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
2412.09082	Towards Long-Horizon Vision-Language Navigation: Platform, Benchmark and Method	Existing Vision-Language Navigation (VLN) methods primarily focus on single-stage navigation, limiting their effectiveness in multi-stage and long-horizon tasks within complex and dynamic environments. To address these limitations, we propose a novel VLN task, named Long-Horizon Vision-Language Navigation (LH-VLN), whi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,356
1910.11121	Face Detection on Surveillance Images	In last few decades, a lot of progress has been made in the field of face detection. Various face detection methods have been proposed by numerous researchers working in this area. The two well-known benchmarking platform: the FDDB and WIDER face detection provide quite challenging scenarios to assess the efficacy of t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	150,694
2108.01193	Wide-Area Damping Control for Interarea Oscillations in Power Grids Based on PMU Measurements	In this paper, a phasor measurement unit (PMU)-based wide-area damping control method is proposed to damp the interarea oscillations that threaten the modern power system stability and security. Utilizing the synchronized PMU data, the proposed almost model-free approach can achieve an effective damping for the selecte...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	248,945
2306.05045	Spain on Fire: A novel wildfire risk assessment model based on image satellite processing and atmospheric information	Each year, wildfires destroy larger areas of Spain, threatening numerous ecosystems. Humans cause 90% of them (negligence or provoked) and the behaviour of individuals is unpredictable. However, atmospheric and environmental variables affect the spread of wildfires, and they can be analysed by using deep learning. In o...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	372,027
2008.13625	Transfer entropy applied on EEG in depression reveals aberrated dynamics	We applied transfer entropy analysis on samples of electroencephalogram recorded from patients diagnosed with major depressive disorder and matched healthy controls. This is the first graphical representation of aberrated dynamics in terms of connectivity and the direction of information between standard centers in MDD...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,899
2206.09410	Low-Mid Adversarial Perturbation against Unauthorized Face Recognition System	In light of the growing concerns regarding the unauthorized use of facial recognition systems and its implications on individual privacy, the exploration of adversarial perturbations as a potential countermeasure has gained traction. However, challenges arise in effectively deploying this approach against unauthorized ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	303,561
2302.12562	A Knowledge Distillation framework for Multi-Organ Segmentation of Medaka Fish in Tomographic Image	Morphological atlases are an important tool in organismal studies, and modern high-throughput Computed Tomography (CT) facilities can produce hundreds of full-body high-resolution volumetric images of organisms. However, creating an atlas from these volumes requires accurate organ segmentation. In the last decade, mach...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	347,613
2206.03654	Solving the Spike Feature Information Vanishing Problem in Spiking Deep Q Network with Potential Based Normalization	Brain inspired spiking neural networks (SNNs) have been successfully applied to many pattern recognition domains. The SNNs based deep structure have achieved considerable results in perceptual tasks, such as image classification, target detection. However, the application of deep SNNs in reinforcement learning (RL) tas...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	301,355
2210.16795	Two-Level Temporal Relation Model for Online Video Instance Segmentation	In Video Instance Segmentation (VIS), current approaches either focus on the quality of the results, by taking the whole video as input and processing it offline; or on speed, by handling it frame by frame at the cost of competitive performance. In this work, we propose an online method that is on par with the performa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	327,460
1809.01194	Challenges of capturing engagement on Facebook for Altmetrics	Previous research shows that, despite its popularity, Facebook is less frequently used to share academic content. In order to investigate this discrepancy we set out to explore engagement numbers through their Graph API by querying the Facebook API with multiple URLs for a random set of 103,539 articles from the Web of...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	106,745
2307.04245	A Novel Pipeline for Improving Optical Character Recognition through Post-processing Using Natural Language Processing	Optical Character Recognition (OCR) technology finds applications in digitizing books and unstructured documents, along with applications in other domains such as mobility statistics, law enforcement, traffic, security systems, etc. The state-of-the-art methods work well with the OCR with printed text on license plates...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	378,337
2109.09468	Completeness of Unbounded Best-First Game Algorithms	In this article, we prove the completeness of the following game search algorithms: unbounded best-first minimax with completion and descent with completion, i.e. we show that, with enough time, they find the best game strategy. We then generalize these two algorithms in the context of perfect information multiplayer g...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	256,286
2407.18841	QT-TDM: Planning With Transformer Dynamics Model and Autoregressive Q-Learning	Inspired by the success of the Transformer architecture in natural language processing and computer vision, we investigate the use of Transformers in Reinforcement Learning (RL), specifically in modeling the environment's dynamics using Transformer Dynamics Models (TDMs). We evaluate the capabilities of TDMs for contin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	476,535
2311.01584	Secured Fiscal Credit Model: Multi-Agent Systems And Decentralized Autonomous Organisations For Tax Credit's Tracking	Tax incentives and fiscal bonuses have had a significant impact on the Italian economy over the past decade. In particular, the "Superbonus 110" tax relief in 2020, offering a generous 110% deduction for expenses related to energy efficiency improvements and seismic risk reduction in buildings, has played a pivotal rol...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	405,096
1707.05228	Object Tracking based on Quantum Particle Swarm Optimization	In Computer Vision domain, moving Object Tracking considered as one of the toughest problem.As there so many factors associated like illumination of light, noise, occlusion, sudden start and stop of moving object, shading which makes tracking even harder problem not only for dynamic background but also for static backg...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	77,185
2405.04800	DeepDamageNet: A two-step deep-learning model for multi-disaster building damage segmentation and classification using satellite imagery	Satellite imagery has played an increasingly important role in post-disaster building damage assessment. Unfortunately, current methods still rely on manual visual interpretation, which is often time-consuming and can cause very low accuracy. To address the limitations of manual interpretation, there has been a signifi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	452,685
2203.16860	Investigating Modality Bias in Audio Visual Video Parsing	We focus on the audio-visual video parsing (AVVP) problem that involves detecting audio and visual event labels with temporal boundaries. The task is especially challenging since it is weakly supervised with only event labels available as a bag of labels for each video. An existing state-of-the-art model for AVVP uses ...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	288,953
2502.11882	Leveraging Dual Process Theory in Language Agent Framework for Real-time Simultaneous Human-AI Collaboration	Agents built on large language models (LLMs) have excelled in turn-by-turn human-AI collaboration but struggle with simultaneous tasks requiring real-time interaction. Latency issues and the challenge of inferring variable human strategies hinder their ability to make autonomous decisions without explicit instructions....	true	false	false	false	true	false	true	false	true	false	false	false	false	false	true	false	false	false	534,584
0709.0680	Designing a Virtual Manikin Animation Framework Aimed at Virtual Prototyping	In the industry, numerous commercial packages provide tools to introduce, and analyse human behaviour in the product's environment (for maintenance, ergonomics...), thanks to Virtual Humans. We will focus on control. Thanks to algorithms newly introduced in recent research papers, we think we can provide an implementat...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	637
2308.05359	Pseudo-label Alignment for Semi-supervised Instance Segmentation	Pseudo-labeling is significant for semi-supervised instance segmentation, which generates instance masks and classes from unannotated images for subsequent training. However, in existing pipelines, pseudo-labels that contain valuable information may be directly filtered out due to mismatches in class and mask quality. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	384,762
2102.05235	Advanced Ore Mine Optimisation under Uncertainty Using Evolution	In this paper, we investigate the impact of uncertainty in advanced ore mine optimisation. We consider Maptek's software system Evolution which optimizes extraction sequences based on evolutionary computation techniques and quantify the uncertainty of the obtained solutions with respect to the ore deposit based on pred...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	219,368
2204.05944	Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization	We consider the problem of multi-objective (MO) blackbox optimization using expensive function evaluations, where the goal is to approximate the true Pareto set of solutions while minimizing the number of function evaluations. For example, in hardware design optimization, we need to find the designs that trade-off perf...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	291,190
2105.00100	Data-driven Full-waveform Inversion Surrogate using Conditional Generative Adversarial Networks	In the Oil and Gas industry, estimating a subsurface velocity field is an essential step in seismic processing, reservoir characterization, and hydrocarbon volume calculation. Full-waveform inversion (FWI) velocity modeling is an iterative advanced technique that provides an accurate and detailed velocity field model, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	233,084
2309.01150	FedFwd: Federated Learning without Backpropagation	In federated learning (FL), clients with limited resources can disrupt the training efficiency. A potential solution to this problem is to leverage a new learning procedure that does not rely on backpropagation (BP). We present a novel approach to FL called FedFwd that employs a recent BP-free method by Hinton (2022), ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	389,566
2106.01650	Learning and Executing Re-usable Behaviour Trees from Natural Language Instruction	Domestic and service robots have the potential to transform industries such as health care and small-scale manufacturing, as well as the homes in which we live. However, due to the overwhelming variety of tasks these robots will be expected to complete, providing generic out-of-the-box solutions that meet the needs of ...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	238,580
2007.10568	Buffer Pool Aware Query Scheduling via Deep Reinforcement Learning	In this extended abstract, we propose a new technique for query scheduling with the explicit goal of reducing disk reads and thus implicitly increasing query performance. We introduce SmartQueue, a learned scheduler that leverages overlapping data reads among incoming queries and learns a scheduling strategy that impro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	188,307
2411.10325	Bitcoin Research with a Transaction Graph Dataset	Bitcoin, launched in 2008 by Satoshi Nakamoto, established a new digital economy where value can be stored and transferred in a fully decentralized manner - alleviating the need for a central authority. This paper introduces a large scale dataset in the form of a transactions graph representing transactions between Bit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	508,594
1805.01506	Prediction of a Gene Regulatory Network from Gene Expression Profiles With Linear Regression and Pearson Correlation Coefficient	Reconstruction of gene regulatory networks is the process of identifying gene dependency from gene expression profile through some computation techniques. In our human body, though all cells pose similar genetic material but the activation state may vary. This variation in the activation of genes helps researchers to u...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	96,666
2207.12613	Rank and pairs of Rank and Dimension of Kernel of $\mathbb{Z}_p\mathbb{Z}_{p^2}$-linear codes	A code $C$ is called $\mathbb{Z}_p\mathbb{Z}_{p^2}$-linear if it is the Gray image of a $\mathbb{Z}_p\mathbb{Z}_{p^2}$-additive code. For any prime number $p$ larger than $3$, the bounds of the rank of $\mathbb{Z}_p\mathbb{Z}_{p^2}$-linear codes are given. For each value of the rank and the pairs of rank and the dimens...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	310,062
1710.10538	Partial Knowledge In Embeddings	Representing domain knowledge is crucial for any task. There has been a wide range of techniques developed to represent this knowledge, from older logic based approaches to the more recent deep learning based techniques (i.e. embeddings). In this paper, we discuss some of these methods, focusing on the representational...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	83,404
2304.07821	Time-dependent Iterative Imputation for Multivariate Longitudinal Clinical Data	Missing data is a major challenge in clinical research. In electronic medical records, often a large fraction of the values in laboratory tests and vital signs are missing. The missingness can lead to biased estimates and limit our ability to draw conclusions from the data. Additionally, many machine learning algorithm...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	358,486
2407.11463	Investigating Imperceptibility of Adversarial Attacks on Tabular Data: An Empirical Analysis	Adversarial attacks are a potential threat to machine learning models by causing incorrect predictions through imperceptible perturbations to the input data. While these attacks have been extensively studied in unstructured data like images, applying them to tabular data, poses new challenges. These challenges arise fr...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	473,468
2403.11852	Reinforcement Learning with Latent State Inference for Autonomous On-ramp Merging under Observation Delay	This paper presents a novel approach to address the challenging problem of autonomous on-ramp merging, where a self-driving vehicle needs to seamlessly integrate into a flow of vehicles on a multi-lane highway. We introduce the Lane-keeping, Lane-changing with Latent-state Inference and Safety Controller (L3IS) agent, ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	438,894
1904.02808	Overlap matrix concentration in optimal Bayesian inference	We consider models of Bayesian inference of signals with vectorial components of finite dimensionality. We show that, under a proper perturbation, these models are replica symmetric in the sense that the overlap matrix concentrates. The overlap matrix is the order parameter in these models and is directly related to er...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	126,530
2108.02581	Handling Inconsistencies in Tables with Nulls and Functional Dependencies	In this paper we address the problem of handling inconsistencies in tables with missing values (also called nulls) and functional dependencies. Although the traditional view is that table instances must respect all functional dependencies imposed on them, it is nevertheless relevant to develop theories about how to han...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	249,380
1503.07211	Universal Approximation of Markov Kernels by Shallow Stochastic Feedforward Networks	We establish upper bounds for the minimal number of hidden units for which a binary stochastic feedforward network with sigmoid activation probabilities and a single hidden layer is a universal approximator of Markov kernels. We show that each possible probabilistic assignment of the states of $n$ output units, given t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	41,446
2306.16092	Chatlaw: A Multi-Agent Collaborative Legal Assistant with Knowledge Graph Enhanced Mixture-of-Experts Large Language Model	AI legal assistants based on Large Language Models (LLMs) can provide accessible legal consulting services, but the hallucination problem poses potential legal risks. This paper presents Chatlaw, an innovative legal assistant utilizing a Mixture-of-Experts (MoE) model and a multi-agent system to enhance the reliability...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	376,276
2403.05897	RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection	Self-supervised feature reconstruction methods have shown promising advances in industrial image anomaly detection and localization. Despite this progress, these methods still face challenges in synthesizing realistic and diverse anomaly samples, as well as addressing the feature redundancy and pre-training bias of pre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,211
1406.6470	Wireless Networks with RF Energy Harvesting: A Contemporary Survey	Radio frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to power the next generation wireless networks. As this emerging technology enables proactive energy replenishment of wireless devices, it is advantageous in supporting applications with quality of service (QoS) requ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	34,121
1401.6362	The Capacity of Known Interference Channel (updated)	In this paper, we investigate the capacity of known interference channel, where the receiver knows the interference data but not the channel gain of the interference data. We first derive a tight upper bound for the capacity of this known-interference channel. After that, we obtain an achievable rate of the channel wit...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	30,339
2502.13270	REALTALK: A 21-Day Real-World Dataset for Long-Term Conversation	Long-term, open-domain dialogue capabilities are essential for chatbots aiming to recall past interactions and demonstrate emotional intelligence (EI). Yet, most existing research relies on synthetic, LLM-generated data, leaving open questions about real-world conversational patterns. To address this gap, we introduce ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	535,291
1303.1667	ALPRS - A New Approach for License Plate Recognition using the Sift Algorithm	This paper presents a new approach for the automatic license plate recognition, which includes the SIFT algorithm in step to locate the plate in the input image. In this new approach, besides the comparison of the features obtained with the SIFT algorithm, the correspondence between the spatial orientations and the pos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	22,743
2408.12769	Enhancing Vehicle Environmental Awareness via Federated Learning and Automatic Labeling	Vehicle environmental awareness is a crucial issue in improving road safety. Through a variety of sensors and vehicle-to-vehicle communication, vehicles can collect a wealth of data. However, to make these data useful, sensor data must be integrated effectively. This paper focuses on the integration of image data and v...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	482,869
2301.05567	Neural network with optimal neuron activation functions based on additive Gaussian process regression	Feed-forward neural networks (NN) are a staple machine learning method widely used in many areas of science and technology. While even a single-hidden layer NN is a universal approximator, its expressive power is limited by the use of simple neuron activation functions (such as sigmoid functions) that are typically the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	340,387
2411.16629	LegoPET: Hierarchical Feature Guided Conditional Diffusion for PET Image Reconstruction	Positron emission tomography (PET) is widely utilized for cancer detection due to its ability to visualize functional and biological processes in vivo. PET images are usually reconstructed from histogrammed raw data (sinograms) using traditional iterative techniques (e.g., OSEM, MLEM). Recently, deep learning (DL) meth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	511,098
2303.04012	Exploration via Epistemic Value Estimation	How to efficiently explore in reinforcement learning is an open problem. Many exploration algorithms employ the epistemic uncertainty of their own value predictions -- for instance to compute an exploration bonus or upper confidence bound. Unfortunately the required uncertainty is difficult to estimate in general with ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	349,931
2405.08359	GPS-IDS: An Anomaly-based GPS Spoofing Attack Detection Framework for Autonomous Vehicles	Autonomous Vehicles (AVs) heavily rely on sensors and communication networks like Global Positioning System (GPS) to navigate autonomously. Prior research has indicated that networks like GPS are vulnerable to cyber-attacks such as spoofing and jamming, thus posing serious risks like navigation errors and system failur...	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	454,075
2405.17968	Matroid Semi-Bandits in Sublinear Time	We study the matroid semi-bandits problem, where at each round the learner plays a subset of $K$ arms from a feasible set, and the goal is to maximize the expected cumulative linear rewards. Existing algorithms have per-round time complexity at least $\Omega(K)$, which becomes expensive when $K$ is large. To address th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	458,213
1504.01452	The Performance Analysis of Coded Cache in Wireless Fading Channel	The rapid growth of data volume and the accompanying congestion problems over the wireless networks have been critical issues to content providers. A novel technique, termed as coded cache, is proposed to relieve the burden. Through creating coded-multicasting opportunities, the coded-cache scheme can provide extra per...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	41,815
2209.07709	LO-Det: Lightweight Oriented Object Detection in Remote Sensing Images	A few lightweight convolutional neural network (CNN) models have been recently designed for remote sensing object detection (RSOD). However, most of them simply replace vanilla convolutions with stacked separable convolutions, which may not be efficient due to a lot of precision losses and may not be able to detect ori...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	317,857
2103.08306	ReinforceBug: A Framework to Generate Adversarial Textual Examples	Adversarial Examples (AEs) generated by perturbing original training examples are useful in improving the robustness of Deep Learning (DL) based models. Most prior works, generate AEs that are either unconscionable due to lexical errors or semantically or functionally deviant from original examples. In this paper, we p...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	224,864
2003.12181	ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds	We propose a novel, end-to-end trainable, deep network called ParSeNet that decomposes a 3D point cloud into parametric surface patches, including B-spline patches as well as basic geometric primitives. ParSeNet is trained on a large-scale dataset of man-made 3D shapes and captures high-level semantic priors for shape ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	169,839
2204.10689	Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition	One-shot fine-grained visual recognition often suffers from the problem of having few training examples for new fine-grained classes. To alleviate this problem, off-the-shelf image generation techniques based on Generative Adversarial Networks (GANs) can potentially create additional training images. However, these GAN...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	292,881
2305.12463	Teaching the Pre-trained Model to Generate Simple Texts for Text Simplification	Randomly masking text spans in ordinary texts in the pre-training stage hardly allows models to acquire the ability to generate simple texts. It can hurt the performance of pre-trained models on text simplification tasks. In this paper, we propose a new continued pre-training strategy to teach the pre-trained model to ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	366,014
1402.6132	Uncovering the information core in recommender systems	With the rapid growth of the Internet and overwhelming amount of information that people are confronted with, recommender systems have been developed to effiectively support users' decision-making process in online systems. So far, much attention has been paid to designing new recommendation algorithms and improving ex...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	31,152
2406.17500	Using iterated local alignment to aggregate trajectory data into a traffic flow map	Vehicle trajectories, with their detailed geolocations, are a promising data source to compute traffic flow maps which facilitate the understanding of traffic flows at scales ranging from the city/regional level to the road level. The trade-off is that trajectory data are prone to measurement noise. While this is negli...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	467,595
1802.07770	Generalizable Adversarial Examples Detection Based on Bi-model Decision Mismatch	Modern applications of artificial neural networks have yielded remarkable performance gains in a wide range of tasks. However, recent studies have discovered that such modelling strategy is vulnerable to Adversarial Examples, i.e. examples with subtle perturbations often too small and imperceptible to humans, but that ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	90,947
2406.08349	Utilizing Navigation Paths to Generate Target Points for Enhanced End-to-End Autonomous Driving Planning	In recent years, end-to-end autonomous driving frameworks have been shown to not only enhance perception performance but also improve planning capabilities. However, most previous end-to-end autonomous driving frameworks have focused primarily on enhancing environmental perception while neglecting the learning of auton...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	463,447
2201.09140	Physics-Aware Safety-Assured Design of Hierarchical Neural Network based Planner	Neural networks have shown great promises in planning, control, and general decision making for learning-enabled cyber-physical systems (LE-CPSs), especially in improving performance under complex scenarios. However, it is very challenging to formally analyze the behavior of neural network based planners for ensuring s...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	276,570
1801.02622	Graph Memory Networks for Molecular Activity Prediction	Molecular activity prediction is critical in drug design. Machine learning techniques such as kernel methods and random forests have been successful for this task. These models require fixed-size feature vectors as input while the molecules are variable in size and structure. As a result, fixed-size fingerprint represe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	87,957
cs/0602035	n-Channel Entropy-Constrained Multiple-Description Lattice Vector Quantization	In this paper we derive analytical expressions for the central and side quantizers which, under high-resolutions assumptions, minimize the expected distortion of a symmetric multiple-description lattice vector quantization (MD-LVQ) system subject to entropy constraints on the side descriptions for given packet-loss pro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,264
1909.03681	Outlier Detection in High Dimensional Data	High-dimensional data poses unique challenges in outlier detection process. Most of the existing algorithms fail to properly address the issues stemming from a large number of features. In particular, outlier detection algorithms perform poorly on data set of small size with a large number of features. In this paper, w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	144,574
1812.02370	Exploring the importance of context and embeddings in neural NER models for task-oriented dialogue systems	Named Entity Recognition (NER), a classic sequence labelling task, is an essential component of natural language understanding (NLU) systems in task-oriented dialog systems for slot filling. For well over a decade, different methods from lookup using gazetteers and domain ontology, classifiers over handcrafted features...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	115,742
2006.14262	SACT: Self-Aware Multi-Space Feature Composition Transformer for Multinomial Attention for Video Captioning	Video captioning works on the two fundamental concepts, feature detection and feature composition. While modern day transformers are beneficial in composing features, they lack the fundamental problems of selecting and understanding of the contents. As the feature length increases, it becomes increasingly important to ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	true	false	false	184,168
2007.03856	BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning	Federated learning enables the development of a machine learning model among collaborating agents without requiring them to share their underlying data. However, malicious agents who train on random data, or worse, on datasets with the result classes inverted, can weaken the combined model. BlockFLow is an accountable ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	186,185
1709.03759	Language Models of Spoken Dutch	In Flanders, all TV shows are subtitled. However, the process of subtitling is a very time-consuming one and can be sped up by providing the output of a speech recognizer run on the audio of the TV show, prior to the subtitling. Naturally, this speech recognition will perform much better if the employed language model ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	80,528
2212.09660	The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges	Code-Switching, a common phenomenon in written text and conversation, has been studied over decades by the natural language processing (NLP) research community. Initially, code-switching is intensively explored by leveraging linguistic theories and, currently, more machine-learning oriented approaches to develop models...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,180
2406.11301	Enhancing and Assessing Instruction-Following with Fine-Grained Instruction Variants	The effective alignment of Large Language Models (LLMs) with precise instructions is essential for their application in diverse real-world scenarios. Current methods focus on enhancing the diversity and complexity of training and evaluation samples, yet they fall short in accurately assessing LLMs' ability to follow si...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	464,829
2010.05421	Factorizable Graph Convolutional Networks	Graphs have been widely adopted to denote structural connections between entities. The relations are in many cases heterogeneous, but entangled together and denoted merely as a single edge between a pair of nodes. For example, in a social network graph, users in different latent relationships like friends and colleague...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	200,122
1605.03926	A Rate-Splitting Strategy for Max-Min Fair Multigroup Multicasting	We consider the problem of transmit beamforming to multiple cochannel multicast groups. The conventional approach is to beamform a designated data stream to each group, while treating potential inter-group interference as noise at the receivers. In overloaded systems where the number of transmit antennas is insufficien...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,810
1902.05387	Simultaneous x, y Pixel Estimation and Feature Extraction for Multiple Small Objects in a Scene: A Description of the ALIEN Network	We present a deep-learning network that detects multiple small objects (hundreds to thousands) in a scene while simultaneously estimating their x,y pixel locations together with a characteristic feature-set (for instance, target orientation and color). All estimations are performed in a single, forward pass which makes...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	121,529
2409.11394	Distributed Perception Aware Safe Leader Follower System via Control Barrier Methods	This paper addresses a distributed leader-follower formation control problem for a group of agents, each using a body-fixed camera with a limited field of view (FOV) for state estimation. The main challenge arises from the need to coordinate the agents' movements with their cameras' FOV to maintain visibility of the le...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	489,139
0705.1148	S\'eparation des Solutions aux Mod\`eles G\'eom\'etriques Direct et Inverse pour les Manipulateurs Pleinement Parall\`eles	This article provides a formalism making it possible to manage the solutions of the direct and inverse kinematic models of the fully parallel manipulators. We introduce the concept of working modes to separate the solutions from the opposite geometrical model. Then, we define, for each working mode, the aspects of thes...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	184
2103.12719	Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations	Recent progress in self-supervised learning has demonstrated promising results in multiple visual tasks. An important ingredient in high-performing self-supervised methods is the use of data augmentation by training models to place different augmented views of the same image nearby in embedding space. However, commonly...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	226,270
1903.07738	Predicting Stochastic Human Forward Reachable Sets Based on Learned Human Behavior	With the recent surge of interest in introducing autonomous vehicles to the everyday lives of people, developing accurate and generalizable algorithms for predicting human behavior becomes highly crucial. Moreover, many of these emerging applications occur in a safety-critical context, making it even more urgent to dev...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	124,679
1905.13656	Investigating an Effective Character-level Embedding in Korean Sentence Classification	Different from the writing systems of many Romance and Germanic languages, some languages or language families show complex conjunct forms in character composition. For such cases where the conjuncts consist of the components representing consonant(s) and vowel, various character encoding schemes can be adopted beyond ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	133,206
2311.13245	A model-free approach to fingertip slip and disturbance detection for grasp stability inference	Robotic capacities in object manipulation are incomparable to those of humans. Besides years of learning, humans rely heavily on the richness of information from physical interaction with the environment. In particular, tactile sensing is crucial in providing such rich feedback. Despite its potential contributions to r...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	409,680
1204.1598	Improving Seek Time for Column Store Using MMH Algorithm	Hash based search has, proven excellence on large data warehouses stored in column store. Data distribution has significant impact on hash based search. To reduce impact of data distribution, we have proposed Memory Managed Hash (MMH) algorithm that uses shift XOR group for Queries and Transactions in column store. Our...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	15,330
1405.3570	Exchanging Conflict Resolution in an Adaptable Implementation of ACT-R	In computational cognitive science, the cognitive architecture ACT-R is very popular. It describes a model of cognition that is amenable to computer implementation, paving the way for computational psychology. Its underlying psychological theory has been investigated in many psychological experiments, but ACT-R lacks a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	33,103
1901.05375	DAFE-FD: Density Aware Feature Enrichment for Face Detection	Recent research on face detection, which is focused primarily on improving accuracy of detecting smaller faces, attempt to develop new anchor design strategies to facilitate increased overlap between anchor boxes and ground truth faces of smaller sizes. In this work, we approach the problem of small face detection with...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	118,778
2107.13203	Collision-free Formation Control of Multiple Nano-quadrotors	The utilisation of unmanned aerial vehicles has witnessed significant growth in real-world applications including surveillance tasks, military missions, and transportation deliveries. This letter investigates practical problems of formation control for multiple nano-quadrotor systems. To be more specific, the first aim...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	248,134
2410.08815	StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurization	Retrieval-augmented generation (RAG) is a key means to effectively enhance large language models (LLMs) in many knowledge-based tasks. However, existing RAG methods struggle with knowledge-intensive reasoning tasks, because useful information required to these tasks are badly scattered. This characteristic makes it dif...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	497,288
2212.09897	Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training	Language tasks involving character-level manipulations (e.g., spelling corrections, arithmetic operations, word games) are challenging for models operating on subword units. To address this, we develop a causal intervention framework to learn robust and interpretable character representations inside subword-based langu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,247
2401.01270	Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions	Motivated by the studies of neural networks (e.g.,the neural tangent kernel theory), we perform a study on the large-dimensional behavior of kernel ridge regression (KRR) where the sample size $n \asymp d^{\gamma}$ for some $\gamma > 0$. Given an RKHS $\mathcal{H}$ associated with an inner product kernel defined on the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	419,297
1808.07285	DeepCorr: Strong Flow Correlation Attacks on Tor Using Deep Learning	Flow correlation is the core technique used in a multitude of deanonymization attacks on Tor. Despite the importance of flow correlation attacks on Tor, existing flow correlation techniques are considered to be ineffective and unreliable in linking Tor flows when applied at a large scale, i.e., they impose high rates o...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	105,711
2210.07269	SODAPOP: Open-Ended Discovery of Social Biases in Social Commonsense Reasoning Models	A common limitation of diagnostic tests for detecting social biases in NLP models is that they may only detect stereotypic associations that are pre-specified by the designer of the test. Since enumerating all possible problematic associations is infeasible, it is likely these tests fail to detect biases that are prese...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	323,633
2210.11017	Multi-Granularity Optimization for Non-Autoregressive Translation	Despite low latency, non-autoregressive machine translation (NAT) suffers severe performance deterioration due to the naive independence assumption. This assumption is further strengthened by cross-entropy loss, which encourages a strict match between the hypothesis and the reference token by token. To alleviate this i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	325,148
1908.01654	Analysis of Two-Dimensional Feedback Systems over Networks Using Dissipativity	This paper investigates the closed-loop $\mathcal{L}_2$ stability of two-dimensional (2-D) feedback systems across a digital communication network by introducing the tool of dissipativity. First, sampling of a continuous 2-D system is considered and an analytical characterization of the $QSR$-dissipativity of the sampl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	140,813
1810.06245	Bringing back simplicity and lightliness into neural image captioning	Neural Image Captioning (NIC) or neural caption generation has attracted a lot of attention over the last few years. Describing an image with a natural language has been an emerging challenge in both fields of computer vision and language processing. Therefore a lot of research has focused on driving this task forward ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	110,406
2210.06257	What can we learn about a generated image corrupting its latent representation?	Generative adversarial networks (GANs) offer an effective solution to the image-to-image translation problem, thereby allowing for new possibilities in medical imaging. They can translate images from one imaging modality to another at a low cost. For unpaired datasets, they rely mostly on cycle loss. Despite its effect...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	323,193
1509.07170	Indirect-adaptive Model Predictive Control for Linear Systems with Polytopic Uncertainty	We develop an indirect-adaptive model predictive control algorithm for uncertain linear systems subject to constraints. The system is modeled as a polytopic linear parameter varying system where the convex combination vector is constant but unknown. Robust constraint satisfaction is obtained by constraints enforcing a ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	47,234
2009.00278	Scaling Up Deep Neural Network Optimization for Edge Inference	Deep neural networks (DNNs) have been increasingly deployed on and integrated with edge devices, such as mobile phones, drones, robots and wearables. To run DNN inference directly on edge devices (a.k.a. edge inference) with a satisfactory performance, optimizing the DNN design (e.g., network architecture and quantizat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	194,006
0709.0787	Sound Generation by a Turbulent Flow in Musical Instruments - Multiphysics Simulation Approach -	Total computational costs of scientific simulations are analyzed between direct numerical simulations (DNS) and multiphysics simulations (MPS) for sound generation in musical instruments. In order to produce acoustic sound by a turbulent flow in a simple recorder-like instrument, compressible fluid dynamic calculations...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	638
1505.03561	Content-type coding	This paper is motivated by the observation that, in many cases, we do not need to serve specific messages, but rather, any message within a content-type. Content-type traffic pervades a host of applications today, ranging from search engines and recommender networks to newsfeeds and advertisement networks. The paper as...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	43,086
1810.10983	Stochastic Control with Stale Information--Part I: Fully Observable Systems	In this study, we adopt age of information as a measure of the staleness of information, and take initial steps towards analyzing the control performance of stochastic systems with stale information. Our goals are to cast light on a fundamental limit on the information staleness that is required for a certain level of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	111,414
1605.08671	An optimal algorithm for the Thresholding Bandit Problem	We study a specific \textit{combinatorial pure exploration stochastic bandit problem} where the learner aims at finding the set of arms whose means are above a given threshold, up to a given precision, and \textit{for a fixed time horizon}. We propose a parameter-free algorithm based on an original heuristic, and prove...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	56,467
2303.16666	SC-VAE: Sparse Coding-based Variational Autoencoder with Learned ISTA	Learning rich data representations from unlabeled data is a key challenge towards applying deep learning algorithms in downstream tasks. Several variants of variational autoencoders (VAEs) have been proposed to learn compact data representations by encoding high-dimensional data in a lower dimensional space. Two main c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,943
2109.15114	A Generalized Kalman Filter Augmented Deep-Learning based Approach for Autonomous Landing in MAVs	Autonomous landing systems for Micro Aerial Vehicles (MAV) have been proposed using various combinations of GPS-based, vision, and fiducial tag-based schemes. Landing is a critical activity that a MAV performs and poor resolution of GPS, degraded camera images, fiducial tags not meeting required specifications and envi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	258,180
2203.15354	Signing at Scale: Learning to Co-Articulate Signs for Large-Scale Photo-Realistic Sign Language Production	Sign languages are visual languages, with vocabularies as rich as their spoken language counterparts. However, current deep-learning based Sign Language Production (SLP) models produce under-articulated skeleton pose sequences from constrained vocabularies and this limits applicability. To be understandable and accepte...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	288,365
2405.19837	Lifelong learning challenges in the era of artificial intelligence: a computational thinking perspective	The rapid advancement of artificial intelligence (AI) has brought significant challenges to the education and workforce skills required to take advantage of AI for human-AI collaboration in the workplace. As AI continues to reshape industries and job markets, the need to define how AI literacy can be considered in life...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	459,091

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