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
2412.01595	Epipolar Attention Field Transformers for Bird's Eye View Semantic Segmentation	Spatial understanding of the semantics of the surroundings is a key capability needed by autonomous cars to enable safe driving decisions. Recently, purely vision-based solutions have gained increasing research interest. In particular, approaches extracting a bird's eye view (BEV) from multiple cameras have demonstrate...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	513,185
2305.09800	Mirages: On Anthropomorphism in Dialogue Systems	Automated dialogue or conversational systems are anthropomorphised by developers and personified by users. While a degree of anthropomorphism may be inevitable due to the choice of medium, conscious and unconscious design choices can guide users to personify such systems to varying degrees. Encouraging users to relate ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	364,779
2206.02104	ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences	This work addresses the problem of discovering non-linear interpretable paths in the latent space of pre-trained GANs in a model-agnostic manner. In the proposed method, the discovery is driven by a set of pairs of natural language sentences with contrasting semantics, named semantic dipoles, that serve as the limits o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	300,749
2305.19901	Adaptive Conformal Regression with Jackknife+ Rescaled Scores	Conformal regression provides prediction intervals with global coverage guarantees, but often fails to capture local error distributions, leading to non-homogeneous coverage. We address this with a new adaptive method based on rescaling conformal scores with an estimate of local score distribution, inspired by the Jack...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	369,726
2206.11948	Strong Duality in Risk-Constrained Nonconvex Functional Programming	We show that risk-constrained functional optimization problems with general integrable nonconvex instantaneous reward/constraint functions exhibit strong duality, regardless of nonconvexity. We consider risk constraints featuring convex and positively homogeneous risk measures admitting dual representations with bounde...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	304,426
quant-ph/0202016	Neural Networks with c-NOT Gated Nodes	We try to design a quantum neural network with qubits instead of classical neurons with deterministic states, and also with quantum operators replacing teh classical action potentials. With our choice of gates interconnecting teh neural lattice, it appears that the state of the system behaves in ways reflecting both th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	540,869
1604.03764	Two-sided Matching Based Cooperative Spectrum Sharing	Dynamic spectrum access (DSA) can effectively improve the spectrum efficiency and alleviate the spectrum scarcity, by allowing unlicensed secondary users (SUs) to access the licensed spectrum of primary users (PUs) opportunistically. Cooperative spectrum sharing is a new promising paradigm to provide necessary incentiv...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	54,564
2402.07419	Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand	Causal inference from observational data plays critical role in many applications in trustworthy machine learning. While sound and complete algorithms exist to compute causal effects, many of them assume access to conditional likelihoods, which is difficult to estimate for high-dimensional (particularly image) data. Re...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	428,710
2303.13175	Enhancement of theColor Image Compression Using a New Algorithm based on Discrete Hermite Wavelet Transform	The Internet has turned the entire world into a small village;this is because it has made it possible to share millions of images and videos. However, sending and receiving a huge amount of data is considered to be a main challenge. To address this issue, a new algorithm is required to reduce image bits and represent t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	353,572
2405.20956	A Robot Walks into a Bar: Can Language Models Serve as Creativity Support Tools for Comedy? An Evaluation of LLMs' Humour Alignment with Comedians	We interviewed twenty professional comedians who perform live shows in front of audiences and who use artificial intelligence in their artistic process as part of 3-hour workshops on ``AI x Comedy'' conducted at the Edinburgh Festival Fringe in August 2023 and online. The workshop consisted of a comedy writing session ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	459,583
2412.18667	State-of-the-Art Underwater Vehicles and Technologies Enabling Smart Ocean: Survey and Classifications	The exploration and sustainable use of marine environments have become increasingly critical as oceans cover over 70% of surface of Earth. This paper provides a comprehensive survey and classification of state-of-the-art underwater vehicles (UVs) and supporting technologies essential for enabling a smart ocean. We cate...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	520,515
2311.03798	Noisy Pair Corrector for Dense Retrieval	Most dense retrieval models contain an implicit assumption: the training query-document pairs are exactly matched. Since it is expensive to annotate the corpus manually, training pairs in real-world applications are usually collected automatically, which inevitably introduces mismatched-pair noise. In this paper, we ex...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	406,003
2402.02694	Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift	Acoustic scene classification (ASC) is a crucial research problem in computational auditory scene analysis, and it aims to recognize the unique acoustic characteristics of an environment. One of the challenges of the ASC task is the domain shift between training and testing data. Since 2018, ASC challenges have focused...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	426,688
1601.01887	Research Project: Text Engineering Tool for Ontological Scientometry	The number of scientific papers grows exponentially in many disciplines. The share of online available papers grows as well. At the same time, the period of time for a paper to loose at chance to be cited anymore shortens. The decay of the citing rate shows similarity to ultradiffusional processes as for other online c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	50,779
1401.6964	Co-Evolution of Friendship and Publishing in Online Blogging Social Networks	In the past decade, blogging web sites have become more sophisticated and influential than ever. Much of this sophistication and influence follows from their network organization. Blogging social networks (BSNs) allow individual bloggers to form contact lists, subscribe to other blogs, comment on blog posts, declare in...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	30,416
2103.10533	Resilient Cooperative Adaptive Cruise Control for Autonomous Vehicles Using Machine Learning	Cooperative Adaptive Cruise Control (CACC) is a fundamental connected vehicle application that extends Adaptive Cruise Control by exploiting vehicle-to-vehicle (V2V) communication. CACC is a crucial ingredient for numerous autonomous vehicle functionalities including platooning, distributed route management, etc. Unfor...	false	false	false	false	false	false	false	true	false	false	true	false	true	false	false	false	false	false	225,484
2107.09427	RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank	Generative Adversarial Networks (GAN) have demonstrated the potential to recover realistic details for single image super-resolution (SISR). To further improve the visual quality of super-resolved results, PIRM2018-SR Challenge employed perceptual metrics to assess the perceptual quality, such as PI, NIQE, and Ma. Howe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	247,026
2402.13379	Referee-Meta-Learning for Fast Adaptation of Locational Fairness	When dealing with data from distinct locations, machine learning algorithms tend to demonstrate an implicit preference of some locations over the others, which constitutes biases that sabotage the spatial fairness of the algorithm. This unfairness can easily introduce biases in subsequent decision-making given broad ad...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	431,215
1707.08705	A Jointly Learned Deep Architecture for Facial Attribute Analysis and Face Detection in the Wild	Facial attribute analysis in the real world scenario is very challenging mainly because of complex face variations. Existing works of analyzing face attributes are mostly based on the cropped and aligned face images. However, this result in the capability of attribute prediction heavily relies on the preprocessing of f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	77,872
2209.15451	Semi-Supervised Domain Generalization for Cardiac Magnetic Resonance Image Segmentation with High Quality Pseudo Labels	Developing a deep learning method for medical segmentation tasks heavily relies on a large amount of labeled data. However, the annotations require professional knowledge and are limited in number. Recently, semi-supervised learning has demonstrated great potential in medical segmentation tasks. Most existing methods r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	320,615
2009.04372	A Generalized Online Algorithm for Translation and Scale Invariant Prediction with Expert Advice	In this work, we aim to create a completely online algorithmic framework for prediction with expert advice that is translation-free and scale-free of the expert losses. Our goal is to create a generalized algorithm that is suitable for use in a wide variety of applications. For this purpose, we study the expected regre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	195,021
2208.02802	Automatic dense annotation of large-vocabulary sign language videos	Recently, sign language researchers have turned to sign language interpreted TV broadcasts, comprising (i) a video of continuous signing and (ii) subtitles corresponding to the audio content, as a readily available and large-scale source of training data. One key challenge in the usability of such data is the lack of s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	311,571
1609.06669	Fast and reliable stereopsis measurement at multiple distances with iPad	Purpose: To present a new fast and reliable application for iPad (ST) for screening stereopsis at multiple distances. Methods: A new iPad application (app) based on a random dot stereogram was designed for screening stereopsis at multiple distances. Sixty-five subjects with no ocular diseases and wearing their habitu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	61,332
2311.01090	Infusion: internal diffusion for inpainting of dynamic textures and complex motion	Video inpainting is the task of filling a region in a video in a visually convincing manner. It is very challenging due to the high dimensionality of the data and the temporal consistency required for obtaining convincing results. Recently, diffusion models have shown impressive results in modeling complex data distrib...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	404,915
2406.15538	Model-based generation of representative rear-end crash scenarios across the full severity range using pre-crash data	Generating representative rear-end crash scenarios is crucial for safety assessments of Advanced Driver Assistance Systems (ADAS) and Automated Driving systems (ADS). However, existing methods for scenario generation face challenges such as limited and biased in-depth crash data and difficulties in validation. This stu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	466,771
2006.01301	Graph Unrolling Networks: Interpretable Neural Networks for Graph Signal Denoising	We propose an interpretable graph neural network framework to denoise single or multiple noisy graph signals. The proposed graph unrolling networks expand algorithm unrolling to the graph domain and provide an interpretation of the architecture design from a signal processing perspective. We unroll an iterative denoisi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	179,735
2008.05284	Modeling Prosodic Phrasing with Multi-Task Learning in Tacotron-based TTS	Tacotron-based end-to-end speech synthesis has shown remarkable voice quality. However, the rendering of prosody in the synthesized speech remains to be improved, especially for long sentences, where prosodic phrasing errors can occur frequently. In this paper, we extend the Tacotron-based speech synthesis framework to...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	191,473
2201.04066	VGAER: Graph Neural Network Reconstruction based Community Detection	Community detection is a fundamental and important issue in network science, but there are only a few community detection algorithms based on graph neural networks, among which unsupervised algorithms are almost blank. By fusing the high-order modularity information with network features, this paper proposes a Variatio...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	275,009
1604.05274	A Novel Gaussian Based Similarity Measure for Clustering Customer Transactions Using Transaction Sequence Vector	Clustering Transactions in sequence, temporal and time series databases is achieving an important attention from the database researchers and software industry. Significant research is carried out towards defining and validating the suitability of new similarity measures for sequence, temporal, time series databases wh...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	54,789
2102.07166	Task-oriented Communication Design in Cyber-Physical Systems: A Survey on Theory and Applications	Communications system design has been traditionally guided by task-agnostic principles, which aim at efficiently transmitting as many correct bits as possible through a given channel. However, in the era of cyber-physical systems, the effectiveness of communications is not dictated simply by the bit rate, but most impo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	220,016
2011.13194	Neural Networks for Pulmonary Disease Diagnosis using Auditory and Demographic Information	Pulmonary diseases impact millions of lives globally and annually. The recent outbreak of the pandemic of the COVID-19, a novel pulmonary infection, has more than ever brought the attention of the research community to the machine-aided diagnosis of respiratory problems. This paper is thus an effort to exploit machine ...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	208,406
2210.12381	S2WAT: Image Style Transfer via Hierarchical Vision Transformer using Strips Window Attention	Transformer's recent integration into style transfer leverages its proficiency in establishing long-range dependencies, albeit at the expense of attenuated local modeling. This paper introduces Strips Window Attention Transformer (S2WAT), a novel hierarchical vision transformer designed for style transfer. S2WAT employ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	325,716
2109.01817	Low SNR Capacity of Keyhole MIMO Channel in Nakagami-m Fading With Full CSI	In this paper, we obtain asymptotic expressions for the ergodic capacity of the keyhole multiple-input multiple-output (MIMO) channel at low signal-to-noise ratio (SNR) in independent and identically distributed Nakagami-$m$ fading conditions with perfect channel state information at the transmitter and receiver. We sh...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	253,544
1203.1515	Multiple Change Point Estimation in Stationary Ergodic Time Series	Given a heterogeneous time-series sample, the objective is to find points in time (called change points) where the probability distribution generating the data has changed. The data are assumed to have been generated by arbitrary unknown stationary ergodic distributions. No modelling, independence or mixing assumptions...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,759
2207.08336	When Fairness Meets Privacy: Fair Classification with Semi-Private Sensitive Attributes	Machine learning models have demonstrated promising performance in many areas. However, the concerns that they can be biased against specific demographic groups hinder their adoption in high-stake applications. Thus, it is essential to ensure fairness in machine learning models. Most previous efforts require direct acc...	false	false	false	false	true	false	true	false	false	false	false	false	true	true	false	false	false	false	308,550
1910.01623	A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data	Recently, there has been significant interest in linear regression in the situation where predictors and responses are not observed in matching pairs corresponding to the same statistical unit as a consequence of separate data collection and uncertainty in data integration. Mismatched pairs can considerably impact the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	147,986
1412.1257	Fast-Decodable Space-Time Codes for the $N$-Relay and Multiple-Access MIMO Channel	In this article, the first general constructions of fast-decodable, more specifically (conditionally) $g$-group decodable, space-time block codes for the Nonorthogonal Amplify and Forward (NAF) Multiple-Input Multiple-Output (MIMO) relay channel under the half-duplex constraint are proposed. In this scenario, the sourc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	38,089
2006.10468	Body Travel Performance Improvement of Space Vehicle Electromagnetic Suspension System using LQG and LQI Control Methods	Electromagnetic suspension system (EMS) is mostly used in the field of high-speed vehicle. In this paper, a space exploring vehicle quarter electromagnetic suspension system is modelled, designed and simulated using linear quadratic optimal control problem. Linear quadratic Gaussian and linear quadratic integral contro...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	182,895
1711.04189	A distributed system for SearchOnMath based on the Microsoft BizSpark program	Mathematical information retrieval is a relatively new area, so the first search tools capable of retrieving mathematical formulas began to appear only a few years ago. The proposals made public so far mostly implement searches on internal university databases, small sets of scientific papers, or Wikipedia in English. ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	84,350
1605.01576	Patch-based Texture Synthesis for Image Inpainting	Image inpaiting is an important task in image processing and vision. In this paper, we develop a general method for patch-based image inpainting by synthesizing new textures from existing one. A novel framework is introduced to find several optimal candidate patches and generate a new texture patch in the process. We f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	55,494
2310.16484	Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training	Representational spaces learned via language modeling are fundamental to Natural Language Processing (NLP), however there has been limited understanding regarding how and when during training various types of linguistic information emerge and interact. Leveraging a novel information theoretic probing suite, which enabl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	402,746
1803.04706	Policy Search in Continuous Action Domains: an Overview	Continuous action policy search is currently the focus of intensive research, driven both by the recent success of deep reinforcement learning algorithms and the emergence of competitors based on evolutionary algorithms. In this paper, we present a broad survey of policy search methods, providing a unified perspective ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	92,502
2205.13709	DP-PCA: Statistically Optimal and Differentially Private PCA	We study the canonical statistical task of computing the principal component from $n$ i.i.d.~data in $d$ dimensions under $(\varepsilon,\delta)$-differential privacy. Although extensively studied in literature, existing solutions fall short on two key aspects: ($i$) even for Gaussian data, existing private algorithms r...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	299,047
1606.00478	Uplink and Downlink Rate Analysis of a Full-Duplex C-RAN with Radio Remote Head Association	We characterize the uplink (UL) and downlink (DL) rates of a full-duplex cloud radio access network (C-RAN) with all participate and single best remote radio head (RRH) association schemes. Specifically, multi-antenna equipped RRHs distributed according to a Poisson point process is assumed. The UL and DL sum rate of t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	56,669
2401.00659	Distinctiveness Maximization in Datasets Assemblage	In this paper, given a user's query set and a budget limit, we aim to help the user assemble a set of datasets that can enrich a base dataset by introducing the maximum number of distinct tuples (i.e., maximizing distinctiveness). We prove this problem to be NP-hard and, subsequently, we develop a greedy algorithm that...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	419,060
1608.02126	How Much Did it Rain? Predicting Real Rainfall Totals Based on Radar Data	We applied a variety of parametric and non-parametric machine learning models to predict the probability distribution of rainfall based on 1M training examples over a single year across several U.S. states. Our top performing model based on a squared loss objective was a cross-validated parametric k-nearest-neighbor pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	59,513
2204.02970	Evolutionary Programmer: Autonomously Creating Path Planning Programs based on Evolutionary Algorithms	Evolutionary algorithms are wildly used in unmanned aerial vehicle path planning for their flexibility and effectiveness. Nevertheless, they are so sensitive to the change of environment that can't adapt to all scenarios. Due to this drawback, the previously successful planner frequently fail in a new scene. In this pa...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	290,145
cs/0510030	A Near Maximum Likelihood Decoding Algorithm for MIMO Systems Based on Semi-Definite Programming	In Multi-Input Multi-Output (MIMO) systems, Maximum-Likelihood (ML) decoding is equivalent to finding the closest lattice point in an N-dimensional complex space. In general, this problem is known to be NP hard. In this paper, we propose a quasi-maximum likelihood algorithm based on Semi-Definite Programming (SDP). We ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,009
2002.12892	Galois hulls of MDS codes and their quantum error correction	The hull of linear codes plays an important role in quantum information and coding theory. In the present paper, by investigating the Galois hulls of generalized Reed-Solomon (GRS) codes and extended GRS codes over the finite field Fq, we give several new families of MDS codes with Galois hulls of arbitrary dimensions ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	166,158
1808.07699	End-to-End Neural Entity Linking	Entity Linking (EL) is an essential task for semantic text understanding and information extraction. Popular methods separately address the Mention Detection (MD) and Entity Disambiguation (ED) stages of EL, without leveraging their mutual dependency. We here propose the first neural end-to-end EL system that jointly d...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	105,795
2309.08929	Leveraging Multi-lingual Positive Instances in Contrastive Learning to Improve Sentence Embedding	Learning multi-lingual sentence embeddings is a fundamental task in natural language processing. Recent trends in learning both mono-lingual and multi-lingual sentence embeddings are mainly based on contrastive learning (CL) among an anchor, one positive, and multiple negative instances. In this work, we argue that lev...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	392,393
1804.00408	Sparse Gaussian ICA	Independent component analysis (ICA) is a cornerstone of modern data analysis. Its goal is to recover a latent random vector S with independent components from samples of X=AS where A is an unknown mixing matrix. Critically, all existing methods for ICA rely on and exploit strongly the assumption that S is not Gaussian...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	94,022
2007.12989	Information Fusion on Belief Networks	This paper will focus on the process of 'fusing' several observations or models of uncertainty into a single resultant model. Many existing approaches to fusion use subjective quantities such as 'strengths of belief' and process these quantities with heuristic algorithms. This paper argues in favor of quantities that c...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	188,986
2111.14053	Towards Conditional Generation of Minimal Action Potential Pathways for Molecular Dynamics	In this paper, we utilized generative models, and reformulate it for problems in molecular dynamics (MD) simulation, by introducing an MD potential energy component to our generative model. By incorporating potential energy as calculated from TorchMD into a conditional generative framework, we attempt to construct a lo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	268,477
2205.04911	Reasoning in the Description Logic ALC under Category Semantics	We present in this paper a reformulation of the usual set-theoretical semantics of the description logic $\mathcal{ALC}$ with general TBoxes by using categorical language. In this setting, $\mathcal{ALC}$ concepts are represented as objects, concept subsumptions as arrows, and memberships as logical quantifiers over ob...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	295,794
1905.03946	Credit Scoring for Micro-Loans	Credit Scores are ubiquitous and instrumental for loan providers and regulators. In this paper we showcase how micro-loan credit system can be developed in real setting. We show what challenges arise and discuss solutions. Particularly, we are concerned about model interpretability and data quality. In the final sectio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	130,332
2502.02883	SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactions	Natural language interaction with sensing systems is crucial for enabling all users to comprehend sensor data and its impact on their everyday lives. However, existing systems, which typically operate in a Question Answering (QA) manner, are significantly limited in terms of the duration and complexity of sensor data t...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	530,509
2005.09202	Multi-modal Sensor Fusion-Based Deep Neural Network for End-to-end Autonomous Driving with Scene Understanding	This study aims to improve the performance and generalization capability of end-to-end autonomous driving with scene understanding leveraging deep learning and multimodal sensor fusion techniques. The designed end-to-end deep neural network takes as input the visual image and associated depth information in an early fu...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	177,851
0908.3710	Randomization for Security in Half-Duplex Two-Way Gaussian Channels	This paper develops a new physical layer framework for secure two-way wireless communication in the presence of a passive eavesdropper, i.e., Eve. Our approach achieves perfect information theoretic secrecy via a novel randomized scheduling and power allocation scheme. The key idea is to allow Alice and Bob to send sym...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	4,343
2306.02479	Contagion Effect Estimation Using Proximal Embeddings	Contagion effect refers to the causal effect of peers' behavior on the outcome of an individual in social networks. Contagion can be confounded due to latent homophily which makes contagion effect estimation very hard: nodes in a homophilic network tend to have ties to peers with similar attributes and can behave simil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	370,916
1304.3119	On the Combinality of Evidence in the Dempster-Shafer Theory	In the current versions of the Dempster-Shafer theory, the only essential restriction on the validity of the rule of combination is that the sources of evidence must be statistically independent. Under this assumption, it is permissible to apply the Dempster-Shafer rule to two or mere distinct probability distributions...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,835
1901.08706	Emergent Linguistic Phenomena in Multi-Agent Communication Games	In this work, we propose a computational framework in which agents equipped with communication capabilities simultaneously play a series of referential games, where agents are trained using deep reinforcement learning. We demonstrate that the framework mirrors linguistic phenomena observed in natural language: i) the o...	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	false	false	false	119,555
2203.04290	Residual Aligner Network	Image registration is important for medical imaging, the estimation of the spatial transformation between different images. Many previous studies have used learning-based methods for coarse-to-fine registration to efficiently perform 3D image registration. The coarse-to-fine approach, however, is limited when dealing w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,407
2312.08591	Joint2Human: High-quality 3D Human Generation via Compact Spherical Embedding of 3D Joints	3D human generation is increasingly significant in various applications. However, the direct use of 2D generative methods in 3D generation often results in losing local details, while methods that reconstruct geometry from generated images struggle with global view consistency. In this work, we introduce Joint2Human, a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,359
2304.11750	DiffVoice: Text-to-Speech with Latent Diffusion	In this work, we present DiffVoice, a novel text-to-speech model based on latent diffusion. We propose to first encode speech signals into a phoneme-rate latent representation with a variational autoencoder enhanced by adversarial training, and then jointly model the duration and the latent representation with a diffus...	true	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	359,953
2011.00120	Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RL	We study the ability of autonomous vehicles to improve the throughput of a bottleneck using a fully decentralized control scheme in a mixed autonomy setting. We consider the problem of improving the throughput of a scaled model of the San Francisco-Oakland Bay Bridge: a two-stage bottleneck where four lanes reduce to t...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	true	false	false	false	204,102
2409.16817	A parametric framework for kernel-based dynamic mode decomposition using deep learning	Surrogate modelling is widely applied in computational science and engineering to mitigate computational efficiency issues for the real-time simulations of complex and large-scale computational models or for many-query scenarios, such as uncertainty quantification and design optimisation. In this work, we propose a par...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	491,525
2309.08475	Doeblin Coefficients and Related Measures	Doeblin coefficients are a classical tool for analyzing the ergodicity and exponential convergence rates of Markov chains. Propelled by recent works on contraction coefficients of strong data processing inequalities, we investigate whether Doeblin coefficients also exhibit some of the notable properties of canonical co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	392,184
2305.14910	From Shortcuts to Triggers: Backdoor Defense with Denoised PoE	Language models are often at risk of diverse backdoor attacks, especially data poisoning. Thus, it is important to investigate defense solutions for addressing them. Existing backdoor defense methods mainly focus on backdoor attacks with explicit triggers, leaving a universal defense against various backdoor attacks wi...	false	false	false	false	true	false	true	false	true	false	false	false	true	false	false	false	false	false	367,328
2309.05361	Cross-tokamak Disruption Prediction based on Physics-Guided Feature Extraction and domain adaptation	The high acquisition cost and the significant demand for disruptive discharges for data-driven disruption prediction models in future tokamaks pose an inherent contradiction in disruption prediction research. In this paper, we demonstrated a novel approach to predict disruption in a future tokamak using only a few disc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	391,059
2208.09224	SoMoFormer: Social-Aware Motion Transformer for Multi-Person Motion Prediction	Multi-person motion prediction remains a challenging problem, especially in the joint representation learning of individual motion and social interactions. Most prior methods only involve learning local pose dynamics for individual motion (without global body trajectory) and also struggle to capture complex interaction...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	313,633
2106.02581	BERT-Based Sentiment Analysis: A Software Engineering Perspective	Sentiment analysis can provide a suitable lead for the tools used in software engineering along with the API recommendation systems and relevant libraries to be used. In this context, the existing tools like SentiCR, SentiStrength-SE, etc. exhibited low f1-scores that completely defeats the purpose of deployment of suc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	238,929
1612.05201	Models of latent consensus	The paper studies the problem of achieving consensus in multi-agent systems in the case where the dependency digraph $\Gamma$ has no spanning in-tree. We consider the regularization protocol that amounts to the addition of a dummy agent (hub) uniformly connected to the agents. The presence of such a hub guarantees the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	65,645
2202.07779	Binary Classification for High Dimensional Data using Supervised Non-Parametric Ensemble Method	High dimensional data for classification does create many difficulties for machine learning algorithms. The generalization can be done using ensemble learning methods such as bagging based supervised non-parametric random forest algorithm. In this paper we solve the problem of binary classification for high dimensional...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	280,651
2002.09515	Petrophysically and geologically guided multi-physics inversion using a dynamic Gaussian mixture model	In a previous paper, we introduced a framework for carrying out petrophysically and geologically guided geophysical inversions. In that framework, petrophysical and geological information is modelled with a Gaussian Mixture Model (GMM). In the inversion, the GMM serves as a prior for the geophysical model. The formulat...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	165,080
1201.6583	Empowerment for Continuous Agent-Environment Systems	This paper develops generalizations of empowerment to continuous states. Empowerment is a recently introduced information-theoretic quantity motivated by hypotheses about the efficiency of the sensorimotor loop in biological organisms, but also from considerations stemming from curiosity-driven learning. Empowemerment ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	14,027
2003.00648	Intelligent Reflecting Surface Assisted Multi-User OFDMA: Channel Estimation and Training Design	To achieve the full passive beamforming gains of intelligent reflecting surface (IRS), accurate channel state information (CSI) is indispensable but practically challenging to acquire, due to the excessive amount of channel parameters to be estimated which increases with the number of IRS reflecting elements as well as...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	166,363
2404.09227	DreamScape: 3D Scene Creation via Gaussian Splatting joint Correlation Modeling	Recent progress in text-to-3D creation has been propelled by integrating the potent prior of Diffusion Models from text-to-image generation into the 3D domain. Nevertheless, generating 3D scenes characterized by multiple instances and intricate arrangements remains challenging. In this study, we present DreamScape, a m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	446,586
2210.05892	Perplexity from PLM Is Unreliable for Evaluating Text Quality	Recently, amounts of works utilize perplexity~(PPL) to evaluate the quality of the generated text. They suppose that if the value of PPL is smaller, the quality(i.e. fluency) of the text to be evaluated is better. However, we find that the PPL referee is unqualified and it cannot evaluate the generated text fairly for ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	323,046
1909.09999	Tag-based Semantic Features for Scene Image Classification	The existing image feature extraction methods are primarily based on the content and structure information of images, and rarely consider the contextual semantic information. Regarding some types of images such as scenes and objects, the annotations and descriptions of them available on the web may provide reliable con...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	146,423
2012.13036	Assured RL: Reinforcement Learning with Almost Sure Constraints	We consider the problem of finding optimal policies for a Markov Decision Process with almost sure constraints on state transitions and action triplets. We define value and action-value functions that satisfy a barrier-based decomposition which allows for the identification of feasible policies independently of the rew...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	213,087
1612.07978	Two-stream convolutional neural network for accurate RGB-D fingertip detection using depth and edge information	Accurate detection of fingertips in depth image is critical for human-computer interaction. In this paper, we present a novel two-stream convolutional neural network (CNN) for RGB-D fingertip detection. Firstly edge image is extracted from raw depth image using random forest. Then the edge information is combined with ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	66,011
2303.17207	Exploiting Redundancy for UWB Anomaly Detection in Infrastructure-Free Multi-Robot Relative Localization	Ultra-wideband (UWB) localization methods have emerged as a cost-effective and accurate solution for GNSS-denied environments. There is a significant amount of previous research in terms of resilience of UWB ranging, with non-line-of-sight and multipath detection methods. However, little attention has been paid to resi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	355,138
1808.01960	Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN	The recently proposed distributional approach to reinforcement learning (DiRL) is centered on learning the distribution of the reward-to-go, often referred to as the value distribution. In this work, we show that the distributional Bellman equation, which drives DiRL methods, is equivalent to a generative adversarial n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	104,678
2108.09814	UzBERT: pretraining a BERT model for Uzbek	Pretrained language models based on the Transformer architecture have achieved state-of-the-art results in various natural language processing tasks such as part-of-speech tagging, named entity recognition, and question answering. However, no such monolingual model for the Uzbek language is publicly available. In this ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	251,712
2012.10610	SpaceML: Distributed Open-source Research with Citizen Scientists for the Advancement of Space Technology for NASA	Traditionally, academic labs conduct open-ended research with the primary focus on discoveries with long-term value, rather than direct products that can be deployed in the real world. On the other hand, research in the industry is driven by its expected commercial return on investment, and hence focuses on a real worl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	212,391
1109.0085	Self-Adaptation Mechanism to Control the Diversity of the Population in Genetic Algorithm	One of the problems in applying Genetic Algorithm is that there is some situation where the evolutionary process converges too fast to a solution which causes it to be trapped in local optima. To overcome this problem, a proper diversity in the candidate solutions must be determined. Most existing diversity-maintenance...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	11,912
2011.00518	AI Marker-based Large-scale AI Literature Mining	The knowledge contained in academic literature is interesting to mine. Inspired by the idea of molecular markers tracing in the field of biochemistry, three named entities, namely, methods, datasets and metrics are used as AI markers for AI literature. These entities can be used to trace the research process described ...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	204,251
1501.01327	Cyclic codes over $\mathbb{Z}_4+u\mathbb{Z}_4$	In this paper, we have studied cyclic codes over the ring $R=\mathbb{Z}_4+u\mathbb{Z}_4$, $u^2=0$. We have considered cyclic codes of odd lengths. A sufficient condition for a cyclic code over $R$ to be a $\mathbb{Z}_4$-free module is presented. We have provided the general form of the generators of a cyclic code over ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,071
2104.05363	Capacity-Driven Low-Interference Fast Beam Synthesis for Next Generation Base Stations	The problem of the real-time multiple-input multiple-output (MIMO) array control when requirements on capacity performance, out-of-cell interference, and computational efficiency are simultaneously enforced is addressed by means of an innovative hybrid beamforming technique. The synthesis of the excitations of the MIMO...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	229,698
1301.6750	Time-Critical Dynamic Decision Making	Recent interests in dynamic decision modeling have led to the development of several representation and inference methods. These methods however, have limited application under time critical conditions where a trade-off between model quality and computational tractability is essential. This paper presents an approach t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,543
2107.12254	The Holy Grail of Multi-Robot Planning: Learning to Generate Online-Scalable Solutions from Offline-Optimal Experts	Many multi-robot planning problems are burdened by the curse of dimensionality, which compounds the difficulty of applying solutions to large-scale problem instances. The use of learning-based methods in multi-robot planning holds great promise as it enables us to offload the online computational burden of expensive, y...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	true	false	false	false	247,848
2303.09383	Unifying Top-down and Bottom-up Scanpath Prediction Using Transformers	Most models of visual attention aim at predicting either top-down or bottom-up control, as studied using different visual search and free-viewing tasks. In this paper we propose the Human Attention Transformer (HAT), a single model that predicts both forms of attention control. HAT uses a novel transformer-based archit...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	352,022
2103.07833	A `Sourceful' Twist: Emoji Prediction Based on Sentiment, Hashtags and Application Source	We widely use emojis in social networking to heighten, mitigate or negate the sentiment of the text. Emoji suggestions already exist in many cross-platform applications but an emoji is predicted solely based a few prominent words instead of understanding the subject and substance of the text. Through this paper, we sho...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	224,711
2005.09406	Embeddings as representation for symbolic music	A representation technique that allows encoding music in a way that contains musical meaning would improve the results of any model trained for computer music tasks like generation of melodies and harmonies of better quality. The field of natural language processing has done a lot of work in finding a way to capture th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	177,923
2106.00506	A Novel Graph-Theoretic Deep Representation Learning Method for Multi-Label Remote Sensing Image Retrieval	This paper presents a novel graph-theoretic deep representation learning method in the framework of multi-label remote sensing (RS) image retrieval problems. The proposed method aims to extract and exploit multi-label co-occurrence relationships associated to each RS image in the archive. To this end, each training ima...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	238,146
1803.03004	Learning Effective Binary Visual Representations with Deep Networks	Although traditionally binary visual representations are mainly designed to reduce computational and storage costs in the image retrieval research, this paper argues that binary visual representations can be applied to large scale recognition and detection problems in addition to hashing in retrieval. Furthermore, the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,176
2502.02457	Orientation-aware interaction-based deep material network in polycrystalline materials modeling	Multiscale simulations are indispensable for connecting microstructural features to the macroscopic behavior of polycrystalline materials, but their high computational demands limit their practicality. Deep material networks (DMNs) have been proposed as efficient surrogate models, yet they fall short of capturing textu...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	530,326
2312.03477	From Detection to Action Recognition: An Edge-Based Pipeline for Robot Human Perception	Mobile service robots are proving to be increasingly effective in a range of applications, such as healthcare, monitoring Activities of Daily Living (ADL), and facilitating Ambient Assisted Living (AAL). These robots heavily rely on Human Action Recognition (HAR) to interpret human actions and intentions. However, for ...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	413,271
1612.02564	Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream	Huge amount of data with both space and text information, e.g., geo-tagged tweets, is flooding on the Internet. Such spatio-textual data stream contains valuable information for millions of users with various interests on different keywords and locations. Publish/subscribe systems enable efficient and effective informa...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	65,248

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