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
1907.11901	Quantum Stochastic Processes and the Modelling of Quantum Noise	This brief article gives an overview of quantum mechanics as a {\em quantum probability theory}. It begins with a review of the basic operator-algebraic elements that connect probability theory with quantum probability theory. Then quantum stochastic processes is formulated as a generalization of stochastic processes w...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	139,978
2209.08708	Autoregressive Entity Generation for End-to-End Task-Oriented Dialog	Task-oriented dialog (TOD) systems often require interaction with an external knowledge base to retrieve necessary entity (e.g., restaurant) information to support the response generation. Most current end-to-end TOD systems either retrieve the KB information explicitly or embed it into model parameters for implicit ac...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	318,232
2206.03931	Learning to Generate Prompts for Dialogue Generation through Reinforcement Learning	Much literature has shown that prompt-based learning is an efficient method to make use of the large pre-trained language model. Recent works also exhibit the possibility of steering a chatbot's output by plugging in an appropriate prompt. Gradient-based methods are often used to perturb the prompts. However, some lang...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	301,454
2303.02322	Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output Codes	Neural network ensembles have been studied extensively in the context of adversarial robustness and most ensemble-based approaches remain vulnerable to adaptive attacks. In this paper, we investigate the robustness of Error-Correcting Output Codes (ECOC) ensembles through architectural improvements and ensemble diversi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	349,307
1607.08654	Characterizing Complex Networks with Forman-Ricci Curvature and Associated Geometric Flows	We introduce Forman-Ricci curvature and its corresponding flow as characteristics for complex networks attempting to extend the common approach of node-based network analysis by edge-based characteristics. Following a theoretical introduction and mathematical motivation, we apply the proposed network-analytic methods t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	59,182
2405.05905	Truthful Aggregation of LLMs with an Application to Online Advertising	The next frontier of online advertising is revenue generation from LLM-generated content. We consider a setting where advertisers aim to influence the responses of an LLM to align with their interests, while platforms seek to maximize advertiser value and ensure user satisfaction. The challenge is that advertisers' pre...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	453,105
2012.11933	Interpreting Deep Learning Models for Epileptic Seizure Detection on EEG signals	While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient interpretability of neural network models. We have tackled this issue by developing inte...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	212,781
2401.03642	A Content-Based Novelty Measure for Scholarly Publications: A Proof of Concept	Novelty, akin to gene mutation in evolution, opens possibilities for scholarly advancement. Although peer review remains the gold standard for evaluating novelty in scholarly communication and resource allocation, the vast volume of submissions necessitates an automated measure of scholarly novelty. Adopting a perspect...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	420,182
2212.05843	Optimizing ship detection efficiency in SAR images	The detection and prevention of illegal fishing is critical to maintaining a healthy and functional ecosystem. Recent research on ship detection in satellite imagery has focused exclusively on performance improvements, disregarding detection efficiency. However, the speed and compute cost of vessel detection are essent...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	335,914
2311.00787	Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning	Knowing the rate at which particle radiation releases energy in a material, the stopping power, is key to designing nuclear reactors, medical treatments, semiconductor and quantum materials, and many other technologies. While the nuclear contribution to stopping power, i.e., elastic scattering between atoms, is well un...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,772
1603.06812	Con-Patch: When a Patch Meets its Context	Measuring the similarity between patches in images is a fundamental building block in various tasks. Naturally, the patch-size has a major impact on the matching quality, and on the consequent application performance. Under the assumption that our patch database is sufficiently sampled, using large patches (e.g. 21-by-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,551
2203.02557	UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translation	Unpaired image-to-image translation has broad applications in art, design, and scientific simulations. One early breakthrough was CycleGAN that emphasizes one-to-one mappings between two unpaired image domains via generative-adversarial networks (GAN) coupled with the cycle-consistency constraint, while more recent wor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,780
2205.02397	Compressive Ptychography using Deep Image and Generative Priors	Ptychography is a well-established coherent diffraction imaging technique that enables non-invasive imaging of samples at a nanometer scale. It has been extensively used in various areas such as the defense industry or materials science. One major limitation of ptychography is the long data acquisition time due to mech...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	294,923
1906.08320	Scalable and Differentially Private Distributed Aggregation in the Shuffled Model	Federated learning promises to make machine learning feasible on distributed, private datasets by implementing gradient descent using secure aggregation methods. The idea is to compute a global weight update without revealing the contributions of individual users. Current practical protocols for secure aggregation work...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	135,832
2009.06975	Harness the Power of DERs for Secure Communications in Electric Energy Systems	Electric energy systems are undergoing significant changes to improve system reliability and accommodate increasing power demands. The penetration of distributed energy resources (DERs) including roof-top solar panels, energy storage, electric vehicles, etc., enables the on-site generation of economically dispatchable ...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	195,804
1403.1013	Covert Communication Gains from Adversary's Ignorance of Transmission Time	The recent square root law (SRL) for covert communication demonstrates that Alice can reliably transmit $\mathcal{O}(\sqrt{n})$ bits to Bob in $n$ uses of an additive white Gaussian noise (AWGN) channel while keeping ineffective any detector employed by the adversary; conversely, exceeding this limit either results in ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	31,348
2003.01607	Deep Multi-Modal Sets	Many vision-related tasks benefit from reasoning over multiple modalities to leverage complementary views of data in an attempt to learn robust embedding spaces. Most deep learning-based methods rely on a late fusion technique whereby multiple feature types are encoded and concatenated and then a multi layer perceptron...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	166,703
2111.14485	CoNIC: Colon Nuclei Identification and Counting Challenge 2022	Nuclear segmentation, classification and quantification within Haematoxylin & Eosin stained histology images enables the extraction of interpretable cell-based features that can be used in downstream explainable models in computational pathology (CPath). However, automatic recognition of different nuclei is faced with ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	268,615
2103.08993	Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning	This paper describes the results of an informal collaboration launched during the African Master of Machine Intelligence (AMMI) in June 2020. After a series of lectures and labs on speech data collection using mobile applications and on self-supervised representation learning from speech, a small group of students and ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	225,049
2410.02890	Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach	Watermarking has emerged as a crucial method to distinguish AI-generated text from human-created text. In this paper, we present a novel theoretical framework for watermarking Large Language Models (LLMs) that jointly optimizes both the watermarking scheme and the detection process. Our approach focuses on maximizing d...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	494,509
2203.13563	An Intelligent End-to-End Neural Architecture Search Framework for Electricity Forecasting Model Development	Recent years have witnessed exponential growth in developing deep learning (DL) models for time-series electricity forecasting in power systems. However, most of the proposed models are designed based on the designers' inherent knowledge and experience without elaborating on the suitability of the proposed neural archi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	287,681
2405.06780	Deep MMD Gradient Flow without adversarial training	We propose a gradient flow procedure for generative modeling by transporting particles from an initial source distribution to a target distribution, where the gradient field on the particles is given by a noise-adaptive Wasserstein Gradient of the Maximum Mean Discrepancy (MMD). The noise-adaptive MMD is trained on dat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	453,449
1709.00799	Non-rigid image registration using fully convolutional networks with deep self-supervision	We propose a novel non-rigid image registration algorithm that is built upon fully convolutional networks (FCNs) to optimize and learn spatial transformations between pairs of images to be registered. Different from most existing deep learning based image registration methods that learn spatial transformations from tra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	79,973
2304.08369	New Product Development (NPD) through Social Media-based Analysis by Comparing Word2Vec and BERT Word Embeddings	This study introduces novel methods for sentiment and opinion classification of tweets to support the New Product Development (NPD) process. Two popular word embedding techniques, Word2Vec and BERT, were evaluated as inputs for classic Machine Learning and Deep Learning algorithms to identify the best-performing approa...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	358,690
1907.11975	Blocking Bandits	We consider a novel stochastic multi-armed bandit setting, where playing an arm makes it unavailable for a fixed number of time slots thereafter. This models situations where reusing an arm too often is undesirable (e.g. making the same product recommendation repeatedly) or infeasible (e.g. compute job scheduling on ma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,999
2101.01715	Local Memory Attention for Fast Video Semantic Segmentation	We propose a novel neural network module that transforms an existing single-frame semantic segmentation model into a video semantic segmentation pipeline. In contrast to prior works, we strive towards a simple, fast, and general module that can be integrated into virtually any single-frame architecture. Our approach ag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	214,432
2011.14473	Kinetics-Informed Neural Networks	Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes. Here, we utilize feed-forward artificial neural networks as basis functions to solve ordinary differen...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	208,786
1310.3101	Deep Multiple Kernel Learning	Deep learning methods have predominantly been applied to large artificial neural networks. Despite their state-of-the-art performance, these large networks typically do not generalize well to datasets with limited sample sizes. In this paper, we take a different approach by learning multiple layers of kernels. We combi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	27,723
2303.07576	Diffusion Models in NLP: A Survey	Diffusion models have become a powerful family of deep generative models, with record-breaking performance in many applications. This paper first gives an overview and derivation of the basic theory of diffusion models, then reviews the research results of diffusion models in the field of natural language processing, f...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	351,296
2501.16581	DialUp! Modeling the Language Continuum by Adapting Models to Dialects and Dialects to Models	Most of the world's languages and dialects are low-resource, and lack support in mainstream machine translation (MT) models. However, many of them have a closely-related high-resource language (HRL) neighbor, and differ in linguistically regular ways from it. This underscores the importance of model robustness to diale...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	528,014
1602.02867	Value Iteration Networks	We introduce the value iteration network (VIN): a fully differentiable neural network with a `planning module' embedded within. VINs can learn to plan, and are suitable for predicting outcomes that involve planning-based reasoning, such as policies for reinforcement learning. Key to our approach is a novel differentiab...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	51,924
2106.01105	Use of Formal Ethical Reviews in NLP Literature: Historical Trends and Current Practices	Ethical aspects of research in language technologies have received much attention recently. It is a standard practice to get a study involving human subjects reviewed and approved by a professional ethics committee/board of the institution. How commonly do we see mention of ethical approvals in NLP research? What types...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	238,389
2309.14372	Human Transcription Quality Improvement	High quality transcription data is crucial for training automatic speech recognition (ASR) systems. However, the existing industry-level data collection pipelines are expensive to researchers, while the quality of crowdsourced transcription is low. In this paper, we propose a reliable method to collect speech transcrip...	false	false	true	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	394,583
1207.6199	Achieving Approximate Soft Clustering in Data Streams	In recent years, data streaming has gained prominence due to advances in technologies that enable many applications to generate continuous flows of data. This increases the need to develop algorithms that are able to efficiently process data streams. Additionally, real-time requirements and evolving nature of data stre...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	17,772
1912.03015	Learning to Correspond Dynamical Systems	Many dynamical systems exhibit similar structure, as often captured by hand-designed simplified models that can be used for analysis and control. We develop a method for learning to correspond pairs of dynamical systems via a learned latent dynamical system. Given trajectory data from two dynamical systems, we learn a ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	156,498
2107.03002	WaspL: Design of a Reconfigurable Logistic Robot for Hospital Settings	Healthcare poses diverse logistic requirements, which resulted in the deployment of several distinctly designed robots within a hospital setting. Each robot comes with its overheads in the form of, namely, none/limited scaling, dedicated charging stations, programming interface, closed architecture, training requiremen...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	245,014
2212.04443	A Distributed Block Chebyshev-Davidson Algorithm for Parallel Spectral Clustering	We develop a distributed Block Chebyshev-Davidson algorithm to solve large-scale leading eigenvalue problems for spectral analysis in spectral clustering. First, the efficiency of the Chebyshev-Davidson algorithm relies on the prior knowledge of the eigenvalue spectrum, which could be expensive to estimate. This issue ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	335,441
1409.7433	Throughput Analysis for Wireless Networks with Full-Duplex Radios	This paper investigates the throughput for wireless network with full-duplex radios using stochastic geometry. Full-duplex (FD) radios can exchange data simultaneously with each other. On the other hand, the downside of FD transmission is that it will inevitably cause extra interference to the network compared to half-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	36,321
2409.00552	Digit Recognition using Multimodal Spiking Neural Networks	Spiking neural networks (SNNs) are the third generation of neural networks that are biologically inspired to process data in a fashion that emulates the exchange of signals in the brain. Within the Computer Vision community SNNs have garnered significant attention due in large part to the availability of event-based se...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	484,965
2104.13591	Development of global optimal coverage control using multiple aerial robots	Coverage control has been widely used for constructing mobile sensor network such as for environmental monitoring, and one of the most commonly used methods is the Lloyd algorithm based on Voronoi partitions. However, when this method is used, the result sometimes converges to a local optimum. To overcome this problem,...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	232,549
2306.15886	Sequential Attention Source Identification Based on Feature Representation	Snapshot observation based source localization has been widely studied due to its accessibility and low cost. However, the interaction of users in existing methods does not be addressed in time-varying infection scenarios. So these methods have a decreased accuracy in heterogeneous interaction scenarios. To solve this ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	376,188
2412.16971	Part-Of-Speech Sensitivity of Routers in Mixture of Experts Models	This study investigates the behavior of model-integrated routers in Mixture of Experts (MoE) models, focusing on how tokens are routed based on their linguistic features, specifically Part-of-Speech (POS) tags. The goal is to explore across different MoE architectures whether experts specialize in processing tokens wit...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	519,777
2401.00876	Balanced Graph Structure Information for Brain Disease Detection	Analyzing connections between brain regions of interest (ROI) is vital to detect neurological disorders such as autism or schizophrenia. Recent advancements employ graph neural networks (GNNs) to utilize graph structures in brains, improving detection performances. Current methods use correlation measures between ROI's...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	419,139
2408.01765	Joint Model Pruning and Resource Allocation for Wireless Time-triggered Federated Learning	Time-triggered federated learning, in contrast to conventional event-based federated learning, organizes users into tiers based on fixed time intervals. However, this network still faces challenges due to a growing number of devices and limited wireless bandwidth, increasing issues like stragglers and communication ove...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	478,366
2501.03286	Inverse Design of Optimal Stern Shape with Convolutional Neural Network-based Pressure Distribution	Hull form designing is an iterative process wherein the performance of the hull form needs to be checked via computational fluid dynamics calculations or model experiments. The stern shape has to undergo a process wherein the hull form variations from the pressure distribution analysis results are repeated until the re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	522,828
2502.01691	Agent-Based Uncertainty Awareness Improves Automated Radiology Report Labeling with an Open-Source Large Language Model	Reliable extraction of structured data from radiology reports using Large Language Models (LLMs) remains challenging, especially for complex, non-English texts like Hebrew. This study introduces an agent-based uncertainty-aware approach to improve the trustworthiness of LLM predictions in medical applications. We analy...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	529,992
2410.13720	Movie Gen: A Cast of Media Foundation Models	We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and generation of personalized videos based on a user's image. Our models set a new sta...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	499,653
2406.06839	EAVE: Efficient Product Attribute Value Extraction via Lightweight Sparse-layer Interaction	Product attribute value extraction involves identifying the specific values associated with various attributes from a product profile. While existing methods often prioritize the development of effective models to improve extraction performance, there has been limited emphasis on extraction efficiency. However, in real...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	462,785
1912.09357	LinCode -- computer classification of linear codes	We present an algorithm for the classification of linear codes over finite fields, based on lattice point enumeration. We validate a correct implementation of our algorithm with known classification results from the literature, which we partially extend to larger ranges of parameters.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	158,056
2407.08347	GUI-based Pedicle Screw Planning on Fluoroscopic Images Utilizing Vertebral Segmentation	The proposed work establishes a novel Graphical User Interface (GUI) framework, primarily designed for intraoperative pedicle screw planning. Current planning workflow in Image Guided Surgeries primarily relies on pre-operative CT planning. Intraoperative CT planning can be time-consuming and expensive and thus is not ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,132
2202.10753	Convolutional Neural Network Modelling for MODIS Land Surface Temperature Super-Resolution	Nowadays, thermal infrared satellite remote sensors enable to extract very interesting information at large scale, in particular Land Surface Temperature (LST). However such data are limited in spatial and/or temporal resolutions which prevents from an analysis at fine scales. For example, MODIS satellite provides dail...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	281,652
2401.17109	Evaluation in Neural Style Transfer: A Review	The field of Neural Style Transfer (NST) has witnessed remarkable progress in the past few years, with approaches being able to synthesize artistic and photorealistic images and videos of exceptional quality. To evaluate such results, a diverse landscape of evaluation methods and metrics is used, including authors' opi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	425,106
1806.09573	Learning Single-Image Depth from Videos using Quality Assessment Networks	Depth estimation from a single image in the wild remains a challenging problem. One main obstacle is the lack of high-quality training data for images in the wild. In this paper we propose a method to automatically generate such data through Structure-from-Motion (SfM) on Internet videos. The core of this method is a Q...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	101,376
2209.02424	Cross apprenticeship learning framework: Properties and solution approaches	Apprenticeship learning is a framework in which an agent learns a policy to perform a given task in an environment using example trajectories provided by an expert. In the real world, one might have access to expert trajectories in different environments where the system dynamics is different while the learning task is...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	316,205
2402.11495	URLBERT:A Contrastive and Adversarial Pre-trained Model for URL Classification	URLs play a crucial role in understanding and categorizing web content, particularly in tasks related to security control and online recommendations. While pre-trained models are currently dominating various fields, the domain of URL analysis still lacks specialized pre-trained models. To address this gap, this paper i...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	430,424
2004.11405	Transliteration of Judeo-Arabic Texts into Arabic Script Using Recurrent Neural Networks	We trained a model to automatically transliterate Judeo-Arabic texts into Arabic script, enabling Arabic readers to access those writings. We employ a recurrent neural network (RNN), combined with the connectionist temporal classification (CTC) loss to deal with unequal input/output lengths. This obligates adjustments ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	173,895
2208.04980	An NLP-Assisted Bayesian Time Series Analysis for Prevalence of Twitter Cyberbullying During the COVID-19 Pandemic	COVID-19 has brought about many changes in social dynamics. Stay-at-home orders and disruptions in school teaching can influence bullying behavior in-person and online, both of which leading to negative outcomes in victims. To study cyberbullying specifically, 1 million tweets containing keywords associated with abuse ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	312,282
2409.08673	Acoustic identification of individual animals with hierarchical contrastive learning	Acoustic identification of individual animals (AIID) is closely related to audio-based species classification but requires a finer level of detail to distinguish between individual animals within the same species. In this work, we frame AIID as a hierarchical multi-label classification task and propose the use of hiera...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	488,011
cs/0611112	Channel Coding: The Road to Channel Capacity	Starting from Shannon's celebrated 1948 channel coding theorem, we trace the evolution of channel coding from Hamming codes to capacity-approaching codes. We focus on the contributions that have led to the most significant improvements in performance vs. complexity for practical applications, particularly on the additi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,899
2405.19761	Revisiting CNNs for Trajectory Similarity Learning	Similarity search is a fundamental but expensive operator in querying trajectory data, due to its quadratic complexity of distance computation. To mitigate the computational burden for long trajectories, neural networks have been widely employed for similarity learning and each trajectory is encoded as a high-dimension...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	459,054
1410.0610	Is Twitter a Public Sphere for Online Conflicts? A Cross-Ideological and Cross-Hierarchical Look	The rise in popularity of Twitter has led to a debate on its impact on public opinions. The optimists foresee an increase in online participation and democratization due to social media's personal and interactive nature. Cyber-pessimists, on the other hand, explain how social media can lead to selective exposure and ca...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	36,487
2203.09663	An Improved Subject-Independent Stress Detection Model Applied to Consumer-grade Wearable Devices	Stress is a complex issue with wide-ranging physical and psychological impacts on human daily performance. Specifically, acute stress detection is becoming a valuable application in contextual human understanding. Two common approaches to training a stress detection model are subject-dependent and subject-independent t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	286,233
1311.6107	Off-policy reinforcement learning for $ H_\infty $ control design	The $H_\infty$ control design problem is considered for nonlinear systems with unknown internal system model. It is known that the nonlinear $ H_\infty $ control problem can be transformed into solving the so-called Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that is genera...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	28,625
2404.14281	Fast and Robust Normal Estimation for Sparse LiDAR Scans	Light Detection and Ranging (LiDAR) technology has proven to be an important part of many robotics systems. Surface normals estimated from LiDAR data are commonly used for a variety of tasks in such systems. As most of the today's mechanical LiDAR sensors produce sparse data, estimating normals from a single scan in a ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	448,625
1903.10735	Interoperability and machine-to-machine translation model with mappings to machine learning tasks	Modern large-scale automation systems integrate thousands to hundreds of thousands of physical sensors and actuators. Demands for more flexible reconfiguration of production systems and optimization across different information models, standards and legacy systems challenge current system interoperability concepts. Aut...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	125,354
1909.10851	Oldie is Goodie: Effective User Retention by In-game Promotion Event Analysis	For sustainable growth and profitability, online game companies are constantly carrying out various events to attract new game users, to maximize return users, and to minimize churn users in online games. Because minimizing churn users is the most cost-effective method, many pieces of research are being conducted on wa...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	146,649
2410.07701	Autonomous Driving in Unstructured Environments: How Far Have We Come?	Research on autonomous driving in unstructured outdoor environments is less advanced than in structured urban settings due to challenges like environmental diversities and scene complexity. These environments-such as rural areas and rugged terrains-pose unique obstacles that are not common in structured urban areas. De...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	496,758
1510.08865	Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation	We study two mixed robust/average-case submodular partitioning problems that we collectively call Submodular Partitioning. These problems generalize both purely robust instances of the problem (namely max-min submodular fair allocation (SFA) and min-max submodular load balancing (SLB) and also generalize average-case i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	48,320
2410.15780	An Efficient System for Automatic Map Storytelling -- A Case Study on Historical Maps	Historical maps provide valuable information and knowledge about the past. However, as they often feature non-standard projections, hand-drawn styles, and artistic elements, it is challenging for non-experts to identify and interpret them. While existing image captioning methods have achieved remarkable success on natu...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	500,726
2410.16540	A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration	Few-shot Chain-of-Thought (CoT) prompting has demonstrated strong performance in improving the reasoning capabilities of large language models (LLMs). While theoretical investigations have been conducted to understand CoT, the underlying transformer used in these studies isolates the CoT reasoning process into separate...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	501,076
1902.06866	A Markov Process Approach to Ensemble Control of Smart Buildings	This paper describes a step-by-step procedure that converts a physical model of a building into a Markov Process that characterizes energy consumption of this and other similar buildings. Relative to existing thermo-physics-based building models, the proposed procedure reduces model complexity and depends on fewer para...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	121,863
2310.04483	Reward Dropout Improves Control: Bi-objective Perspective on Reinforced LM	We study the theoretical aspects of Reinforced Language Models (RLMs) from a bi-objective optimization perspective. Specifically, we consider the RLMs as a Pareto optimization problem that maximizes the two conflicting objectives, i.e., reward objective and likelihood objectives, simultaneously. Our main contribution c...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	397,686
2501.12319	Metric for Evaluating Performance of Reference-Free Demorphing Methods	A facial morph is an image created by combining two (or more) face images pertaining to two (or more) distinct identities. Reference-free face demorphing inverts the process and tries to recover the face images constituting a facial morph without using any other information. However, there is no consensus on the evalua...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	526,257
2309.03713	Word segmentation granularity in Korean	This paper describes word {segmentation} granularity in Korean language processing. From a word separated by blank space, which is termed an eojeol, to a sequence of morphemes in Korean, there are multiple possible levels of word segmentation granularity in Korean. For specific language processing and corpus annotation...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	390,479
2205.01749	Mixed-effects transformers for hierarchical adaptation	Language use differs dramatically from context to context. To some degree, modern language models like GPT-3 are able to account for such variance by conditioning on a string of previous input text, or prompt. Yet prompting is ineffective when contexts are sparse, out-of-sample, or extra-textual; for instance, accounti...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	294,700
1501.01242	Efficient Online Relative Comparison Kernel Learning	Learning a kernel matrix from relative comparison human feedback is an important problem with applications in collaborative filtering, object retrieval, and search. For learning a kernel over a large number of objects, existing methods face significant scalability issues inhibiting the application of these methods to s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	39,062
1109.2355	Decision-Theoretic Planning with non-Markovian Rewards	A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decision-theoretic planning, where many desirable behaviours are more naturally expressed as properties of execution sequences rather than as properties of st...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	12,115
1708.05490	Standard Bases for Linear Codes over Prime Fields	It is known that a linear code can be represented by a binomial ideal. In this paper, we give standard bases for the ideals in a localization of the multivariate polynomial ring in the case of linear codes over prime fields.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	79,141
2410.12622	From Measurement Instruments to Data: Leveraging Theory-Driven Synthetic Training Data for Classifying Social Constructs	Computational text classification is a challenging task, especially for multi-dimensional social constructs. Recently, there has been increasing discussion that synthetic training data could enhance classification by offering examples of how these constructs are represented in texts. In this paper, we systematically ex...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	499,115
2502.09298	Convex Is Back: Solving Belief MDPs With Convexity-Informed Deep Reinforcement Learning	We present a novel method for Deep Reinforcement Learning (DRL), incorporating the convex property of the value function over the belief space in Partially Observable Markov Decision Processes (POMDPs). We introduce hard- and soft-enforced convexity as two different approaches, and compare their performance against sta...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	533,398
2211.09302	You Only Label Once: 3D Box Adaptation from Point Cloud to Image via Semi-Supervised Learning	The image-based 3D object detection task expects that the predicted 3D bounding box has a ``tightness'' projection (also referred to as cuboid), which fits the object contour well on the image while still keeping the geometric attribute on the 3D space, e.g., physical dimension, pairwise orthogonal, etc. These requirem...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	330,929
1005.4769	A Network Coding Approach to Loss Tomography	Network tomography aims at inferring internal network characteristics based on measurements at the edge of the network. In loss tomography, in particular, the characteristic of interest is the loss rate of individual links and multicast and/or unicast end-to-end probes are typically used. Independently, recent advances...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	6,570
2209.09813	Register Variation Remains Stable Across 60 Languages	This paper measures the stability of cross-linguistic register variation. A register is a variety of a language that is associated with extra-linguistic context. The relationship between a register and its context is functional: the linguistic features that make up a register are motivated by the needs and constraints ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	318,647
1909.10171	Syntax-Aware Aspect-Level Sentiment Classification with Proximity-Weighted Convolution Network	It has been widely accepted that Long Short-Term Memory (LSTM) network, coupled with attention mechanism and memory module, is useful for aspect-level sentiment classification. However, existing approaches largely rely on the modelling of semantic relatedness of an aspect with its context words, while to some extent ig...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	146,470
2009.09919	Improving Graph Property Prediction with Generalized Readout Functions	Graph property prediction is drawing increasing attention in the recent years due to the fact that graphs are one of the most general data structures since they can contain an arbitrary number of nodes and connections between them, and it is the backbone for many different tasks like classification and regression on su...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	196,733
2107.04724	Longitudinal Correlation Analysis for Decoding Multi-Modal Brain Development	Starting from childhood, the human brain restructures and rewires throughout life. Characterizing such complex brain development requires effective analysis of longitudinal and multi-modal neuroimaging data. Here, we propose such an analysis approach named Longitudinal Correlation Analysis (LCA). LCA couples the data o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	245,546
1905.11034	Unsupervised Learning of Anomaly Detection from Contaminated Image Data using Simultaneous Encoder Training	Unsupervised learning of anomaly detection in high-dimensional data, such as images, is a challenging problem recently subject to intense research. Through careful modelling of the data distribution of normal samples, it is possible to detect deviant samples, so called anomalies. Generative Adversarial Networks (GANs) ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	132,311
2107.14572	Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-modal Pretraining	Nowadays, customer's demands for E-commerce are more diversified, which introduces more complications to the product retrieval industry. Previous methods are either subject to single-modal input or perform supervised image-level product retrieval, thus fail to accommodate real-life scenarios where enormous weakly annot...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	248,500
2205.06118	Findings of the Shared Task on Offensive Span Identification from Code-Mixed Tamil-English Comments	Offensive content moderation is vital in social media platforms to support healthy online discussions. However, their prevalence in codemixed Dravidian languages is limited to classifying whole comments without identifying part of it contributing to offensiveness. Such limitation is primarily due to the lack of annotat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	296,141
2001.06935	75,000,000,000 Streaming Inserts/Second Using Hierarchical Hypersparse GraphBLAS Matrices	The SuiteSparse GraphBLAS C-library implements high performance hypersparse matrices with bindings to a variety of languages (Python, Julia, and Matlab/Octave). GraphBLAS provides a lightweight in-memory database implementation of hypersparse matrices that are ideal for analyzing many types of network data, while provi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	true	160,928
2001.01376	Coding for Sequence Reconstruction for Single Edits	The sequence reconstruction problem, introduced by Levenshtein in 2001, considers a communication scenario where the sender transmits a codeword from some codebook and the receiver obtains multiple noisy reads of the codeword. The common setup assumes the codebook to be the entire space and the problem is to determine ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	159,476
2212.13819	Don't do it: Safer Reinforcement Learning With Rule-based Guidance	During training, reinforcement learning systems interact with the world without considering the safety of their actions. When deployed into the real world, such systems can be dangerous and cause harm to their surroundings. Often, dangerous situations can be mitigated by defining a set of rules that the system should n...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	338,404
2101.11452	Robust Instability Radius for Multi-agent Dynamical Systems with Cyclic Structure	This paper is concerned with robust instability analysis for linear multi-agent dynamical systems with cyclic structure. This relates to interesting and important periodic oscillation phenomena in biology and neuronal science, since the nonlinear phenomena often occur when the linearized model around an equilibrium poi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	217,285
2309.13596	Advancements in 3D Lane Detection Using LiDAR Point Clouds: From Data Collection to Model Development	Advanced Driver-Assistance Systems (ADAS) have successfully integrated learning-based techniques into vehicle perception and decision-making. However, their application in 3D lane detection for effective driving environment perception is hindered by the lack of comprehensive LiDAR datasets. The sparse nature of LiDAR p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,274
2003.13088	Generative Partial Multi-View Clustering	Nowadays, with the rapid development of data collection sources and feature extraction methods, multi-view data are getting easy to obtain and have received increasing research attention in recent years, among which, multi-view clustering (MVC) forms a mainstream research direction and is widely used in data analysis. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	170,102
2407.12838	Historical Ink: 19th Century Latin American Spanish Newspaper Corpus with LLM OCR Correction	This paper presents two significant contributions: First, it introduces a novel dataset of 19th-century Latin American newspaper texts, addressing a critical gap in specialized corpora for historical and linguistic analysis in this region. Second, it develops a flexible framework that utilizes a Large Language Model fo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	474,112
1912.11160	RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback	Recent research has shown the advantages of using autoencoders based on deep neural networks for collaborative filtering. In particular, the recently proposed Mult-VAE model, which used the multinomial likelihood variational autoencoders, has shown excellent results for top-N recommendations. In this work, we propose t...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	158,492
2303.12558	Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees	Although deep reinforcement learning (DRL) has many success stories, the large-scale deployment of policies learned through these advanced techniques in safety-critical scenarios is hindered by their lack of formal guarantees. Variational Markov Decision Processes (VAE-MDPs) are discrete latent space models that provid...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	353,299
2412.13852	RadField3D: A Data Generator and Data Format for Deep Learning in Radiation-Protection Dosimetry for Medical Applications	In this research work, we present our open-source Geant4-based Monte-Carlo simulation application, called RadField3D, for generating threedimensional radiation field datasets for dosimetry. Accompanying, we introduce a fast, machine-interpretable data format with a Python API for easy integration into neural network re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	518,477
1407.4477	Convex separable problems with linear and box constraints in signal processing and communications	In this work, we focus on separable convex optimization problems with box constraints and a set of triangular linear constraints. The solution is given in closed-form as a function of some Lagrange multipliers that can be computed through an iterative procedure in a finite number of steps. Graphical interpretations are...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,707

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