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
1906.09322	A Syllable-Structured, Contextually-Based Conditionally Generation of Chinese Lyrics	This paper presents a novel, syllable-structured Chinese lyrics generation model given a piece of original melody. Most previously reported lyrics generation models fail to include the relationship between lyrics and melody. In this work, we propose to interpret lyrics-melody alignments as syllable structural informati...	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	136,116
cs/0512048	Spatial Precoder Design for Space-Time Coded MIMO Systems: Based on Fixed Parameters of MIMO Channels	In this paper, we introduce the novel use of linear spatial precoding based on fixed and known parameters of multiple-input multiple-output (MIMO) channels to improve the performance of space-time coded MIMO systems. We derive linear spatial precoding schemes for both coherent (channel is known at the receiver) and non...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,142
1112.1770	Polar codes for the m-user multiple access channels	Polar codes are constructed for m-user multiple access channels (MAC) whose input alphabet size is a prime number. The block error probability under successive cancelation decoding decays exponentially with the square root of the block length. Although the sum capacity is achieved by this coding scheme, some points in ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	13,369
2405.07043	Optimal Multilayered Motion Planning for Multiple Differential Drive Mobile Robots with Hierarchical Prioritization (OM-MP)	We present a novel framework for addressing the challenges of multi-Agent planning and formation control within intricate and dynamic environments. This framework transforms the Multi-Agent Path Finding (MAPF) problem into a Multi-Agent Trajectory Planning (MATP) problem. Unlike traditional MAPF solutions, our multilay...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	453,561
2412.12617	PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detection	Point cloud anomaly detection under the anomaly-free setting poses significant challenges as it requires accurately capturing the features of 3D normal data to identify deviations indicative of anomalies. Current efforts focus on devising reconstruction tasks, such as acquiring normal data representations by restoring ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	517,948
2211.13297	Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data	Missing data are ubiquitous in real world applications and, if not adequately handled, may lead to the loss of information and biased findings in downstream analysis. Particularly, high-dimensional incomplete data with a moderate sample size, such as analysis of multi-omics data, present daunting challenges. Imputation...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	332,422
2012.03044	Self-Supervised Visual Representation Learning from Hierarchical Grouping	We create a framework for bootstrapping visual representation learning from a primitive visual grouping capability. We operationalize grouping via a contour detector that partitions an image into regions, followed by merging of those regions into a tree hierarchy. A small supervised dataset suffices for training this g...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	209,965
1806.00637	Quality-Assured Synchronized Task Assignment in Crowdsourcing	With the rapid development of crowdsourcing platforms that aggregate the intelligence of Internet workers, crowdsourcing has been widely utilized to address problems that require human cognitive abilities. Considering great dynamics of worker arrival and departure, it is of vital importance to design a task assignment ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	99,354
2006.04964	InFocus: A spatial coding technique to mitigate misfocus in near field LoS beamforming	Phased arrays, commonly used in IEEE 802.11ad and 5G radios, are capable of focusing radio frequency signals in a specific direction or a spatial region. Beamforming achieves such directional or spatial concentration of signals and enables phased array-based radios to achieve high data rates. Designing beams for millim...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	180,875
2401.03240	Interpreting Adaptive Gradient Methods by Parameter Scaling for Learning-Rate-Free Optimization	We address the challenge of estimating the learning rate for adaptive gradient methods used in training deep neural networks. While several learning-rate-free approaches have been proposed, they are typically tailored for steepest descent. However, although steepest descent methods offer an intuitive approach to findin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	420,033
1705.05640	WebVision Challenge: Visual Learning and Understanding With Web Data	We present the 2017 WebVision Challenge, a public image recognition challenge designed for deep learning based on web images without instance-level human annotation. Following the spirit of previous vision challenges, such as ILSVRC, Places2 and PASCAL VOC, which have played critical roles in the development of compute...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,528
1708.07493	Decentralized Coded Caching Without File Splitting	Coded caching is an effective technique to reduce the redundant traffic in wireless networks. The existing coded caching schemes require the splitting of files into a possibly large number of subfiles, i.e., they perform coded subfile caching. Keeping the files intact during the caching process would actually be appeal...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	79,486
2404.02570	MaiNLP at SemEval-2024 Task 1: Analyzing Source Language Selection in Cross-Lingual Textual Relatedness	This paper presents our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness (STR), on Track C: Cross-lingual. The task aims to detect semantic relatedness of two sentences in a given target language without access to direct supervision (i.e. zero-shot cross-lingual transfer). To this end, we focu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,915
2405.00843	Can a Hallucinating Model help in Reducing Human "Hallucination"?	The prevalence of unwarranted beliefs, spanning pseudoscience, logical fallacies, and conspiracy theories, presents substantial societal hurdles and the risk of disseminating misinformation. Utilizing established psychometric assessments, this study explores the capabilities of large language models (LLMs) vis-a-vis th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	451,102
1908.02005	RSATree: Distribution-Aware Data Representation of Large-Scale Tabular Datasets for Flexible Visual Query	Analysts commonly investigate the data distributions derived from statistical aggregations of data that are represented by charts, such as histograms and binned scatterplots, to visualize and analyze a large-scale dataset. Aggregate queries are implicitly executed through such a process. Datasets are constantly extreme...	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	140,909
2309.12769	Maximum-order complexity and $2$-adic complexity	The $2$-adic complexity has been well-analyzed in the periodic case. However, we are not aware of any theoretical results on the $N$th $2$-adic complexity of any promising candidate for a pseudorandom sequence of finite length $N$ or results on a part of the period of length $N$ of a periodic sequence, respectively. He...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	393,931
1608.06417	Geometric Interpretation of Theoretical Bounds for RSS-based Source Localization with Uncertain Anchor Positions	The Received Signal Strength based source localization can encounter severe problems originating from uncertain information about the anchor positions in practice. The anchor positions, although commonly assumed to be precisely known prior to the source localization, are usually obtained using previous estimation algor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	60,112
2107.02827	Plot2Spectra: an Automatic Spectra Extraction Tool	Different types of spectroscopies, such as X-ray absorption near edge structure (XANES) and Raman spectroscopy, play a very important role in analyzing the characteristics of different materials. In scientific literature, XANES/Raman data are usually plotted in line graphs which is a visually appropriate way to represe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	244,951
2111.11030	Reinforcement Learning for Few-Shot Text Generation Adaptation	Controlling the generative model to adapt a new domain with limited samples is a difficult challenge and it is receiving increasing attention. Recently, methods based on meta-learning have shown promising results for few-shot domain adaptation. However, meta-learning-based methods usually suffer from the problem of ove...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	267,527
2212.06864	Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability	Spatio-temporal machine learning is critically needed for a variety of societal applications, such as agricultural monitoring, hydrological forecast, and traffic management. These applications greatly rely on regional features that characterize spatial and temporal differences. However, spatio-temporal data often exhib...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	336,233
1808.04245	Active Learning for Regression Using Greedy Sampling	Regression problems are pervasive in real-world applications. Generally a substantial amount of labeled samples are needed to build a regression model with good generalization ability. However, many times it is relatively easy to collect a large number of unlabeled samples, but time-consuming or expensive to label them...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	105,094
2110.08164	Accurate Fine-grained Layout Analysis for the Historical Tibetan Document Based on the Instance Segmentation	Accurate layout analysis without subsequent text-line segmentation remains an ongoing challenge, especially when facing the Kangyur, a kind of historical Tibetan document featuring considerable touching components and mottled background. Aiming at identifying different regions in document images, layout analysis is ind...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	261,272
2310.16665	Robust Source-Free Domain Adaptation for Fundus Image Segmentation	Unsupervised Domain Adaptation (UDA) is a learning technique that transfers knowledge learned in the source domain from labelled training data to the target domain with only unlabelled data. It is of significant importance to medical image segmentation because of the usual lack of labelled training data. Although exten...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	402,823
2108.02704	Rotaflip: A New CNN Layer for Regularization and Rotational Invariance in Medical Images	Regularization in convolutional neural networks (CNNs) is usually addressed with dropout layers. However, dropout is sometimes detrimental in the convolutional part of a CNN as it simply sets to zero a percentage of pixels in the feature maps, adding unrepresentative examples during training. Here, we propose a CNN lay...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	249,416
1407.5212	Context Aware Dynamic Traffic Signal Optimization	Conventional urban traffic control systems have been based on historical traffic data. Later advancements made use of detectors, which enabled the gathering of real time traffic data, in order to reorganize and calibrate traffic signalization programs. Further evolvement provided the ability to forecast traffic conditi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	34,758
1304.3405	Do Social Explanations Work? Studying and Modeling the Effects of Social Explanations in Recommender Systems	Recommender systems associated with social networks often use social explanations (e.g. "X, Y and 2 friends like this") to support the recommendations. We present a study of the effects of these social explanations in a music recommendation context. We start with an experiment with 237 users, in which we show explanati...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	23,855
2006.05656	Why Attentions May Not Be Interpretable?	Attention-based methods have played important roles in model interpretations, where the calculated attention weights are expected to highlight the critical parts of inputs~(e.g., keywords in sentences). However, recent research found that attention-as-importance interpretations often do not work as we expected. For exa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,155
2312.00627	Rethinking the Domain Gap in Near-infrared Face Recognition	Heterogeneous face recognition (HFR) involves the intricate task of matching face images across the visual domains of visible (VIS) and near-infrared (NIR). While much of the existing literature on HFR identifies the domain gap as a primary challenge and directs efforts towards bridging it at either the input or featur...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,114
1811.03478	Multi-view Laplacian Eigenmaps Based on Bag-of-Neighbors For RGBD Human Emotion Recognition	Human emotion recognition is an important direction in the field of biometric and information forensics. However, most existing human emotion research are based on the single RGB view. In this paper, we introduce a RGBD video-emotion dataset and a RGBD face-emotion dataset for research. To our best knowledge, this may ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	112,848
2405.00293	MoPEFT: A Mixture-of-PEFTs for the Segment Anything Model	The emergence of foundation models, such as the Segment Anything Model (SAM), has sparked interest in Parameter-Efficient Fine-Tuning (PEFT) methods that tailor these large models to application domains outside their training data. However, different PEFT techniques modify the representation of a model differently, mak...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,865
2404.08778	Towards Sim-to-Real Industrial Parts Classification with Synthetic Dataset	This paper is about effectively utilizing synthetic data for training deep neural networks for industrial parts classification, in particular, by taking into account the domain gap against real-world images. To this end, we introduce a synthetic dataset that may serve as a preliminary testbed for the Sim-to-Real challe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	446,395
2309.11911	InstructERC: Reforming Emotion Recognition in Conversation with Multi-task Retrieval-Augmented Large Language Models	The field of emotion recognition of conversation (ERC) has been focusing on separating sentence feature encoding and context modeling, lacking exploration in generative paradigms based on unified designs. In this study, we propose a novel approach, InstructERC, to reformulate the ERC task from a discriminative framewor...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	393,588
2403.17264	EXPLORA: A teacher-apprentice methodology for eliciting natural child-computer interactions	Investigating child-computer interactions within their contexts is vital for designing technology that caters to children's needs. However, determining what aspects of context are relevant for designing child-centric technology remains a challenge. We introduce EXPLORA, a multimodal, multistage online methodology compr...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	441,385
1712.10164	Polyp detection inside the capsule endoscopy: an approach for power consumption reduction	Capsule endoscopy is a novel and non-invasive method for diagnosis, which assists gastroenterologists to monitor the digestive track. Although this new technology has many advantages over the conventional endoscopy, there are weaknesses that limits the usage of this technology. Some weaknesses are due to using small-si...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	87,464
1810.01586	Machine learning for accelerating effective property prediction for poroelasticity problem in stochastic media	In this paper, we consider a numerical homogenization of the poroelasticity problem with stochastic properties. The proposed method based on the construction of the deep neural network (DNN) for fast calculation of the effective properties for a coarse grid approximation of the problem. We train neural networks on the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,429
2501.15280	Who's Driving? Game Theoretic Path Risk of AGI Development	Who controls the development of Artificial General Intelligence (AGI) might matter less than how we handle the fight for control itself. We formalize this "steering wheel problem" as humanity's greatest near-term existential risk may stem not from misaligned AGI, but from the dynamics of competing to develop it. Just a...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	true	527,483
1011.3754	Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey	This paper provides a comprehensive review of the domain of physical layer security in multiuser wireless networks. The essential premise of physical-layer security is to enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers without relying on higher-layer enc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,255
2312.11462	Cascade Speculative Drafting for Even Faster LLM Inference	Introduced to enhance the efficiency of large language model (LLM) inference, speculative decoding operates by having a smaller model generate a draft. A larger target model then reviews this draft to align with its output, and any acceptance by the target model results in a reduction of the number of the target model ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	416,576
2006.16132	Human Activity Recognition based on Dynamic Spatio-Temporal Relations	Human activity, which usually consists of several actions, generally covers interactions among persons and or objects. In particular, human actions involve certain spatial and temporal relationships, are the components of more complicated activity, and evolve dynamically over time. Therefore, the description of a singl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	184,721
2408.01877	Improving Zero-Shot ObjectNav with Generative Communication	We propose a new method for improving zero-shot ObjectNav that aims to utilize potentially available environmental percepts for navigational assistance. Our approach takes into account that the ground agent may have limited and sometimes obstructed view. Our formulation encourages Generative Communication (GC) between ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	478,403
2412.10515	Active Semantic Mapping with Mobile Manipulator in Horticultural Environments	Semantic maps are fundamental for robotics tasks such as navigation and manipulation. They also enable yield prediction and phenotyping in agricultural settings. In this paper, we introduce an efficient and scalable approach for active semantic mapping in horticultural environments, employing a mobile robot manipulator...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	516,973
1908.02884	BEACHES: Beamspace Channel Estimation for Multi-Antenna mmWave Systems and Beyond	Massive multi-antenna millimeter wave (mmWave) and terahertz wireless systems promise high-bandwidth communication to multiple user equipments in the same time-frequency resource. The high path loss of wave propagation at such frequencies and the fine-grained nature of beamforming with massive antenna arrays necessitat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	141,110
1306.4193	Gravity Effects on Information Filtering and Network Evolving	In this paper, based on the gravity principle of classical physics, we propose a tunable gravity-based model, which considers tag usage pattern to weigh both the mass and distance of network nodes. We then apply this model in solving the problems of information filtering and network evolving. Experimental results on tw...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	25,294
1907.01326	A Semantic Approach for User-Brand Targeting in On-Line Social Networks	We propose a general framework for the recommendation of possible customers (users) to advertisers (e.g., brands) based on the comparison between On-line Social Network profiles. In particular, we represent both user and brand profiles as trees where nodes correspond to categories and sub-categories in the associated O...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	137,293
2008.11757	Deep Learning for Constrained Utility Maximisation	This paper proposes two algorithms for solving stochastic control problems with deep learning, with a focus on the utility maximisation problem. The first algorithm solves Markovian problems via the Hamilton Jacobi Bellman (HJB) equation. We solve this highly nonlinear partial differential equation (PDE) with a second ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,365
1902.09159	A Survey of Crowdsourcing in Medical Image Analysis	Rapid advances in image processing capabilities have been seen across many domains, fostered by the application of machine learning algorithms to "big-data". However, within the realm of medical image analysis, advances have been curtailed, in part, due to the limited availability of large-scale, well-annotated dataset...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	122,359
2209.09742	Yet Another Format of Universal Dependencies for Korean	In this study, we propose a morpheme-based scheme for Korean dependency parsing and adopt the proposed scheme to Universal Dependencies. We present the linguistic rationale that illustrates the motivation and the necessity of adopting the morpheme-based format, and develop scripts that convert between the original form...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	318,629
2405.16519	Fourier Sliced-Wasserstein Embedding for Multisets and Measures	We present the $\textit{Fourier Sliced Wasserstein (FSW) embedding}\unicode{x2014}$a novel method to embed multisets and measures over $\mathbb{R}^d$ into Euclidean space. Our proposed embedding approximately preserves the sliced Wasserstein distance on distributions, thereby yielding geometrically meaningful represe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	457,471
2311.12727	Soft Random Sampling: A Theoretical and Empirical Analysis	Soft random sampling (SRS) is a simple yet effective approach for efficient training of large-scale deep neural networks when dealing with massive data. SRS selects a subset uniformly at random with replacement from the full data set in each epoch. In this paper, we conduct a theoretical and empirical analysis of SRS. ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	409,452
1702.00723	Handwritten Recognition Using SVM, KNN and Neural Network	Handwritten recognition (HWR) is the ability of a computer to receive and interpret intelligible handwritten input from source such as paper documents, photographs, touch-screens and other devices. In this paper we will using three (3) classification t o re cognize the handwritten which is SVM, KNN and Neural Network.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	67,696
2310.10158	Character-LLM: A Trainable Agent for Role-Playing	Large language models (LLMs) can be used to serve as agents to simulate human behaviors, given the powerful ability to understand human instructions and provide high-quality generated texts. Such ability stimulates us to wonder whether LLMs can simulate a person in a higher form than simple human behaviors. Therefore, ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	400,116
2405.08114	RATLIP: Generative Adversarial CLIP Text-to-Image Synthesis Based on Recurrent Affine Transformations	Synthesizing high-quality photorealistic images with textual descriptions as a condition is very challenging. Generative Adversarial Networks (GANs), the classical model for this task, frequently suffer from low consistency between image and text descriptions and insufficient richness in synthesized images. Recently, c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	453,988
2210.02231	Decanus to Legatus: Synthetic training for 2D-3D human pose lifting	3D human pose estimation is a challenging task because of the difficulty to acquire ground-truth data outside of controlled environments. A number of further issues have been hindering progress in building a universal and robust model for this task, including domain gaps between different datasets, unseen actions betwe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	321,576
1904.01638	A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging	This work provides a strong baseline for the problem of multi-source multi-target domain adaptation and generalization in medical imaging. Using a diverse collection of ten chest X-ray datasets, we empirically demonstrate the benefits of training medical imaging deep learning models on varied patient populations for ge...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	126,193
2502.05783	WatchGuardian: Enabling User-Defined Personalized Just-in-Time Intervention on Smartwatch	While just-in-time interventions (JITIs) have effectively targeted common health behaviors, individuals often have unique needs to intervene in personal undesirable actions that can negatively affect physical, mental, and social well-being. We present WatchGuardian, a smartwatch-based JITI system that empowers users to...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	531,775
2411.15640	AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset	Recent advancements in large language model(LLM) performance on medical multiple choice question (MCQ) benchmarks have stimulated interest from healthcare providers and patients globally. Particularly in low-and middle-income countries (LMICs) facing acute physician shortages and lack of specialists, LLMs offer a poten...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	510,699
1112.0992	The Web economy: goods, users, models and policies	Web emerged as an antidote to the rapidly increasing quantity of accumulated knowledge and become successful because it facilitates massive participation and communication with minimum costs. Today, its enormous impact, scale and dynamism in time and space make very difficult (and sometimes impossible) to measure and a...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	13,319
1604.06022	Constructing error-correcting binary codes using transitive permutation groups	Let $A_2(n,d)$ be the maximum size of a binary code of length $n$ and minimum distance $d$. In this paper we present the following new lower bounds: $A_2(18,4) \ge 5632$, $A_2(21,4) \ge 40960$, $A_2(22,4) \ge 81920$, $A_2(23,4) \ge 163840$, $A_2(24,4) \ge 327680$, $A_2(24,10) \ge 136$, and $A_2(25,6) \ge 17920$. The ne...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	54,890
1911.04489	Making Good on LSTMs' Unfulfilled Promise	LSTMs promise much to financial time-series analysis, temporal and cross-sectional inference, but we find that they do not deliver in a real-world financial management task. We examine an alternative called Continual Learning (CL), a memory-augmented approach, which can provide transparent explanations, i.e. which memo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	153,010
2403.06489	Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling	Uplift modeling aims to measure the incremental effect, which we call uplift, of a strategy or action on the users from randomized experiments or observational data. Most existing uplift methods only use individual data, which are usually not informative enough to capture the unobserved and complex hidden factors regar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	436,479
2302.01441	Commonsense-Aware Prompting for Controllable Empathetic Dialogue Generation	Improving the emotional awareness of pre-trained language models is an emerging important problem for dialogue generation tasks. Although prior studies have introduced methods to improve empathetic dialogue generation, few have discussed how to incorporate commonsense knowledge into pre-trained language models for cont...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	343,600
2403.03536	Towards Efficient and Effective Unlearning of Large Language Models for Recommendation	The significant advancements in large language models (LLMs) give rise to a promising research direction, i.e., leveraging LLMs as recommenders (LLMRec). The efficacy of LLMRec arises from the open-world knowledge and reasoning capabilities inherent in LLMs. LLMRec acquires the recommendation capabilities through instr...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	435,235
1904.04956	Distributed Deep Learning Strategies For Automatic Speech Recognition	In this paper, we propose and investigate a variety of distributed deep learning strategies for automatic speech recognition (ASR) and evaluate them with a state-of-the-art Long short-term memory (LSTM) acoustic model on the 2000-hour Switchboard (SWB2000), which is one of the most widely used datasets for ASR performa...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	127,162
1703.07822	Information-theoretic Model Identification and Policy Search using Physics Engines with Application to Robotic Manipulation	We consider the problem of a robot learning the mechanical properties of objects through physical interaction with the object, and introduce a practical, data-efficient approach for identifying the motion models of these objects. The proposed method utilizes a physics engine, where the robot seeks to identify the inert...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	70,459
2410.21708	Unsupervised Modality Adaptation with Text-to-Image Diffusion Models for Semantic Segmentation	Despite their success, unsupervised domain adaptation methods for semantic segmentation primarily focus on adaptation between image domains and do not utilize other abundant visual modalities like depth, infrared and event. This limitation hinders their performance and restricts their application in real-world multimod...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	503,362
2409.14424	Dormant: Defending against Pose-driven Human Image Animation	Pose-driven human image animation has achieved tremendous progress, enabling the generation of vivid and realistic human videos from just one single photo. However, it conversely exacerbates the risk of image misuse, as attackers may use one available image to create videos involving politics, violence and other illega...	false	false	false	false	true	false	false	false	false	false	false	true	true	false	false	false	false	false	490,459
2001.10163	Real-time trajectory planning for automated vehicle safety and performance in dynamic environments	Safe trajectory planning for high-performance automated vehicles in an environment with both static and moving obstacles is a challenging problem. Part of the challenge is developing a formulation that can be solved in real-time while including the following set of specifications: minimum time-to-goal, a dynamic vehicl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	161,754
2502.06835	Reinforcement Learning on AYA Dyads to Enhance Medication Adherence	Medication adherence is critical for the recovery of adolescents and young adults (AYAs) who have undergone hematopoietic cell transplantation (HCT). However, maintaining adherence is challenging for AYAs after hospital discharge, who experience both individual (e.g. physical and emotional symptoms) and interpersonal b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	532,280
2103.00891	Using contrastive learning to improve the performance of steganalysis schemes	To improve the detection accuracy and generalization of steganalysis, this paper proposes the Steganalysis Contrastive Framework (SCF) based on contrastive learning. The SCF improves the feature representation of steganalysis by maximizing the distance between features of samples of different categories and minimizing ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	222,445
2101.04414	Reliable Fleet Analytics for Edge IoT Solutions	In recent years we have witnessed a boom in Internet of Things (IoT) device deployments, which has resulted in big data and demand for low-latency communication. This shift in the demand for infrastructure is also enabling real-time decision making using artificial intelligence for IoT applications. Artificial Intellig...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	215,148
2410.12350	GECTurk WEB: An Explainable Online Platform for Turkish Grammatical Error Detection and Correction	Sophisticated grammatical error detection/correction tools are available for a small set of languages such as English and Chinese. However, it is not straightforward -- if not impossible -- to adapt them to morphologically rich languages with complex writing rules like Turkish which has more than 80 million speakers. E...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	498,987
2304.14415	Generative AI Perceptions: A Survey to Measure the Perceptions of Faculty, Staff, and Students on Generative AI Tools in Academia	ChatGPT is a natural language processing tool that can engage in human-like conversations and generate coherent and contextually relevant responses to various prompts. ChatGPT is capable of understanding natural text that is input by a user and generating appropriate responses in various forms. This tool represents a m...	true	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	360,952
1912.02332	3D Objectness Estimation via Bottom-up Regret Grouping	3D objectness estimation, namely discovering semantic objects from 3D scene, is a challenging and significant task in 3D understanding. In this paper, we propose a 3D objectness method working in a bottom-up manner. Beginning with over-segmented 3D segments, we iteratively group them into object proposals by learning a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	156,319
2405.08295	SpeechVerse: A Large-scale Generalizable Audio Language Model	Large language models (LLMs) have shown incredible proficiency in performing tasks that require semantic understanding of natural language instructions. Recently, many works have further expanded this capability to perceive multimodal audio and text inputs, but their capabilities are often limited to specific fine-tune...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	454,048
1802.09646	Optimizing over a Restricted Policy Class in Markov Decision Processes	We address the problem of finding an optimal policy in a Markov decision process under a restricted policy class defined by the convex hull of a set of base policies. This problem is of great interest in applications in which a number of reasonably good (or safe) policies are already known and we are only interested in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	91,354
1804.10266	Tensor Methods for Nonlinear Matrix Completion	In the low-rank matrix completion (LRMC) problem, the low-rank assumption means that the columns (or rows) of the matrix to be completed are points on a low-dimensional linear algebraic variety. This paper extends this thinking to cases where the columns are points on a low-dimensional nonlinear algebraic variety, a pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	96,123
2005.10825	Instance-aware Image Colorization	Image colorization is inherently an ill-posed problem with multi-modal uncertainty. Previous methods leverage the deep neural network to map input grayscale images to plausible color outputs directly. Although these learning-based methods have shown impressive performance, they usually fail on the input images that con...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	178,295
2211.05396	Learning Visual Representation of Underwater Acoustic Imagery Using Transformer-Based Style Transfer Method	Underwater automatic target recognition (UATR) has been a challenging research topic in ocean engineering. Although deep learning brings opportunities for target recognition on land and in the air, underwater target recognition techniques based on deep learning have lagged due to sensor performance and the size of trai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	329,537
2112.04229	Replay For Safety	Experience replay \citep{lin1993reinforcement, mnih2015human} is a widely used technique to achieve efficient use of data and improved performance in RL algorithms. In experience replay, past transitions are stored in a memory buffer and re-used during learning. Various suggestions for sampling schemes from the replay ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	270,467
1401.1757	An efficient algorithm for the calculation of reserves for non-unit linked life policies	The underlying stochastic nature of the requirements for the Solvency II regulations has introduced significant challenges if the required calculations are to be performed correctly, without resorting to excessive approximations, within practical timescales. It is generally acknowledged by practising actuaries within U...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	29,681
2110.05691	Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation	Neural Machine Translation (NMT) models are known to suffer from noisy inputs. To make models robust, we generate adversarial augmentation samples that attack the model and preserve the source-side semantic meaning at the same time. To generate such samples, we propose a doubly-trained architecture that pairs two NMT m...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	260,360
2308.05725	EXPRESSO: A Benchmark and Analysis of Discrete Expressive Speech Resynthesis	Recent work has shown that it is possible to resynthesize high-quality speech based, not on text, but on low bitrate discrete units that have been learned in a self-supervised fashion and can therefore capture expressive aspects of speech that are hard to transcribe (prosody, voice styles, non-verbal vocalization). The...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	384,884
2407.09283	DAHRS: Divergence-Aware Hallucination-Remediated SRL Projection	Semantic role labeling (SRL) enriches many downstream applications, e.g., machine translation, question answering, summarization, and stance/belief detection. However, building multilingual SRL models is challenging due to the scarcity of semantically annotated corpora for multiple languages. Moreover, state-of-the-art...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	472,518
2303.09139	Real-Time Decentralized Navigation of Nonholonomic Agents Using Shifted Yielding Areas	We present a lightweight, decentralized algorithm for navigating multiple nonholonomic agents through challenging environments with narrow passages. Our key idea is to allow agents to yield to each other in large open areas instead of narrow passages, to increase the success rate of conventional decentralized algorithm...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	351,926
1812.09570	EgoReID Dataset: Person Re-identification in Videos Acquired by Mobile Devices with First-Person Point-of-View	In recent years, we have seen the performance of video-based person Re-Identification (ReID) methods have improved considerably. However, most of the work in this area has dealt with videos acquired by fixed cameras with wider field of view. Recently, widespread use of wearable cameras and recording devices such as cel...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,183
2011.00577	FusiformNet: Extracting Discriminative Facial Features on Different Levels	Over the last several years, research on facial recognition based on Deep Neural Network has evolved with approaches like task-specific loss functions, image normalization and augmentation, network architectures, etc. However, there have been few approaches with attention to how human faces differ from person to person...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	204,278
2404.19644	MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation	Out-of-distribution (OOD) problems in few-shot classification (FSC) occur when novel classes sampled from testing distributions differ from base classes drawn from training distributions, which considerably degrades the performance of deep learning models deployed in real-world applications. Recent studies suggest that...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,721
1711.09405	Learning a Rotation Invariant Detector with Rotatable Bounding Box	Detection of arbitrarily rotated objects is a challenging task due to the difficulties of locating the multi-angle objects and separating them effectively from the background. The existing methods are not robust to angle varies of the objects because of the use of traditional bounding box, which is a rotation variant s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,398
2102.12999	An Advection-Diffusion based Filter for Machinable Designs in Topology Optimization	This paper introduces a simple formulation for topology optimization problems ensuring manufacturability by machining. The method distinguishes itself from existing methods by using the advection-diffusion equation with Robin boundary conditions to perform a filtering of the design variables. The proposed approach is l...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	221,916
2405.12237	EKM: An exact, polynomial-time algorithm for the $K$-medoids problem	The $K$-medoids problem is a challenging combinatorial clustering task, widely used in data analysis applications. While numerous algorithms have been proposed to solve this problem, none of these are able to obtain an exact (globally optimal) solution for the problem in polynomial time. In this paper, we present EKM: ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	455,453
2003.10149	Modelling High-Order Social Relations for Item Recommendation	The prevalence of online social network makes it compulsory to study how social relations affect user choice. However, most existing methods leverage only first-order social relations, that is, the direct neighbors that are connected to the target user. The high-order social relations, e.g., the friends of friends, whi...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	169,252
1901.05305	Seizure Detection using Least EEG Channels by Deep Convolutional Neural Network	This work aims to develop an end-to-end solution for seizure onset detection. We design the SeizNet, a Convolutional Neural Network for seizure detection. To compare SeizNet with traditional machine learning approach, a baseline classifier is implemented using spectrum band power features with Support Vector Machines (...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	118,763
1404.4975	Joint Latency and Cost Optimization for Erasure-coded Data Center Storage	Modern distributed storage systems offer large capacity to satisfy the exponentially increasing need of storage space. They often use erasure codes to protect against disk and node failures to increase reliability, while trying to meet the latency requirements of the applications and clients. This paper provides an ins...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	32,456
2005.04886	Gleason Score Prediction using Deep Learning in Tissue Microarray Image	Prostate cancer (PCa) is one of the most common cancers in men around the world. The most accurate method to evaluate lesion levels of PCa is microscopic inspection of stained biopsy tissue and estimate the Gleason score of tissue microarray (TMA) image by expert pathologists. However, it is time-consuming for patholog...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	176,589
2103.01563	Performance Analysis of OTFS Modulation with Receive Antenna Selection	In this paper, we analyze the performance of orthogonal time frequency space (OTFS) modulation with antenna selection at the receiver, where $n_s$ out of $n_r$ receive antennas with maximum channel Frobenius norms in the delay-Doppler (DD) domain are selected. Single-input multiple-output OTFS (SIMO-OTFS), multiple-inp...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	222,670
2111.09859	On the use of high order central difference schemes for differential equation based wall distance computations	A computationally efficient high-order solver is developed to compute the wall distances by solving the relevant partial differential equations, namely: Eikonal, Hamilton-Jacobi (HJ) and Poisson equations. In contrast to the upwind schemes widely used in the literature, we explore the suitability of high-order central ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	267,131
1506.02633	A Topological Approach to Spectral Clustering	We propose two related unsupervised clustering algorithms which, for input, take data assumed to be sampled from a uniform distribution supported on a metric space $X$, and output a clustering of the data based on the selection of a topological model for the connected components of $X$. Both algorithms work by selectin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	43,953
2105.12038	Unpaired Depth Super-Resolution in the Wild	Depth maps captured with commodity sensors are often of low quality and resolution; these maps need to be enhanced to be used in many applications. State-of-the-art data-driven methods of depth map super-resolution rely on registered pairs of low- and high-resolution depth maps of the same scenes. Acquisition of real-w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	236,896
1506.05547	Quantum Gaussian Channels with Weak Measurements	In this paper we perform a novel analysis of quantum Gaussian channels in the context of weak measurements. Suppose Alice sends classical information to Bob using a quantum channel. Suppose Bob is allowed to use only weak measurements, what would be the channel capacity? We formulate weak measurement theory in these te...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	44,310
2009.10644	Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models	Software flaw detection using multimodal deep learning models has been demonstrated as a very competitive approach on benchmark problems. In this work, we demonstrate that even better performance can be achieved using neural architecture search (NAS) combined with multimodal learning models. We adapt a NAS framework ai...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	196,948

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