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
2112.03270	Toward a Taxonomy of Trust for Probabilistic Machine Learning	Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. We need evidence to support that the resulting decisions are well-founded. To aid development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1)...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	270,146
1506.03365	LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop	While there has been remarkable progress in the performance of visual recognition algorithms, the state-of-the-art models tend to be exceptionally data-hungry. Large labeled training datasets, expensive and tedious to produce, are required to optimize millions of parameters in deep network models. Lagging behind the gr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	44,041
2309.09298	OWL: A Large Language Model for IT Operations	With the rapid development of IT operations, it has become increasingly crucial to efficiently manage and analyze large volumes of data for practical applications. The techniques of Natural Language Processing (NLP) have shown remarkable capabilities for various tasks, including named entity recognition, machine transl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	392,551
2106.01420	Parallelizing Thompson Sampling	How can we make use of information parallelism in online decision making problems while efficiently balancing the exploration-exploitation trade-off? In this paper, we introduce a batch Thompson Sampling framework for two canonical online decision making problems, namely, stochastic multi-arm bandit and linear contextu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	238,483
2011.11517	Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games	This paper introduces an information-theoretic constraint on learned policy complexity in the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) reinforcement learning algorithm. Previous research with a related approach in continuous control experiments suggests that this method favors learning policies that are ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	207,849
2002.00664	Influencing Opinion Dynamics in Networks with Limited Interaction	The focus of this work is on designing influencing strategies to shape the collective opinion of a network of individuals. We consider a variant of the voter model where opinions evolve in one of two ways. In the absence of external influence, opinions evolve via interactions between individuals in the network, while, ...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	162,421
1605.03865	A New Manifold Distance Measure for Visual Object Categorization	Manifold distances are very effective tools for visual object recognition. However, most of the traditional manifold distances between images are based on the pixel-level comparison and thus easily affected by image rotations and translations. In this paper, we propose a new manifold distance to model the dissimilariti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	55,805
2211.03511	End-to-End Evaluation of a Spoken Dialogue System for Learning Basic Mathematics	The advances in language-based Artificial Intelligence (AI) technologies applied to build educational applications can present AI for social-good opportunities with a broader positive impact. Across many disciplines, enhancing the quality of mathematics education is crucial in building critical thinking and problem-sol...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	328,953
2104.00814	CURIE: An Iterative Querying Approach for Reasoning About Situations	Recently, models have been shown to predict the effects of unexpected situations, e.g., would cloudy skies help or hinder plant growth? Given a context, the goal of such situational reasoning is to elicit the consequences of a new situation (st) that arises in that context. We propose a method to iteratively build a gr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	228,129
2011.10712	Near-Optimal Data Source Selection for Bayesian Learning	We study a fundamental problem in Bayesian learning, where the goal is to select a set of data sources with minimum cost while achieving a certain learning performance based on the data streams provided by the selected data sources. First, we show that the data source selection problem for Bayesian learning is NP-hard....	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	207,596
2108.12618	Asymptotic Frame Theory for Analog Coding	Over-complete systems of vectors, or in short, frames, play the role of analog codes in many areas of communication and signal processing. To name a few, spreading sequences for code-division multiple access (CDMA), over-complete representations for multiple-description (MD) source coding, space-time codes, sensing mat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	252,557
2410.16633	Graph-Structured Trajectory Extraction from Travelogues	Previous studies on sequence-based extraction of human movement trajectories have an issue of inadequate trajectory representation. Specifically, a pair of locations may not be lined up in a sequence especially when one location includes the other geographically. In this study, we propose a graph representation that re...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	501,110
2303.06049	Affordable Artificial Intelligence -- Augmenting Farmer Knowledge with AI	Farms produce hundreds of thousands of data points on the ground daily. Farming technique which combines farming practices with the insights uncovered in these data points using AI technology is called precision farming. Precision farming technology augments and extends farmers' deep knowledge about their land, making ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	350,679
0903.2711	Performance Assessment of MIMO-BICM Demodulators based on System Capacity	We provide a comprehensive performance comparison of soft-output and hard-output demodulators in the context of non-iterative multiple-input multiple-output bit-interleaved coded modulation (MIMO-BICM). Coded bit error rate (BER), widely used in literature for demodulator comparison, has the drawback of depending stron...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,358
2210.07463	Polycentric Clustering and Structural Regularization for Source-free Unsupervised Domain Adaptation	Source-Free Domain Adaptation (SFDA) aims to solve the domain adaptation problem by transferring the knowledge learned from a pre-trained source model to an unseen target domain. Most existing methods assign pseudo-labels to the target data by generating feature prototypes. However, due to the discrepancy in the data d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	323,720
2308.08544	MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions	This paper strives for motion expressions guided video segmentation, which focuses on segmenting objects in video content based on a sentence describing the motion of the objects. Existing referring video object datasets typically focus on salient objects and use language expressions that contain excessive static attri...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,946
2005.01512	The Fractional Preferential Attachment Scale-Free Network Model	Many networks generated by nature have two generic properties: they are formed in the process of {preferential attachment} and they are scale-free. Considering these features, by interfering with mechanism of the {preferential attachment}, we propose a generalisation of the Barab\'asi--Albert model---the 'Fractional Pr...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	175,595
1212.3385	Approximating rational Bezier curves by constrained Bezier curves of arbitrary degree	In this paper, we propose a method to obtain a constrained approximation of a rational B\'{e}zier curve by a polynomial B\'{e}zier curve. This problem is reformulated as an approximation problem between two polynomial B\'{e}zier curves based on weighted least-squares method, where weight functions $\rho(t)=\omega(t)$ a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	20,389
1906.07592	Towards Robust Named Entity Recognition for Historic German	Recent advances in language modeling using deep neural networks have shown that these models learn representations, that vary with the network depth from morphology to semantic relationships like co-reference. We apply pre-trained language models to low-resource named entity recognition for Historic German. We show on ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	135,639
2402.00881	On the Interplay of Artificial Intelligence and Space-Air-Ground Integrated Networks: A Survey	Space-Air-Ground Integrated Networks (SAGINs), which incorporate space and aerial networks with terrestrial wireless systems, are vital enablers of the emerging sixth-generation (6G) wireless networks. Besides bringing significant benefits to various applications and services, SAGINs are envisioned to extend high-speed...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	425,767
cmp-lg/9707018	Multilingual phonological analysis and speech synthesis	We give an overview of multilingual speech synthesis using the IPOX system. The first part discusses work in progress for various languages: Tashlhit Berber, Urdu and Dutch. The second part discusses a multilingual phonological grammar, which can be adapted to a particular language by setting parameters and adding lang...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,785
2501.12295	Towards Accurate Unified Anomaly Segmentation	Unsupervised anomaly detection (UAD) from images strives to model normal data distributions, creating discriminative representations to distinguish and precisely localize anomalies. Despite recent advancements in the efficient and unified one-for-all scheme, challenges persist in accurately segmenting anomalies for fur...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	526,249
2111.09876	One-Shot Generative Domain Adaptation	This work aims at transferring a Generative Adversarial Network (GAN) pre-trained on one image domain to a new domain referring to as few as just one target image. The main challenge is that, under limited supervision, it is extremely difficult to synthesize photo-realistic and highly diverse images, while acquiring re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,136
2303.09590	Visual Analytics of Multivariate Networks with Representation Learning and Composite Variable Construction	Multivariate networks are commonly found in real-world data-driven applications. Uncovering and understanding the relations of interest in multivariate networks is not a trivial task. This paper presents a visual analytics workflow for studying multivariate networks to extract associations between different structural ...	true	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	352,103
2103.16424	Two-stage Robust Energy Storage Planning with Probabilistic Guarantees: A Data-driven Approach	This paper addresses a central challenge of jointly considering shorter-term (e.g. hourly) and longer-term (e.g. yearly) uncertainties in power system planning with increasing penetration of renewable and storage resources. In conventional planning decision making, shorter-term (e.g., hourly) variations are not explici...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	227,579
2408.07079	Anatomical Foundation Models for Brain MRIs	Deep Learning (DL) in neuroimaging has become increasingly relevant for detecting neurological conditions and neurodegenerative disorders. One of the most predominant biomarkers in neuroimaging is represented by brain age, which has been shown to be a good indicator for different conditions, such as Alzheimer's Disease...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	480,441
2010.12760	Dataset Dynamics via Gradient Flows in Probability Space	Various machine learning tasks, from generative modeling to domain adaptation, revolve around the concept of dataset transformation and manipulation. While various methods exist for transforming unlabeled datasets, principled methods to do so for labeled (e.g., classification) datasets are missing. In this work, we pro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,834
2411.12469	AI Flow at the Network Edge	Recent advancements in large language models (LLMs) and their multimodal variants have led to remarkable progress across various domains, demonstrating impressive capabilities and unprecedented potential. In the era of ubiquitous connectivity, leveraging communication networks to distribute intelligence is a transforma...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	509,421
2401.04787	A Convex Optimization Approach to Compute Trapping Regions for Lossless Quadratic Systems	Quadratic systems with lossless quadratic terms arise in many applications, including models of atmosphere and incompressible fluid flows. Such systems have a trapping region if all trajectories eventually converge to and stay within a bounded set. Conditions for the existence and characterization of trapping regions h...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	420,539
2103.12685	Generative Minimization Networks: Training GANs Without Competition	Many applications in machine learning can be framed as minimization problems and solved efficiently using gradient-based techniques. However, recent applications of generative models, particularly GANs, have triggered interest in solving min-max games for which standard optimization techniques are often not suitable. A...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	226,256
1905.08022	An iterative scheme for feature based positioning using a weighted dissimilarity measure	We propose an iterative scheme for feature-based positioning using a new weighted dissimilarity measure with the goal of reducing the impact of large errors among the measured or modeled features. The weights are computed from the location-dependent standard deviations of the features and stored as part of the referenc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	131,379
2103.13671	Actuator Fault-Tolerant Vehicle Motion Control: A Survey	The advent of automated vehicles operating at SAE levels 4 and 5 poses high fault tolerance demands for all functions contributing to the driving task. At the actuator level, fault-tolerant vehicle motion control, which exploits functional redundancies among the actuators, is one means to achieve the required degree of...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	226,572
2501.05399	Performance of YOLOv7 in Kitchen Safety While Handling Knife	Safe knife practices in the kitchen significantly reduce the risk of cuts, injuries, and serious accidents during food preparation. Using YOLOv7, an advanced object detection model, this study focuses on identifying safety risks during knife handling, particularly improper finger placement and blade contact with hand. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	523,562
cs/0701052	Time Series Forecasting: Obtaining Long Term Trends with Self-Organizing Maps	Kohonen self-organisation maps are a well know classification tool, commonly used in a wide variety of problems, but with limited applications in time series forecasting context. In this paper, we propose a forecasting method specifically designed for multi-dimensional long-term trends prediction, with a double applica...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	540,031
2412.16167	Hierarchical Multi-Agent DRL Based Dynamic Cluster Reconfiguration for UAV Mobility Management	Multi-connectivity involves dynamic cluster formation among distributed access points (APs) and coordinated resource allocation from these APs, highlighting the need for efficient mobility management strategies for users with multi-connectivity. In this paper, we propose a novel mobility management scheme for unmanned ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	519,385
2207.03582	X-haul Outage Compensation in 5G/6G Using Reconfigurable Intelligent Surfaces	5G network operators consider the dense deployment of small base-stations (SBSs) to increase network coverage and capacity. Hence, operators face the challenge of X-hauling, i.e., backhauling or fronthauling, their traffic to the core network. Also, SBSs densification will increase the possibility of failure of these X...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	306,901
2104.02988	Optimal Algorithms for Differentially Private Stochastic Monotone Variational Inequalities and Saddle-Point Problems	In this work, we conduct the first systematic study of stochastic variational inequality (SVI) and stochastic saddle point (SSP) problems under the constraint of differential privacy (DP). We propose two algorithms: Noisy Stochastic Extragradient (NSEG) and Noisy Inexact Stochastic Proximal Point (NISPP). We show that ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	228,931
2308.04323	Embracing Safe Contacts with Contact-aware Planning and Control	Unlike human beings that can employ the entire surface of their limbs as a means to establish contact with their environment, robots are typically programmed to interact with their environments via their end-effectors, in a collision-free fashion, to avoid damaging their environment. In a departure from such a traditio...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	384,370
1707.09938	Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network	Model based iterative reconstruction (MBIR) algorithms for low-dose X-ray CT are computationally expensive. To address this problem, we recently proposed a deep convolutional neural network (CNN) for low-dose X-ray CT and won the second place in 2016 AAPM Low-Dose CT Grand Challenge. However, some of the texture were n...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	78,116
0712.2869	Density estimation in linear time	We consider the problem of choosing a density estimate from a set of distributions F, minimizing the L1-distance to an unknown distribution (Devroye, Lugosi 2001). Devroye and Lugosi analyze two algorithms for the problem: Scheffe tournament winner and minimum distance estimate. The Scheffe tournament estimate requires...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	1,051
1908.08178	Multi-Stream Single Shot Spatial-Temporal Action Detection	We present a 3D Convolutional Neural Networks (CNNs) based single shot detector for spatial-temporal action detection tasks. Our model includes: (1) two short-term appearance and motion streams, with single RGB and optical flow image input separately, in order to capture the spatial and temporal information for the cur...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	142,482
2112.07076	Real-Time Neural Voice Camouflage	Automatic speech recognition systems have created exciting possibilities for applications, however they also enable opportunities for systematic eavesdropping. We propose a method to camouflage a person's voice over-the-air from these systems without inconveniencing the conversation between people in the room. Standard...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	271,365
2502.11736	ReviewEval: An Evaluation Framework for AI-Generated Reviews	The escalating volume of academic research, coupled with a shortage of qualified reviewers, necessitates innovative approaches to peer review. While large language model (LLMs) offer potential for automating this process, their current limitations include superficial critiques, hallucinations, and a lack of actionable ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	534,522
2410.06617	Learning Evolving Tools for Large Language Models	Tool learning enables large language models (LLMs) to interact with external tools and APIs, greatly expanding the application scope of LLMs. However, due to the dynamic nature of external environments, these tools and APIs may become outdated over time, preventing LLMs from correctly invoking tools. Existing research ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	496,283
2402.05423	MTSA-SNN: A Multi-modal Time Series Analysis Model Based on Spiking Neural Network	Time series analysis and modelling constitute a crucial research area. Traditional artificial neural networks struggle with complex, non-stationary time series data due to high computational complexity, limited ability to capture temporal information, and difficulty in handling event-driven data. To address these chall...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	427,858
2210.00695	Automated Performance Estimation for Decentralized Optimization via Network Size Independent Problems	We develop a novel formulation of the Performance Estimation Problem (PEP) for decentralized optimization whose size is independent of the number of agents in the network. The PEP approach allows computing automatically the worst-case performance and worst-case instance of first-order optimization methods by solving an...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	320,961
2203.08488	Pushing the limits of raw waveform speaker recognition	In recent years, speaker recognition systems based on raw waveform inputs have received increasing attention. However, the performance of such systems are typically inferior to the state-of-the-art handcrafted feature-based counterparts, which demonstrate equal error rates under 1% on the popular VoxCeleb1 test set. Th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	285,810
2209.14604	Spherical Image Inpainting with Frame Transformation and Data-driven Prior Deep Networks	Spherical image processing has been widely applied in many important fields, such as omnidirectional vision for autonomous cars, global climate modelling, and medical imaging. It is non-trivial to extend an algorithm developed for flat images to the spherical ones. In this work, we focus on the challenging task of sphe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	320,304
1911.09271	Cantonese Automatic Speech Recognition Using Transfer Learning from Mandarin	We propose a system to develop a basic automatic speech recognizer(ASR) for Cantonese, a low-resource language, through transfer learning of Mandarin, a high-resource language. We take a time-delayed neural network trained on Mandarin, and perform weight transfer of several layers to a newly initialized model for Canto...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	154,455
2409.01935	Map-Assisted Remote-Sensing Image Compression at Extremely Low Bitrates	Remote-sensing (RS) image compression at extremely low bitrates has always been a challenging task in practical scenarios like edge device storage and narrow bandwidth transmission. Generative models including VAEs and GANs have been explored to compress RS images into extremely low-bitrate streams. However, these gene...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,514
2101.11538	Multi-agent simulation of voter's behaviour	The goal of this paper is to simulate the voters behaviour given a voting method. Our approach uses a multi-agent simulation in order to model a voting process through many iterations, so that the voters can vote by taking into account the results of polls. Here we only tried basic rules and a single voting method, but...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	217,314
cs/0703135	Dependency Parsing with Dynamic Bayesian Network	Exact parsing with finite state automata is deemed inappropriate because of the unbounded non-locality languages overwhelmingly exhibit. We propose a way to structure the parsing task in order to make it amenable to local classification methods. This allows us to build a Dynamic Bayesian Network which uncovers the synt...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	540,269
2401.00629	Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning	We propose WSAC (Weighted Safe Actor-Critic), a novel algorithm for Safe Offline Reinforcement Learning (RL) under functional approximation, which can robustly optimize policies to improve upon an arbitrary reference policy with limited data coverage. WSAC is designed as a two-player Stackelberg game to optimize a refi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	419,048
2211.13793	Tensor Decomposition of Large-scale Clinical EEGs Reveals Interpretable Patterns of Brain Physiology	Identifying abnormal patterns in electroencephalography (EEG) remains the cornerstone of diagnosing several neurological diseases. The current clinical EEG review process relies heavily on expert visual review, which is unscalable and error-prone. In an effort to augment the expert review process, there is a significan...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	332,597
2408.13666	Discovery and Simulation of Data-Aware Business Processes	Simulation is a common approach to predict the effect of business process changes on quantitative performance. The starting point of Business Process Simulation (BPS) is a process model enriched with simulation parameters. To cope with the typically large parameter spaces of BPS models, several methods have been propos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	483,236
1111.6983	Aggregation of Composite Solutions: strategies, models, examples	The paper addresses aggregation issues for composite (modular) solutions. A systemic view point is suggested for various aggregation problems. Several solution structures are considered: sets, set morphologies, trees, etc. Mainly, the aggregation approach is targeted to set morphologies. The aggregation problems are ba...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	13,233
2410.05997	An Eye for an Ear: Zero-shot Audio Description Leveraging an Image Captioner using Audiovisual Distribution Alignment	Multimodal large language models have fueled progress in image captioning. These models, fine-tuned on vast image datasets, exhibit a deep understanding of semantic concepts. In this work, we show that this ability can be re-purposed for audio captioning, where the joint image-language decoder can be leveraged to descr...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	496,005
2406.19711	CHASE: A Causal Heterogeneous Graph based Framework for Root Cause Analysis in Multimodal Microservice Systems	In recent years, the widespread adoption of distributed microservice architectures within the industry has significantly increased the demand for enhanced system availability and robustness. Due to the complex service invocation paths and dependencies at enterprise-level microservice systems, it is challenging to locat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	468,535
2405.00602	Investigating Automatic Scoring and Feedback using Large Language Models	Automatic grading and feedback have been long studied using traditional machine learning and deep learning techniques using language models. With the recent accessibility to high performing large language models (LLMs) like LLaMA-2, there is an opportunity to investigate the use of these LLMs for automatic grading and ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	450,983
2406.06593	Differentiable Combinatorial Scheduling at Scale	This paper addresses the complex issue of resource-constrained scheduling, an NP-hard problem that spans critical areas including chip design and high-performance computing. Traditional scheduling methods often stumble over scalability and applicability challenges. We propose a novel approach using a differentiable com...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	462,676
2011.07424	Intention-Based Lane Changing and Lane Keeping Haptic Guidance Steering System	Haptic guidance in a shared steering assistance system has drawn significant attention in intelligent vehicle fields, owing to its mutual communication ability for vehicle control. By exerting continuous torque on the steering wheel, both the driver and support system can share lateral control of the vehicle. However, ...	true	false	false	false	true	false	true	true	false	false	true	false	false	false	false	false	false	false	206,548
2109.10082	DeepTimeAnomalyViz: A Tool for Visualizing and Post-processing Deep Learning Anomaly Detection Results for Industrial Time-Series	Industrial processes are monitored by a large number of various sensors that produce time-series data. Deep Learning offers a possibility to create anomaly detection methods that can aid in preventing malfunctions and increasing efficiency. But creating such a solution can be a complicated task, with factors such as in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	256,505
2410.19141	Versatile Demonstration Interface: Toward More Flexible Robot Demonstration Collection	Previous methods for Learning from Demonstration leverage several approaches for a human to teach motions to a robot, including teleoperation, kinesthetic teaching, and natural demonstrations. However, little previous work has explored more general interfaces that allow for multiple demonstration types. Given the varie...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	502,175
2307.04231	Mx2M: Masked Cross-Modality Modeling in Domain Adaptation for 3D Semantic Segmentation	Existing methods of cross-modal domain adaptation for 3D semantic segmentation predict results only via 2D-3D complementarity that is obtained by cross-modal feature matching. However, as lacking supervision in the target domain, the complementarity is not always reliable. The results are not ideal when the domain gap ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	378,336
2203.05890	Video Coding for Machines with Feature-Based Rate-Distortion Optimization	Common state-of-the-art video codecs are optimized to deliver a low bitrate by providing a certain quality for the final human observer, which is achieved by rate-distortion optimization (RDO). But, with the steady improvement of neural networks solving computer vision tasks, more and more multimedia data is not observ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,944
2405.06234	TS3IM: Unveiling Structural Similarity in Time Series through Image Similarity Assessment Insights	In the realm of time series analysis, accurately measuring similarity is crucial for applications such as forecasting, anomaly detection, and clustering. However, existing metrics often fail to capture the complex, multidimensional nature of time series data, limiting their effectiveness and application. This paper int...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	453,222
2001.03093	Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data	Reasoning about human motion is an important prerequisite to safe and socially-aware robotic navigation. As a result, multi-agent behavior prediction has become a core component of modern human-robot interactive systems, such as self-driving cars. While there exist many methods for trajectory forecasting, most do not e...	true	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	159,882
2405.01646	Explaining models relating objects and privacy	Accurately predicting whether an image is private before sharing it online is difficult due to the vast variety of content and the subjective nature of privacy itself. In this paper, we evaluate privacy models that use objects extracted from an image to determine why the image is predicted as private. To explain the de...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	451,442
1205.4067	Optimum Commutative Group Codes	A method for finding an optimum $n$-dimensional commutative group code of a given order $M$ is presented. The approach explores the structure of lattices related to these codes and provides a significant reduction in the number of non-isometric cases to be analyzed. The classical factorization of matrices into Hermite ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,061
2408.17350	Regular Pairings for Non-quadratic Lyapunov Functions and Contraction Analysis	Recent studies on stability and contractivity have highlighted the importance of semi-inner products, which we refer to as ``pairings'', associated with general norms. A pairing is a binary operation that relates the derivative of a curve's norm to the radius-vector of the curve and its tangent. This relationship, know...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	484,672
2204.08499	DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning	Coreset selection, which aims to select a subset of the most informative training samples, is a long-standing learning problem that can benefit many downstream tasks such as data-efficient learning, continual learning, neural architecture search, active learning, etc. However, many existing coreset selection methods ar...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	292,107
1208.2925	Using Program Synthesis for Social Recommendations	This paper presents a new approach to select events of interest to a user in a social media setting where events are generated by the activities of the user's friends through their mobile devices. We argue that given the unique requirements of the social media setting, the problem is best viewed as an inductive learnin...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	true	true	18,074
2007.11180	MI^2GAN: Generative Adversarial Network for Medical Image Domain Adaptation using Mutual Information Constraint	Domain shift between medical images from multicentres is still an open question for the community, which degrades the generalization performance of deep learning models. Generative adversarial network (GAN), which synthesize plausible images, is one of the potential solutions to address the problem. However, the existi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,487
1801.09054	Ear Recognition With Score-Level Fusion Based On CMC In Long-Wave Infrared Spectrum	Only a few studies have been reported regarding human ear recognition in long wave infrared band. Thus, we have created ear database based on long wave infrared band. We have called that the database is long wave infrared band MIDAS consisting of 2430 records of 81 subjects. Thermal band provides seamless operation bot...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,037
2405.15273	Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders	Time series anomaly detection plays a vital role in a wide range of applications. Existing methods require training one specific model for each dataset, which exhibits limited generalization capability across different target datasets, hindering anomaly detection performance in various scenarios with scarce training da...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	456,843
2104.09304	A Tunable Model for Graph Generation Using LSTM and Conditional VAE	With the development of graph applications, generative models for graphs have been more crucial. Classically, stochastic models that generate graphs with a pre-defined probability of edges and nodes have been studied. Recently, some models that reproduce the structural features of graphs by learning from actual graph d...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	231,182
2205.13051	Online Deep Equilibrium Learning for Regularization by Denoising	Plug-and-Play Priors (PnP) and Regularization by Denoising (RED) are widely-used frameworks for solving imaging inverse problems by computing fixed-points of operators combining physical measurement models and learned image priors. While traditional PnP/RED formulations have focused on priors specified using image deno...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	298,783
2201.05929	Characterizing Big Data Management	Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any k...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	true	false	275,553
2207.09908	Integrated Finite Element Neural Network (I-FENN) for non-local continuum damage mechanics	We present a new Integrated Finite Element Neural Network framework (I-FENN), with the objective to accelerate the numerical solution of nonlinear computational mechanics problems. We leverage the swift predictive capability of neural networks (NNs) and we embed them inside the finite element stiffness function, to com...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	309,066
2205.10430	Using machine learning on new feature sets extracted from 3D models of broken animal bones to classify fragments according to break agent	Distinguishing agents of bone modification at paleoanthropological sites is at the root of much of the research directed at understanding early hominin exploitation of large animal resources and the effects those subsistence behaviors had on early hominin evolution. However, current methods, particularly in the area of...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	297,698
2406.18449	Cascading Large Language Models for Salient Event Graph Generation	Generating event graphs from long documents is challenging due to the inherent complexity of multiple tasks involved such as detecting events, identifying their relationships, and reconciling unstructured input with structured graphs. Recent studies typically consider all events with equal importance, failing to distin...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	468,011
1910.10566	Tropical Cyclone Track Forecasting using Fused Deep Learning from Aligned Reanalysis Data	The forecast of tropical cyclone trajectories is crucial for the protection of people and property. Although forecast dynamical models can provide high-precision short-term forecasts, they are computationally demanding, and current statistical forecasting models have much room for improvement given that the database of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	150,528
2110.03292	Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations	This paper deals with robotic lever control using Explainable Deep Reinforcement Learning. First, we train a policy by using the Deep Deterministic Policy Gradient algorithm and the Hindsight Experience Replay technique, where the goal is to control a robotic manipulator to manipulate a lever. This enables us both to u...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	259,438
2205.07516	The use of deep learning in interventional radiotherapy (brachytherapy): a review with a focus on open source and open data	Deep learning advanced to one of the most important technologies in almost all medical fields. Especially in areas, related to medical imaging it plays a big role. However, in interventional radiotherapy (brachytherapy) deep learning is still in an early phase. In this review, first, we investigated and scrutinised the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	296,629
2403.06800	MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology	Multiple Instance Learning (MIL) has emerged as a dominant paradigm to extract discriminative feature representations within Whole Slide Images (WSIs) in computational pathology. Despite driving notable progress, existing MIL approaches suffer from limitations in facilitating comprehensive and efficient interactions am...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,607
2407.07000	Etalon: Holistic Performance Evaluation Framework for LLM Inference Systems	Serving large language models (LLMs) in production can incur substantial costs, which has prompted recent advances in inference system optimizations. Today, these systems are evaluated against conventional latency and throughput metrics (eg. TTFT, TBT, Normalised Latency and TPOT). However, these metrics fail to fully ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	471,604
2105.09198	A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning	We curated WikiPII, an automatically labeled dataset composed of Wikipedia biography pages, annotated for personal information extraction. Although automatic annotation can lead to a high degree of label noise, it is an inexpensive process and can generate large volumes of annotated documents. We trained a BERT-based N...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	235,998
2410.03770	A Two-Stage Proactive Dialogue Generator for Efficient Clinical Information Collection Using Large Language Model	Efficient patient-doctor interaction is among the key factors for a successful disease diagnosis. During the conversation, the doctor could query complementary diagnostic information, such as the patient's symptoms, previous surgery, and other related information that goes beyond medical evidence data (test results) to...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	494,955
2307.07925	Can Sparse Arrays Outperform Collocated Arrays for Future Wireless Communications?	Multiple-input multiple-output (MIMO) has become a key technology for contemporary wireless communication systems. For typical MIMO systems, antenna arrays are separated by half of the signal wavelength, which are termed collocated arrays. In this paper, we ask the following question: For future wireless communication ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	379,593
2204.14141	Learning Anisotropic Interaction Rules from Individual Trajectories in a Heterogeneous Cellular Population	Interacting particle system (IPS) models have proven to be highly successful for describing the spatial movement of organisms. However, it has proven challenging to infer the interaction rules directly from data. In the field of equation discovery, the Weak form Sparse Identification of Nonlinear Dynamics (WSINDy) meth...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	294,067
2407.15675	Flow-guided Motion Prediction with Semantics and Dynamic Occupancy Grid Maps	Accurate prediction of driving scenes is essential for road safety and autonomous driving. Occupancy Grid Maps (OGMs) are commonly employed for scene prediction due to their structured spatial representation, flexibility across sensor modalities and integration of uncertainty. Recent studies have successfully combined ...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	475,278
2303.17531	Asymmetric Image Retrieval with Cross Model Compatible Ensembles	The asymmetrical retrieval setting is a well suited solution for resource constrained applications such as face recognition and image retrieval. In this setting, a large model is used for indexing the gallery while a lightweight model is used for querying. The key principle in such systems is ensuring that both models ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,239
2410.11340	Toward a Well-Calibrated Discrimination via Survival Outcome-Aware Contrastive Learning	Previous deep learning approaches for survival analysis have primarily relied on ranking losses to improve discrimination performance, which often comes at the expense of calibration performance. To address such an issue, we propose a novel contrastive learning approach specifically designed to enhance discrimination \...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,512
2301.09637	InfiniCity: Infinite-Scale City Synthesis	Toward infinite-scale 3D city synthesis, we propose a novel framework, InfiniCity, which constructs and renders an unconstrainedly large and 3D-grounded environment from random noises. InfiniCity decomposes the seemingly impractical task into three feasible modules, taking advantage of both 2D and 3D data. First, an in...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	341,558
2006.07593	Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search	Neural architecture search (NAS) automates the design of deep neural networks. One of the main challenges in searching complex and non-continuous architectures is to compare the similarity of networks that the conventional Euclidean metric may fail to capture. Optimal transport (OT) is resilient to such complex structu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	181,871
2403.16331	Modeling Analog Dynamic Range Compressors using Deep Learning and State-space Models	We describe a novel approach for developing realistic digital models of dynamic range compressors for digital audio production by analyzing their analog prototypes. While realistic digital dynamic compressors are potentially useful for many applications, the design process is challenging because the compressors operate...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	440,980
2304.05233	Mask-conditioned latent diffusion for generating gastrointestinal polyp images	In order to take advantage of AI solutions in endoscopy diagnostics, we must overcome the issue of limited annotations. These limitations are caused by the high privacy concerns in the medical field and the requirement of getting aid from experts for the time-consuming and costly medical data annotation process. In com...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	357,546
2104.12419	ECLIPSE : Envisioning CLoud Induced Perturbations in Solar Energy	Efficient integration of solar energy into the electricity mix depends on a reliable anticipation of its intermittency. A promising approach to forecast the temporal variability of solar irradiance resulting from the cloud cover dynamics is based on the analysis of sequences of ground-taken sky images or satellite obse...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	232,204
2403.09022	Smart Resource Allocation at mmWave/THz Frequencies with Cooperative Rate-Splitting	In this paper, we propose algorithms to minimize the energy consumption in millimeter wave/terahertz multi-user downlink communication systems. To ensure coverage in blockage-vulnerable high frequency systems, we consider cooperative rate-splitting (CRS) and transmission over multiple time blocks, where via CRS, multip...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	437,585
2409.12753	DrivingForward: Feed-forward 3D Gaussian Splatting for Driving Scene Reconstruction from Flexible Surround-view Input	We propose DrivingForward, a feed-forward Gaussian Splatting model that reconstructs driving scenes from flexible surround-view input. Driving scene images from vehicle-mounted cameras are typically sparse, with limited overlap, and the movement of the vehicle further complicates the acquisition of camera extrinsics. T...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	489,709

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