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
2409.11629	Designing Interfaces for Multimodal Vector Search Applications	Multimodal vector search offers a new paradigm for information retrieval by exposing numerous pieces of functionality which are not possible in traditional lexical search engines. While multimodal vector search can be treated as a drop in replacement for these traditional systems, the experience can be significantly en...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	489,241
2412.01189	MiningGPT -- A Domain-Specific Large Language Model for the Mining Industry	Recent advancements of generative LLMs (Large Language Models) have exhibited human-like language capabilities but have shown a lack of domain-specific understanding. Therefore, the research community has started the development of domain-specific LLMs for many domains. In this work we focus on discussing how to build ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	512,998
2211.01478	A machine learning model to identify corruption in M\'exico's public procurement contracts	The costs and impacts of government corruption range from impairing a country's economic growth to affecting its citizens' well-being and safety. Public contracting between government dependencies and private sector instances, referred to as public procurement, is a fertile land of opportunity for corrupt practices, ge...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	328,237
2311.01852	Optimisation of Active Space Debris Removal Missions With Multiple Targets Using Quantum Annealing	A strategy for the analysis of active debris removal missions targeting multiple objects from a set of objects in near-circular orbit with similar inclination is presented. Algebraic techniques successfully reduce the orbital mechanics regarding specific inter-debris transfer and disposal methods to simple computations...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	405,203
1705.10245	Deep Learning for Patient-Specific Kidney Graft Survival Analysis	An accurate model of patient-specific kidney graft survival distributions can help to improve shared-decision making in the treatment and care of patients. In this paper, we propose a deep learning method that directly models the survival function instead of estimating the hazard function to predict survival times for ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	74,358
2108.13046	Data-driven Small-signal Modeling for Converter-based Power Systems	This article details a complete procedure to derive a data-driven small-signal-based model useful to perform converter-based power system related studies. To compute the model, Decision Tree (DT) regression, both using single DT and ensemble DT, and Spline regression have been employed and their performances have been ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	252,694
1803.09010	Datasheets for Datasets	The machine learning community currently has no standardized process for documenting datasets, which can lead to severe consequences in high-stakes domains. To address this gap, we propose datasheets for datasets. In the electronics industry, every component, no matter how simple or complex, is accompanied with a datas...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	93,396
2203.15758	A Sparsity-promoting Dictionary Model for Variational Autoencoders	Structuring the latent space in probabilistic deep generative models, e.g., variational autoencoders (VAEs), is important to yield more expressive models and interpretable representations, and to avoid overfitting. One way to achieve this objective is to impose a sparsity constraint on the latent variables, e.g., via a...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	288,524
2304.03031	Evidentiality-aware Retrieval for Overcoming Abstractiveness in Open-Domain Question Answering	The long-standing goal of dense retrievers in abtractive open-domain question answering (ODQA) tasks is to learn to capture evidence passages among relevant passages for any given query, such that the reader produce factually correct outputs from evidence passages. One of the key challenge is the insufficient amount of...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	356,645
2212.09885	Python Code Generation by Asking Clarification Questions	Code generation from text requires understanding the user's intent from a natural language description and generating an executable code snippet that satisfies this intent. While recent pretrained language models demonstrate remarkable performance for this task, these models fail when the given natural language descrip...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,244
2310.12036	A General Theoretical Paradigm to Understand Learning from Human Preferences	The prevalent deployment of learning from human preferences through reinforcement learning (RLHF) relies on two important approximations: the first assumes that pairwise preferences can be substituted with pointwise rewards. The second assumes that a reward model trained on these pointwise rewards can generalize from c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	400,879
2411.15396	The Decoy Dilemma in Online Medical Information Evaluation: A Comparative Study of Credibility Assessments by LLM and Human Judges	Can AI be cognitively biased in automated information judgment tasks? Despite recent progresses in measuring and mitigating social and algorithmic biases in AI and large language models (LLMs), it is not clear to what extent LLMs behave "rationally", or if they are also vulnerable to human cognitive bias triggers. To a...	true	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	510,592
2307.11476	Data-driven dual-loop control for platooning mixed human-driven and automated vehicles	This paper considers controlling automated vehicles (AVs) to form a platoon with human-driven vehicles (HVs) under consideration of unknown HV model parameters and propulsion time constants. The proposed design is a data-driven dual-loop control strategy for the ego AVs, where the inner loop controller ensures platoon ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	380,922
2409.16456	Communication and Energy Efficient Federated Learning using Zero-Order Optimization Technique	Federated learning (FL) is a popular machine learning technique that enables multiple users to collaboratively train a model while maintaining the user data privacy. A significant challenge in FL is the communication bottleneck in the upload direction, and thus the corresponding energy consumption of the devices, attri...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	491,349
2210.04987	Loop Unrolled Shallow Equilibrium Regularizer (LUSER) -- A Memory-Efficient Inverse Problem Solver	In inverse problems we aim to reconstruct some underlying signal of interest from potentially corrupted and often ill-posed measurements. Classical optimization-based techniques proceed by optimizing a data consistency metric together with a regularizer. Current state-of-the-art machine learning approaches draw inspira...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	322,649
2008.09706	Detecting and Classifying Malevolent Dialogue Responses: Taxonomy, Data and Methodology	Conversational interfaces are increasingly popular as a way of connecting people to information. Corpus-based conversational interfaces are able to generate more diverse and natural responses than template-based or retrieval-based agents. With their increased generative capacity of corpusbased conversational agents com...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	192,798
2404.06389	Raster Forge: Interactive Raster Manipulation Library and GUI for Python	Raster Forge is a Python library and graphical user interface for raster data manipulation and analysis. The tool is focused on remote sensing applications, particularly in wildfire management. It allows users to import, visualize, and process raster layers for tasks such as image compositing or topographical analysis....	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	true	445,446
2111.05576	Topic-aware latent models for representation learning on networks	Network representation learning (NRL) methods have received significant attention over the last years thanks to their success in several graph analysis problems, including node classification, link prediction, and clustering. Such methods aim to map each vertex of the network into a low-dimensional space in a way that ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,835
2105.08336	Exemplar-Based Open-Set Panoptic Segmentation Network	We extend panoptic segmentation to the open-world and introduce an open-set panoptic segmentation (OPS) task. This task requires performing panoptic segmentation for not only known classes but also unknown ones that have not been acknowledged during training. We investigate the practical challenges of the task and cons...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	235,735
1703.10701	Concurrent Segmentation and Localization for Tracking of Surgical Instruments	Real-time instrument tracking is a crucial requirement for various computer-assisted interventions. In order to overcome problems such as specular reflections and motion blur, we propose a novel method that takes advantage of the interdependency between localization and segmentation of the surgical tool. In particular,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,960
2102.12365	Modelling SARS-CoV-2 coevolution with genetic algorithms	At the end of 2020, policy responses to the SARS-CoV-2 outbreak have been shaken by the emergence of virus variants, impacting public health and policy measures worldwide. The emergence of these strains suspected to be more contagious, more severe, or even resistant to antibodies and vaccines, seem to have taken by sur...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	221,712
2309.11512	Multidimensional well-being of US households at a fine spatial scale using fused household surveys: fusionACS	Social science often relies on surveys of households and individuals. Dozens of such surveys are regularly administered by the U.S. government. However, they field independent, unconnected samples with specialized questions, limiting research questions to those that can be answered by a single survey. The fusionACS pro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	393,436
2011.08819	Spatio-Temporal Analysis of Facial Actions using Lifecycle-Aware Capsule Networks	Most state-of-the-art approaches for Facial Action Unit (AU) detection rely upon evaluating facial expressions from static frames, encoding a snapshot of heightened facial activity. In real-world interactions, however, facial expressions are usually more subtle and evolve in a temporal manner requiring AU detection mod...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	207,004
2402.05445	Accurate LoRA-Finetuning Quantization of LLMs via Information Retention	The LoRA-finetuning quantization of LLMs has been extensively studied to obtain accurate yet compact LLMs for deployment on resource-constrained hardware. However, existing methods cause the quantized LLM to severely degrade and even fail to benefit from the finetuning of LoRA. This paper proposes a novel IR-QLoRA for ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	427,867
2108.07886	Modulating Language Models with Emotions	Generating context-aware language that embodies diverse emotions is an important step towards building empathetic NLP systems. In this paper, we propose a formulation of modulated layer normalization -- a technique inspired by computer vision -- that allows us to use large-scale language models for emotional response g...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	251,047
1905.11015	Unsupervised Euclidean Distance Attack on Network Embedding	Considering the wide application of network embedding methods in graph data mining, inspired by the adversarial attack in deep learning, this paper proposes a Genetic Algorithm (GA) based Euclidean Distance Attack strategy (EDA) to attack the network embedding, so as to prevent certain structural information from being...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	132,305
2008.05583	Impact of Disturbances on Mixed Traffic Control with Autonomous Vehicles	This paper investigates the impact of disturbances on controlling an autonomous vehicle to smooth mixed traffic flow in a ring road setup. By exploiting the ring structure of this system, it is shown that velocity perturbations impacting any vehicle on the ring enter an uncontrollable and marginally stable mode defined...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	191,544
2402.10510	Human Goal Recognition as Bayesian Inference: Investigating the Impact of Actions, Timing, and Goal Solvability	Goal recognition is a fundamental cognitive process that enables individuals to infer intentions based on available cues. Current goal recognition algorithms often take only observed actions as input, but here we use a Bayesian framework to explore the role of actions, timing, and goal solvability in goal recognition. ...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	429,996
2212.09900	Policy learning "without" overlap: Pessimism and generalized empirical Bernstein's inequality	This paper studies offline policy learning, which aims at utilizing observations collected a priori (from either fixed or adaptively evolving behavior policies) to learn an optimal individualized decision rule that achieves the best overall outcomes for a given population. Existing policy learning methods rely on a uni...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	337,249
2102.10315	EXTRA: Explanation Ranking Datasets for Explainable Recommendation	Recently, research on explainable recommender systems has drawn much attention from both academia and industry, resulting in a variety of explainable models. As a consequence, their evaluation approaches vary from model to model, which makes it quite difficult to compare the explainability of different models. To achie...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	221,048
2411.14816	Unsupervised Multi-view UAV Image Geo-localization via Iterative Rendering	Unmanned Aerial Vehicle (UAV) Cross-View Geo-Localization (CVGL) presents significant challenges due to the view discrepancy between oblique UAV images and overhead satellite images. Existing methods heavily rely on the supervision of labeled datasets to extract viewpoint-invariant features for cross-view retrieval. Ho...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	510,337
2405.11014	The Arabic Noun System Generation	In this paper, we show that the multiple-stem approach to nouns with a broken plural pattern allows for greater generalizations to be stated in the morphological system. Such an approach dispenses with truncating/deleting rules and other complex rules that are required to account for the highly allomorphic broken plura...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	454,976
2401.14931	Do LLMs Dream of Ontologies?	Large Language Models (LLMs) have demonstrated remarkable performance across diverse natural language processing tasks, yet their ability to memorize structured knowledge remains underexplored. In this paper, we investigate the extent to which general-purpose pre-trained LLMs retain and correctly reproduce concept iden...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	424,265
2407.15455	Score matching for bridges without time-reversals	We propose a new algorithm for learning a bridged diffusion process using score-matching methods. Our method relies on reversing the dynamics of the forward process and using this to learn a score function, which, via Doob's $h$-transform, gives us a bridged diffusion process; that is, a process conditioned on an endpo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	475,194
2003.06686	Perception of prosodic variation for speech synthesis using an unsupervised discrete representation of F0	In English, prosody adds a broad range of information to segment sequences, from information structure (e.g. contrast) to stylistic variation (e.g. expression of emotion). However, when learning to control prosody in text-to-speech voices, it is not clear what exactly the control is modifying. Existing research on disc...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	168,192
2401.04210	FunnyNet-W: Multimodal Learning of Funny Moments in Videos in the Wild	Automatically understanding funny moments (i.e., the moments that make people laugh) when watching comedy is challenging, as they relate to various features, such as body language, dialogues and culture. In this paper, we propose FunnyNet-W, a model that relies on cross- and self-attention for visual, audio and text da...	false	false	true	false	true	false	false	false	true	false	false	true	false	false	false	false	false	true	420,360
1910.06444	Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks	In all types of disasters, from earthquakes to armed conflicts, aid workers need accurate and timely data such as damage to buildings and population displacement to mount an effective response. Remote sensing provides this data at an unprecedented scale, but extracting operationalizable information from satellite image...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	149,335
2308.12198	Hierarchical Beam Alignment for Millimeter-Wave Communication Systems: A Deep Learning Approach	Fast and precise beam alignment is crucial for high-quality data transmission in millimeter-wave (mmWave) communication systems, where large-scale antenna arrays are utilized to overcome the severe propagation loss. To tackle the challenging problem, we propose a novel deep learning-based hierarchical beam alignment me...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	387,450
2001.03750	SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems	We propose new symplectic networks (SympNets) for identifying Hamiltonian systems from data based on a composition of linear, activation and gradient modules. In particular, we define two classes of SympNets: the LA-SympNets composed of linear and activation modules, and the G-SympNets composed of gradient modules. Cor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,048
0908.0163	An Improvement of Cover/El Gamal's Compress-and-Forward Relay Scheme	The compress-and-forward relay scheme developed by (Cover and El Gamal, 1979) is improved with a modification on the decoding process. The improvement follows as a result of realizing that it is not necessary for the destination to decode the compressed observation of the relay; and even if the compressed observation i...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,199
2005.00728	RMM: A Recursive Mental Model for Dialog Navigation	Language-guided robots must be able to both ask humans questions and understand answers. Much existing work focuses only on the latter. In this paper, we go beyond instruction following and introduce a two-agent task where one agent navigates and asks questions that a second, guiding agent answers. Inspired by theory o...	false	false	false	false	true	false	true	true	true	false	false	true	false	false	false	false	false	false	175,355
2111.00514	Visualization: the missing factor in Simultaneous Speech Translation	Simultaneous speech translation (SimulST) is the task in which output generation has to be performed on partial, incremental speech input. In recent years, SimulST has become popular due to the spread of cross-lingual application scenarios, like international live conferences and streaming lectures, in which on-the-fly...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	264,243
2202.04219	Improving Computational Complexity in Statistical Models with Second-Order Information	It is known that when the statistical models are singular, i.e., the Fisher information matrix at the true parameter is degenerate, the fixed step-size gradient descent algorithm takes polynomial number of steps in terms of the sample size $n$ to converge to a final statistical radius around the true parameter, which c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,491
2110.12765	"So You Think You're Funny?": Rating the Humour Quotient in Standup Comedy	Computational Humour (CH) has attracted the interest of Natural Language Processing and Computational Linguistics communities. Creating datasets for automatic measurement of humour quotient is difficult due to multiple possible interpretations of the content. In this work, we create a multi-modal humour-annotated datas...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	262,958
2501.11881	Channel Resolvability Using Multiplicative Weight Update Algorithm	We study the channel resolvability problem, which is used to prove strong converse of identification via channel. Channel resolvability has been solved by only random coding in the literature. We prove channel resolvability using the multiplicative weight update algorithm. This is the first approach to channel resolvab...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	526,076
2210.16107	SeaDroneSim: Simulation of Aerial Images for Detection of Objects Above Water	Unmanned Aerial Vehicles (UAVs) are known for their fast and versatile applicability. With UAVs' growth in availability and applications, they are now of vital importance in serving as technological support in search-and-rescue(SAR) operations in marine environments. High-resolution cameras and GPUs can be equipped on ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	327,227
2102.12896	Predicting times of waiting on red signals using BERT	We present a method for approximating outcomes of road traffic simulations using BERT-based models, which may find applications in, e.g., optimizing traffic signal settings, especially with the presence of autonomous and connected vehicles. The experiments were conducted on a dataset generated using the Traffic Simulat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	221,876
1808.06022	Characterizing Transgender Health Issues in Twitter	Although there are millions of transgender people in the world, a lack of information exists about their health issues. This issue has consequences for the medical field, which only has a nascent understanding of how to identify and meet this population's health-related needs. Social media sites like Twitter provide ne...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	105,456
2004.04069	Convolutional neural net face recognition works in non-human-like ways	Convolutional neural networks (CNNs) give state of the art performance in many pattern recognition problems but can be fooled by carefully crafted patterns of noise. We report that CNN face recognition systems also make surprising "errors". We tested six commercial face recognition CNNs and found that they outperform t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	171,768
2012.04428	A General Computational Framework to Measure the Expressiveness of Complex Networks Using a Tighter Upper Bound of Linear Regions	The expressiveness of deep neural network (DNN) is a perspective to understandthe surprising performance of DNN. The number of linear regions, i.e. pieces thata piece-wise-linear function represented by a DNN, is generally used to measurethe expressiveness. And the upper bound of regions number partitioned by a rec-tif...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	210,453
2206.09182	Coin Flipping Neural Networks	We show that neural networks with access to randomness can outperform deterministic networks by using amplification. We call such networks Coin-Flipping Neural Networks, or CFNNs. We show that a CFNN can approximate the indicator of a $d$-dimensional ball to arbitrary accuracy with only 2 layers and $\mathcal{O}(1)$ ne...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	303,461
2111.07507	Convergence and Equilibria Analysis of a Networked Bivirus Epidemic Model	This paper studies a networked bivirus model, in which two competing viruses spread across a network of interconnected populations; each node represents a population with a large number of individuals. The viruses may spread through possibly different network structures, and an individual cannot be simultaneously infec...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	266,398
2405.03929	Unicorn: U-Net for Sea Ice Forecasting with Convolutional Neural Ordinary Differential Equations	Sea ice at the North Pole is vital to global climate dynamics. However, accurately forecasting sea ice poses a significant challenge due to the intricate interaction among multiple variables. Leveraging the capability to integrate multiple inputs and powerful performances seamlessly, many studies have turned to neural ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	452,365
2007.03204	Learning Branching Heuristics for Propositional Model Counting	Propositional model counting, or #SAT, is the problem of computing the number of satisfying assignments of a Boolean formula. Many problems from different application areas, including many discrete probabilistic inference problems, can be translated into model counting problems to be solved by #SAT solvers. Exact #SAT ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	185,986
2303.03211	Using a Variational Autoencoder to Learn Valid Search Spaces of Safely Monitored Autonomous Robots for Last-Mile Delivery	The use of autonomous robots for delivery of goods to customers is an exciting new way to provide a reliable and sustainable service. However, in the real world, autonomous robots still require human supervision for safety reasons. We tackle the realworld problem of optimizing autonomous robot timings to maximize deliv...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	false	false	349,648
2005.07656	A Deep Q-learning/genetic Algorithms Based Novel Methodology For Optimizing Covid-19 Pandemic Government Actions	Whenever countries are threatened by a pandemic, as is the case with the COVID-19 virus, governments should take the right actions to safeguard public health as well as to mitigate the negative effects on the economy. In this regard, there are two completely different approaches governments can take: a restrictive one,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,341
2303.01869	Intrinsic Physical Concepts Discovery with Object-Centric Predictive Models	The ability to discover abstract physical concepts and understand how they work in the world through observing lies at the core of human intelligence. The acquisition of this ability is based on compositionally perceiving the environment in terms of objects and relations in an unsupervised manner. Recent approaches lea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	349,139
2303.07489	MRET: Multi-resolution Transformer for Video Quality Assessment	No-reference video quality assessment (NR-VQA) for user generated content (UGC) is crucial for understanding and improving visual experience. Unlike video recognition tasks, VQA tasks are sensitive to changes in input resolution. Since large amounts of UGC videos nowadays are 720p or above, the fixed and relatively sma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,266
1603.02772	Unscented External Force and Torque Estimation for Quadrotors	In this paper, we describe an algorithm, based on the well-known Unscented Quaternion Estimator, to estimate external forces and torques acting on a quadrotor. This formulation uses a non-linear model for the quadrotor dynamics, naturally incorporates process and measurement noise, requires only a few parameters to be ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	53,055
1506.04209	A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization	We propose a general algorithmic framework for constrained matrix and tensor factorization, which is widely used in signal processing and machine learning. The new framework is a hybrid between alternating optimization (AO) and the alternating direction method of multipliers (ADMM): each matrix factor is updated in tur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	44,136
1501.07399	Particle swarm optimization for time series motif discovery	Efficiently finding similar segments or motifs in time series data is a fundamental task that, due to the ubiquity of these data, is present in a wide range of domains and situations. Because of this, countless solutions have been devised but, to date, none of them seems to be fully satisfactory and flexible. In this a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	39,703
2211.00526	Leveraging Graph-based Cross-modal Information Fusion for Neural Sign Language Translation	Sign Language (SL), as the mother tongue of the deaf community, is a special visual language that most hearing people cannot understand. In recent years, neural Sign Language Translation (SLT), as a possible way for bridging communication gap between the deaf and the hearing people, has attracted widespread academic at...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	327,901
1012.3023	Generating constrained random graphs using multiple edge switches	The generation of random graphs using edge swaps provides a reliable method to draw uniformly random samples of sets of graphs respecting some simple constraints, e.g. degree distributions. However, in general, it is not necessarily possible to access all graphs obeying some given con- straints through a classical swit...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	8,534
2410.01444	Geometric Signatures of Compositionality Across a Language Model's Lifetime	By virtue of linguistic compositionality, few syntactic rules and a finite lexicon can generate an unbounded number of sentences. That is, language, though seemingly high-dimensional, can be explained using relatively few degrees of freedom. An open question is whether contemporary language models (LMs) reflect the int...	false	false	false	false	true	false	true	false	true	true	false	false	false	false	false	false	false	false	493,777
2210.11467	Multi-View Guided Multi-View Stereo	This paper introduces a novel deep framework for dense 3D reconstruction from multiple image frames, leveraging a sparse set of depth measurements gathered jointly with image acquisition. Given a deep multi-view stereo network, our framework uses sparse depth hints to guide the neural network by modulating the plane-sw...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	325,322
2311.13016	Image-Based Soil Organic Carbon Remote Sensing from Satellite Images with Fourier Neural Operator and Structural Similarity	Soil organic carbon (SOC) sequestration is the transfer and storage of atmospheric carbon dioxide in soils, which plays an important role in climate change mitigation. SOC concentration can be improved by proper land use, thus it is beneficial if SOC can be estimated at a regional or global scale. As multispectral sate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	409,588
1705.06477	Protecting Against Untrusted Relays: An Information Self-encrypted Approach	The reliability and transmission distance are generally limited for the wireless communications due to the severe channel fading. As an effective way to resist the channel fading, cooperative relaying is usually adopted in wireless networks where neighbouring nodes act as relays to help the transmission between the sou...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	73,641
1707.01341	A Modern Approach to Integrate Database Queries for Searching E-Commerce Product	E commerce refers to the utilization of electronic data transmission for enhancing business processes and implementing business strategies. Explicit components of e commerce include providing after sales services, promoting services or products to services, processing payment, engaging in transaction processes, identif...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	76,520
2406.17563	Multi-property Steering of Large Language Models with Dynamic Activation Composition	Activation steering methods were shown to be effective in conditioning language model generation by additively intervening over models' intermediate representations. However, the evaluation of these techniques has so far been limited to single conditioning properties and synthetic settings. In this work, we conduct a c...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	467,623
2002.09797	Reliable Fidelity and Diversity Metrics for Generative Models	Devising indicative evaluation metrics for the image generation task remains an open problem. The most widely used metric for measuring the similarity between real and generated images has been the Fr\'echet Inception Distance (FID) score. Because it does not differentiate the fidelity and diversity aspects of the gene...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	165,183
2407.15811	Stretching Each Dollar: Diffusion Training from Scratch on a Micro-Budget	As scaling laws in generative AI push performance, they also simultaneously concentrate the development of these models among actors with large computational resources. With a focus on text-to-image (T2I) generative models, we aim to address this bottleneck by demonstrating very low-cost training of large-scale T2I dif...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	475,343
2404.10942	What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning	In sequential decision-making problems involving sensitive attributes like race and gender, reinforcement learning (RL) agents must carefully consider long-term fairness while maximizing returns. Recent works have proposed many different types of fairness notions, but how unfairness arises in RL problems remains unclea...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	447,315
2404.12560	Dubo-SQL: Diverse Retrieval-Augmented Generation and Fine Tuning for Text-to-SQL	The current state-of-the-art (SOTA) for automated text-to-SQL still falls well short of expert human performance as measured by execution accuracy (EX) on the BIRD-SQL benchmark. The most accurate methods are also slow and expensive. To advance the SOTA for text-to-SQL while reducing cost and improving speed, we explor...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	447,935
2410.01978	LLM+KG@VLDB'24 Workshop Summary	The unification of large language models (LLMs) and knowledge graphs (KGs) has emerged as a hot topic. At the LLM+KG'24 workshop, held in conjunction with VLDB 2024 in Guangzhou, China, one of the key themes explored was important data management challenges and opportunities due to the effective interaction between LLM...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	494,042
2107.07871	Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations	Recently, physics-informed neural networks (PINNs) have offered a powerful new paradigm for solving problems relating to differential equations. Compared to classical numerical methods PINNs have several advantages, for example their ability to provide mesh-free solutions of differential equations and their ability to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	246,554
1009.5750	Use of multiple singular value decompositions to analyze complex intracellular calcium ion signals	We compare calcium ion signaling ($\mathrm {Ca}^{2+}$) between two exposures; the data are present as movies, or, more prosaically, time series of images. This paper describes novel uses of singular value decompositions (SVD) and weighted versions of them (WSVD) to extract the signals from such movies, in a way that is...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	7,705
1712.07887	Multiagent-based Participatory Urban Simulation through Inverse Reinforcement Learning	The multiagent-based participatory simulation features prominently in urban planning as the acquired model is considered as the hybrid system of the domain and the local knowledge. However, the key problem of generating realistic agents for particular social phenomena invariably remains. The existing models have attemp...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	87,117
2408.11470	A Thorough Comparison Between Independent Cascade and Susceptible-Infected-Recovered Models	We study cascades in social networks with the independent cascade (IC) model and the Susceptible-Infected-recovered (SIR) model. The well-studied IC model fails to capture the feature of node recovery, and the SIR model is a variant of the IC model with the node recovery feature. In the SIR model, by computing the prob...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	482,310
2402.18434	Graph Regularized Encoder Training for Extreme Classification	Deep extreme classification (XC) aims to train an encoder architecture and an accompanying classifier architecture to tag a data point with the most relevant subset of labels from a very large universe of labels. XC applications in ranking, recommendation and tagging routinely encounter tail labels for which the amount...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	433,431
2406.04549	Concurrent Training and Layer Pruning of Deep Neural Networks	We propose an algorithm capable of identifying and eliminating irrelevant layers of a neural network during the early stages of training. In contrast to weight or filter-level pruning, layer pruning reduces the harder to parallelize sequential computation of a neural network. We employ a structure using residual connec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	461,727
1301.2840	Unsupervised Feature Learning for low-level Local Image Descriptors	Unsupervised feature learning has shown impressive results for a wide range of input modalities, in particular for object classification tasks in computer vision. Using a large amount of unlabeled data, unsupervised feature learning methods are utilized to construct high-level representations that are discriminative en...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	21,046
2403.18762	ModaLink: Unifying Modalities for Efficient Image-to-PointCloud Place Recognition	Place recognition is an important task for robots and autonomous cars to localize themselves and close loops in pre-built maps. While single-modal sensor-based methods have shown satisfactory performance, cross-modal place recognition that retrieving images from a point-cloud database remains a challenging problem. Cur...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	442,067
2206.05108	Deep Multi-Agent Reinforcement Learning with Hybrid Action Spaces based on Maximum Entropy	Multi-agent deep reinforcement learning has been applied to address a variety of complex problems with either discrete or continuous action spaces and achieved great success. However, most real-world environments cannot be described by only discrete action spaces or only continuous action spaces. And there are few work...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	301,894
2102.05847	ZeroScatter: Domain Transfer for Long Distance Imaging and Vision through Scattering Media	Adverse weather conditions, including snow, rain, and fog, pose a major challenge for both human and computer vision. Handling these environmental conditions is essential for safe decision making, especially in autonomous vehicles, robotics, and drones. Most of today's supervised imaging and vision approaches, however,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	219,562
1808.05140	A Framework for Automated Cellular Network Tuning with Reinforcement Learning	Tuning cellular network performance against always occurring wireless impairments can dramatically improve reliability to end users. In this paper, we formulate cellular network performance tuning as a reinforcement learning (RL) problem and provide a solution to improve the performance for indoor and outdoor environme...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	105,300
2007.14730	Amplify-and-Forward Relaying for Hierarchical Over-the-Air Computation	This paper studies a hierarchical over-the-air computation (AirComp) network over a large area, in which multiple relays are exploited to facilitate data aggregation from massive WDs. We present a two-phase amplify-and-forward (AF) relaying protocol. In the first phase, the WDs simultaneously send their data to the rel...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	189,481
2207.09725	OTPose: Occlusion-Aware Transformer for Pose Estimation in Sparsely-Labeled Videos	Although many approaches for multi-human pose estimation in videos have shown profound results, they require densely annotated data which entails excessive man labor. Furthermore, there exists occlusion and motion blur that inevitably lead to poor estimation performance. To address these problems, we propose a method t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,005
2009.09259	Bid Shading by Win-Rate Estimation and Surplus Maximization	This paper describes a new win-rate based bid shading algorithm (WR) that does not rely on the minimum-bid-to-win feedback from a Sell-Side Platform (SSP). The method uses a modified logistic regression to predict the profit from each possible shaded bid price. The function form allows fast maximization at run-time, a ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	196,516
2410.14913	ReeFRAME: Reeb Graph based Trajectory Analysis Framework to Capture Top-Down and Bottom-Up Patterns of Life	In this paper, we present ReeFRAME, a scalable Reeb graph-based framework designed to analyze vast volumes of GPS-enabled human trajectory data generated at 1Hz frequency. ReeFRAME models Patterns-of-life (PoL) at both the population and individual levels, utilizing Multi-Agent Reeb Graphs (MARGs) for population-level ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	500,261
2407.12842	MS2SL: Multimodal Spoken Data-Driven Continuous Sign Language Production	Sign language understanding has made significant strides; however, there is still no viable solution for generating sign sequences directly from entire spoken content, e.g., text or speech. In this paper, we propose a unified framework for continuous sign language production, easing communication between sign and non-s...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	474,115
2204.05103	Transformer-Based Self-Supervised Learning for Emotion Recognition	In order to exploit representations of time-series signals, such as physiological signals, it is essential that these representations capture relevant information from the whole signal. In this work, we propose to use a Transformer-based model to process electrocardiograms (ECG) for emotion recognition. Attention mecha...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	290,910
2102.06741	Discovery of Options via Meta-Learned Subgoals	Temporal abstractions in the form of options have been shown to help reinforcement learning (RL) agents learn faster. However, despite prior work on this topic, the problem of discovering options through interaction with an environment remains a challenge. In this paper, we introduce a novel meta-gradient approach for ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	219,853
2009.08368	A new front-tracking Lagrangian model for the modeling of dynamic and post-dynamic recrystallization	A new method for the simulation of evolving multi-domains problems has been introduced in previous works (RealIMotion), Florez et al. (2020) and further developed in parallel in the context of isotropic Grain Growth (GG) with no consideration for the effects of the Stored Energy (SE) due to dislocations. The methodolog...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	196,218
2311.17836	On Scaling Robust Feedback Control and State Estimation Problems in Power Networks	Many mainstream robust control/estimation algorithms for power networks are designed using the Lyapunov theory as it provides performance guarantees for linear/nonlinear models of uncertain power networks but comes at the expense of scalability and sensitivity. In particular, Lyapunov-based approaches rely on forming s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	411,431
2411.16797	Enhancing Answer Reliability Through Inter-Model Consensus of Large Language Models	We explore the collaborative dynamics of an innovative language model interaction system involving advanced models such as GPT-4-0125-preview, Meta-LLaMA-3-70B-Instruct, Claude-3-Opus, and Gemini-1.5-Flash. These models generate and answer complex, PhD-level statistical questions without exact ground-truth answers. Our...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	511,190
2012.09842	$\mathbb{X}$Resolution Correspondence Networks	In this paper, we aim at establishing accurate dense correspondences between a pair of images with overlapping field of view under challenging illumination variation, viewpoint changes, and style differences. Through an extensive ablation study of the state-of-the-art correspondence networks, we surprisingly discovered...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	212,188
2111.10330	Data-driven verification and synthesis of stochastic systems via barrier certificates	In this work, we study verification and synthesis problems for safety specifications over unknown discrete-time stochastic systems. When a model of the system is available, barrier certificates have been successfully applied for ensuring the satisfaction of safety specifications. In this work, we formulate the computat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	267,286
2205.12722	Mathematical Models of Human Drivers Using Artificial Risk Fields	In this paper, we use the concept of artificial risk fields to predict how human operators control a vehicle in response to upcoming road situations. A risk field assigns a non-negative risk measure to the state of the system in order to model how close that state is to violating a safety property, such as hitting an o...	true	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	298,687
2405.09959	Patient-Specific Real-Time Segmentation in Trackerless Brain Ultrasound	Intraoperative ultrasound (iUS) imaging has the potential to improve surgical outcomes in brain surgery. However, its interpretation is challenging, even for expert neurosurgeons. In this work, we designed the first patient-specific framework that performs brain tumor segmentation in trackerless iUS. To disambiguate ul...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	454,599
2203.04358	ARcall: Real-Time AR Communication using Smartphones and Smartglasses	Augmented Reality (AR) smartglasses are increasingly regarded as the next generation personal computing platform. However, there is a lack of understanding about how to design communication systems using them. We present ARcall, a novel Augmented Reality-based real-time communication system that enables an immersive, d...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	284,435

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.