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
2207.11211	Improving Predictive Performance and Calibration by Weight Fusion in Semantic Segmentation	Averaging predictions of a deep ensemble of networks is apopular and effective method to improve predictive performance andcalibration in various benchmarks and Kaggle competitions. However, theruntime and training cost of deep ensembles grow linearly with the size ofthe ensemble, making them unsuitable for many applic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,546
1207.3932	Automatic Segmentation of Manipuri (Meiteilon) Word into Syllabic Units	The work of automatic segmentation of a Manipuri language (or Meiteilon) word into syllabic units is demonstrated in this paper. This language is a scheduled Indian language of Tibeto-Burman origin, which is also a very highly agglutinative language. This language usages two script: a Bengali script and Meitei Mayek (S...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	17,522
2412.17331	Uncertainty-Participation Context Consistency Learning for Semi-supervised Semantic Segmentation	Semi-supervised semantic segmentation has attracted considerable attention for its ability to mitigate the reliance on extensive labeled data. However, existing consistency regularization methods only utilize high certain pixels with prediction confidence surpassing a fixed threshold for training, failing to fully leve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	519,930
1903.10012	A mixture of experts model for predicting persistent weather patterns	Weather and atmospheric patterns are often persistent. The simplest weather forecasting method is the so-called persistence model, which assumes that the future state of a system will be similar (or equal) to the present state. Machine learning (ML) models are widely used in different weather forecasting applications, ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	125,183
2502.04892	A Foundational Brain Dynamics Model via Stochastic Optimal Control	We introduce a foundational model for brain dynamics that utilizes stochastic optimal control (SOC) and amortized inference. Our method features a continuous-discrete state space model (SSM) that can robustly handle the intricate and noisy nature of fMRI signals. To address computational limitations, we implement an ap...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	531,357
2202.13406	Towards Unifying Logical Entailment and Statistical Estimation	This paper gives a generative model of the interpretation of formal logic for data-driven logical reasoning. The key idea is to represent the interpretation as likelihood of a formula being true given a model of formal logic. Using the likelihood, Bayes' theorem gives the posterior of the model being the case given the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	282,590
2302.04447	Contour Completion using Deep Structural Priors	Humans can easily perceive illusory contours and complete missing forms in fragmented shapes. This work investigates whether such capability can arise in convolutional neural networks (CNNs) using deep structural priors computed directly from images. In this work, we present a framework that completes disconnected cont...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	344,705
2305.00832	First- and Second-Order Bounds for Adversarial Linear Contextual Bandits	We consider the adversarial linear contextual bandit setting, which allows for the loss functions associated with each of $K$ arms to change over time without restriction. Assuming the $d$-dimensional contexts are drawn from a fixed known distribution, the worst-case expected regret over the course of $T$ rounds is kno...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,464
1702.02372	On Multilevel Coding Schemes Based on Non-Binary LDPC Codes	We address the problem of constructing of coding schemes for the channels with high-order modulations. It is known, that non-binary LDPC codes are especially good for such channels and significantly outperform their binary counterparts. Unfortunately, their decoding complexity is still large. In order to reduce the dec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,967
2105.04335	Geometrical Characterization of Sensor Placement for Cone-Invariant and Multi-Agent Systems against Undetectable Zero-Dynamics Attacks	Undetectable attacks are an important class of malicious attacks threatening the security of cyber-physical systems, which can modify a system's state but leave the system output measurements unaffected, and hence cannot be detected from the output. This paper studies undetectable attacks on cone-invariant systems and ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	234,477
2409.14088	Intelligent Reflecting Surface-Aided Multiuser Communication: Co-design of Transmit Diversity and Active/Passive Precoding	Intelligent reflecting surface (IRS) has become a cost-effective solution for constructing a smart and adaptive radio environment. Most previous works on IRS have jointly designed the active and passive precoding based on perfectly or partially known channel state information (CSI). However, in delay-sensitive or high-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	490,319
2412.07541	A data-driven learned discretization approach in finite volume schemes for hyperbolic conservation laws and varying boundary conditions	This paper presents a data-driven finite volume method for solving 1D and 2D hyperbolic partial differential equations. This work builds upon the prior research incorporating a data-driven finite-difference approximation of smooth solutions of scalar conservation laws, where optimal coefficients of neural networks appr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	515,709
1411.3230	Sparse Modeling for Image and Vision Processing	In recent years, a large amount of multi-disciplinary research has been conducted on sparse models and their applications. In statistics and machine learning, the sparsity principle is used to perform model selection---that is, automatically selecting a simple model among a large collection of them. In signal processin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	37,481
1409.5317	A Bayesian model for recognizing handwritten mathematical expressions	Recognizing handwritten mathematics is a challenging classification problem, requiring simultaneous identification of all the symbols comprising an input as well as the complex two-dimensional relationships between symbols and subexpressions. Because of the ambiguity present in handwritten input, it is often unrealisti...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	36,155
2009.04508	Narrative Maps: An Algorithmic Approach to Represent and Extract Information Narratives	Narratives are fundamental to our perception of the world and are pervasive in all activities that involve the representation of events in time. Yet, modern online information systems do not incorporate narratives in their representation of events occurring over time. This article aims to bridge this gap, combining the...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	195,055
2006.11631	Estimating Model Uncertainty of Neural Networks in Sparse Information Form	We present a sparse representation of model uncertainty for Deep Neural Networks (DNNs) where the parameter posterior is approximated with an inverse formulation of the Multivariate Normal Distribution (MND), also known as the information form. The key insight of our work is that the information matrix, i.e. the invers...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	183,308
2406.15891	The Unlikely Duel: Evaluating Creative Writing in LLMs through a Unique Scenario	This is a summary of the paper "A Confederacy of Models: a Comprehensive Evaluation of LLMs on Creative Writing", which was published in Findings of EMNLP 2023. We evaluate a range of recent state-of-the-art, instruction-tuned large language models (LLMs) on an English creative writing task, and compare them to human w...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	466,909
2010.04974	Distilling a Deep Neural Network into a Takagi-Sugeno-Kang Fuzzy Inference System	Deep neural networks (DNNs) demonstrate great success in classification tasks. However, they act as black boxes and we don't know how they make decisions in a particular classification task. To this end, we propose to distill the knowledge from a DNN into a fuzzy inference system (FIS), which is Takagi-Sugeno-Kang (TSK...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	199,944
2410.24166	Approaches to human activity recognition via passive radar	The thesis explores novel methods for Human Activity Recognition (HAR) using passive radar with a focus on non-intrusive Wi-Fi Channel State Information (CSI) data. Traditional HAR approaches often use invasive sensors like cameras or wearables, raising privacy issues. This study leverages the non-intrusive nature of C...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,356
1304.1516	Inference Policies	It is suggested that an AI inference system should reflect an inference policy that is tailored to the domain of problems to which it is applied -- and furthermore that an inference policy need not conform to any general theory of rational inference or induction. We note, for instance, that Bayesian reasoning about the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,549
1904.05083	On the $k$-error linear complexity of subsequences of $d$-ary Sidel'nikov sequences over prime field $\mathbb{F}_{d}$	We study the $k$-error linear complexity of subsequences of the $d$-ary Sidel'nikov sequences over the prime field $\mathbb{F}_{d}$. A general lower bound for the $k$-error linear complexity is given. For several special periods, we show that these sequences have large $k$-error linear complexity.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	127,208
2110.06894	Audio-Visual Scene-Aware Dialog and Reasoning using Audio-Visual Transformers with Joint Student-Teacher Learning	In previous work, we have proposed the Audio-Visual Scene-Aware Dialog (AVSD) task, collected an AVSD dataset, developed AVSD technologies, and hosted an AVSD challenge track at both the 7th and 8th Dialog System Technology Challenges (DSTC7, DSTC8). In these challenges, the best-performing systems relied heavily on hu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	260,779
2305.01733	Cross-view Action Recognition via Contrastive View-invariant Representation	Cross view action recognition (CVAR) seeks to recognize a human action when observed from a previously unseen viewpoint. This is a challenging problem since the appearance of an action changes significantly with the viewpoint. Applications of CVAR include surveillance and monitoring of assisted living facilities where ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	361,781
2103.00887	Counterfactual Zero-Shot and Open-Set Visual Recognition	We present a novel counterfactual framework for both Zero-Shot Learning (ZSL) and Open-Set Recognition (OSR), whose common challenge is generalizing to the unseen-classes by only training on the seen-classes. Our idea stems from the observation that the generated samples for unseen-classes are often out of the true dis...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	222,444
1910.10679	A Useful Taxonomy for Adversarial Robustness of Neural Networks	Adversarial attacks and defenses are currently active areas of research for the deep learning community. A recent review paper divided the defense approaches into three categories; gradient masking, robust optimization, and adversarial example detection. We divide gradient masking and robust optimization differently: (...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	150,553
2204.11822	Zero-Shot Logit Adjustment	Semantic-descriptor-based Generalized Zero-Shot Learning (GZSL) poses challenges in recognizing novel classes in the test phase. The development of generative models enables current GZSL techniques to probe further into the semantic-visual link, culminating in a two-stage form that includes a generator and a classifier...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	293,270
1911.10120	Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighbourhood Structures	Multi-agent coordination is prevalent in many real-world applications. However, such coordination is challenging due to its combinatorial nature. An important observation in this regard is that agents in the real world often only directly affect a limited set of neighbouring agents. Leveraging such loose couplings amon...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	154,737
2306.13956	Pointwise-in-Time Explanation for Linear Temporal Logic Rules	The new field of Explainable Planning (XAIP) has produced a variety of approaches to explain and describe the behavior of autonomous agents to human observers. Many summarize agent behavior in terms of the constraints, or ''rules,'' which the agent adheres to during its trajectories. In this work, we narrow the focus f...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	375,473
2412.11521	On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory	Symmetries (transformations by group actions) are present in many datasets, and leveraging them holds significant promise for improving predictions in machine learning. In this work, we aim to understand when and how deep networks can learn symmetries from data. We focus on a supervised classification paradigm where da...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	517,455
2409.12929	LogicPro: Improving Complex Logical Reasoning via Program-Guided Learning	In this paper, we propose a new data synthesis method called \textbf{LogicPro}, which leverages LeetCode-style algorithm \underline{Pro}blems and their corresponding \underline{Pro}gram solutions to synthesize Complex \underline{Logic}al Reasoning data in text format. First, we synthesize complex reasoning problems thr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	489,775
2101.05205	Automated 3D cephalometric landmark identification using computerized tomography	Identification of 3D cephalometric landmarks that serve as proxy to the shape of human skull is the fundamental step in cephalometric analysis. Since manual landmarking from 3D computed tomography (CT) images is a cumbersome task even for the trained experts, automatic 3D landmark detection system is in a great need. R...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	215,359
2205.01711	On the Level Crossing Rate of Fluid Antenna Systems	Multiple-input multiple-output (MIMO) technology has significantly impacted wireless communication, by providing extraordinary performance gains. However, a minimum inter-antenna space constraint in MIMO systems does not allow its integration in devices with limited space. In this context, the concept of fluid antenna ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	294,688
1711.09130	Temporal Properties in Component-Based Cyber Physical Systems - Appendix	In this document, we provide supplementary material to a paper that will be published in ERTS2. It includes a more detailed description of the described requirement transformations, outlined in the paper. For this purpose, we also provide a formal description of the temporal semantics model.	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	85,330
2302.01035	Deep Learning Based Predictive Beamforming Design	This paper investigates deep learning techniques to predict transmit beamforming based on only historical channel data without current channel information in the multiuser multiple-input-single-output downlink. This will significantly reduce the channel estimation overhead and improve the spectrum efficiency especially...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	343,457
2109.07433	Encoding and Decoding with Partitioned Complementary Sequences for Low-PAPR OFDM	In this study, we propose partitioned complementary sequences (CSs) where the gaps between the clusters encode information bits to achieve low peak-to-average-power ratio (PAPR) orthogonal frequency division multiplexing (OFDM) symbols. We show that the partitioning rule without losing the feature of being a CS coincid...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	255,519
2201.07120	Contextual road lane and symbol generation for autonomous driving	In this paper we present a novel approach for lane detection and segmentation using generative models. Traditionally discriminative models have been employed to classify pixels semantically on a road. We model the probability distribution of lanes and road symbols by training a generative adversarial network. Based on ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	275,936
2203.03638	Unsupervised Image Registration Towards Enhancing Performance and Explainability in Cardiac And Brain Image Analysis	Magnetic Resonance Imaging (MRI) typically recruits multiple sequences (defined here as "modalities"). As each modality is designed to offer different anatomical and functional clinical information, there are evident disparities in the imaging content across modalities. Inter- and intra-modality affine and non-rigid im...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	284,171
quant-ph/0411140	Improved Bounds on Quantum Learning Algorithms	In this article we give several new results on the complexity of algorithms that learn Boolean functions from quantum queries and quantum examples. Hunziker et al. conjectured that for any class C of Boolean functions, the number of quantum black-box queries which are required to exactly identify an unknown function ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	540,880
2305.17198	A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem	Training multiple agents to coordinate is an essential problem with applications in robotics, game theory, economics, and social sciences. However, most existing Multi-Agent Reinforcement Learning (MARL) methods are online and thus impractical for real-world applications in which collecting new interactions is costly o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	368,457
2311.18576	Fixed-length Dense Descriptor for Efficient Fingerprint Matching	In fingerprint matching, fixed-length descriptors generally offer greater efficiency compared to minutiae set, but the recognition accuracy is not as good as that of the latter. Although much progress has been made in deep learning based fixed-length descriptors recently, they often fall short when dealing with incompl...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	411,731
1806.01186	Penalizing side effects using stepwise relative reachability	How can we design safe reinforcement learning agents that avoid unnecessary disruptions to their environment? We show that current approaches to penalizing side effects can introduce bad incentives, e.g. to prevent any irreversible changes in the environment, including the actions of other agents. To isolate the source...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	99,499
2407.21363	ESIQA: Perceptual Quality Assessment of Vision-Pro-based Egocentric Spatial Images	With the development of eXtended Reality (XR), head-mounted shooting and display technology have experienced significant advancement and gained considerable attention. Egocentric spatial images and videos are emerging as a compelling form of stereoscopic XR content. Different from traditional 2D images, egocentric spat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	477,509
2409.03024	NUMOSIM: A Synthetic Mobility Dataset with Anomaly Detection Benchmarks	Collecting real-world mobility data is challenging. It is often fraught with privacy concerns, logistical difficulties, and inherent biases. Moreover, accurately annotating anomalies in large-scale data is nearly impossible, as it demands meticulous effort to distinguish subtle and complex patterns. These challenges si...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	485,896
2409.19846	Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels	Large-scale vision-language models like CLIP have demonstrated impressive open-vocabulary capabilities for image-level tasks, excelling in recognizing what objects are present. However, they struggle with pixel-level recognition tasks like semantic segmentation, which additionally require understanding where the object...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	492,880
1805.08562	Best of many worlds: Robust model selection for online supervised learning	We introduce algorithms for online, full-information prediction that are competitive with contextual tree experts of unknown complexity, in both probabilistic and adversarial settings. We show that by incorporating a probabilistic framework of structural risk minimization into existing adaptive algorithms, we can robus...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	98,172
1804.01189	Real-Time Prediction of the Duration of Distribution System Outages	This paper addresses the problem of predicting duration of unplanned power outages, using historical outage records to train a series of neural network predictors. The initial duration prediction is made based on environmental factors, and it is updated based on incoming field reports using natural language processing ...	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	94,187
2002.11045	Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks	In the future 6th generation networks, ultra-reliable and low-latency communications (URLLC) will lay the foundation for emerging mission-critical applications that have stringent requirements on end-to-end delay and reliability. Existing works on URLLC are mainly based on theoretical models and assumptions. The model-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	165,596
2202.01011	Auto-Transfer: Learning to Route Transferrable Representations	Knowledge transfer between heterogeneous source and target networks and tasks has received a lot of attention in recent times as large amounts of quality labeled data can be difficult to obtain in many applications. Existing approaches typically constrain the target deep neural network (DNN) feature representations to ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	278,342
2206.09731	Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers	Semantic segmentation necessitates approaches that learn high-level characteristics while dealing with enormous amounts of data. Convolutional neural networks (CNNs) can learn unique and adaptive features to achieve this aim. However, due to the large size and high spatial resolution of remote sensing images, these net...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	303,669
2301.09715	PrimeQA: The Prime Repository for State-of-the-Art Multilingual Question Answering Research and Development	The field of Question Answering (QA) has made remarkable progress in recent years, thanks to the advent of large pre-trained language models, newer realistic benchmark datasets with leaderboards, and novel algorithms for key components such as retrievers and readers. In this paper, we introduce PRIMEQA: a one-stop and ...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	341,576
2305.05065	Recommender Systems with Generative Retrieval	Modern recommender systems perform large-scale retrieval by first embedding queries and item candidates in the same unified space, followed by approximate nearest neighbor search to select top candidates given a query embedding. In this paper, we propose a novel generative retrieval approach, where the retrieval model ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	362,986
2305.05214	CharSpan: Utilizing Lexical Similarity to Enable Zero-Shot Machine Translation for Extremely Low-resource Languages	We address the task of machine translation (MT) from extremely low-resource language (ELRL) to English by leveraging cross-lingual transfer from 'closely-related' high-resource language (HRL). The development of an MT system for ELRL is challenging because these languages typically lack parallel corpora and monolingual...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	363,053
2009.01312	A Simple Global Neural Discourse Parser	Discourse parsing is largely dominated by greedy parsers with manually-designed features, while global parsing is rare due to its computational expense. In this paper, we propose a simple chart-based neural discourse parser that does not require any manually-crafted features and is based on learned span representations...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	194,268
2407.11730	Monocular Occupancy Prediction for Scalable Indoor Scenes	Camera-based 3D occupancy prediction has recently garnered increasing attention in outdoor driving scenes. However, research in indoor scenes remains relatively unexplored. The core differences in indoor scenes lie in the complexity of scene scale and the variance in object size. In this paper, we propose a novel metho...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,591
1803.04345	Sparse 3D Topological Graphs for Micro-Aerial Vehicle Planning	Micro-Aerial Vehicles (MAVs) have the advantage of moving freely in 3D space. However, creating compact and sparse map representations that can be efficiently used for planning for such robots is still an open problem. In this paper, we take maps built from noisy sensor data and construct a sparse graph containing topo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	92,438
1807.04049	Perception of Image Features in Post-Mortem Iris Recognition: Humans vs Machines	Post-mortem iris recognition can offer an additional forensic method of personal identification. However, in contrary to already well-established human examination of fingerprints, making iris recognition human-interpretable is harder, and therefore it has never been applied in forensic proceedings. There is no strong ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	102,657
1706.02153	Usage Bibliometrics as a Tool to Measure Research Activity	Measures for research activity and impact have become an integral ingredient in the assessment of a wide range of entities (individual researchers, organizations, instruments, regions, disciplines). Traditional bibliometric indicators, like publication and citation based indicators, provide an essential part of this pi...	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	true	74,923
2201.08455	LOSTIN: Logic Optimization via Spatio-Temporal Information with Hybrid Graph Models	Despite the stride made by machine learning (ML) based performance modeling, two major concerns that may impede production-ready ML applications in EDA are stringent accuracy requirements and generalization capability. To this end, we propose hybrid graph neural network (GNN) based approaches towards highly accurate qu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	276,341
2310.08574	Jigsaw: Supporting Designers to Prototype Multimodal Applications by Chaining AI Foundation Models	Recent advancements in AI foundation models have made it possible for them to be utilized off-the-shelf for creative tasks, including ideating design concepts or generating visual prototypes. However, integrating these models into the creative process can be challenging as they often exist as standalone applications ta...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	399,439
1302.1571	Score and Information for Recursive Exponential Models with Incomplete Data	Recursive graphical models usually underlie the statistical modelling concerning probabilistic expert systems based on Bayesian networks. This paper defines a version of these models, denoted as recursive exponential models, which have evolved by the desire to impose sophisticated domain knowledge onto local fragments ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,871
1905.05150	AMZ Driverless: The Full Autonomous Racing System	This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and extensibility. In order to autonomously race around a previously unknown track, the proposed solution combines state of the art techniques ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	130,644
2101.06103	Is the Chen-Sbert Divergence a Metric?	Recently, Chen and Sbert proposed a general divergence measure. This report presents some interim findings about the question whether the divergence measure is a metric or not. It has been postulated that (i) the measure might be a metric when (0 < k <= 1), and (ii) the k-th root of the measure might be a metric when (...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	215,611
2304.14610	ALL-E: Aesthetics-guided Low-light Image Enhancement	Evaluating the performance of low-light image enhancement (LLE) is highly subjective, thus making integrating human preferences into image enhancement a necessity. Existing methods fail to consider this and present a series of potentially valid heuristic criteria for training enhancement models. In this paper, we propo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	361,035
2006.04760	Outlier Detection Using a Novel method: Quantum Clustering	We propose a new assumption in outlier detection: Normal data instances are commonly located in the area that there is hardly any fluctuation on data density, while outliers are often appeared in the area that there is violent fluctuation on data density. And based on this hypothesis, we apply a novel density-based app...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	180,813
1707.04859	Constructions of Optimal and Near-Optimal Quasi-Complementary Sequence Sets from an Almost Difference Set	Compared with the perfect complementary sequence sets, quasi-complementary sequence sets (QCSSs) can support more users to work in multicarrier CDMA communications. A near-optimal periodic QCSS is constructed in this paper by using an optimal quaternary sequence set and an almost difference set. With the change of the ...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	77,115
2107.10373	A Public Ground-Truth Dataset for Handwritten Circuit Diagram Images	The development of digitization methods for line drawings (especially in the area of electrical engineering) relies on the availability of publicly available training and evaluation data. This paper presents such an image set along with annotations. The dataset consists of 1152 images of 144 circuits by 12 drafters and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	247,275
2401.03726	UAV-enabled Integrated Sensing and Communication: Tracking Design and Optimization	Integrated sensing and communications (ISAC) enabled by unmanned aerial vehicles (UAVs) is a promising technology to facilitate target tracking applications. In contrast to conventional UAV-based ISAC system designs that mainly focus on estimating the target position, the target velocity estimation also needs to be con...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	420,207
2204.04612	Confidence Estimation Transformer for Long-term Renewable Energy Forecasting in Reinforcement Learning-based Power Grid Dispatching	The expansion of renewable energy could help realizing the goals of peaking carbon dioxide emissions and carbon neutralization. Some existing grid dispatching methods integrating short-term renewable energy prediction and reinforcement learning (RL) have been proved to alleviate the adverse impact of energy fluctuation...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	290,715
1606.02407	Structured Convolution Matrices for Energy-efficient Deep learning	We derive a relationship between network representation in energy-efficient neuromorphic architectures and block Toplitz convolutional matrices. Inspired by this connection, we develop deep convolutional networks using a family of structured convolutional matrices and achieve state-of-the-art trade-off between energy e...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	56,955
2311.07499	Bridging the Sim-to-Real Gap with Dynamic Compliance Tuning for Industrial Insertion	Contact-rich manipulation tasks often exhibit a large sim-to-real gap. For instance, industrial assembly tasks frequently involve tight insertions where the clearance is less than 0.1 mm and can even be negative when dealing with a deformable receptacle. This narrow clearance leads to complex contact dynamics that are ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	407,349
2408.00901	A value-focused thinking approach to measure community resilience	Community resilience refers to the ability to prepare for, absorb, recover from, and adapt to disruptive events, but specific definitions and measures for resilience can vary widely from researcher to researcher or from discipline to discipline. Community resilience is often measured using a set of indicators based on ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	478,019
2101.05022	Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels	ImageNet has been arguably the most popular image classification benchmark, but it is also the one with a significant level of label noise. Recent studies have shown that many samples contain multiple classes, despite being assumed to be a single-label benchmark. They have thus proposed to turn ImageNet evaluation into...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	215,311
2010.15560	Genetic U-Net: Automatically Designed Deep Networks for Retinal Vessel Segmentation Using a Genetic Algorithm	Recently, many methods based on hand-designed convolutional neural networks (CNNs) have achieved promising results in automatic retinal vessel segmentation. However, these CNNs remain constrained in capturing retinal vessels in complex fundus images. To improve their segmentation performance, these CNNs tend to have ma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	203,807
1102.1475	Security Embedding Codes	This paper considers the problem of simultaneously communicating two messages, a high-security message and a low-security message, to a legitimate receiver, referred to as the security embedding problem. An information-theoretic formulation of the problem is presented. A coding scheme that combines rate splitting, supe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,070
cs/0011003	Applying Machine Translation to Two-Stage Cross-Language Information Retrieval	Cross-language information retrieval (CLIR), where queries and documents are in different languages, needs a translation of queries and/or documents, so as to standardize both of them into a common representation. For this purpose, the use of machine translation is an effective approach. However, computational cost is ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,246
1208.2434	Distributed Multi-objective Multidisciplinary Design Optimization Algorithms	This work proposes multi-agent systems setting for concurrent engineering system design optimization and gradually paves the way towards examining graph theoretic constructs in the context of multidisciplinary design optimization problem. The flow of the algorithm can be described as follow; generated estimates of the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	18,043
2306.16384	Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses	Graph Neural Networks (GNNs) are emerging as a powerful tool for learning from graph-structured data and performing sophisticated inference tasks in various application domains. Although GNNs have been shown to be effective on modest-sized graphs, training them on large-scale graphs remains a significant challenge due ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	376,353
2403.19889	Towards a Robust Retrieval-Based Summarization System	This paper describes an investigation of the robustness of large language models (LLMs) for retrieval augmented generation (RAG)-based summarization tasks. While LLMs provide summarization capabilities, their performance in complex, real-world scenarios remains under-explored. Our first contribution is LogicSumm, an in...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	442,518
1812.08898	Capacity Scaling of Massive MIMO in Strong Spatial Correlation Regimes	This paper investigates the capacity scaling of multicell massive MIMO systems in the presence of spatially correlated fading. In particular, we focus on the strong spatial correlation regimes where the covariance matrix of each user channel vector has a rank that scales sublinearly with the number of base station ante...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	117,060
2204.03994	LaF: Labeling-Free Model Selection for Automated Deep Neural Network Reusing	Applying deep learning to science is a new trend in recent years which leads DL engineering to become an important problem. Although training data preparation, model architecture design, and model training are the normal processes to build DL models, all of them are complex and costly. Therefore, reusing the open-sourc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	290,503
1803.09518	Fr\'echet ChemNet Distance: A metric for generative models for molecules in drug discovery	The new wave of successful generative models in machine learning has increased the interest in deep learning driven de novo drug design. However, assessing the performance of such generative models is notoriously difficult. Metrics that are typically used to assess the performance of such generative models are the perc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	93,513
2305.07035	Shhh! The Logic of Clandestine Operations	An operation is called covert if it conceals the identity of the actor; it is called clandestine if the very fact that the operation is conducted is concealed. The paper proposes a formal semantics of clandestine operations and introduces a sound and complete logical system that describes the interplay between the dist...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	363,754
1805.01386	Boosting Domain Adaptation by Discovering Latent Domains	Current Domain Adaptation (DA) methods based on deep architectures assume that the source samples arise from a single distribution. However, in practice, most datasets can be regarded as mixtures of multiple domains. In these cases exploiting single-source DA methods for learning target classifiers may lead to sub-opti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,649
2307.04091	CMDFusion: Bidirectional Fusion Network with Cross-modality Knowledge Distillation for LIDAR Semantic Segmentation	2D RGB images and 3D LIDAR point clouds provide complementary knowledge for the perception system of autonomous vehicles. Several 2D and 3D fusion methods have been explored for the LIDAR semantic segmentation task, but they suffer from different problems. 2D-to-3D fusion methods require strictly paired data during inf...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	378,278
1804.04082	Ranking CGANs: Subjective Control over Semantic Image Attributes	In this paper, we investigate the use of generative adversarial networks in the task of image generation according to subjective measures of semantic attributes. Unlike the standard (CGAN) that generates images from discrete categorical labels, our architecture handles both continuous and discrete scales. Given pairwis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,754
2406.12730	Predicting the energetic proton flux with a machine learning regression algorithm	The need of real-time of monitoring and alerting systems for Space Weather hazards has grown significantly in the last two decades. One of the most important challenge for space mission operations and planning is the prediction of solar proton events (SPEs). In this context, artificial intelligence and machine learning...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	465,546
1906.09094	Hybrid Planning for Dynamic Multimodal Stochastic Shortest Paths	Sequential decision problems in applications such as manipulation in warehouses, multi-step meal preparation, and routing in autonomous vehicle networks often involve reasoning about uncertainty, planning over discrete modes as well as continuous states, and reacting to dynamic updates. To formalize such problems gener...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	136,063
1403.3077	Set-Membership Adaptive Constant Modulus Algorithm with a Generalized Sidelobe Canceler and Dynamic Bounds for Beamforming	In this work, we propose an adaptive set-membership constant modulus (SM-CM) algorithm with a generalized sidelobe canceler (GSC) structure for blind beamforming. We develop a stochastic gradient (SG) type algorithm based on the concept of SM filtering for adaptive implementation. The filter weights are updated only if...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	31,536
2411.01166	Role Play: Learning Adaptive Role-Specific Strategies in Multi-Agent Interactions	Zero-shot coordination problem in multi-agent reinforcement learning (MARL), which requires agents to adapt to unseen agents, has attracted increasing attention. Traditional approaches often rely on the Self-Play (SP) framework to generate a diverse set of policies in a policy pool, which serves to improve the generali...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	504,941
2406.02630	AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathways	An Artificial Intelligence (AI) agent is a software entity that autonomously performs tasks or makes decisions based on pre-defined objectives and data inputs. AI agents, capable of perceiving user inputs, reasoning and planning tasks, and executing actions, have seen remarkable advancements in algorithm development an...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	460,876
2410.21142	Modeling and Monitoring of Indoor Populations using Sparse Positioning Data (Extension)	In large venues like shopping malls and airports, knowledge on the indoor populations fuels applications such as business analytics, venue management, and safety control. In this work, we provide means of modeling populations in partitions of indoor space offline and of monitoring indoor populations continuously, by us...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	503,105
2310.06474	Multilingual Jailbreak Challenges in Large Language Models	While large language models (LLMs) exhibit remarkable capabilities across a wide range of tasks, they pose potential safety concerns, such as the ``jailbreak'' problem, wherein malicious instructions can manipulate LLMs to exhibit undesirable behavior. Although several preventive measures have been developed to mitigat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	398,595
1901.09659	Simple Surveys: Response Retrieval Inspired by Recommendation Systems	In the last decade, the use of simple rating and comparison surveys has proliferated on social and digital media platforms to fuel recommendations. These simple surveys and their extrapolation with machine learning algorithms shed light on user preferences over large and growing pools of items, such as movies, songs an...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	119,805
1803.02099	A Hybrid Method for Traffic Flow Forecasting Using Multimodal Deep Learning	Traffic flow forecasting has been regarded as a key problem of intelligent transport systems. In this work, we propose a hybrid multimodal deep learning method for short-term traffic flow forecasting, which can jointly and adaptively learn the spatial-temporal correlation features and long temporal interdependence of m...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	91,991
1801.07839	Improved list-decodability of random linear binary codes	There has been a great deal of work establishing that random linear codes are as list-decodable as uniformly random codes, in the sense that a random linear binary code of rate $1 - H(p) - \epsilon$ is $(p,O(1/\epsilon))$-list-decodable with high probability. In this work, we show that such codes are $(p, H(p)/\epsilon...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	88,859
2111.11874	Is this IoT Device Likely to be Secure? Risk Score Prediction for IoT Devices Using Gradient Boosting Machines	Security risk assessment and prediction are critical for organisations deploying Internet of Things (IoT) devices. An absolute minimum requirement for enterprises is to verify the security risk of IoT devices for the reported vulnerabilities in the National Vulnerability Database (NVD). This paper proposes a novel risk...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	267,808
1806.03000	Noise-adding Methods of Saliency Map as Series of Higher Order Partial Derivative	SmoothGrad and VarGrad are techniques that enhance the empirical quality of standard saliency maps by adding noise to input. However, there were few works that provide a rigorous theoretical interpretation of those methods. We analytically formalize the result of these noise-adding methods. As a result, we observe two ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	99,909
2406.18627	AssertionBench: A Benchmark to Evaluate Large-Language Models for Assertion Generation	Assertions have been the de facto collateral for simulation-based and formal verification of hardware designs for over a decade. The quality of hardware verification, \ie, detection and diagnosis of corner-case design bugs, is critically dependent on the quality of the assertions. There has been a considerable amount o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	468,117
2210.06328	Momentum Aggregation for Private Non-convex ERM	We introduce new algorithms and convergence guarantees for privacy-preserving non-convex Empirical Risk Minimization (ERM) on smooth $d$-dimensional objectives. We develop an improved sensitivity analysis of stochastic gradient descent on smooth objectives that exploits the recurrence of examples in different epochs. B...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,232
2409.07040	Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement	Low-light image enhancement, particularly in cross-domain tasks such as mapping from the raw domain to the sRGB domain, remains a significant challenge. Many deep learning-based methods have been developed to address this issue and have shown promising results in recent years. However, single-stage methods, which attem...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,363

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