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
1905.13561	Speaker Anonymization Using X-vector and Neural Waveform Models	The social media revolution has produced a plethora of web services to which users can easily upload and share multimedia documents. Despite the popularity and convenience of such services, the sharing of such inherently personal data, including speech data, raises obvious security and privacy concerns. In particular, ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	133,172
1606.03695	Nearest Neighbour Distance Distribution in Hard-Core Point Processes	In this paper we present an analytic framework for formulating the statistical distribution of the nearest neighbour distance in hard-core point processes. We apply this framework to Mat\'{e}rn hard-core point process (MHC) to derive the cumulative distribution function of the contact distance in three cases. The first...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	57,134
1610.05424	Modern WLAN Fingerprinting Indoor Positioning Methods and Deployment Challenges	Wireless Local Area Network (WLAN) has become a promising choice for indoor positioning as the only existing and established infrastructure, to localize the mobile and stationary users indoors. However, since WLAN has been initially designed for wireless networking and not positioning, the localization task based on WL...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	62,507
2404.15378	Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions	Sliced Wasserstein (SW) and Generalized Sliced Wasserstein (GSW) have been widely used in applications due to their computational and statistical scalability. However, the SW and the GSW are only defined between distributions supported on a homogeneous domain. This limitation prevents their usage in applications with h...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	449,076
1908.03963	A Review of Cooperative Multi-Agent Deep Reinforcement Learning	Deep Reinforcement Learning has made significant progress in multi-agent systems in recent years. In this review article, we have focused on presenting recent approaches on Multi-Agent Reinforcement Learning (MARL) algorithms. In particular, we have focused on five common approaches on modeling and solving cooperative ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	141,365
2203.16518	Collaborative Transformers for Grounded Situation Recognition	Grounded situation recognition is the task of predicting the main activity, entities playing certain roles within the activity, and bounding-box groundings of the entities in the given image. To effectively deal with this challenging task, we introduce a novel approach where the two processes for activity classificatio...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	288,816
2411.12573	Locomotion Mode Transitions: Tackling System- and User-Specific Variability in Lower-Limb Exoskeletons	Accurate detection of locomotion transitions, such as walk to sit, walk to stair ascent, and descent, is crucial to effectively control robotic assistive devices, such as lower-limb exoskeletons, as each locomotion mode requires specific assistance. Variability in collected sensor data introduced by user- or system-spe...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	509,452
2407.11108	SSSD-ECG-nle: New Label Embeddings with Structured State-Space Models for ECG generation	An electrocardiogram (ECG) is vital for identifying cardiac diseases, offering crucial insights for diagnosing heart conditions and informing potentially life-saving treatments. However, like other types of medical data, ECGs are subject to privacy concerns when distributed and analyzed. Diffusion models have made sign...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	473,314
2002.06048	AutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks	Existing fine-tuning methods use a single learning rate over all layers. In this paper, first, we discuss that trends of layer-wise weight variations by fine-tuning using a single learning rate do not match the well-known notion that lower-level layers extract general features and higher-level layers extract specific f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	164,074
2106.07353	Posthoc Verification and the Fallibility of the Ground Truth	Classifiers commonly make use of pre-annotated datasets, wherein a model is evaluated by pre-defined metrics on a held-out test set typically made of human-annotated labels. Metrics used in these evaluations are tied to the availability of well-defined ground truth labels, and these metrics typically do not allow for i...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	240,891
2212.06832	Multi-Target Decision Making under Conditions of Severe Uncertainty	The quality of consequences in a decision making problem under (severe) uncertainty must often be compared among different targets (goals, objectives) simultaneously. In addition, the evaluations of a consequence's performance under the various targets often differ in their scale of measurement, classically being eithe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	336,227
2209.03356	AST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting	Electric Vehicle (EV) charging demand and charging station availability forecasting is one of the challenges in the intelligent transportation system. With the accurate EV station situation prediction, suitable charging behaviors could be scheduled in advance to relieve range anxiety. Many existing deep learning method...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	316,480
2207.11679	Affective Behaviour Analysis Using Pretrained Model with Facial Priori	Affective behaviour analysis has aroused researchers' attention due to its broad applications. However, it is labor exhaustive to obtain accurate annotations for massive face images. Thus, we propose to utilize the prior facial information via Masked Auto-Encoder (MAE) pretrained on unlabeled face images. Furthermore, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,735
2202.03078	Fair Interpretable Representation Learning with Correction Vectors	Neural network architectures have been extensively employed in the fair representation learning setting, where the objective is to learn a new representation for a given vector which is independent of sensitive information. Various representation debiasing techniques have been proposed in the literature. However, as ne...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	279,067
2408.01737	Tightly Coupled SLAM with Imprecise Architectural Plans	Robots navigating indoor environments often have access to architectural plans, which can serve as prior knowledge to enhance their localization and mapping capabilities. While some SLAM algorithms leverage these plans for global localization in real-world environments, they typically overlook a critical challenge: the...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	478,356
2107.05315	Contrastive Learning for Cold-Start Recommendation	Recommending cold-start items is a long-standing and fundamental challenge in recommender systems. Without any historical interaction on cold-start items, CF scheme fails to use collaborative signals to infer user preference on these items. To solve this problem, extensive studies have been conducted to incorporate sid...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	245,739
1911.09816	Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy	Principal component analysis (PCA) is arguably the most widely used dimension-reduction method for vector-type data. When applied to a sample of images, PCA requires vectorization of the image data, which in turn entails solving an eigenvalue problem for the sample covariance matrix. We propose herein a two-stage dimen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	154,626
2207.11158	SPRT-based Efficient Best Arm Identification in Stochastic Bandits	This paper investigates the best arm identification (BAI) problem in stochastic multi-armed bandits in the fixed confidence setting. The general class of the exponential family of bandits is considered. The existing algorithms for the exponential family of bandits face computational challenges. To mitigate these challe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	309,521
1902.08061	Development of a classifiers/quantifiers dictionary towards French-Japanese MT	Although classifiers/quantifiers (CQs) expressions appear frequently in everyday communications or written documents, they are described neither in classical bilingual paper dictionaries , nor in machine-readable dictionaries. The paper describes a CQs dictionary, edited from the corpus we have annotated, and its usage...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	122,118
2101.02897	Sequential Naive Learning	We analyze boundedly rational updating from aggregate statistics in a model with binary actions and binary states. Agents each take an irreversible action in sequence after observing the unordered set of previous actions. Each agent first forms her prior based on the aggregate statistic, then incorporates her signal wi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	214,764
2306.00021	Explaining Hate Speech Classification with Model Agnostic Methods	There have been remarkable breakthroughs in Machine Learning and Artificial Intelligence, notably in the areas of Natural Language Processing and Deep Learning. Additionally, hate speech detection in dialogues has been gaining popularity among Natural Language Processing researchers with the increased use of social med...	true	false	false	true	true	false	false	false	true	false	false	false	false	false	false	false	false	false	369,836
2410.17735	New Insight in Cervical Cancer Diagnosis Using Convolution Neural Network Architecture	The Pap smear is a screening method for early cervical cancer diagnosis. The selection of the right optimizer in the convolutional neural network (CNN) model is key to the success of the CNN in image classification, including the classification of cervical cancer Pap smear images. In this study, stochastic gradient des...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	501,590
2212.14197	PointVST: Self-Supervised Pre-training for 3D Point Clouds via View-Specific Point-to-Image Translation	The past few years have witnessed the great success and prevalence of self-supervised representation learning within the language and 2D vision communities. However, such advancements have not been fully migrated to the field of 3D point cloud learning. Different from existing pre-training paradigms designed for deep p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	338,540
2401.05928	Mitigating Unhelpfulness in Emotional Support Conversations with Multifaceted AI Feedback	An emotional support conversation system aims to alleviate users' emotional distress and assist them in addressing their challenges. To generate supportive responses, it is critical to consider multiple factors such as empathy, support strategies, and response coherence, as established in prior methods. Nonetheless, pr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	420,963
1407.5396	Symblicit algorithms for optimal strategy synthesis in monotonic Markov decision processes	When treating Markov decision processes (MDPs) with large state spaces, using explicit representations quickly becomes unfeasible. Lately, Wimmer et al. have proposed a so-called symblicit algorithm for the synthesis of optimal strategies in MDPs, in the quantitative setting of expected mean-payoff. This algorithm, bas...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	34,773
1904.07974	Discovering Episodes with Compact Minimal Windows	Discovering the most interesting patterns is the key problem in the field of pattern mining. While ranking or selecting patterns is well-studied for itemsets it is surprisingly under-researched for other, more complex, pattern types. In this paper we propose a new quality measure for episodes. An episode is essential...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	127,927
1901.04292	Risk-Aware Resource Allocation for URLLC: Challenges and Strategies with Machine Learning	Supporting ultra-reliable low-latency communications (URLLC) is a major challenge of 5G wireless networks. Stringent delay and reliability requirements need to be satisfied for both scheduled and non-scheduled URLLC traffic to enable a diverse set of 5G applications. Although physical and media access control layer sol...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	118,581
2409.10864	Distributed Optimization for Traffic Light Control and Connected Automated Vehicle Coordination in Mixed-Traffic Intersections	In this paper, we consider the problem of coordinating traffic light systems and connected automated vehicles (CAVs) in mixed-traffic intersections. We aim to develop an optimization-based control framework that leverages both the coordination capabilities of CAVs at higher penetration rates and intelligent traffic man...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	488,906
2204.06835	GloCAL: Glocalized Curriculum-Aided Learning of Multiple Tasks with Application to Robotic Grasping	The domain of robotics is challenging to apply deep reinforcement learning due to the need for large amounts of data and for ensuring safety during learning. Curriculum learning has shown good performance in terms of sample- efficient deep learning. In this paper, we propose an algorithm (named GloCAL) that creates a c...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	291,464
2302.01364	Cycles in Impulsive Goodwin's Oscillators of Arbitrary Order	Existence of periodical solutions, i.e. cycles, in the Impulsive Goodwin's Oscillator (IGO) with the continuous part of an arbitrary order m is considered. The original IGO with a third-order continuous part is a hybrid model that portrays a chemical or biochemical system composed of three substances represented by the...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	343,567
1308.5673	Nonlocal linear compression of two-photon time interval distribution	We propose a linear compression technique for the time interval distribution of photon pairs. Using a partially frequency-entangled two-photon (TP) state with appropriate mean time width, the compressed TP time interval width can be kept in the minimum limit set by the phase modulation, and is independent of its initia...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	26,654
1810.12195	Efficient convex optimization for optimal PMU placement in large distribution grids	The small amount of measurements in distribution grids makes their monitoring more difficult. Topological observability may not be possible, and thus, pseudo-measurements are needed to perform state estimation, which is required to control elements such as distributed generation or transformers at distribution grids. T...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	111,715
2204.01134	Control Co-design of a Hydrokinetic Turbine with Open-loop Optimal Control	This paper introduces a control co-design (CCD) framework to simultaneously explore the physical parameters and control spaces for a hydro-kinetic turbine (HKT) rotor optimization. The optimization formulation incorporates a coupled dynamic-hydrodynamic model to maximize the rotor power efficiency for various time-vari...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	289,508
0809.0158	Network Tomography Based on Additive Metrics	Inference of the network structure (e.g., routing topology) and dynamics (e.g., link performance) is an essential component in many network design and management tasks. In this paper we propose a new, general framework for analyzing and designing routing topology and link performance inference algorithms using ideas an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	2,257
2206.01465	PAC Statistical Model Checking of Mean Payoff in Discrete- and Continuous-Time MDP	Markov decision processes (MDP) and continuous-time MDP (CTMDP) are the fundamental models for non-deterministic systems with probabilistic uncertainty. Mean payoff (a.k.a. long-run average reward) is one of the most classic objectives considered in their context. We provide the first algorithm to compute mean payoff p...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	300,486
2406.18020	MolFusion: Multimodal Fusion Learning for Molecular Representations via Multi-granularity Views	Artificial Intelligence predicts drug properties by encoding drug molecules, aiding in the rapid screening of candidates. Different molecular representations, such as SMILES and molecule graphs, contain complementary information for molecular encoding. Thus exploiting complementary information from different molecular ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	467,835
1903.00812	3D Hand Shape and Pose Estimation from a Single RGB Image	This work addresses a novel and challenging problem of estimating the full 3D hand shape and pose from a single RGB image. Most current methods in 3D hand analysis from monocular RGB images only focus on estimating the 3D locations of hand keypoints, which cannot fully express the 3D shape of hand. In contrast, we prop...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	123,106
2105.07553	Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing	Due to its powerful capability of representation learning and high-efficiency computation, deep hashing has made significant progress in large-scale image retrieval. However, deep hashing networks are vulnerable to adversarial examples, which is a practical secure problem but seldom studied in hashing-based retrieval f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	235,469
2408.07989	IIU: Independent Inference Units for Knowledge-based Visual Question Answering	Knowledge-based visual question answering requires external knowledge beyond visible content to answer the question correctly. One limitation of existing methods is that they focus more on modeling the inter-modal and intra-modal correlations, which entangles complex multimodal clues by implicit embeddings and lacks in...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	480,808
2312.17642	Research on the Laws of Multimodal Perception and Cognition from a Cross-cultural Perspective -- Taking Overseas Chinese Gardens as an Example	This study aims to explore the complex relationship between perceptual and cognitive interactions in multimodal data analysis,with a specific emphasis on spatial experience design in overseas Chinese gardens. It is found that evaluation content and images on social media can reflect individuals' concerns and sentiment ...	false	false	false	true	true	false	false	false	true	false	false	true	false	false	false	false	false	false	418,815
2407.12501	EmoFace: Audio-driven Emotional 3D Face Animation	Audio-driven emotional 3D face animation aims to generate emotionally expressive talking heads with synchronized lip movements. However, previous research has often overlooked the influence of diverse emotions on facial expressions or proved unsuitable for driving MetaHuman models. In response to this deficiency, we in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	473,958
1604.03901	Single-Image Depth Perception in the Wild	This paper studies single-image depth perception in the wild, i.e., recovering depth from a single image taken in unconstrained settings. We introduce a new dataset "Depth in the Wild" consisting of images in the wild annotated with relative depth between pairs of random points. We also propose a new algorithm that lea...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	54,575
1911.04787	Effects of data ambiguity and cognitive biases on the interpretability of machine learning models in humanitarian decision making	The effectiveness of machine learning algorithms depends on the quality and amount of data and the operationalization and interpretation by the human analyst. In humanitarian response, data is often lacking or overburdening, thus ambiguous, and the time-scarce, volatile, insecure environments of humanitarian activities...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,077
2207.07117	A Novel Implementation of Machine Learning for the Efficient, Explainable Diagnosis of COVID-19 from Chest CT	In a worldwide health crisis as exigent as COVID-19, there has become a pressing need for rapid, reliable diagnostics. Currently, popular testing methods such as reverse transcription polymerase chain reaction (RT-PCR) can have high false negative rates. Consequently, COVID-19 patients are not accurately identified nor...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	308,112
2308.13340	TriGait: Aligning and Fusing Skeleton and Silhouette Gait Data via a Tri-Branch Network	Gait recognition is a promising biometric technology for identification due to its non-invasiveness and long-distance. However, external variations such as clothing changes and viewpoint differences pose significant challenges to gait recognition. Silhouette-based methods preserve body shape but neglect internal struct...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,881
2405.14249	Identifying Breakdowns in Conversational Recommender Systems using User Simulation	We present a methodology to systematically test conversational recommender systems with regards to conversational breakdowns. It involves examining conversations generated between the system and simulated users for a set of pre-defined breakdown types, extracting responsible conversational paths, and characterizing the...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	456,331
2111.12495	Altering Backward Pass Gradients improves Convergence	In standard neural network training, the gradients in the backward pass are determined by the forward pass. As a result, the two stages are coupled. This is how most neural networks are trained currently. However, gradient modification in the backward pass has seldom been studied in the literature. In this paper we exp...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	267,986
2305.15332	Inverse optimal control for averaged cost per stage linear quadratic regulators	Inverse Optimal Control (IOC) is a powerful framework for learning a behaviour from observations of experts. The framework aims to identify the underlying cost function that the observed optimal trajectories (the experts' behaviour) are optimal with respect to. In this work, we considered the case of identifying the co...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	367,570
2202.01046	Towards High-Payload Admittance Control for Manual Guidance with Environmental Contact	Force control enables hands-on teaching and physical collaboration, with the potential to improve ergonomics and flexibility of automation. Established methods for the design of compliance, impedance control, and \rev{collision response} can achieve free-space stability and acceptable peak contact force on lightweight,...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	278,355
2304.00698	A Post-Training Framework for Improving Heterogeneous Graph Neural Networks	Recent years have witnessed the success of heterogeneous graph neural networks (HGNNs) in modeling heterogeneous information networks (HINs). In this paper, we focus on the benchmark task of HGNNs, i.e., node classification, and empirically find that typical HGNNs are not good at predicting the label of a test node who...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	355,779
2307.16788	Congestion Analysis for the DARPA OFFSET CCAST Swarm	The Defense Advanced Research Projects Agency (DARPA) OFFensive Swarm-Enabled Tactics program's goal of launching 250 unmanned aerial and ground vehicles from a limited sized launch zone was a daunting challenge. The swarm's aerial vehicles were primarily multirotor platforms, which can efficiently be launched en masse...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	382,736
2102.10283	Imitation Learning for Variable Speed Contact Motion for Operation up to Control Bandwidth	The generation of robot motions in the real world is difficult by using conventional controllers alone and requires highly intelligent processing. In this regard, learning-based motion generations are currently being investigated. However, the main issue has been improvements of the adaptability to spatially varying en...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	221,035
2411.17598	Agentic AI for Improving Precision in Identifying Contributions to Sustainable Development Goals	As research institutions increasingly commit to supporting the United Nations' Sustainable Development Goals (SDGs), there is a pressing need to accurately assess their research output against these goals. Current approaches, primarily reliant on keyword-based Boolean search queries, conflate incidental keyword matches...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	true	511,511
1805.09957	Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions	Various 3D semantic attributes such as segmentation masks, geometric features, keypoints, and materials can be encoded as per-point probe functions on 3D geometries. Given a collection of related 3D shapes, we consider how to jointly analyze such probe functions over different shapes, and how to discover common latent ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	98,538
2302.13212	Implicit Contact-Rich Manipulation Planning for a Manipulator with Insufficient Payload	This paper uses a mobile manipulator with a collaborative robotic arm to manipulate objects beyond the robot's maximum payload. It proposes a single-shot probabilistic roadmap-based method to plan and optimize manipulation motion with environment support. The method uses an expanded object mesh model to examine contact...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	347,860
2203.07973	MOBDrone: a Drone Video Dataset for Man OverBoard Rescue	Modern Unmanned Aerial Vehicles (UAV) equipped with cameras can play an essential role in speeding up the identification and rescue of people who have fallen overboard, i.e., man overboard (MOB). To this end, Artificial Intelligence techniques can be leveraged for the automatic understanding of visual data acquired fro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,622
1507.00448	Cross Modal Distillation for Supervision Transfer	In this work we propose a technique that transfers supervision between images from different modalities. We use learned representations from a large labeled modality as a supervisory signal for training representations for a new unlabeled paired modality. Our method enables learning of rich representations for unlabele...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	44,760
2106.00219	Question-aware Transformer Models for Consumer Health Question Summarization	Searching for health information online is becoming customary for more and more consumers every day, which makes the need for efficient and reliable question answering systems more pressing. An important contributor to the success rates of these systems is their ability to fully understand the consumers' questions. How...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	238,038
1404.4884	Causal Interfaces	The interaction of two binary variables, assumed to be empirical observations, has three degrees of freedom when expressed as a matrix of frequencies. Usually, the size of causal influence of one variable on the other is calculated as a single value, as increase in recovery rate for a medical treatment, for example. We...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	32,441
2106.05227	Understanding Privacy Attitudes and Concerns Towards Remote Communications During the COVID-19 Pandemic	Since December 2019, the COVID-19 pandemic has caused people around the world to exercise social distancing, which has led to an abrupt rise in the adoption of remote communications for working, socializing, and learning from home. As remote communications will outlast the pandemic, it is crucial to protect users' secu...	true	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	false	240,016
2309.07662	Guaranteed approximations of arbitrarily quantified reachability problems	We propose an approach to compute inner and outer-approximations of the sets of values satisfying constraints expressed as arbitrarily quantified formulas. Such formulas arise for instance when specifying important problems in control such as robustness, motion planning or controllers comparison. We propose an interval...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	391,858
2006.01414	Enhanced Universal Dependency Parsing with Second-Order Inference and Mixture of Training Data	This paper presents the system used in our submission to the \textit{IWPT 2020 Shared Task}. Our system is a graph-based parser with second-order inference. For the low-resource Tamil corpus, we specially mixed the training data of Tamil with other languages and significantly improved the performance of Tamil. Due to o...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	179,767
2412.14570	Characterising Simulation-Based Program Equilibria	In Tennenholtz's program equilibrium, players of a game submit programs to play on their behalf. Each program receives the other programs' source code and outputs an action. This can model interactions involving AI agents, mutually transparent institutions, or commitments. Tennenholtz (2004) proves a folk theorem for p...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	518,767
2410.14170	Personalized Image Generation with Large Multimodal Models	Personalized content filtering, such as recommender systems, has become a critical infrastructure to alleviate information overload. However, these systems merely filter existing content and are constrained by its limited diversity, making it difficult to meet users' varied content needs. To address this limitation, pe...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	true	499,909
1906.00183	Relay-Aided Channel Estimation for mmWave Systems with Imperfect Antenna Arrays	Compressed Sensing (CS) based channel estimation techniques have recently emerged as an effective way to acquire the channel of millimeter-wave (mmWave) systems with a small number of measurements. These techniques, however, are based on prior knowledge of transmit and receive array manifolds, and assume perfect antenn...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	133,296
1802.08920	Geometric Surface-Based Tracking Control of a Quadrotor UAV	New quadrotor UAV control algorithms are developed, based on nonlinear surfaces composed of tracking errors that evolve directly on the nonlinear configuration manifold, thus inherently including in the control design the nonlinear characteristics of the SE(3) configuration space. In particular, geometric surface-based...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	91,218
2408.15990	A Control Theoretic Approach to Simultaneously Estimate Average Value of Time and Determine Dynamic Price for High-occupancy Toll Lanes	The dynamic pricing problem of a freeway corridor with high-occupancy toll (HOT) lanes was formulated and solved based on a point queue abstraction of the traffic system [Yin and Lou, 2009]. However, existing pricing strategies cannot guarantee that the closed-loop system converges to the optimal state, in which the HO...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	484,146
1811.06560	High Granular Operator Spaces, and Less-Contaminated General Rough Mereologies	Granular operator spaces and variants had been introduced and used in theoretical investigations on the foundations of general rough sets by the present author over the last few years. In this research, higher order versions of these are presented uniformly as partial algebraic systems. They are also adapted for practi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	113,550
2409.13649	RainbowSight: A Family of Generalizable, Curved, Camera-Based Tactile Sensors For Shape Reconstruction	Camera-based tactile sensors can provide high resolution positional and local geometry information for robotic manipulation. Curved and rounded fingers are often advantageous, but it can be difficult to derive illumination systems that work well within curved geometries. To address this issue, we introduce RainbowSight...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	490,083
1906.11356	Personalized Student Stress Prediction with Deep Multitask Network	With the growing popularity of wearable devices, the ability to utilize physiological data collected from these devices to predict the wearer's mental state such as mood and stress suggests great clinical applications, yet such a task is extremely challenging. In this paper, we present a general platform for personaliz...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	136,643
2410.06083	Classification of simulation relations for symbolic control	Abstraction-based control design is a promising approach for ensuring safety-critical control of complex cyber-physical systems. A key aspect of this methodology is the relation between the original and abstract systems, which ensures that the abstract controller can be transformed into a valid controller for the origi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	496,043
2310.07525	ViT-A: Legged Robot Path Planning using Vision Transformer A	Legged robots, particularly quadrupeds, offer promising navigation capabilities, especially in scenarios requiring traversal over diverse terrains and obstacle avoidance. This paper addresses the challenge of enabling legged robots to navigate complex environments effectively through the integration of data-driven path...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	399,009
2006.15273	Data-Driven Topology Optimization with Multiclass Microstructures using Latent Variable Gaussian Process	The data-driven approach is emerging as a promising method for the topological design of multiscale structures with greater efficiency. However, existing data-driven methods mostly focus on a single class of microstructures without considering multiple classes to accommodate spatially varying desired properties. The ke...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,456
2010.11644	Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks	Researchers often treat data-driven and theory-driven models as two disparate or even conflicting methods in travel behavior analysis. However, the two methods are highly complementary because data-driven methods are more predictive but less interpretable and robust, while theory-driven methods are more interpretable a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,346
2105.03296	VIRAL SLAM: Tightly Coupled Camera-IMU-UWB-Lidar SLAM	In this paper, we propose a tightly-coupled, multi-modal simultaneous localization and mapping (SLAM) framework, integrating an extensive set of sensors: IMU, cameras, multiple lidars, and Ultra-wideband (UWB) range measurements, hence referred to as VIRAL (visual-inertial-ranging-lidar) SLAM. To achieve such a compreh...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	234,104
2305.16816	Songs Across Borders: Singable and Controllable Neural Lyric Translation	The development of general-domain neural machine translation (NMT) methods has advanced significantly in recent years, but the lack of naturalness and musical constraints in the outputs makes them unable to produce singable lyric translations. This paper bridges the singability quality gap by formalizing lyric translat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	368,266
2406.09661	Temporal Planning via Interval Logic Satisfiability for Autonomous Systems	Many automated planning methods and formulations rely on suitably designed abstractions or simplifications of the constrained dynamics associated with agents to attain computational scalability. We consider formulations of temporal planning where intervals are associated with both action and fluent atoms, and relations...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	true	464,028
1709.05231	A Spectral Method for Activity Shaping in Continuous-Time Information Cascades	Information Cascades Model captures dynamical properties of user activity in a social network. In this work, we develop a novel framework for activity shaping under the Continuous-Time Information Cascades Model which allows the administrator for local control actions by allocating targeted resources that can alter the...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	80,811
2003.00380	Unblind Your Apps: Predicting Natural-Language Labels for Mobile GUI Components by Deep Learning	According to the World Health Organization(WHO), it is estimated that approximately 1.3 billion people live with some forms of vision impairment globally, of whom 36 million are blind. Due to their disability, engaging these minority into the society is a challenging problem. The recent rise of smart mobile phones prov...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	166,277
1610.05710	Feasibility Based Large Margin Nearest Neighbor Metric Learning	Large margin nearest neighbor (LMNN) is a metric learner which optimizes the performance of the popular $k$NN classifier. However, its resulting metric relies on pre-selected target neighbors. In this paper, we address the feasibility of LMNN's optimization constraints regarding these target points, and introduce a mat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	62,551
2010.04532	Measuring What Counts: The case of Rumour Stance Classification	Stance classification can be a powerful tool for understanding whether and which users believe in online rumours. The task aims to automatically predict the stance of replies towards a given rumour, namely support, deny, question, or comment. Numerous methods have been proposed and their performance compared in the Rum...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	199,775
2107.11637	Group-based Motion Prediction for Navigation in Crowded Environments	We focus on the problem of planning the motion of a robot in a dynamic multiagent environment such as a pedestrian scene. Enabling the robot to navigate safely and in a socially compliant fashion in such scenes requires a representation that accounts for the unfolding multiagent dynamics. Existing approaches to this pr...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	247,644
2210.00137	Going In Blind: Object Motion Classification using Distributed Tactile Sensing for Safe Reaching in Clutter	Robotic manipulators navigating cluttered shelves or cabinets may find it challenging to avoid contact with obstacles. Indeed, rearranging obstacles may be necessary to access a target. Rather than planning explicit motions that place obstacles into a desired pose, we suggest allowing incidental contacts to rearrange o...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	320,752
2403.18356	MonoHair: High-Fidelity Hair Modeling from a Monocular Video	Undoubtedly, high-fidelity 3D hair is crucial for achieving realism, artistic expression, and immersion in computer graphics. While existing 3D hair modeling methods have achieved impressive performance, the challenge of achieving high-quality hair reconstruction persists: they either require strict capture conditions,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	441,904
2407.09935	LeRF: Learning Resampling Function for Adaptive and Efficient Image Interpolation	Image resampling is a basic technique that is widely employed in daily applications, such as camera photo editing. Recent deep neural networks (DNNs) have made impressive progress in performance by introducing learned data priors. Still, these methods are not the perfect substitute for interpolation, due to the drawbac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	472,779
2112.00516	Simultaneous Controller and Lyapunov Function Design for Constrained Nonlinear Systems	This paper presents a method to stabilize state and input constrained nonlinear systems using an offline optimization on variable triangulations of the set of admissible states. For control-affine systems, by choosing a continuous piecewise affine (CPA) controller structure, the non-convex optimization is formulated as...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	269,160
2006.01671	A generalized linear joint trained framework for semi-supervised learning of sparse features	The elastic-net is among the most widely used types of regularization algorithms, commonly associated with the problem of supervised generalized linear model estimation via penalized maximum likelihood. Its nice properties originate from a combination of $\ell_1$ and $\ell_2$ norms, which endow this method with the abi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	179,838
2011.01285	Exemplar Guided Active Learning	We consider the problem of wisely using a limited budget to label a small subset of a large unlabeled dataset. We are motivated by the NLP problem of word sense disambiguation. For any word, we have a set of candidate labels from a knowledge base, but the label set is not necessarily representative of what occurs in th...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	204,535
2003.08593	Curriculum DeepSDF	When learning to sketch, beginners start with simple and flexible shapes, and then gradually strive for more complex and accurate ones in the subsequent training sessions. In this paper, we design a "shape curriculum" for learning continuous Signed Distance Function (SDF) on shapes, namely Curriculum DeepSDF. Inspired ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,785
2311.02461	SPHEAR: Spherical Head Registration for Complete Statistical 3D Modeling	We present \emph{SPHEAR}, an accurate, differentiable parametric statistical 3D human head model, enabled by a novel 3D registration method based on spherical embeddings. We shift the paradigm away from the classical Non-Rigid Registration methods, which operate under various surface priors, increasing reconstruction f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	405,453
2409.06187	Bottleneck-based Encoder-decoder ARchitecture (BEAR) for Learning Unbiased Consumer-to-Consumer Image Representations	Unbiased representation learning is still an object of study under specific applications and contexts. Novel architectures are usually crafted to resolve particular problems using mixtures of fundamental pieces. This paper presents different image feature extraction mechanisms that work together with residual connectio...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	487,030
2212.08888	Exploiting Rich Textual User-Product Context for Improving Sentiment Analysis	User and product information associated with a review is useful for sentiment polarity prediction. Typical approaches incorporating such information focus on modeling users and products as implicitly learned representation vectors. Most do not exploit the potential of historical reviews, or those that currently do requ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	336,907
2007.07841	Align then Summarize: Automatic Alignment Methods for Summarization Corpus Creation	Summarizing texts is not a straightforward task. Before even considering text summarization, one should determine what kind of summary is expected. How much should the information be compressed? Is it relevant to reformulate or should the summary stick to the original phrasing? State-of-the-art on automatic text summar...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	187,450
2104.07932	Interval-censored Hawkes processes	Interval-censored data solely records the aggregated counts of events during specific time intervals - such as the number of patients admitted to the hospital or the volume of vehicles passing traffic loop detectors - and not the exact occurrence time of the events. It is currently not understood how to fit the Hawkes ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	230,604
2302.09319	MAILS -- Meta AI Literacy Scale: Development and Testing of an AI Literacy Questionnaire Based on Well-Founded Competency Models and Psychological Change- and Meta-Competencies	The goal of the present paper is to develop and validate a questionnaire to assess AI literacy. In particular, the questionnaire should be deeply grounded in the existing literature on AI literacy, should be modular (i.e., including different facets that can be used independently of each other) to be flexibly applicabl...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	346,371
2106.12398	End-to-End Lexically Constrained Machine Translation for Morphologically Rich Languages	Lexically constrained machine translation allows the user to manipulate the output sentence by enforcing the presence or absence of certain words and phrases. Although current approaches can enforce terms to appear in the translation, they often struggle to make the constraint word form agree with the rest of the gener...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	242,717
1508.04186	Distributed Deep Q-Learning	We propose a distributed deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is based on the deep Q-network, a convolutional neural network trained with a variant of Q-learning. Its input is raw pixels and its output is a value ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	true	46,101
1203.1338	Network Structure, Topology and Dynamics in Generalized Models of Synchronization	We explore the interplay of network structure, topology, and dynamic interactions between nodes using the paradigm of distributed synchronization in a network of coupled oscillators. As the network evolves to a global steady state, interconnected oscillators synchronize in stages, revealing network's underlying communi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	14,743
1809.04227	Deep Co-investment Network Learning for Financial Assets	Most recent works model the market structure of the stock market as a correlation network of the stocks. They apply pre-defined patterns to extract correlation information from the time series of stocks. Without considering the influences of the evolving market structure to the market index trends, these methods hardly...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	107,507
1909.13046	Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation	This paper tackles the problem of video object segmentation. We are specifically concerned with the task of segmenting all pixels of a target object in all frames, given the annotation mask in the first frame. Even when such annotation is available this remains a challenging problem because of the changing appearance a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	147,309

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