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
1908.00301	General Information Theory: Time and Information	This paper introduces time into information theory, gives a more accurate definition of information, and unifies the information in cognition and Shannon information theory. Specially, we consider time as a measure of information, giving a definition of time, event independence at the time frame, and definition of cond...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	140,482
2304.09059	Coupling Global Context and Local Contents for Weakly-Supervised Semantic Segmentation	Thanks to the advantages of the friendly annotations and the satisfactory performance, Weakly-Supervised Semantic Segmentation (WSSS) approaches have been extensively studied. Recently, the single-stage WSSS was awakened to alleviate problems of the expensive computational costs and the complicated training procedures ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	358,919
2210.17264	Cross-lingual Text-To-Speech with Flow-based Voice Conversion for Improved Pronunciation	This paper presents a method for end-to-end cross-lingual text-to-speech (TTS) which aims to preserve the target language's pronunciation regardless of the original speaker's language. The model used is based on a non-attentive Tacotron architecture, where the decoder has been replaced with a normalizing flow network c...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	327,623
2203.15799	StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis	Although progress has been made for text-to-image synthesis, previous methods fall short of generalizing to unseen or underrepresented attribute compositions in the input text. Lacking compositionality could have severe implications for robustness and fairness, e.g., inability to synthesize the face images of underrepr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	288,545
2011.01844	A Comprehensive Study of Class Incremental Learning Algorithms for Visual Tasks	The ability of artificial agents to increment their capabilities when confronted with new data is an open challenge in artificial intelligence. The main challenge faced in such cases is catastrophic forgetting, i.e., the tendency of neural networks to underfit past data when new ones are ingested. A first group of appr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	204,728
2401.14626	Towards Lifelong Scene Graph Generation with Knowledge-ware In-context Prompt Learning	Scene graph generation (SGG) endeavors to predict visual relationships between pairs of objects within an image. Prevailing SGG methods traditionally assume a one-off learning process for SGG. This conventional paradigm may necessitate repetitive training on all previously observed samples whenever new relationships em...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,163
2208.00160	Learning Feature Decomposition for Domain Adaptive Monocular Depth Estimation	Monocular depth estimation (MDE) has attracted intense study due to its low cost and critical functions for robotic tasks such as localization, mapping and obstacle detection. Supervised approaches have led to great success with the advance of deep learning, but they rely on large quantities of ground-truth depth annot...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	310,757
2205.03339	Transferring Chemical and Energetic Knowledge Between Molecular Systems with Machine Learning	Predicting structural and energetic properties of a molecular system is one of the fundamental tasks in molecular simulations, and it has use cases in chemistry, biology, and medicine. In the past decade, the advent of machine learning algorithms has impacted on molecular simulations for various tasks, including proper...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	295,252
2408.02377	A Few-Shot Approach for Relation Extraction Domain Adaptation using Large Language Models	Knowledge graphs (KGs) have been successfully applied to the analysis of complex scientific and technological domains, with automatic KG generation methods typically building upon relation extraction models capturing fine-grained relations between domain entities in text. While these relations are fully applicable acro...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	478,617
2404.01604	WaveDH: Wavelet Sub-bands Guided ConvNet for Efficient Image Dehazing	The surge in interest regarding image dehazing has led to notable advancements in deep learning-based single image dehazing approaches, exhibiting impressive performance in recent studies. Despite these strides, many existing methods fall short in meeting the efficiency demands of practical applications. In this paper,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	443,490
2106.16036	A Generative Model for Raw Audio Using Transformer Architectures	This paper proposes a novel way of doing audio synthesis at the waveform level using Transformer architectures. We propose a deep neural network for generating waveforms, similar to wavenet. This is fully probabilistic, auto-regressive, and causal, i.e. each sample generated depends only on the previously observed samp...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	243,949
2305.14964	Detecting Multidimensional Political Incivility on Social Media	The rise of social media has been argued to intensify uncivil and hostile online political discourse. Yet, to date, there is a lack of clarity on what incivility means in the political sphere. In this work, we utilize a multidimensional perspective of political incivility, developed in the fields of political science a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	367,359
1512.02902	MovieQA: Understanding Stories in Movies through Question-Answering	We introduce the MovieQA dataset which aims to evaluate automatic story comprehension from both video and text. The dataset consists of 14,944 questions about 408 movies with high semantic diversity. The questions range from simpler "Who" did "What" to "Whom", to "Why" and "How" certain events occurred. Each question c...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	49,977
2303.10173	VideoSum: A Python Library for Surgical Video Summarization	The performance of deep learning (DL) algorithms is heavily influenced by the quantity and the quality of the annotated data. However, in Surgical Data Science, access to it is limited. It is thus unsurprising that substantial research efforts are made to develop methods aiming at mitigating the scarcity of annotated S...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,340
2410.18425	Doubly Non-Central Beta Matrix Factorization for Stable Dimensionality Reduction of Bounded Support Matrix Data	We consider the problem of developing interpretable and computationally efficient matrix decomposition methods for matrices whose entries have bounded support. Such matrices are found in large-scale DNA methylation studies and many other settings. Our approach decomposes the data matrix into a Tucker representation whe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	501,882
2311.05607	Real-Time Neural Rasterization for Large Scenes	We propose a new method for realistic real-time novel-view synthesis (NVS) of large scenes. Existing neural rendering methods generate realistic results, but primarily work for small scale scenes (<50 square meters) and have difficulty at large scale (>10000 square meters). Traditional graphics-based rasterization rend...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	406,640
nlin/0309039	Self-organizing Traffic Control: First Results	We developed a virtual laboratory for traffic control where agents use different strategies in order to self-organize on the road. We present our first results where we compare the performance and behaviour promoted by environmental constrains and five different simple strategies: three inspired in flocking behaviour, ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	540,773
2310.02567	Improving Automatic VQA Evaluation Using Large Language Models	8 years after the visual question answering (VQA) task was proposed, accuracy remains the primary metric for automatic evaluation. VQA Accuracy has been effective so far in the IID evaluation setting. However, our community is undergoing a shift towards open-ended generative models and OOD evaluation. In this new parad...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	396,906
2409.07672	An Unsupervised Dialogue Topic Segmentation Model Based on Utterance Rewriting	Dialogue topic segmentation plays a crucial role in various types of dialogue modeling tasks. The state-of-the-art unsupervised DTS methods learn topic-aware discourse representations from conversation data through adjacent discourse matching and pseudo segmentation to further mine useful clues in unlabeled conversatio...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	487,608
2207.00383	ReLER@ZJU-Alibaba Submission to the Ego4D Natural Language Queries Challenge 2022	In this report, we present the ReLER@ZJU-Alibaba submission to the Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2022. Given a video clip and a text query, the goal of this challenge is to locate a temporal moment of the video clip where the answer to the query can be obtained. To tackle this task, we propose ...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	305,735
2302.12686	Older Adults' Task Preferences for Robot Assistance in the Home	Artificial intelligence technologies that can assist with at-home tasks have the potential to help older adults age in place. Robot assistance in particular has been applied towards physical and cognitive support for older adults living independently at home. Surveys, questionnaires, and group interviews have been used...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	347,661
2207.09185	Multimodal hierarchical Variational AutoEncoders with Factor Analysis latent space	Purpose: Handling heterogeneous and mixed data types has become increasingly critical with the exponential growth in real-world databases. While deep generative models attempt to merge diverse data views into a common latent space, they often sacrifice interpretability, flexibility, and modularity. This study proposes ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	308,828
2410.13768	Rapid and Automated Alloy Design with Graph Neural Network-Powered LLM-Driven Multi-Agent Systems	A multi-agent AI model is used to automate the discovery of new metallic alloys, integrating multimodal data and external knowledge including insights from physics via atomistic simulations. Our multi-agent system features three key components: (a) a suite of LLMs responsible for tasks such as reasoning and planning, (...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	499,675
2105.06022	Principled Exploration via Optimistic Bootstrapping and Backward Induction	One principled approach for provably efficient exploration is incorporating the upper confidence bound (UCB) into the value function as a bonus. However, UCB is specified to deal with linear and tabular settings and is incompatible with Deep Reinforcement Learning (DRL). In this paper, we propose a principled explorati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	234,993
2004.10247	GGDs: Graph Generating Dependencies	We propose Graph Generating Dependencies (GGDs), a new class of dependencies for property graphs. Extending the expressivity of state of the art constraint languages, GGDs can express both tuple- and equality-generating dependencies on property graphs, both of which find broad application in graph data management. We p...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	173,580
1112.2791	Secrecy Outage Capacity of Fading Channels	This paper considers point to point secure communication over flat fading channels under an outage constraint. More specifically, we extend the definition of outage capacity to account for the secrecy constraint and obtain sharp characterizations of the corresponding fundamental limits under two different assumptions o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	13,442
2201.10918	Behavior Tree-Based Task Planning for Multiple Mobile Robots using a Data Distribution Service	In this study, we propose task planning framework for multiple robots that builds on a behavior tree (BT). BTs communicate with a data distribution service (DDS) to send and receive data. Since the standard BT derived from one root node with a single tick is unsuitable for multiple robots, a novel type of BT action and...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	true	277,137
2004.03329	MedDialog: Two Large-scale Medical Dialogue Datasets	Medical dialogue systems are promising in assisting in telemedicine to increase access to healthcare services, improve the quality of patient care, and reduce medical costs. To facilitate the research and development of medical dialogue systems, we build two large-scale medical dialogue datasets: MedDialog-EN and MedDi...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	171,514
2305.15048	Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation	In this paper, we introduce Ranger - a toolkit to facilitate the easy use of effect-size-based meta-analysis for multi-task evaluation in NLP and IR. We observed that our communities often face the challenge of aggregating results over incomparable metrics and scenarios, which makes conclusions and take-away messages l...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	367,420
1106.1216	Using More Data to Speed-up Training Time	In many recent applications, data is plentiful. By now, we have a rather clear understanding of how more data can be used to improve the accuracy of learning algorithms. Recently, there has been a growing interest in understanding how more data can be leveraged to reduce the required training runtime. In this paper, we...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	10,744
0712.3298	CLAIRLIB Documentation v1.03	The Clair library is intended to simplify a number of generic tasks in Natural Language Processing (NLP), Information Retrieval (IR), and Network Analysis. Its architecture also allows for external software to be plugged in with very little effort. Functionality native to Clairlib includes Tokenization, Summarization, ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	1,059
1705.05091	Bandit Regret Scaling with the Effective Loss Range	We study how the regret guarantees of nonstochastic multi-armed bandits can be improved, if the effective range of the losses in each round is small (e.g. the maximal difference between two losses in a given round). Despite a recent impossibility result, we show how this can be made possible under certain mild addition...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	73,430
2105.05619	Synergistic Benefits in IRS- and RS-enabled C-RAN with Energy-Efficient Clustering	The potential of intelligent reflecting surfaces (IRSs) is investigated as a promising technique for enhancing the energy efficiency of wireless networks. Specifically, the IRS enables passive beamsteering by employing many low-cost individually controllable reflect elements. The resulting change of the channel state, ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	234,874
2311.11628	Incorporating LLM Priors into Tabular Learners	We present a method to integrate Large Language Models (LLMs) and traditional tabular data classification techniques, addressing LLMs challenges like data serialization sensitivity and biases. We introduce two strategies utilizing LLMs for ranking categorical variables and generating priors on correlations between cont...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	409,019
2311.09104	Cross-view and Cross-pose Completion for 3D Human Understanding	Human perception and understanding is a major domain of computer vision which, like many other vision subdomains recently, stands to gain from the use of large models pre-trained on large datasets. We hypothesize that the most common pre-training strategy of relying on general purpose, object-centric image datasets suc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	407,992
2106.12933	GNMR: A provable one-line algorithm for low rank matrix recovery	Low rank matrix recovery problems, including matrix completion and matrix sensing, appear in a broad range of applications. In this work we present GNMR -- an extremely simple iterative algorithm for low rank matrix recovery, based on a Gauss-Newton linearization. On the theoretical front, we derive recovery guarantees...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	242,895
2305.17175	Multi-Stage Monte Carlo Tree Search for Non-Monotone Object Rearrangement Planning in Narrow Confined Environments	Non-monotone object rearrangement planning in confined spaces such as cabinets and shelves is a widely occurring but challenging problem in robotics. Both the robot motion and the available regions for object relocation are highly constrained because of the limited space. This work proposes a Multi-Stage Monte Carlo Tr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	368,442
2310.09469	Towards More Accurate Diffusion Model Acceleration with A Timestep Aligner	A diffusion model, which is formulated to produce an image using thousands of denoising steps, usually suffers from a slow inference speed. Existing acceleration algorithms simplify the sampling by skipping most steps yet exhibit considerable performance degradation. By viewing the generation of diffusion models as a d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	399,786
2501.18794	Survey and Improvement Strategies for Gene Prioritization with Large Language Models	Rare diseases are challenging to diagnose due to limited patient data and genetic diversity. Despite advances in variant prioritization, many cases remain undiagnosed. While large language models (LLMs) have performed well in medical exams, their effectiveness in diagnosing rare genetic diseases has not been assessed. ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	528,858
2108.13202	PTRAIL -- A python package for parallel trajectory data preprocessing	Trajectory data represent a trace of an object that changes its position in space over time. This kind of data is complex to handle and analyze, since it is generally produced in huge quantities, often prone to errors generated by the geolocation device, human mishandling, or area coverage limitation. Therefore, there ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	252,740
1408.1542	Measuring and Optimizing Cultural Markets	Social influence has been shown to create significant unpredictability in cultural markets, providing one potential explanation why experts routinely fail at predicting commercial success of cultural products. To counteract the difficulty of making accurate predictions, "measure and react" strategies have been advocate...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	35,185
2310.05978	Analyzing Key Users' behavior trends in Volunteer-Based Networks	Online social networks usage has increased significantly in the last decade and continues to grow in popularity. Multiple social platforms use volunteers as a central component. The behavior of volunteers in volunteer-based networks has been studied extensively in recent years. Here, we explore the development of volun...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	398,381
2406.18777	Aligning Model Properties via Conformal Risk Control	AI model alignment is crucial due to inadvertent biases in training data and the underspecified machine learning pipeline, where models with excellent test metrics may not meet end-user requirements. While post-training alignment via human feedback shows promise, these methods are often limited to generative AI setting...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	468,165
2405.16909	A Cross-Dataset Study for Text-based 3D Human Motion Retrieval	We provide results of our study on text-based 3D human motion retrieval and particularly focus on cross-dataset generalization. Due to practical reasons such as dataset-specific human body representations, existing works typically benchmarkby training and testing on partitions from the same dataset. Here, we employ a u...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	457,675
2302.02854	NA-SODINN: a deep learning algorithm for exoplanet image detection based on residual noise regimes	Supervised deep learning was recently introduced in high-contrast imaging (HCI) through the SODINN algorithm, a convolutional neural network designed for exoplanet detection in angular differential imaging (ADI) datasets. The benchmarking of HCI algorithms within the Exoplanet Imaging Data Challenge (EIDC) showed that ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	344,131
2411.12960	I Can Tell What I am Doing: Toward Real-World Natural Language Grounding of Robot Experiences	Understanding robot behaviors and experiences through natural language is crucial for developing intelligent and transparent robotic systems. Recent advancement in large language models (LLMs) makes it possible to translate complex, multi-modal robotic experiences into coherent, human-readable narratives. However, grou...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	509,612
2012.00155	A Contemporary Survey on Free Space Optical Communication: Potential, Technical Challenges, Recent Advances and Research Direction	Optical wireless communication (OWC) covering an ultra-wide range of unlicensed spectrum has emerged as an extent efficient solution to mitigate conventional RF spectrum scarcity ranging from communication distances from nm to several kilometers. Free space optical (FSO) systems operating near IR (NIR) band in OWC link...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	209,039
2210.15977	FedVMR: A New Federated Learning method for Video Moment Retrieval	Despite the great success achieved, existing video moment retrieval (VMR) methods are developed under the assumption that data are centralizedly stored. However, in real-world applications, due to the inherent nature of data generation and privacy concerns, data are often distributed on different silos, bringing huge c...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	true	327,168
2006.13510	Dynamic Functional Connectivity and Graph Convolution Network for Alzheimer's Disease Classification	Alzheimer's disease (AD) is the most prevalent form of dementia. Traditional methods cannot achieve efficient and accurate diagnosis of AD. In this paper, we introduce a novel method based on dynamic functional connectivity (dFC) that can effectively capture changes in the brain. We compare and combine four different t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	183,941
2205.13793	Dither Signal Design for PAPR Reduction in OFDM-IM over a Rayleigh Fading Channel	Orthogonal frequency division multiplexing with index modulation (OFDM-IM) is a novel scheme where the information bits are conveyed through the subcarrier activation pattern (SAP) and the symbols on the active subcarriers. Unfortunately, OFDM-IM inherits the high peak-to-average power ratio (PAPR) problem from the cla...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	299,091
2204.10776	Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images	In this paper, we present a generalizable model-free 6-DoF object pose estimator called Gen6D. Existing generalizable pose estimators either need high-quality object models or require additional depth maps or object masks in test time, which significantly limits their application scope. In contrast, our pose estimator ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	292,911
2405.16128	How Well Do Deep Learning Models Capture Human Concepts? The Case of the Typicality Effect	How well do representations learned by ML models align with those of humans? Here, we consider concept representations learned by deep learning models and evaluate whether they show a fundamental behavioral signature of human concepts, the typicality effect. This is the finding that people judge some instances (e.g., r...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	457,273
2105.02480	A Simple and Strong Baseline for Universal Targeted Attacks on Siamese Visual Tracking	Siamese trackers are shown to be vulnerable to adversarial attacks recently. However, the existing attack methods craft the perturbations for each video independently, which comes at a non-negligible computational cost. In this paper, we show the existence of universal perturbations that can enable the targeted attack,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	233,832
1611.06430	Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks	We introduce a simple semi-supervised learning approach for images based on in-painting using an adversarial loss. Images with random patches removed are presented to a generator whose task is to fill in the hole, based on the surrounding pixels. The in-painted images are then presented to a discriminator network that ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	64,185
2210.03142	On Distillation of Guided Diffusion Models	Classifier-free guided diffusion models have recently been shown to be highly effective at high-resolution image generation, and they have been widely used in large-scale diffusion frameworks including DALLE-2, Stable Diffusion and Imagen. However, a downside of classifier-free guided diffusion models is that they are ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	321,914
1801.08694	PDNet: Semantic Segmentation integrated with a Primal-Dual Network for Document binarization	Binarization of digital documents is the task of classifying each pixel in an image of the document as belonging to the background (parchment/paper) or foreground (text/ink). Historical documents are often subjected to degradations, that make the task challenging. In the current work a deep neural network architecture ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	88,987
2404.05238	Allowing humans to interactively guide machines where to look does not always improve human-AI team's classification accuracy	Via thousands of papers in Explainable AI (XAI), attention maps \cite{vaswani2017attention} and feature importance maps \cite{bansal2020sam} have been established as a common means for finding how important each input feature is to an AI's decisions. It is an interesting, unexplored question whether allowing users to e...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,001
1811.10159	An Unknown Input Multi-Observer Approach for Estimation, Attack Isolation, and Control of LTI Systems under Actuator Attacks	We address the problem of state estimation, attack isolation, and control for discrete-time Linear Time Invariant (LTI) systems under (potentially unbounded) actuator false data injection attacks. Using a bank of Unknown Input Observers (UIOs), each observer leading to an exponentially stable estimation error in the at...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	114,428
2408.05882	Creating Arabic LLM Prompts at Scale	The debut of chatGPT and BARD has popularized instruction following text generation using LLMs, where a user can interrogate an LLM using natural language requests and obtain natural language answers that matches their requests. Training LLMs to respond in this manner requires a large number of worked out examples of u...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	479,980
2405.19334	LLMs Meet Multimodal Generation and Editing: A Survey	With the recent advancement in large language models (LLMs), there is a growing interest in combining LLMs with multimodal learning. Previous surveys of multimodal large language models (MLLMs) mainly focus on multimodal understanding. This survey elaborates on multimodal generation and editing across various domains, ...	false	false	true	false	true	false	false	false	true	false	false	true	false	false	false	false	false	true	458,853
2203.08134	Privacy-Aware Compression for Federated Data Analysis	Federated data analytics is a framework for distributed data analysis where a server compiles noisy responses from a group of distributed low-bandwidth user devices to estimate aggregate statistics. Two major challenges in this framework are privacy, since user data is often sensitive, and compression, since the user d...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	285,685
2011.12433	Optimal Mean Estimation without a Variance	We study the problem of heavy-tailed mean estimation in settings where the variance of the data-generating distribution does not exist. Concretely, given a sample $\mathbf{X} = \{X_i\}_{i = 1}^n$ from a distribution $\mathcal{D}$ over $\mathbb{R}^d$ with mean $\mu$ which satisfies the following \emph{weak-moment} assum...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	208,152
2001.04358	DoF Region of the Decentralized MIMO Broadcast Channel -- How many informed antennas do we need?	In this work, we study the impact of imperfect sharing of the Channel State Information (CSI) available at the transmitters on a Network MIMO setting in which a set of $M$ transmit antennas, possibly not co-located, jointly serve two multi-antenna users endowed with $N_1$ and $N_2$ antennas, respectively. We consider t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	160,234
2304.02392	Network-Aware Electric Vehicle Coordination for Vehicle-to-Anything Value Stacking Considering Uncertainties	The increased adoption of electric vehicles (EVs) has led to the development of vehicle-to-anything (V2X) technologies, including vehicle-to-home (V2H), vehicle-to-grid (V2G), and energy trading of EVs in the local grid. The EV coordination can provide value to the grid and generate benefits for EVs. However, network c...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	356,420
2007.11534	Dynamic Task Allocation for Robotic Network Cloud Systems	Every robotic network cloud system can be seen as a graph with nodes as hardware with independent computational processing powers and edges as data transmissions between nodes. When assigning a task to a node we may change several values corresponding to the node such as distance to other nodes, the time to complete al...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	188,575
2304.02766	Shape complexity estimation using VAE	In this paper, we compare methods for estimating the complexity of two-dimensional shapes and introduce a method that exploits reconstruction loss of Variational Autoencoders with different sizes of latent vectors. Although complexity of a shape is not a well defined attribute, different aspects of it can be estimated....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,536
1604.07379	Context Encoders: Feature Learning by Inpainting	We present an unsupervised visual feature learning algorithm driven by context-based pixel prediction. By analogy with auto-encoders, we propose Context Encoders -- a convolutional neural network trained to generate the contents of an arbitrary image region conditioned on its surroundings. In order to succeed at this t...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	55,085
2109.05342	Relaxed Zero-Forcing Beamformer under Temporally-Correlated Interference	The relaxed zero-forcing (RZF) beamformer is a quadratically-and-linearly constrained minimum variance beamformer. The central question addressed in this paper is whether RZF performs better than the widely-used minimum variance distortionless response and zero-forcing beamformers under temporally-correlated interferen...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	254,751
1705.03487	A neural network system for transformation of regional cuisine style	We propose a novel system which can transform a recipe into any selected regional style (e.g., Japanese, Mediterranean, or Italian). This system has two characteristics. First the system can identify the degree of regional cuisine style mixture of any selected recipe and visualize such regional cuisine style mixtures u...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	73,192
1412.0252	Channel Estimation Techniques for Quantized Distributed Reception in MIMO Systems	The Internet of Things (IoT) could enable the development of cloud multiple-input multiple-output (MIMO) systems where internet-enabled devices can work as distributed transmission/reception entities. We expect that spatial multiplexing with distributed reception using cloud MIMO would be a key factor of future wireles...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	38,008
2501.15337	Finite Strain Robust Topology Optimization Considering Multiple Uncertainties	This paper presents a computational framework for the robust stiffness design of hyperelastic structures at finite deformations subject to various uncertain sources. In particular, the loading, material properties, and geometry uncertainties are incorporated within the topology optimization framework and are modeled by...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	527,505
1601.04207	The discrete analogue of the method of quickest descent for an inverse acoustic problem in case of a smooth source	The article considers the discrete analogue of the method of quickest descent for an inverse Acoustics problem in case of a smooth source. The authors derived the gradient of functional in differential and discrete cases, described the algorithm of solving a problem, and compared gradients of functional in continuous a...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	50,998
2109.09378	FreeStyleGAN: Free-view Editable Portrait Rendering with the Camera Manifold	Current Generative Adversarial Networks (GANs) produce photorealistic renderings of portrait images. Embedding real images into the latent space of such models enables high-level image editing. While recent methods provide considerable semantic control over the (re-)generated images, they can only generate a limited se...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	256,256
2105.14476	CSCAD: Correlation Structure-based Collective Anomaly Detection in Complex System	Detecting anomalies in large complex systems is a critical and challenging task. The difficulties arise from several aspects. First, collecting ground truth labels or prior knowledge for anomalies is hard in real-world systems, which often lead to limited or no anomaly labels in the dataset. Second, anomalies in large ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	237,688
2411.10198	STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing	Spatio-Temporal predictive Learning is a self-supervised learning paradigm that enables models to identify spatial and temporal patterns by predicting future frames based on past frames. Traditional methods, which use recurrent neural networks to capture temporal patterns, have proven their effectiveness but come with ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	508,546
2005.03453	A combination of 'pooling' with a prediction model can reduce by 73% the number of COVID-19 (Corona-virus) tests	We show that combining a prediction model (based on neural networks), with a new method of test pooling (better than the original Dorfman method, and better than double-pooling) called 'Grid', we can reduce the number of Covid-19 tests by 73%.	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	176,169
2310.00831	Action Recognition Utilizing YGAR Dataset	The scarcity of high quality actions video data is a bottleneck in the research and application of action recognition. Although significant effort has been made in this area, there still exist gaps in the range of available data types a more flexible and comprehensive data set could help bridge. In this paper, we prese...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	396,167
2305.10906	RobustFair: Adversarial Evaluation through Fairness Confusion Directed Gradient Search	Deep neural networks (DNNs) often face challenges due to their vulnerability to various adversarial perturbations, including false perturbations that undermine prediction accuracy and biased perturbations that cause biased predictions for similar inputs. This paper introduces a novel approach, RobustFair, to evaluate t...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	365,284
2103.16245	Linear time DBSCAN for sorted 1D data and laser range scan segmentation	This paper introduces new algorithm for line extraction from laser range data including methodology for efficient computation. The task is cast to series of one dimensional problems in various spaces. A fast and simple specialization of DBSCAN algorithm is proposed to solve one dimensional subproblems. Experiments sugg...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	227,514
2307.03004	Analysis and design of model predictive control frameworks for dynamic operation -- An overview	This article provides an overview of model predictive control (MPC) frameworks for dynamic operation of nonlinear constrained systems. Dynamic operation is often an integral part of the control objective, ranging from tracking of reference signals to the general economic operation of a plant under online changing time-...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	377,890
2403.05086	UFORecon: Generalizable Sparse-View Surface Reconstruction from Arbitrary and UnFavOrable Sets	Generalizable neural implicit surface reconstruction aims to obtain an accurate underlying geometry given a limited number of multi-view images from unseen scenes. However, existing methods select only informative and relevant views using predefined scores for training and testing phases. This constraint renders the mo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	435,860
2305.06610	Planted vertex cover problem on regular random graphs and nonmonotonic temperature-dependence in the supercooled region	We introduce a planted vertex cover problem on regular random graphs and study it by the cavity method of statistical mechanics. Different from conventional Ising models, the equilibrium ferromagnetic phase transition of this binary-spin two-body interaction system is discontinuous, as the paramagnetic phase is separat...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	363,608
1807.02682	A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images	The lack of proper class discrimination among the Hyperspectral (HS) data points poses a potential challenge in HS classification. To address this issue, this paper proposes an optimal geometry-aware transformation for enhancing the classification accuracy. The underlying idea of this method is to obtain a linear proje...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	102,322
2308.11590	Vision-Based Intelligent Robot Grasping Using Sparse Neural Network	In the modern era of Deep Learning, network parameters play a vital role in models efficiency but it has its own limitations like extensive computations and memory requirements, which may not be suitable for real time intelligent robot grasping tasks. Current research focuses on how the model efficiency can be maintain...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	387,199
2411.06339	Probabilistic Shaped Multilevel Polar Coding for Wiretap Channel	A wiretap channel is served as the fundamental model of physical layer security techniques, where the secrecy capacity of the Gaussian wiretap channel is proven to be achieved by Gaussian input. However, there remains a gap between the Gaussian secrecy capacity and the secrecy rate with conventional uniformly distribut...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	507,071
2112.05837	Learning distributed channel access policies for networked estimation: data-driven optimization in the mean-field regime	The problem of communicating sensor measurements over shared networks is prevalent in many modern large-scale distributed systems such as cyber-physical systems, wireless sensor networks, and the internet of things. Due to bandwidth constraints, the system designer must jointly design decentralized medium access transm...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	270,969
2309.16507	Innovation Modeling Grid	This technical document presents the committee driven innovation modeling methodology "Innovation Modeling Grid" in detail. This document is the successor of three publications on IMoG and focuses on presenting all details of the methodology	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	395,375
1607.01033	An Application of the EM-algorithm to Approximate Empirical Distributions of Financial Indices with the Gaussian Mixtures	In this study I briefly illustrate application of the Gaussian mixtures to approximate empirical distributions of financial indices (DAX, Dow Jones, Nikkei, RTSI, S&P 500). The resulting distributions illustrate very high quality of approximation as evaluated by Kolmogorov-Smirnov test. This implies further study of ap...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	58,168
1811.02563	Joint Point Cloud and Image Based Localization For Efficient Inspection in Mixed Reality	This paper introduces a method of structure inspection using mixed-reality headsets to reduce the human effort in reporting accurate inspection information such as fault locations in 3D coordinates. Prior to every inspection, the headset needs to be localized. While external pose estimation and fiducial marker based lo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	112,617
1208.0651	Fast and Accurate Algorithms for Re-Weighted L1-Norm Minimization	To recover a sparse signal from an underdetermined system, we often solve a constrained L1-norm minimization problem. In many cases, the signal sparsity and the recovery performance can be further improved by replacing the L1 norm with a "weighted" L1 norm. Without any prior information about nonzero elements of the si...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	17,929
2104.04901	Global Convergence of Policy Gradient Primal-dual Methods for Risk-constrained LQRs	While the techniques in optimal control theory are often model-based, the policy optimization (PO) approach directly optimizes the performance metric of interest. Even though it has been an essential approach for reinforcement learning problems, there is little theoretical understanding on its performance. In this pape...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	229,533
2103.14460	Unsupervised Multi-Index Semantic Hashing	Semantic hashing represents documents as compact binary vectors (hash codes) and allows both efficient and effective similarity search in large-scale information retrieval. The state of the art has primarily focused on learning hash codes that improve similarity search effectiveness, while assuming a brute-force linear...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	226,867
2204.11718	Predicting Real-time Scientific Experiments Using Transformer models and Reinforcement Learning	Life and physical sciences have always been quick to adopt the latest advances in machine learning to accelerate scientific discovery. Examples of this are cell segmentation or cancer detection. Nevertheless, these exceptional results are based on mining previously created datasets to discover patterns or trends. Recen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	293,242
1612.02183	Fusion of Range and Thermal Images for Person Detection	Detecting people in images is a challenging problem. Differences in pose, clothing and lighting, along with other factors, cause a lot of variation in their appearance. To overcome these issues, we propose a system based on fused range and thermal infrared images. These measurements show considerably less variation and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	65,201
2305.12564	ChatGPT Is More Likely to Be Perceived as Male Than Female	We investigate how people perceive ChatGPT, and, in particular, how they assign human-like attributes such as gender to the chatbot. Across five pre-registered studies (N = 1,552), we find that people are more likely to perceive ChatGPT to be male than female. Specifically, people perceive male gender identity (1) foll...	true	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	366,060
1612.05552	Secure Estimation and Zero-Error Secrecy Capacity	We study the problem of securely estimating the states of an unstable dynamical system subject to nonstochastic disturbances. The estimator obtains all its information through an uncertain channel which is subject to nonstochastic disturbances as well, and an eavesdropper obtains a disturbed version of the channel inpu...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	65,698
2301.08898	Recurrent Generic Contour-based Instance Segmentation with Progressive Learning	Contour-based instance segmentation has been actively studied, thanks to its flexibility and elegance in processing visual objects within complex backgrounds. In this work, we propose a novel deep network architecture, i.e., PolySnake, for generic contour-based instance segmentation. Motivated by the classic Snake algo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	341,336
1402.4380	A Comparative Study of Machine Learning Methods for Verbal Autopsy Text Classification	A Verbal Autopsy is the record of an interview about the circumstances of an uncertified death. In developing countries, if a death occurs away from health facilities, a field-worker interviews a relative of the deceased about the circumstances of the death; this Verbal Autopsy can be reviewed off-site. We report on a ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	30,958
2309.01083	Chinese Text Recognition with A Pre-Trained CLIP-Like Model Through Image-IDS Aligning	Scene text recognition has been studied for decades due to its broad applications. However, despite Chinese characters possessing different characteristics from Latin characters, such as complex inner structures and large categories, few methods have been proposed for Chinese Text Recognition (CTR). Particularly, the c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	389,537
1708.00497	Car sharing through the data analysis lens	Car sharing is one the pillars of a smart transportation infrastructure, as it is expected to reduce traffic congestion, parking demands and pollution in our cities. From the point of view of demand modelling, car sharing is a weak signal in the city landscape: only a small percentage of the population uses it, and thu...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	true	false	78,218

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