizing such platforms to their fullest. In this paper, we develop a novel technique for mining conversation...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	89,547
2308.02039	Harnessing Web3 on Carbon Offset Market for Sustainability: Framework and A Case Study	Blockchain, pivotal in shaping the metaverse and Web3, often draws criticism for high energy consumption and carbon emission. The rise of sustainability-focused blockchains, especially when intersecting with innovative wireless technologies, revises this predicament. To understand blockchain's role in sustainability, w...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	383,461
2410.10623	Robust Gradient Descent for Phase Retrieval	Recent progress in robust statistical learning has mainly tackled convex problems, like mean estimation or linear regression, with non-convex challenges receiving less attention. Phase retrieval exemplifies such a non-convex problem, requiring the recovery of a signal from only the magnitudes of its linear measurements...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,159
2406.18624	Robust Low-Cost Drone Detection and Classification in Low SNR Environments	The proliferation of drones, or unmanned aerial vehicles (UAVs), has raised significant safety concerns due to their potential misuse in activities such as espionage, smuggling, and infrastructure disruption. This paper addresses the critical need for effective drone detection and classification systems that operate in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	468,114
2402.07191	GSINA: Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention	Graph invariant learning (GIL) has been an effective approach to discovering the invariant relationships between graph data and its labels for different graph learning tasks under various distribution shifts. Many recent endeavors of GIL focus on extracting the invariant subgraph from the input graph for prediction as ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	428,602
1602.08742	Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm	We present a novel algorithm for optimizing the order in which Chinese characters are learned, one that incorporates the benefits of learning them in order of usage frequency and in order of their hierarchal structural relationships. We show that our work outperforms previously published orders and algorithms. Our algo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	52,685
2202.01692	Review on the stabilization of non linear systems achieved by output feedback control technique	Stability and control of a non-linear system represent an important system configuration that frequently arises in practical engineering. Stability covers a vast range of systems that do not obey the superposition principle and applies to more real-world systems because all real control systems are non-linear. For effi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	278,554
2308.11578	Refashioning Emotion Recognition Modelling: The Advent of Generalised Large Models	After the inception of emotion recognition or affective computing, it has increasingly become an active research topic due to its broad applications. Over the past couple of decades, emotion recognition models have gradually migrated from statistically shallow models to neural network-based deep models, which can signi...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	387,194
2403.12201	Compositional learning of functions in humans and machines	The ability to learn and compose functions is foundational to efficient learning and reasoning in humans, enabling flexible generalizations such as creating new dishes from known cooking processes. Beyond sequential chaining of functions, existing linguistics literature indicates that humans can grasp more complex comp...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	439,072
1503.03004	Fast and Robust Fixed-Rank Matrix Recovery	We address the problem of efficient sparse fixed-rank (S-FR) matrix decomposition, i.e., splitting a corrupted matrix $M$ into an uncorrupted matrix $L$ of rank $r$ and a sparse matrix of outliers $S$. Fixed-rank constraints are usually imposed by the physical restrictions of the system under study. Here we propose a m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	41,001
2411.16111	LLMPirate: LLMs for Black-box Hardware IP Piracy	The rapid advancement of large language models (LLMs) has enabled the ability to effectively analyze and generate code nearly instantaneously, resulting in their widespread adoption in software development. Following this advancement, researchers and companies have begun integrating LLMs across the hardware design and ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	510,897
2207.11089	Do Artificial Intelligence Systems Understand?	Are intelligent machines really intelligent? Is the underlying philosophical concept of intelligence satisfactory for describing how the present systems work? Is understanding a necessary and sufficient condition for intelligence? If a machine could understand, should we attribute subjectivity to it? This paper address...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	309,495
2105.13465	Verb Sense Clustering using Contextualized Word Representations for Semantic Frame Induction	Contextualized word representations have proven useful for various natural language processing tasks. However, it remains unclear to what extent these representations can cover hand-coded semantic information such as semantic frames, which specify the semantic role of the arguments associated with a predicate. In this ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	237,309
2404.01453	Unveiling Divergent Inductive Biases of LLMs on Temporal Data	Unraveling the intricate details of events in natural language necessitates a subtle understanding of temporal dynamics. Despite the adeptness of Large Language Models (LLMs) in discerning patterns and relationships from data, their inherent comprehension of temporal dynamics remains a formidable challenge. This resear...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	443,425
1912.07254	VLSI Mask Optimization: From Shallow To Deep Learning	VLSI mask optimization is one of the most critical stages in manufacturability aware design, which is costly due to the complicated mask optimization and lithography simulation. Recent researches have shown prominent advantages of machine learning techniques dealing with complicated and big data problems, which bring p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	157,562
2008.00095	Intelligent Management of Mobile Systems through Computational Self-Awareness	Runtime resource management for many-core systems is increasingly complex. The complexity can be due to diverse workload characteristics with conflicting demands, or limited shared resources such as memory bandwidth and power. Resource management strategies for many-core systems must distribute shared resource(s) appro...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	189,894
2412.13168	Lifting Scheme-Based Implicit Disentanglement of Emotion-Related Facial Dynamics in the Wild	In-the-wild dynamic facial expression recognition (DFER) encounters a significant challenge in recognizing emotion-related expressions, which are often temporally and spatially diluted by emotion-irrelevant expressions and global context. Most prior DFER methods directly utilize coupled spatiotemporal representations t...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	518,187
2401.15912	Private Information Retrieval within 1-bit/sec/Hz of the full Gaussian MAC Capacity	In this paper, we revisit the problem of Private Information Retrieval (PIR), where there are $N$ replicated non-communicating databases containing the same $M$ messages and a user who wishes to retrieve one of the messages without revealing the message's index to the databases. However, we assume a block-fading Additi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	424,644
2403.08182	SeCG: Semantic-Enhanced 3D Visual Grounding via Cross-modal Graph Attention	3D visual grounding aims to automatically locate the 3D region of the specified object given the corresponding textual description. Existing works fail to distinguish similar objects especially when multiple referred objects are involved in the description. Experiments show that direct matching of language and visual m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	437,213
2106.08147	Perceptually-inspired super-resolution of compressed videos	Spatial resolution adaptation is a technique which has often been employed in video compression to enhance coding efficiency. This approach encodes a lower resolution version of the input video and reconstructs the original resolution during decoding. Instead of using conventional up-sampling filters, recent work has e...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	241,198
2308.03033	FourLLIE: Boosting Low-Light Image Enhancement by Fourier Frequency Information	Recently, Fourier frequency information has attracted much attention in Low-Light Image Enhancement (LLIE). Some researchers noticed that, in the Fourier space, the lightness degradation mainly exists in the amplitude component and the rest exists in the phase component. By incorporating both the Fourier frequency and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	383,871
1804.10750	Efficient Subpixel Refinement with Symbolic Linear Predictors	We present an efficient subpixel refinement method usinga learning-based approach called Linear Predictors. Two key ideas are shown in this paper. Firstly, we present a novel technique, called Symbolic Linear Predictors, which makes the learning step efficient for subpixel refinement. This makes our approach feasible f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,219
2407.16276	Continuous-Time Robust Control for Cancer Treatment Robots	The control system in surgical robots must ensure patient safety and real time control. As such, all the uncertainties which could appear should be considered into an extended model of the plant. After such an uncertain plant is formed, an adequate controller which ensures a minimum set of performances for each situati...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	475,536
2201.00097	Adversarial Attack via Dual-Stage Network Erosion	Deep neural networks are vulnerable to adversarial examples, which can fool deep models by adding subtle perturbations. Although existing attacks have achieved promising results, it still leaves a long way to go for generating transferable adversarial examples under the black-box setting. To this end, this paper propos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	273,862
2309.10835	Analysing race and sex bias in brain age prediction	Brain age prediction from MRI has become a popular imaging biomarker associated with a wide range of neuropathologies. The datasets used for training, however, are often skewed and imbalanced regarding demographics, potentially making brain age prediction models susceptible to bias. We analyse the commonly used ResNet-...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	393,174
1605.02633	Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering	State-of-the-art subspace clustering methods are based on expressing each data point as a linear combination of other data points while regularizing the matrix of coefficients with $\ell_1$, $\ell_2$ or nuclear norms. $\ell_1$ regularization is guaranteed to give a subspace-preserving affinity (i.e., there are no conne...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	55,652
2004.10863	Dense Embeddings Preserving the Semantic Relationships in WordNet	In this paper, we provide a novel way to generate low dimensional vector embeddings for the noun and verb synsets in WordNet, where the hypernym-hyponym relationship is preserved in the embeddings. We call this embedding the Sense Spectrum (and Sense Spectra for embeddings). In order to create suitable labels for the t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	173,740
2301.03953	Channel-aware Decoupling Network for Multi-turn Dialogue Comprehension	Training machines to understand natural language and interact with humans is one of the major goals of artificial intelligence. Recent years have witnessed an evolution from matching networks to pre-trained language models (PrLMs). In contrast to the plain-text modeling as the focus of the PrLMs, dialogue texts involve...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	339,924
2312.14193	Clustering and Uncertainty Analysis to Improve the Machine Learning-based Predictions of SAFARI-1 Control Follower Assembly Axial Neutron Flux Profiles	The goal of this work is to develop accurate Machine Learning (ML) models for predicting the assembly axial neutron flux profiles in the SAFARI-1 research reactor, trained by measurement data from historical cycles. The data-driven nature of ML models makes them susceptible to uncertainties which are introduced by sour...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	417,528
1802.03252	Multiple Target Tracking by Learning Feature Representation and Distance Metric Jointly	Designing a robust affinity model is the key issue in multiple target tracking (MTT). This paper proposes a novel affinity model by learning feature representation and distance metric jointly in a unified deep architecture. Specifically, we design a CNN network to obtain appearance cue tailored towards person Re-ID, an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,932
1708.06633	Nonparametric regression using deep neural networks with ReLU activation function	Consider the multivariate nonparametric regression model. It is shown that estimators based on sparsely connected deep neural networks with ReLU activation function and properly chosen network architecture achieve the minimax rates of convergence (up to $\log n$-factors) under a general composition assumption on the re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	79,351
1504.05498	DoF-Delay Trade-Off for the $K$-user MIMO Interference Channel With Delayed CSIT	The degrees of freedom (DoF) of the $K$-user multiple-input multiple-output (MIMO) interference channel are studied when perfect, but delayed channel state information is available at the transmitter side (delayed CSIT). Recent works have proposed schemes that achieve increasing DoF values, but at the cost of long comm...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,281
1201.1733	On Conditional Decomposability	The requirement of a language to be conditionally decomposable is imposed on a specification language in the coordination supervisory control framework of discrete-event systems. In this paper, we present a polynomial-time algorithm for the verification whether a language is conditionally decomposable with respect to g...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	13,736
2407.14733	Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL	With the advent of foundation models, prompt tuning has positioned itself as an important technique for directing model behaviors and eliciting desired responses. Prompt tuning regards selecting appropriate keywords included into the input, thereby adapting to the downstream task without adjusting or fine-tuning the mo...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	474,882
2203.03847	Trust in AI and Implications for the AEC Research: A Literature Analysis	Engendering trust in technically acceptable and psychologically embraceable systems requires domain-specific research to capture unique characteristics of the field of application. The architecture, engineering, and construction (AEC) research community has been recently harnessing advanced solutions offered by artific...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	284,249
1911.09879	Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality	Granger causality is a widely-used criterion for analyzing interactions in large-scale networks. As most physical interactions are inherently nonlinear, we consider the problem of inferring the existence of pairwise Granger causality between nonlinearly interacting stochastic processes from their time series measuremen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	154,655
1901.10133	Structuring an unordered text document	Segmenting an unordered text document into different sections is a very useful task in many text processing applications like multiple document summarization, question answering, etc. This paper proposes structuring of an unordered text document based on the keywords in the document. We test our approach on Wikipedia d...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	119,937
2307.00883	Augmenting Deep Learning Adaptation for Wearable Sensor Data through Combined Temporal-Frequency Image Encoding	Deep learning advancements have revolutionized scalable classification in many domains including computer vision. However, when it comes to wearable-based classification and domain adaptation, existing computer vision-based deep learning architectures and pretrained models trained on thousands of labeled images for mon...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	377,164
2002.12671	Analyzing large frequency disruptions in power systems using large deviations theory	We propose a method for determining the most likely cause, in terms of conventional generator outages and renewable fluctuations, of power system frequency reaching a predetermined level that is deemed unacceptable to the system operator. Our parsimonious model of system frequency incorporates primary and secondary con...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	166,107
2402.02355	Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning	Recent Meta-learning for Black-Box Optimization (MetaBBO) methods harness neural networks to meta-learn configurations of traditional black-box optimizers. Despite their success, they are inevitably restricted by the limitations of predefined hand-crafted optimizers. In this paper, we present \textsc{Symbol}, a novel f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	426,515
2006.15264	Attention-Guided Generative Adversarial Network to Address Atypical Anatomy in Modality Transfer	Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown rapidly in radiation therapy. However, developing class solutions for medical images that contain atypical anatomy remains a major limitation. In this paper, we propose a novel spatial attention-guided generative adversarial network...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	184,454
2309.06809	TAP: Targeted Prompting for Task Adaptive Generation of Textual Training Instances for Visual Classification	Vision and Language Models (VLMs), such as CLIP, have enabled visual recognition of a potentially unlimited set of categories described by text prompts. However, for the best visual recognition performance, these models still require tuning to better fit the data distributions of the downstream tasks, in order to overc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,556
2010.15008	Optimal Questionnaires for Screening of Strategic Agents	During the COVID-$19$ pandemic the health authorities at airports and train stations try to screen and identify the travellers possibly exposed to the virus. However, many individuals avoid getting tested and hence may misreport their travel history. This is a challenge for the health authorities who wish to ascertain ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	203,643
2405.17069	Training-free Editioning of Text-to-Image Models	Inspired by the software industry's practice of offering different editions or versions of a product tailored to specific user groups or use cases, we propose a novel task, namely, training-free editioning, for text-to-image models. Specifically, we aim to create variations of a base text-to-image model without retrain...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	457,749
1801.10056	Uplink and Downlink Transceiver Design for OFDM with Index Modulation in Multi-user Networks	A new modulation scheme called OFDM with index modulation (OFDM-IM) is introduced recently. This scheme allows to transmit additional bits by mapping a part of incoming bit stream to the indices of the subcarriers. In this work, performance of OFDM-IM in multi-user networks for uplink and downlink scenario is studied. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	89,217
2302.06754	Relatedly: Scaffolding Literature Reviews with Existing Related Work Sections	Scholars who want to research a scientific topic must take time to read, extract meaning, and identify connections across many papers. As scientific literature grows, this becomes increasingly challenging. Meanwhile, authors summarize prior research in papers' related work sections, though this is scoped to support a s...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	345,519
1103.3240	Decentralized Constraint Satisfaction	We show that several important resource allocation problems in wireless networks fit within the common framework of Constraint Satisfaction Problems (CSPs). Inspired by the requirements of these applications, where variables are located at distinct network devices that may not be able to communicate but may interfere, ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	9,642
1809.03740	Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System	In this paper we present the results of an investigation of the importance of verbs in a deep learning QA system trained on SQuAD dataset. We show that main verbs in questions carry little influence on the decisions made by the system - in over 90% of researched cases swapping verbs for their antonyms did not change sy...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	107,399
2411.15459	MambaVLT: Time-Evolving Multimodal State Space Model for Vision-Language Tracking	The vision-language tracking task aims to perform object tracking based on various modality references. Existing Transformer-based vision-language tracking methods have made remarkable progress by leveraging the global modeling ability of self-attention. However, current approaches still face challenges in effectively ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,622
2304.01042	DivClust: Controlling Diversity in Deep Clustering	Clustering has been a major research topic in the field of machine learning, one to which Deep Learning has recently been applied with significant success. However, an aspect of clustering that is not addressed by existing deep clustering methods, is that of efficiently producing multiple, diverse partitionings for a g...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,911
2210.03290	Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning	Academic networks in the real world can usually be portrayed as heterogeneous information networks (HINs) with multi-type, universally connected nodes and multi-relationships. Some existing studies for the representation learning of homogeneous information networks cannot be applicable to heterogeneous information netw...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	321,973
2005.09042	BLAZE: Blazing Fast Privacy-Preserving Machine Learning	Machine learning tools have illustrated their potential in many significant sectors such as healthcare and finance, to aide in deriving useful inferences. The sensitive and confidential nature of the data, in such sectors, raise natural concerns for the privacy of data. This motivated the area of Privacy-preserving Mac...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	177,793
2109.01467	Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations	Fast and accurate solutions of time-dependent partial differential equations (PDEs) are of pivotal interest to many research fields, including physics, engineering, and biology. Generally, implicit/semi-implicit schemes are preferred over explicit ones to improve stability and correctness. However, existing semi-implic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	253,442
2404.16672	RUMOR: Reinforcement learning for Understanding a Model of the Real World for Navigation in Dynamic Environments	Autonomous navigation in dynamic environments is a complex but essential task for autonomous robots, with recent deep reinforcement learning approaches showing promising results. However, the complexity of the real world makes it infeasible to train agents in every possible scenario configuration. Moreover, existing me...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	449,582
2110.07379	Towards Safer Transportation: a self-supervised learning approach for traffic video deraining	Video monitoring of traffic is useful for traffic management and control, traffic counting, and traffic law enforcement. However, traffic monitoring during inclement weather such as rain is a challenging task because video quality is corrupted by streaks of falling rain on the video image, and this hinders reliable cha...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	260,966
2012.09156	Learning Accurate Long-term Dynamics for Model-based Reinforcement Learning	Accurately predicting the dynamics of robotic systems is crucial for model-based control and reinforcement learning. The most common way to estimate dynamics is by fitting a one-step ahead prediction model and using it to recursively propagate the predicted state distribution over long horizons. Unfortunately, this app...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	211,978
2310.01766	Learning Causal Alignment for Reliable Disease Diagnosis	Aligning the decision-making process of machine learning algorithms with that of experienced radiologists is crucial for reliable diagnosis. While existing methods have attempted to align their diagnosis behaviors to those of radiologists reflected in the training data, this alignment is primarily associational rather ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	396,561
2312.17475	EHR Interaction Between Patients and AI: NoteAid EHR Interaction	With the rapid advancement of Large Language Models (LLMs) and their outstanding performance in semantic and contextual comprehension, the potential of LLMs in specialized domains warrants exploration. This paper introduces the NoteAid EHR Interaction Pipeline, an innovative approach developed using generative LLMs to ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	418,761
2104.06498	A multiagent based framework secured with layered SVM-based IDS for remote healthcare systems	Since the number of elderly and patients who are in hospitals and healthcare centers are growing, providing efficient remote healthcare services seems very important. Currently, most such systems benefit from the distribution and autonomy features of multiagent systems and the structure of wireless sensor networks. On ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	230,093
1709.08248	Discovery Radiomics via Deep Multi-Column Radiomic Sequencers for Skin Cancer Detection	While skin cancer is the most diagnosed form of cancer in men and women, with more cases diagnosed each year than all other cancers combined, sufficiently early diagnosis results in very good prognosis and as such makes early detection crucial. While radiomics have shown considerable promise as a powerful diagnostic to...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	81,438
2104.08160	Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration	Registering point clouds of dressed humans to parametric human models is a challenging task in computer vision. Traditional approaches often rely on heavily engineered pipelines that require accurate manual initialization of human poses and tedious post-processing. More recently, learning-based methods are proposed in ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	230,684
1302.4980	Accounting for Context in Plan Recognition, with Application to Traffic Monitoring	Typical approaches to plan recognition start from a representation of an agent's possible plans, and reason evidentially from observations of the agent's actions to assess the plausibility of the various candidates. A more expansive view of the task (consistent with some prior work) accounts for the context in which th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,254
2012.00353	Robust and Accurate Object Velocity Detection by Stereo Camera for Autonomous Driving	Although the number of camera-based sensors mounted on vehicles has recently increased dramatically, robust and accurate object velocity detection is difficult. Additionally, it is still common to use radar as a fusion system. We have developed a method to accurately detect the velocity of object using a camera, based ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	209,109
1105.5441	Computational Aspects of Reordering Plans	This article studies the problem of modifying the action ordering of a plan in order to optimise the plan according to various criteria. One of these criteria is to make a plan less constrained and the other is to minimize its parallel execution time. Three candidate definitions are proposed for the first of these crit...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,518
2403.14163	Leveraging Large Language Model-based Room-Object Relationships Knowledge for Enhancing Multimodal-Input Object Goal Navigation	Object-goal navigation is a crucial engineering task for the community of embodied navigation; it involves navigating to an instance of a specified object category within unseen environments. Although extensive investigations have been conducted on both end-to-end and modular-based, data-driven approaches, fully enabli...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	439,945
2009.08906	Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders	We present a novel generalized zero-shot algorithm to recognize perceived emotions from gestures. Our task is to map gestures to novel emotion categories not encountered in training. We introduce an adversarial, autoencoder-based representation learning that correlates 3D motion-captured gesture sequence with the vecto...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	196,382
2308.13352	A Generic Machine Learning Framework for Fully-Unsupervised Anomaly Detection with Contaminated Data	Anomaly detection (AD) tasks have been solved using machine learning algorithms in various domains and applications. The great majority of these algorithms use normal data to train a residual-based model and assign anomaly scores to unseen samples based on their dissimilarity with the learned normal regime. The underly...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	387,884
0904.1149	Chaitin \Omega numbers and halting problems	Chaitin [G. J. Chaitin, J. Assoc. Comput. Mach., vol.22, pp.329-340, 1975] introduced \Omega number as a concrete example of random real. The real \Omega is defined as the probability that an optimal computer halts, where the optimal computer is a universal decoding algorithm used to define the notion of program-size c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	3,498
1812.00440	Pedestrian Detection with Autoregressive Network Phases	We present an autoregressive pedestrian detection framework with cascaded phases designed to progressively improve precision. The proposed framework utilizes a novel lightweight stackable decoder-encoder module which uses convolutional re-sampling layers to improve features while maintaining efficient memory and runtim...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	115,256
1206.5327	XACML 3.0 in Answer Set Programming	We present a systematic technique for transforming XACML 3.0 policies in Answer Set Programming (ASP). We show that the resulting logic program has a unique answer set that directly corresponds to our formalisation of the standard semantics of XACML 3.0 from Ramli et. al. We demonstrate how our results make it possible...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,833
2404.01148	Joint Beam Scheduling and Beamforming Design for Cooperative Positioning in Multi-beam LEO Satellite Networks	Cooperative positioning with multiple low earth orbit (LEO) satellites is promising in providing location-based services and enhancing satellite-terrestrial communication. However, positioning accuracy is greatly affected by inter-beam interference and satellite-terrestrial topology geometry. To select the best combina...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	443,276
2007.14569	Space- and Computationally-Efficient Set Reconciliation via Parity Bitmap Sketch (PBS)	Set reconciliation is a fundamental algorithmic problem that arises in many networking, system, and database applications. In this problem, two large sets A and B of objects (bitcoins, files, records, etc.) are stored respectively at two different network-connected hosts, which we name Alice and Bob respectively. Alice...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	189,441

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