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
1905.10927	Magnetoresistive RAM for error resilient XNOR-Nets	We trained three Binarized Convolutional Neural Network architectures (LeNet-4, Network-In-Network, AlexNet) on a variety of datasets (MNIST, CIFAR-10, CIFAR-100, extended SVHN, ImageNet) using error-prone activations and tested them without errors to study the resilience of the training process. With the exception of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,257
1506.01062	Quizz: Targeted crowdsourcing with a billion (potential) users	We describe Quizz, a gamified crowdsourcing system that simultaneously assesses the knowledge of users and acquires new knowledge from them. Quizz operates by asking users to complete short quizzes on specific topics; as a user answers the quiz questions, Quizz estimates the user's competence. To acquire new knowledge,...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	43,749
2101.03238	Neurosymbolic Transformers for Multi-Agent Communication	We study the problem of inferring communication structures that can solve cooperative multi-agent planning problems while minimizing the amount of communication. We quantify the amount of communication as the maximum degree of the communication graph; this metric captures settings where agents have limited bandwidth. M...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	214,861
2409.02897	LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QA	Though current long-context large language models (LLMs) have demonstrated impressive capacities in answering user questions based on extensive text, the lack of citations in their responses makes user verification difficult, leading to concerns about their trustworthiness due to their potential hallucinations. In this...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	485,867
2001.07381	Q-ary Multi-Mode OFDM with Index Modulation	In this paper, we propose a novel orthogonal frequency division multiplexing with index modulation (OFDM-IM) scheme, which we call Q-ary multi-mode OFDM-IM (Q-MM-OFDM-IM). In the proposed scheme, Q disjoint M-ary constellations are used repeatedly on each subcarrier, and a maximum-distance separable code is applied to ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	161,024
2310.02324	ALT-Pilot: Autonomous navigation with Language augmented Topometric maps	We present an autonomous navigation system that operates without assuming HD LiDAR maps of the environment. Our system, ALT-Pilot, relies only on publicly available road network information and a sparse (and noisy) set of crowdsourced language landmarks. With the help of onboard sensors and a language-augmented topomet...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	396,797
2102.07786	PeriodNet: A non-autoregressive waveform generation model with a structure separating periodic and aperiodic components	We propose PeriodNet, a non-autoregressive (non-AR) waveform generation model with a new model structure for modeling periodic and aperiodic components in speech waveforms. The non-AR waveform generation models can generate speech waveforms parallelly and can be used as a speech vocoder by conditioning an acoustic feat...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	220,218
1701.08783	On the Capacity of the Slotted Strongly Asynchronous Channel with a Bursty User	In this paper, the trade-off between the number of transmissions (or burstiness) $K_n=e^{n\nu}$ of a user, the asynchronism level $A_n=e^{n\alpha}$ in a slotted strongly asynchronous channel, and the ability to distinguish $M_n=e^{nR}$ messages per transmission with vanishingly error probability is investigated in the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,523
1811.03511	Effective Representation for Easy-First Dependency Parsing	Easy-first parsing relies on subtree re-ranking to build the complete parse tree. Whereas the intermediate state of parsing processing is represented by various subtrees, whose internal structural information is the key lead for later parsing action decisions, we explore a better representation for such subtrees. In de...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	112,855
1906.07658	Consistency of semi-supervised learning algorithms on graphs: Probit and one-hot methods	Graph-based semi-supervised learning is the problem of propagating labels from a small number of labelled data points to a larger set of unlabelled data. This paper is concerned with the consistency of optimization-based techniques for such problems, in the limit where the labels have small noise and the underlying unl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	135,652
2105.12344	Probabilistic Selective Encryption of Convolutional Neural Networks for Hierarchical Services	Model protection is vital when deploying Convolutional Neural Networks (CNNs) for commercial services, due to the massive costs of training them. In this work, we propose a selective encryption (SE) algorithm to protect CNN models from unauthorized access, with a unique feature of providing hierarchical services to use...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	236,979
2006.07809	ReLGAN: Generalization of Consistency for GAN with Disjoint Constraints and Relative Learning of Generative Processes for Multiple Transformation Learning	Image to image transformation has gained popularity from different research communities due to its enormous impact on different applications, including medical. In this work, we have introduced a generalized scheme for consistency for GAN architectures with two new concepts of Transformation Learning (TL) and Relative ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	181,952
2409.01213	Supervised Pattern Recognition Involving Skewed Feature Densities	Pattern recognition constitutes a particularly important task underlying a great deal of scientific and technologica activities. At the same time, pattern recognition involves several challenges, including the choice of features to represent the data elements, as well as possible respective transformations. In the pres...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	485,257
2312.12808	Enhancing Consistency in Multimodal Dialogue System Using LLM with Dialogue Scenario	This paper describes our dialogue system submitted to Dialogue Robot Competition 2023. The system's task is to help a user at a travel agency decide on a plan for visiting two sightseeing spots in Kyoto City that satisfy the user. Our dialogue system is flexible and stable and responds to user requirements by controlli...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	417,115
2011.04105	Evolution of Artificial Intelligent Plane	With the growth of the internet, it is becoming hard to manage, configure and monitor networks. Recent trends to control and operate them is artificial intelligence based automation to minimize human intervention. Albeit this concept has been introduced since a decade with several different names, but the underlying go...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	205,462
2312.13004	Reconfigurable Intelligent Surface-Aided Near-field Communications for 6G: Opportunities and Challenges	Reconfigurable intelligent surface (RIS)-aided near-field communications is investigated. First, the necessity of investigating RIS-aided near-field communications and the advantages brought about by the unique spherical-wave-based near-field propagation are discussed. Then, the family of patch-array-based RISs and met...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	417,178
2208.02653	ATP: A holistic attention integrated approach to enhance ABSA	Aspect based sentiment analysis (ABSA) deals with the identification of the sentiment polarity of a review sentence towards a given aspect. Deep Learning sequential models like RNN, LSTM, and GRU are current state-of-the-art methods for inferring the sentiment polarity. These methods work well to capture the contextual...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	311,528
1608.06651	Unsupervised, Efficient and Semantic Expertise Retrieval	We introduce an unsupervised discriminative model for the task of retrieving experts in online document collections. We exclusively employ textual evidence and avoid explicit feature engineering by learning distributed word representations in an unsupervised way. We compare our model to state-of-the-art unsupervised st...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	60,137
2411.04967	AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation	Neural network architecture design requires making many crucial decisions. The common desiderata is that similar decisions, with little modifications, can be reused in a variety of tasks and applications. To satisfy that, architectures must provide promising latency and performance trade-offs, support a variety of task...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	506,484
2106.06769	Cross-Subject Domain Adaptation for Classifying Working Memory Load with Multi-Frame EEG Images	Working memory (WM), denoting the information temporally stored in the mind, is a fundamental research topic in the field of human cognition. Electroencephalograph (EEG), which can monitor the electrical activity of the brain, has been widely used in measuring the level of WM. However, one of the critical challenges is...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	240,613
2305.04158	Koopman-type inverse operator for linear non-minimum phase systems with disturbances	In this paper, a novel Koopman-type inverse operator for linear time-invariant non-minimum phase systems with stochastic disturbances is proposed. This operator employs functions of the desired output to directly calculate the input. Furthermore, it can be applied as a data-driven approach for systems with unknown para...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	362,661
2305.18295	RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths	Text-to-image generation has recently witnessed remarkable achievements. We introduce a text-conditional image diffusion model, termed RAPHAEL, to generate highly artistic images, which accurately portray the text prompts, encompassing multiple nouns, adjectives, and verbs. This is achieved by stacking tens of mixture-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,944
1810.11998	Asynchronous Distributed Power Control of Multi-Microgrid Systems Based on the Operator Splitting Approach	Forming (hybrid) AC/DC microgrids (MGs) has become a promising manner for the interconnection of various kinds of distributed generators that are inherently AC or DC electric sources. This paper addresses the distributed asynchronous power control problem of hybrid microgrids, considering imperfect communication due to...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	111,659
2210.02753	Community as a Vague Operator: Epistemological Questions for a Critical Heuristics of Community Detection Algorithms	In this article, we aim to analyse the nature and epistemic consequences of what figures in network science as patterns of nodes and edges called 'communities'. Tracing these patterns as multi-faceted and ambivalent, we propose to describe the concept of community as a 'vague operator', a variant of Susan Leigh Star's ...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	321,772
2209.00514	Efficient Chemical Space Exploration Using Active Learning Based on Marginalized Graph Kernel: an Application for Predicting the Thermodynamic Properties of Alkanes with Molecular Simulation	We introduce an explorative active learning (AL) algorithm based on Gaussian process regression and marginalized graph kernel (GPR-MGK) to explore chemical space with minimum cost. Using high-throughput molecular dynamics simulation to generate data and graph neural network (GNN) to predict, we constructed an active le...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	315,606
1210.7335	Professional diversity and the productivity of cities	The relationships between diversity, productivity and scale determine much of the structure and robustness of complex biological and social systems. While arguments for the link between specialization and productivity are common, diversity has often been invoked as a hedging strategy, allowing systems to evolve in resp...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	19,424
2210.07934	Codes, Patterns and Shapes of Contemporary Online Antisemitism and Conspiracy Narratives -- an Annotation Guide and Labeled German-Language Dataset in the Context of COVID-19	Over the course of the COVID-19 pandemic, existing conspiracy theories were refreshed and new ones were created, often interwoven with antisemitic narratives, stereotypes and codes. The sheer volume of antisemitic and conspiracy theory content on the Internet makes data-driven algorithmic approaches essential for anti-...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	323,924
2306.03608	A Survey of Quantum-Cognitively Inspired Sentiment Analysis Models	Quantum theory, originally proposed as a physical theory to describe the motions of microscopic particles, has been applied to various non-physics domains involving human cognition and decision-making that are inherently uncertain and exhibit certain non-classical, quantum-like characteristics. Sentiment analysis is a ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	371,412
2409.10365	Robust image representations with counterfactual contrastive learning	Contrastive pretraining can substantially increase model generalisation and downstream performance. However, the quality of the learned representations is highly dependent on the data augmentation strategy applied to generate positive pairs. Positive contrastive pairs should preserve semantic meaning while discarding u...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	488,722
1701.03234	Focusing on a Probability Element: Parameter Selection of Message Importance Measure in Big Data	Message importance measure (MIM) is applicable to characterize the importance of information in the scenario of big data, similar to entropy in information theory. In fact, MIM with a variable parameter can make an effect on the characterization of distribution. Furthermore, by choosing an appropriate parameter of MIM,...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	66,671
1504.03363	Outage Probability for Multi-Hop Full-Duplex Decode and Forward MIMO Relay	In this paper, a multi-hop (MH) decode-and-forward (DF) multiple-input multiple-output (MIMO) relay network has been studied. To consider a more realistic scenario, Full-Duplex (FD) operation with Relay Self-Interference (RSI) is employed. Assuming that the MIMO channels are subject to Rayleigh fading, a simple and c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,021
2310.17569	SD4Match: Learning to Prompt Stable Diffusion Model for Semantic Matching	In this paper, we address the challenge of matching semantically similar keypoints across image pairs. Existing research indicates that the intermediate output of the UNet within the Stable Diffusion (SD) can serve as robust image feature maps for such a matching task. We demonstrate that by employing a basic prompt tu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	403,193
2012.06866	Linear codes and incidence structures of bent functions and their generalizations	In this paper we consider further applications of $(n,m)$-functions for the construction of 2-designs. For instance, we provide a new application of the extended Assmus-Mattson theorem, by showing that linear codes of APN functions with the classical Walsh spectrum support 2-designs. On the other hand, we use linear co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	211,253
2308.15647	A General Recipe for Automated Machine Learning in Practice	Automated Machine Learning (AutoML) is an area of research that focuses on developing methods to generate machine learning models automatically. The idea of being able to build machine learning models with very little human intervention represents a great opportunity for the practice of applied machine learning. Howeve...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	388,743
2202.08510	Multi-Scale Hybrid Vision Transformer for Learning Gastric Histology: AI-Based Decision Support System for Gastric Cancer Treatment	Gastric endoscopic screening is an effective way to decide appropriate gastric cancer (GC) treatment at an early stage, reducing GC-associated mortality rate. Although artificial intelligence (AI) has brought a great promise to assist pathologist to screen digitalized whole slide images, existing AI systems are limited...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	280,903
1908.11825	The Communication Complexity of Set Intersection and Multiple Equality Testing	In this paper we explore fundamental problems in randomized communication complexity such as computing Set Intersection on sets of size $k$ and Equality Testing between vectors of length $k$. Sa\u{g}lam and Tardos and Brody et al. showed that for these types of problems, one can achieve optimal communication volume of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	143,484
1612.04023	Proceedings of the The First Workshop on Verification and Validation of Cyber-Physical Systems	The first International Workshop on Verification and Validation of Cyber-Physical Systems (V2CPS-16) was held in conjunction with the 12th International Conference on integration of Formal Methods (iFM 2016) in Reykjavik, Iceland. The purpose of V2CPS-16 was to bring together researchers and experts of the fields of fo...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	65,467
2405.17676	Utilising a Quantum Hybrid Solver for Bi-objective Quadratic Assignment Problems	The intersection between quantum computing and optimisation has been an area of interest in recent years. There have been numerous studies exploring the application of quantum and quantum-hybrid solvers to various optimisation problems. This work explores scalarisation methods within the context of solving the bi-objec...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	458,055
2011.03451	Deep Cross-modal Hashing via Margin-dynamic-softmax Loss	Due to their high retrieval efficiency and low storage cost for cross-modal search task, cross-modal hashing methods have attracted considerable attention. For the supervised cross-modal hashing methods, how to make the learned hash codes preserve semantic information sufficiently contained in the label of datapoints i...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	true	205,247
2406.14347	$\nabla^2$DFT: A Universal Quantum Chemistry Dataset of Drug-Like Molecules and a Benchmark for Neural Network Potentials	Methods of computational quantum chemistry provide accurate approximations of molecular properties crucial for computer-aided drug discovery and other areas of chemical science. However, high computational complexity limits the scalability of their applications. Neural network potentials (NNPs) are a promising alternat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	466,273
2406.11838	Autoregressive Image Generation without Vector Quantization	Conventional wisdom holds that autoregressive models for image generation are typically accompanied by vector-quantized tokens. We observe that while a discrete-valued space can facilitate representing a categorical distribution, it is not a necessity for autoregressive modeling. In this work, we propose to model the p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,092
2007.04536	Attention-based Residual Speech Portrait Model for Speech to Face Generation	Given a speaker's speech, it is interesting to see if it is possible to generate this speaker's face. One main challenge in this task is to alleviate the natural mismatch between face and speech. To this end, in this paper, we propose a novel Attention-based Residual Speech Portrait Model (AR-SPM) by introducing the id...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	186,385
2209.00260	Deep Sparse Conformer for Speech Recognition	Conformer has achieved impressive results in Automatic Speech Recognition (ASR) by leveraging transformer's capturing of content-based global interactions and convolutional neural network's exploiting of local features. In Conformer, two macaron-like feed-forward layers with half-step residual connections sandwich the ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	315,531
1910.12175	Small Memory Robust Simulation of Client-Server Interactive Protocols over Oblivious Noisy Channels	We revisit the problem of low-memory robust simulation of interactive protocols over noisy channels. Haeupler [FOCS 2014] considered robust simulation of two-party interactive protocols over oblivious, as well as adaptive, noisy channels. Since the simulation does not need to have fixed communication pattern, the achie...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	150,991
2305.13786	Perception Test: A Diagnostic Benchmark for Multimodal Video Models	We propose a novel multimodal video benchmark - the Perception Test - to evaluate the perception and reasoning skills of pre-trained multimodal models (e.g. Flamingo, SeViLA, or GPT-4). Compared to existing benchmarks that focus on computational tasks (e.g. classification, detection or tracking), the Perception Test fo...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	366,684
2502.08525	Checkerboard Target Measurement in Unordered Point Clouds with Coloured ICP	In this work, we investigate the problem of measuring a the centre checkerboard target in an 3D point cloud. This is an important problem which has applications in registration, long term monitoring and linking to other sensor systems. We use a 3D template matching approach based on the coloured ICP algorithm to solve ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	533,043
2008.09994	Discriminative Residual Analysis for Image Set Classification with Posture and Age Variations	Image set recognition has been widely applied in many practical problems like real-time video retrieval and image caption tasks. Due to its superior performance, it has grown into a significant topic in recent years. However, images with complicated variations, e.g., postures and human ages, are difficult to address, a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	192,876
1705.08991	Approximation and Convergence Properties of Generative Adversarial Learning	Generative adversarial networks (GAN) approximate a target data distribution by jointly optimizing an objective function through a "two-player game" between a generator and a discriminator. Despite their empirical success, however, two very basic questions on how well they can approximate the target distribution remain...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	74,124
2303.11908	Non-Asymptotic Pointwise and Worst-Case Bounds for Classical Spectrum Estimators	Spectrum estimation is a fundamental methodology in the analysis of time-series data, with applications including medicine, speech analysis, and control design. The asymptotic theory of spectrum estimation is well-understood, but the theory is limited when the number of samples is fixed and finite. This paper gives non...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	353,057
2303.08301	Dataset Management Platform for Machine Learning	The quality of the data in a dataset can have a substantial impact on the performance of a machine learning model that is trained and/or evaluated using the dataset. Effective dataset management, including tasks such as data cleanup, versioning, access control, dataset transformation, automation, integrity and security...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	351,586
2403.15371	Can large language models explore in-context?	We investigate the extent to which contemporary Large Language Models (LLMs) can engage in exploration, a core capability in reinforcement learning and decision making. We focus on native performance of existing LLMs, without training interventions. We deploy LLMs as agents in simple multi-armed bandit environments, sp...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	440,517
2306.04064	Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings	Research on adversarial robustness is primarily focused on image and text data. Yet, many scenarios in which lack of robustness can result in serious risks, such as fraud detection, medical diagnosis, or recommender systems often do not rely on images or text but instead on tabular data. Adversarial robustness in tabul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	371,586
1302.5002	Asymptotic Data Rates of Receive-Diversity Systems with MMSE Estimation and Spatially Correlated Interferers	An asymptotic technique is presented to characterize the bits/symbol achievable on a representative wireless link in a spatially distributed network with active interferers at correlated positions, N receive diversity branches, and linear Minimum-Mean-Square-Error (MMSE) receivers. This framework is then applied to sys...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,268
1908.06576	A Co-analysis Framework for Exploring Multivariate Scientific Data	In complex multivariate data sets, different features usually include diverse associations with different variables, and different variables are associated within different regions. Therefore, exploring the associations between variables and voxels locally becomes necessary to better understand the underlying phenomena...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	142,052
2204.09983	DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimation	Monocular 6D pose estimation is a fundamental task in computer vision. Existing works often adopt a two-stage pipeline by establishing correspondences and utilizing a RANSAC algorithm to calculate 6 degrees-of-freedom (6DoF) pose. Recent works try to integrate differentiable RANSAC algorithms to achieve an end-to-end 6...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	292,632
2404.17525	Large Language Model Agent as a Mechanical Designer	Conventional mechanical design paradigms rely on experts systematically refining concepts through experience-guided modification and FEA to meet specific requirements. However, this approach can be time-consuming and heavily dependent on prior knowledge and experience. While numerous machine learning models have been d...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	449,889
2012.10412	PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection	LiDAR-based 3D object detection is an important task for autonomous driving and current approaches suffer from sparse and partial point clouds of distant and occluded objects. In this paper, we propose a novel two-stage approach, namely PC-RGNN, dealing with such challenges by two specific solutions. On the one hand, w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	212,341
2209.08376	Unveil the unseen: Exploit information hidden in noise	Noise and uncertainty are usually the enemy of machine learning, noise in training data leads to uncertainty and inaccuracy in the predictions. However, we develop a machine learning architecture that extracts crucial information out of the noise itself to improve the predictions. The phenomenology computes and then ut...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	318,101
2412.07026	GenAI4UQ: A Software for Inverse Uncertainty Quantification Using Conditional Generative Models	We introduce GenAI4UQ, a software package for inverse uncertainty quantification in model calibration, parameter estimation, and ensemble forecasting in scientific applications. GenAI4UQ leverages a generative artificial intelligence (AI) based conditional modeling framework to address the limitations of traditional in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	515,478
2007.14120	Reachable Sets of Classifiers and Regression Models: (Non-)Robustness Analysis and Robust Training	Neural networks achieve outstanding accuracy in classification and regression tasks. However, understanding their behavior still remains an open challenge that requires questions to be addressed on the robustness, explainability and reliability of predictions. We answer these questions by computing reachable sets of ne...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	189,311
2411.04118	Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?	Several recent works seek to develop foundation models specifically for medical applications, adapting general-purpose large language models (LLMs) and vision-language models (VLMs) via continued pretraining on publicly available biomedical corpora. These works typically claim that such domain-adaptive pretraining (DAP...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	506,154
2108.12988	Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning	In multi-agent reinforcement learning, the behaviors that agents learn in a single Markov Game (MG) are typically confined to the given agent number. Every single MG induced by varying the population may possess distinct optimal joint strategies and game-specific knowledge, which are modeled independently in modern mul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	252,672
1309.3611	Ultrametric Component Analysis with Application to Analysis of Text and of Emotion	We review the theory and practice of determining what parts of a data set are ultrametric. It is assumed that the data set, to begin with, is endowed with a metric, and we include discussion of how this can be brought about if a dissimilarity, only, holds. The basis for part of the metric-endowed data set being ultrame...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	27,029
2211.02111	Translated Skip Connections -- Expanding the Receptive Fields of Fully Convolutional Neural Networks	The effective receptive field of a fully convolutional neural network is an important consideration when designing an architecture, as it defines the portion of the input visible to each convolutional kernel. We propose a neural network module, extending traditional skip connections, called the translated skip connecti...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	328,469
1508.06183	Performance of a Free Space Optical Relay-Assisted Hybrid RF/FSO System in Generalized M-Distributed Channels	This paper investigates the average symbol error rate (ASER) performance of a dual-hop hybrid relaying system relying on both radio frequency (RF) and free space optical (FSO) links. Specifically, the RF link is used for supporting mobile communication, while the FSO link is adopted as the backhaul of the cellular infr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	46,302
2006.04300	Machine Learning Interpretability and Its Impact on Smart Campus Projects	Machine learning (ML) has shown increasing abilities for predictive analytics over the last decades. It is becoming ubiquitous in different fields, such as healthcare, criminal justice, finance and smart city. For instance, the University of Northampton is building a smart system with multiple layers of IoT and softwar...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	180,643
2202.05607	Online Decision Transformer	Recent work has shown that offline reinforcement learning (RL) can be formulated as a sequence modeling problem (Chen et al., 2021; Janner et al., 2021) and solved via approaches similar to large-scale language modeling. However, any practical instantiation of RL also involves an online component, where policies pretra...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	279,924
2302.12190	MCWDST: a Minimum-Cost Weighted Directed Spanning Tree Algorithm for Real-Time Fake News Mitigation in Social Media	The widespread availability of internet access and handheld devices confers to social media a power similar to the one newspapers used to have. People seek affordable information on social media and can reach it within seconds. Yet this convenience comes with dangers; any user may freely post whatever they please and t...	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	true	false	false	347,469
2306.10754	Collaborative Optimization of Multi-microgrids System with Shared Energy Storage Based on Multi-agent Stochastic Game and Reinforcement Learning	Achieving the economical and stable operation of Multi-microgrids (MMG) systems is vital. However, there are still some challenging problems to be solved. Firstly, from the perspective of stable operation, it is necessary to minimize the energy fluctuation of the main grid. Secondly, the characteristics of energy conve...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	374,351
2410.14241	Graph Neural Patching for Cold-Start Recommendations	The cold start problem in recommender systems remains a critical challenge. Current solutions often train hybrid models on auxiliary data for both cold and warm users/items, potentially degrading the experience for the latter. This drawback limits their viability in practical scenarios where the satisfaction of existin...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	499,948
2406.11863	The Transformation Risk-Benefit Model of Artificial Intelligence: Balancing Risks and Benefits Through Practical Solutions and Use Cases	This paper summarizes the most cogent advantages and risks associated with Artificial Intelligence from an in-depth review of the literature. Then the authors synthesize the salient risk-related models currently being used in AI, technology and business-related scenarios. Next, in view of an updated context of AI along...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	465,107
2411.06958	Data-driven discovery of mechanical models directly from MRI spectral data	Finding interpretable biomechanical models can provide insight into the functionality of organs with regard to physiology and disease. However, identifying broadly applicable dynamical models for in vivo tissue remains challenging. In this proof of concept study we propose a reconstruction framework for data-driven dis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	507,334
2010.07611	Layer-adaptive sparsity for the Magnitude-based Pruning	Recent discoveries on neural network pruning reveal that, with a carefully chosen layerwise sparsity, a simple magnitude-based pruning achieves state-of-the-art tradeoff between sparsity and performance. However, without a clear consensus on "how to choose," the layerwise sparsities are mostly selected algorithm-by-alg...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	200,888
1502.04652	Inferring 3D Object Pose in RGB-D Images	The goal of this work is to replace objects in an RGB-D scene with corresponding 3D models from a library. We approach this problem by first detecting and segmenting object instances in the scene using the approach from Gupta et al. [13]. We use a convolutional neural network (CNN) to predict the pose of the object. Th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	40,292
2203.15375	A Style-aware Discriminator for Controllable Image Translation	Current image-to-image translations do not control the output domain beyond the classes used during training, nor do they interpolate between different domains well, leading to implausible results. This limitation largely arises because labels do not consider the semantic distance. To mitigate such problems, we propose...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	288,376
1404.0074	Quantum Turing automata	A denotational semantics of quantum Turing machines having a quantum control is defined in the dagger compact closed category of finite dimensional Hilbert spaces. Using the Moore-Penrose generalized inverse, a new additive trace is introduced on the restriction of this category to isometries, which trace is carried ov...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	31,978
2411.18423	Efficient and Diverse Generative Robot Designs using Evolution and Intrinsic Motivation	Methods for generative design of robot physical configurations can automatically find optimal and innovative solutions for challenging tasks in complex environments. The vast search-space includes the physical design-space and the controller parameter-space, making it a challenging problem in machine learning and optim...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	511,862
2007.00084	Deep neural networks for the evaluation and design of photonic devices	The data sciences revolution is poised to transform the way photonic systems are simulated and designed. Photonics are in many ways an ideal substrate for machine learning: the objective of much of computational electromagnetics is the capture of non-linear relationships in high dimensional spaces, which is the core st...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,997
2312.00963	Spatiotemporal Transformer for Imputing Sparse Data: A Deep Learning Approach	Effective management of environmental resources and agricultural sustainability heavily depends on accurate soil moisture data. However, datasets like the SMAP/Sentinel-1 soil moisture product often contain missing values across their spatiotemporal grid, which poses a significant challenge. This paper introduces a nov...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	412,250
2003.12660	Towards Supervised and Unsupervised Neural Machine Translation Baselines for Nigerian Pidgin	Nigerian Pidgin is arguably the most widely spoken language in Nigeria. Variants of this language are also spoken across West and Central Africa, making it a very important language. This work aims to establish supervised and unsupervised neural machine translation (NMT) baselines between English and Nigerian Pidgin. W...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	169,974
2206.06780	Memory-Oriented Design-Space Exploration of Edge-AI Hardware for XR Applications	Low-Power Edge-AI capabilities are essential for on-device extended reality (XR) applications to support the vision of Metaverse. In this work, we investigate two representative XR workloads: (i) Hand detection and (ii) Eye segmentation, for hardware design space exploration. For both applications, we train deep neural...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	302,496
2303.00836	Ensemble flow reconstruction in the atmospheric boundary layer from spatially limited measurements through latent diffusion models	Due to costs and practical constraints, field campaigns in the atmospheric boundary layer typically only measure a fraction of the atmospheric volume of interest. Machine learning techniques have previously successfully reconstructed unobserved regions of flow in canonical fluid mechanics problems and two-dimensional g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	348,717
2202.10036	Guided Visual Attention Model Based on Interactions Between Top-down and Bottom-up Information for Robot Pose Prediction	Deep robot vision models are widely used for recognizing objects from camera images, but shows poor performance when detecting objects at untrained positions. Although such problem can be alleviated by training with large datasets, the dataset collection cost cannot be ignored. Existing visual attention models tackled ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	281,403
1704.03951	Sparsity-Sensitive Finite Abstraction	Abstraction of a continuous-space model into a finite state and input dynamical model is a key step in formal controller synthesis tools. To date, these software tools have been limited to systems of modest size (typically $\leq$ 6 dimensions) because the abstraction procedure suffers from an exponential runtime with r...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	71,715
2301.12520	Producing Usable Taxonomies Cheaply and Rapidly at Pinterest Using Discovered Dynamic $\mu$-Topics	Creating a taxonomy of interests is expensive and human-effort intensive: not only do we need to identify nodes and interconnect them, in order to use the taxonomy, we must also connect the nodes to relevant entities such as users, pins, and queries. Connecting to entities is challenging because of ambiguities inherent...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	342,560
2007.14626	Object-and-Action Aware Model for Visual Language Navigation	Vision-and-Language Navigation (VLN) is unique in that it requires turning relatively general natural-language instructions into robot agent actions, on the basis of the visible environment. This requires to extract value from two very different types of natural-language information. The first is object description (e....	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	189,459
2310.14029	LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions	The prediction of crystal properties plays a crucial role in the crystal design process. Current methods for predicting crystal properties focus on modeling crystal structures using graph neural networks (GNNs). Although GNNs are powerful, accurately modeling the complex interactions between atoms and molecules within ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	401,680
2106.13385	Trends, Politics, Sentiments, and Misinformation: Understanding People's Reactions to COVID-19 During its Early Stages	The sudden outbreak of COVID-19 resulted in large volumes of data shared on different social media platforms. Analyzing and visualizing these data is doubtlessly essential to having a deep understanding of the pandemic's impacts on people's lives and their reactions to them. In this work, we conduct a large-scale spati...	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	243,056
1611.05222	Simple Yet Effective Methods for Large-Scale Scholarly Publication Ranking	With the growing amount of published research, automatic evaluation of scholarly publications is becoming an important task. In this paper we address this problem and present a simple and transparent approach for evaluating the importance of scholarly publications. Our method has been ranked among the top performers in...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	63,981
2409.01761	PRoGS: Progressive Rendering of Gaussian Splats	Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's individual data must be stored. While compression techniques offer a potential solution...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	485,458
2406.19464	ManiWAV: Learning Robot Manipulation from In-the-Wild Audio-Visual Data	Audio signals provide rich information for the robot interaction and object properties through contact. This information can surprisingly ease the learning of contact-rich robot manipulation skills, especially when the visual information alone is ambiguous or incomplete. However, the usage of audio data in robot manipu...	false	false	true	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	468,424
2308.04867	Learning Type-Generalized Actions for Symbolic Planning	Symbolic planning is a powerful technique to solve complex tasks that require long sequences of actions and can equip an intelligent agent with complex behavior. The downside of this approach is the necessity for suitable symbolic representations describing the state of the environment as well as the actions that can c...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	384,590
2306.09682	OCTScenes: A Versatile Real-World Dataset of Tabletop Scenes for Object-Centric Learning	Humans possess the cognitive ability to comprehend scenes in a compositional manner. To empower AI systems with similar capabilities, object-centric learning aims to acquire representations of individual objects from visual scenes without any supervision. Although recent advances in object-centric learning have made re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	373,926
2202.09938	Generative Target Update for Adaptive Siamese Tracking	Siamese trackers perform similarity matching with templates (i.e., target models) to recursively localize objects within a search region. Several strategies have been proposed in the literature to update a template based on the tracker output, typically extracted from the target search region in the current frame, and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	281,369
1806.10741	Robust Neural Malware Detection Models for Emulation Sequence Learning	Malicious software, or malware, presents a continuously evolving challenge in computer security. These embedded snippets of code in the form of malicious files or hidden within legitimate files cause a major risk to systems with their ability to run malicious command sequences. Malware authors even use polymorphism to ...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	101,587
2312.16835	RimSet: Quantitatively Identifying and Characterizing Chronic Active Multiple Sclerosis Lesion on Quantitative Susceptibility Maps	Background: Rim+ lesions in multiple sclerosis (MS), detectable via Quantitative Susceptibility Mapping (QSM), correlate with increased disability. Existing literature lacks quantitative analysis of these lesions. We introduce RimSet for quantitative identification and characterization of rim+ lesions on QSM. Methods: ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	418,531
1910.09910	WeatherNet: Recognising weather and visual conditions from street-level images using deep residual learning	Extracting information related to weather and visual conditions at a given time and space is indispensable for scene awareness, which strongly impacts our behaviours, from simply walking in a city to riding a bike, driving a car, or autonomous drive-assistance. Despite the significance of this subject, it is still not ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	150,334
2403.08213	Can Large Language Models Identify Authorship?	The ability to accurately identify authorship is crucial for verifying content authenticity and mitigating misinformation. Large Language Models (LLMs) have demonstrated an exceptional capacity for reasoning and problem-solving. However, their potential in authorship analysis remains under-explored. Traditional studies...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	437,232
2209.08862	Gradient Norm Minimization of Nesterov Acceleration: $o(1/k^3)$	In the history of first-order algorithms, Nesterov's accelerated gradient descent (NAG) is one of the milestones. However, the cause of the acceleration has been a mystery for a long time. It has not been revealed with the existence of gradient correction until the high-resolution differential equation framework propos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	318,296
1610.07722	Sparse Hierarchical Tucker Factorization and its Application to Healthcare	We propose a new tensor factorization method, called the Sparse Hierarchical-Tucker (Sparse H-Tucker), for sparse and high-order data tensors. Sparse H-Tucker is inspired by its namesake, the classical Hierarchical Tucker method, which aims to compute a tree-structured factorization of an input data set that may be rea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	62,836

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