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
2309.15054	Near Real-Time Position Tracking for Robot-Guided Evacuation	During the evacuation of a building, the rapid and accurate tracking of human evacuees can be used by a guide robot to increase the effectiveness of the evacuation [1],[2]. This paper introduces a near real-time human position tracking solution tailored for evacuation robots. Using a pose detector, our system first ide...	false	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	394,833
2312.15416	On Completeness of SDP-Based Barrier Certificate Synthesis over Unbounded Domains	Barrier certificates, serving as differential invariants that witness system safety, play a crucial role in the verification of cyber-physical systems (CPS). Prevailing computational methods for synthesizing barrier certificates are based on semidefinite programming (SDP) by exploiting Putinar Positivstellensatz. Conse...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	418,005
2409.06848	Shadow Removal Refinement via Material-Consistent Shadow Edges	Shadow boundaries can be confused with material boundaries as both exhibit sharp changes in luminance or contrast within a scene. However, shadows do not modify the intrinsic color or texture of surfaces. Therefore, on both sides of shadow edges traversing regions with the same material, the original color and textures...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,295
2101.10800	Robust Scheduling of Virtual Power Plant under Exogenous and Endogenous Uncertainties	Virtual power plant (VPP) provides a flexible solution to distributed energy resources integration by aggregating renewable generation units, conventional power plants, energy storages, and flexible demands. This paper proposes a novel model for determining the optimal offering strategy in the day-ahead energy-reserve ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	217,054
2307.12348	ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting	Diffusion-based image super-resolution (SR) methods are mainly limited by the low inference speed due to the requirements of hundreds or even thousands of sampling steps. Existing acceleration sampling techniques inevitably sacrifice performance to some extent, leading to over-blurry SR results. To address this issue, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,234
2006.09534	Towards improving discriminative reconstruction via simultaneous dense and sparse coding	Discriminative features extracted from the sparse coding model have been shown to perform well for classification. Recent deep learning architectures have further improved reconstruction in inverse problems by considering new dense priors learned from data. We propose a novel dense and sparse coding model that integrat...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	182,572
2010.12406	UNER: Universal Named-Entity RecognitionFramework	We introduce the Universal Named-Entity Recognition (UNER)framework, a 4-level classification hierarchy, and the methodology that isbeing adopted to create the first multilingual UNER corpus: the SETimesparallel corpus annotated for named-entities. First, the English SETimescorpus will be annotated using existing tools...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	202,682
2501.18733	Integrating LMM Planners and 3D Skill Policies for Generalizable Manipulation	The recent advancements in visual reasoning capabilities of large multimodal models (LMMs) and the semantic enrichment of 3D feature fields have expanded the horizons of robotic capabilities. These developments hold significant potential for bridging the gap between high-level reasoning from LMMs and low-level control ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	528,832
2209.12806	FONDUE: an algorithm to find the optimal dimensionality of the latent representations of variational autoencoders	When training a variational autoencoder (VAE) on a given dataset, determining the optimal number of latent variables is mostly done by grid search: a costly process in terms of computational time and carbon footprint. In this paper, we explore the intrinsic dimension estimation (IDE) of the data and latent representati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	319,664
2004.13843	Template-based Question Answering using Recursive Neural Networks	We propose a neural network-based approach to automatically learn and classify natural language questions into its corresponding template using recursive neural networks. An obvious advantage of using neural networks is the elimination of the need for laborious feature engineering that can be cumbersome and error-prone...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	174,682
2210.01508	How Masterly Are People at Playing with Their Vocabulary? Analysis of the Wordle Game for Latvian	In this paper, we describe adaptation of a simple word guessing game that occupied the hearts and minds of people around the world. There are versions for all three Baltic countries and even several versions of each. We specifically pay attention to the Latvian version and look into how people form their guesses given ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	321,289
2305.17352	Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?	Centralized Training with Decentralized Execution (CTDE) has recently emerged as a popular framework for cooperative Multi-Agent Reinforcement Learning (MARL), where agents can use additional global state information to guide training in a centralized way and make their own decisions only based on decentralized local p...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	368,543
2407.07110	Foundation Models for ECG: Leveraging Hybrid Self-Supervised Learning for Advanced Cardiac Diagnostics	Using foundation models enhanced by self-supervised learning (SSL) methods presents an innovative approach to electrocardiogram (ECG) analysis, which is crucial for cardiac health monitoring and diagnosis. This study comprehensively evaluates foundation models for ECGs, leveraging SSL methods, including generative and ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	471,653
2302.06786	Interference and noise cancellation for joint communication radar (JCR) system based on contextual information	This paper examines the separation of wireless communication and radar signals, thereby guaranteeing cohabitation and acting as a panacea to spectrum sensing. First, considering that the channel impulse response was known by the receivers (communication and radar), we showed that the optimizing beamforming weights miti...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	345,529
1010.3541	Heterogenous scaling in interevent time of on-line bookmarking	In this paper, we study the statistical properties of bookmarking behaviors in Delicious.com. We find that the interevent time distributions of bookmarking decays powerlike as interevent time increases at both individual and population level. Remarkably, we observe a significant change in the exponent when interevent t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	7,933
1608.02307	SANTIAGO: Spine Association for Neuron Topology Improvement and Graph Optimization	Developing automated and semi-automated solutions for reconstructing wiring diagrams of the brain from electron micrographs is important for advancing the field of connectomics. While the ultimate goal is to generate a graph of neuron connectivity, most prior automated methods have focused on volume segmentation rather...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,547
2211.00752	DeltaFinger: a 3-DoF Wearable Haptic Display Enabling High-Fidelity Force Vector Presentation at a User Finger	This paper presents a novel haptic device DeltaFinger designed to deliver the force of interaction with virtual objects by guiding user's finger with wearable delta mechanism. The developed interface is capable to deliver 3D force vector to the fingertip of the index finger of the user, allowing complex rendering of vi...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	327,985
1906.10511	Benchmarking Neural Machine Translation for Southern African Languages	Unlike major Western languages, most African languages are very low-resourced. Furthermore, the resources that do exist are often scattered and difficult to obtain and discover. As a result, the data and code for existing research has rarely been shared. This has lead a struggle to reproduce reported results, and few p...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	136,450
1011.6441	LP Decodable Permutation Codes based on Linearly Constrained Permutation Matrices	A set of linearly constrained permutation matrices are proposed for constructing a class of permutation codes. Making use of linear constraints imposed on the permutation matrices, we can formulate a minimum Euclidian distance decoding problem for the proposed class of permutation codes as a linear programming (LP) pro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,367
2401.07764	When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignment	AI agents based on multimodal large language models (LLMs) are expected to revolutionize human-computer interaction and offer more personalized assistant services across various domains like healthcare, education, manufacturing, and entertainment. Deploying LLM agents in 6G networks enables users to access previously e...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	421,648
1704.04336	An entity-driven recursive neural network model for chinese discourse coherence modeling	Chinese discourse coherence modeling remains a challenge taskin Natural Language Processing field.Existing approaches mostlyfocus on the need for feature engineering, whichadoptthe sophisticated features to capture the logic or syntactic or semantic relationships acrosssentences within a text.In this paper, we present ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	71,792
1811.04376	Explaining Deep Learning Models using Causal Inference	Although deep learning models have been successfully applied to a variety of tasks, due to the millions of parameters, they are becoming increasingly opaque and complex. In order to establish trust for their widespread commercial use, it is important to formalize a principled framework to reason over these models. In t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	113,076
2404.02124	Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models	Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices. One of the most important aspects of MCQs is the distractors, i.e., incorrect options that are designed to target common errors or misconcep...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,729
cs/0702071	What is needed to exploit knowledge of primary transmissions?	Recently, Tarokh and others have raised the possibility that a cognitive radio might know the interference signal being transmitted by a strong primary user in a non-causal way, and use this knowledge to increase its data rates. However, there is a subtle difference between knowing the signal transmitted by the primary...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,155
2109.05771	Perturbation CheckLists for Evaluating NLG Evaluation Metrics	Natural Language Generation (NLG) evaluation is a multifaceted task requiring assessment of multiple desirable criteria, e.g., fluency, coherency, coverage, relevance, adequacy, overall quality, etc. Across existing datasets for 6 NLG tasks, we observe that the human evaluation scores on these multiple criteria are oft...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	254,936
1903.02330	Self-Supervised Learning of 3D Human Pose using Multi-view Geometry	Training accurate 3D human pose estimators requires large amount of 3D ground-truth data which is costly to collect. Various weakly or self supervised pose estimation methods have been proposed due to lack of 3D data. Nevertheless, these methods, in addition to 2D ground-truth poses, require either additional supervisi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	123,482
1902.00369	Medical Image Super-Resolution Using a Generative Adversarial Network	During the growing popularity of electronic medical records, electronic medical record (EMR) data has exploded increasingly. It is very meaningful to retrieve high quality EMR in mass data. In this paper, an EMR value network with retrieval function is constructed by taking stroke disease as the research object. It mai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	120,388
2006.04334	Characterizing Sociolinguistic Variation in the Competing Vaccination Communities	Public health practitioners and policy makers grapple with the challenge of devising effective message-based interventions for debunking public health misinformation in cyber communities. "Framing" and "personalization" of the message is one of the key features for devising a persuasive messaging strategy. For an effec...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	180,653
1603.06729	On the Statistical Analysis of Practical SPARQL Queries	In this paper, we analyze some basic features of SPARQL queries coming from our practical world in a statistical way. These features include three statistic features such as the occurrence frequency of triple patterns, fragments, well-designed patterns and four semantic features such as monotonicity, non-monotonicity, ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	53,533
2410.06042	Weighted Embeddings for Low-Dimensional Graph Representation	Learning low-dimensional numerical representations from symbolic data, e.g., embedding the nodes of a graph into a geometric space, is an important concept in machine learning. While embedding into Euclidean space is common, recent observations indicate that hyperbolic geometry is better suited to represent hierarchica...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	496,027
2401.09340	SceneVerse: Scaling 3D Vision-Language Learning for Grounded Scene Understanding	3D vision-language grounding, which focuses on aligning language with the 3D physical environment, stands as a cornerstone in the development of embodied agents. In comparison to recent advancements in the 2D domain, grounding language in 3D scenes faces several significant challenges: (i) the inherent complexity of 3D...	false	false	false	false	true	false	true	true	true	false	false	true	false	false	false	false	false	false	422,227
2303.02052	Interruptions detection in video conferences	In recent years, video conferencing (VC) popularity has skyrocketed for a wide range of activities. As a result, the number of VC users surged sharply. The sharp increase in VC usage has been accompanied by various newly emerging privacy and security challenges. VC meetings became a target for various security attacks,...	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	349,207
1805.11730	Learn to Combine Modalities in Multimodal Deep Learning	Combining complementary information from multiple modalities is intuitively appealing for improving the performance of learning-based approaches. However, it is challenging to fully leverage different modalities due to practical challenges such as varying levels of noise and conflicts between modalities. Existing metho...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	98,993
1408.5667	Dependent Nonparametric Bayesian Group Dictionary Learning for online reconstruction of Dynamic MR images	In this paper, we introduce a dictionary learning based approach applied to the problem of real-time reconstruction of MR image sequences that are highly undersampled in k-space. Unlike traditional dictionary learning, our method integrates both global and patch-wise (local) sparsity information and incorporates some p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	35,572
2004.11020	SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution	In this paper, we tackle a fully unsupervised super-resolution problem, i.e., neither paired images nor ground truth HR images. We assume that low resolution (LR) images are relatively easy to collect compared to high resolution (HR) images. By allowing multiple LR images, we build a set of pseudo pairs by denoising an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,795
2502.14785	Real-Time Device Reach Forecasting Using HLL and MinHash Data Sketches	Predicting the right number of TVs (Device Reach) in real-time based on a user-specified targeting attributes is imperative for running multi-million dollar ADs business. The traditional approach of SQL queries to join billions of records across multiple targeting dimensions is extremely slow. As a workaround, many app...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	535,976
2106.07732	Learning Audio-Visual Dereverberation	Reverberation not only degrades the quality of speech for human perception, but also severely impacts the accuracy of automatic speech recognition. Prior work attempts to remove reverberation based on the audio modality only. Our idea is to learn to dereverberate speech from audio-visual observations. The visual enviro...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	241,024
0711.2501	Error Exponents of Erasure/List Decoding Revisited via Moments of Distance Enumerators	The analysis of random coding error exponents pertaining to erasure/list decoding, due to Forney, is revisited. Instead of using Jensen's inequality as well as some other inequalities in the derivation, we demonstrate that an exponentially tight analysis can be carried out by assessing the relevant moments of a certain...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	903
2011.00399	Temporally-Continuous Probabilistic Prediction using Polynomial Trajectory Parameterization	A commonly-used representation for motion prediction of actors is a sequence of waypoints (comprising positions and orientations) for each actor at discrete future time-points. While this approach is simple and flexible, it can exhibit unrealistic higher-order derivatives (such as acceleration) and approximation errors...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	204,196
2208.01847	Advance sharing of quantum shares for classical secrets	Secret sharing schemes for classical secrets can be classified into classical secret sharing schemes and quantum secret sharing schemes. Classical secret sharing has been known to be able to distribute some shares before a given secret. On the other hand, quantum mechanics extends the capabilities of secret sharing bey...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	311,294
1904.10446	Generated Loss, Augmented Training, and Multiscale VAE	The variational autoencoder (VAE) framework remains a popular option for training unsupervised generative models, especially for discrete data where generative adversarial networks (GANs) require workaround to create gradient for the generator. In our work modeling US postal addresses, we show that our discrete VAE wit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	128,633
1410.0925	A Framework for the Volumetric Integration of Depth Images	Volumetric models have become a popular representation for 3D scenes in recent years. One of the breakthroughs leading to their popularity was KinectFusion, where the focus is on 3D reconstruction using RGB-D sensors. However, monocular SLAM has since also been tackled with very similar approaches. Representing the rec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	36,509
2108.00552	PSE-Match: A Viewpoint-free Place Recognition Method with Parallel Semantic Embedding	Accurate localization on autonomous driving cars is essential for autonomy and driving safety, especially for complex urban streets and search-and-rescue subterranean environments where high-accurate GPS is not available. However current odometry estimation may introduce the drifting problems in long-term navigation wi...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	248,751
2305.18387	Augmenting Character Designers Creativity Using Generative Adversarial Networks	Recent advances in Generative Adversarial Networks (GANs) continue to attract the attention of researchers in different fields due to the wide range of applications devised to take advantage of their key features. Most recent GANs are focused on realism, however, generating hyper-realistic output is not a priority for ...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	369,006
2202.08171	Capitalization Normalization for Language Modeling with an Accurate and Efficient Hierarchical RNN Model	Capitalization normalization (truecasing) is the task of restoring the correct case (uppercase or lowercase) of noisy text. We propose a fast, accurate and compact two-level hierarchical word-and-character-based recurrent neural network model. We use the truecaser to normalize user-generated text in a Federated Learnin...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	280,786
1801.02270	Perceptual Context in Cognitive Hierarchies	Cognition does not only depend on bottom-up sensor feature abstraction, but also relies on contextual information being passed top-down. Context is higher level information that helps to predict belief states at lower levels. The main contribution of this paper is to provide a formalisation of perceptual context and it...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	87,897
2310.08929	Leveraging Image Augmentation for Object Manipulation: Towards Interpretable Controllability in Object-Centric Learning	The binding problem in artificial neural networks is actively explored with the goal of achieving human-level recognition skills through the comprehension of the world in terms of symbol-like entities. Especially in the field of computer vision, object-centric learning (OCL) is extensively researched to better understa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	399,605
1811.04577	Forecasting People's Needs in Hurricane Events from Social Network	Social networks can serve as a valuable communication channel for calls for help, offering assistance, and coordinating rescue activities in disaster. Social networks such as Twitter allow users to continuously update relevant information, which is especially useful during a crisis, where the rapidly changing condition...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	113,123
1809.01093	Adversarial Attacks on Node Embeddings via Graph Poisoning	The goal of network representation learning is to learn low-dimensional node embeddings that capture the graph structure and are useful for solving downstream tasks. However, despite the proliferation of such methods, there is currently no study of their robustness to adversarial attacks. We provide the first adversari...	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	false	106,734
2003.08737	A Matlab Toolbox for Feature Importance Ranking	More attention is being paid for feature importance ranking (FIR), in particular when thousands of features can be extracted for intelligent diagnosis and personalized medicine. A large number of FIR approaches have been proposed, while few are integrated for comparison and real-life applications. In this study, a matl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,828
1709.08924	UBSegNet: Unified Biometric Region of Interest Segmentation Network	Digital human identity management, can now be seen as a social necessity, as it is essentially required in almost every public sector such as, financial inclusions, security, banking, social networking e.t.c. Hence, in today's rampantly emerging world with so many adversarial entities, relying on a single biometric tra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	81,551
1807.04073	A punishment voting algorithm based on super categories construction for acoustic scene classification	In acoustic scene classification researches, audio segment is usually split into multiple samples. Majority voting is then utilized to ensemble the results of the samples. In this paper, we propose a punishment voting algorithm based on the super categories construction method for acoustic scene classification. Specifi...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	102,666
2412.16445	Mixed geometry information regularization for image multiplicative denoising	This paper focuses on solving the multiplicative gamma denoising problem via a variation model. Variation-based regularization models have been extensively employed in a variety of inverse problem tasks in image processing. However, sufficient geometric priors and efficient algorithms are still very difficult problems ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	519,518
0804.0611	Channel State Feedback Schemes for Multiuser MIMO-OFDM Downlink	Channel state feedback schemes for the MIMO broadcast downlink have been widely studied in the frequency-flat case. This work focuses on the more relevant frequency selective case, where some important new aspects emerge. We consider a MIMO-OFDM broadcast channel and compare achievable ergodic rates under three channel...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,532
2205.09256	Training Vision-Language Transformers from Captions	Vision-Language Transformers can be learned without low-level human labels (e.g. class labels, bounding boxes, etc). Existing work, whether explicitly utilizing bounding boxes or patches, assumes that the visual backbone must first be trained on ImageNet class prediction before being integrated into a multimodal lingui...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	297,203
2311.11252	Submeter-level Land Cover Mapping of Japan	Deep learning has shown promising performance in submeter-level mapping tasks; however, the annotation cost of submeter-level imagery remains a challenge, especially when applied on a large scale. In this paper, we present the first submeter-level land cover mapping of Japan with eight classes, at a relatively low anno...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	408,873
2406.04769	Diffusion-based Generative Image Outpainting for Recovery of FOV-Truncated CT Images	Field-of-view (FOV) recovery of truncated chest CT scans is crucial for accurate body composition analysis, which involves quantifying skeletal muscle and subcutaneous adipose tissue (SAT) on CT slices. This, in turn, enables disease prognostication. Here, we present a method for recovering truncated CT slices using ge...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	461,833
2411.07933	Prediction of Acoustic Communication Performance for AUVs using Gaussian Process Classification	Cooperating autonomous underwater vehicles (AUVs) often rely on acoustic communication to coordinate their actions effectively. However, the reliability of underwater acoustic communication decreases as the communication range between vehicles increases. Consequently, teams of cooperating AUVs typically make conservati...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	507,723
1905.00626	On Linear Learning with Manycore Processors	A new generation of manycore processors is on the rise that offers dozens and more cores on a chip and, in a sense, fuses host processor and accelerator. In this paper we target the efficient training of generalized linear models on these machines. We propose a novel approach for achieving parallelism which we call Het...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	129,526
2308.09300	V2A-Mapper: A Lightweight Solution for Vision-to-Audio Generation by Connecting Foundation Models	Building artificial intelligence (AI) systems on top of a set of foundation models (FMs) is becoming a new paradigm in AI research. Their representative and generative abilities learnt from vast amounts of data can be easily adapted and transferred to a wide range of downstream tasks without extra training from scratch...	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	386,230
2206.08967	Random Forest of Epidemiological Models for Influenza Forecasting	Forecasting the hospitalizations caused by the Influenza virus is vital for public health planning so that hospitals can be better prepared for an influx of patients. Many forecasting methods have been used in real-time during the Influenza seasons and submitted to the CDC for public communication. The forecasting mode...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	303,374
2403.01874	A Survey on Evaluation of Out-of-Distribution Generalization	Machine learning models, while progressively advanced, rely heavily on the IID assumption, which is often unfulfilled in practice due to inevitable distribution shifts. This renders them susceptible and untrustworthy for deployment in risk-sensitive applications. Such a significant problem has consequently spawned vari...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	434,617
1912.00011	Heuristic Strategies in Uncertain Approval Voting Environments	In many collective decision making situations, agents vote to choose an alternative that best represents the preferences of the group. Agents may manipulate the vote to achieve a better outcome by voting in a way that does not reflect their true preferences. In real world voting scenarios, people often do not have comp...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	155,647
1304.7607	A Discrete State Transition Algorithm for Generalized Traveling Salesman Problem	Generalized traveling salesman problem (GTSP) is an extension of classical traveling salesman problem (TSP), which is a combinatorial optimization problem and an NP-hard problem. In this paper, an efficient discrete state transition algorithm (DSTA) for GTSP is proposed, where a new local search operator named \textit{...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	24,276
2410.07094	An Approach for Auto Generation of Labeling Functions for Software Engineering Chatbots	Software engineering (SE) chatbots are increasingly gaining attention for their role in enhancing development processes. At the core of chatbots are the Natural Language Understanding platforms (NLUs), which enable them to comprehend and respond to user queries. Before deploying NLUs, there is a need to train them with...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	496,464
1504.08256	Manipulation is Harder with Incomplete Votes	The Coalitional Manipulation (CM) problem has been studied extensively in the literature for many voting rules. The CM problem, however, has been studied only in the complete information setting, that is, when the manipulators know the votes of the non-manipulators. A more realistic scenario is an incomplete informatio...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	42,637
1802.04350	Cost-Aware Learning for Improved Identifiability with Multiple Experiments	We analyze the sample complexity of learning from multiple experiments where the experimenter has a total budget for obtaining samples. In this problem, the learner should choose a hypothesis that performs well with respect to multiple experiments, and their related data distributions. Each collected sample is associat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	90,197
2306.03978	B\"{u}y\"{u}k dil modellerinin T\"{u}rk\c{c}e verisetleri ile e\u{g}itilmesi ve ince ayarlanmas\i	Large language models have advanced enormously, gained vast attraction and are having a phase of intensed research. Some of the developed models and training datasets have been made open-accessible. Hence these may be further fine-tuned with some techniques to obtain specialized models for specific tasks. When it comes...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	371,551
2502.04420	KVTuner: Sensitivity-Aware Layer-wise Mixed Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference	KV cache quantization can improve Large Language Models (LLMs) inference throughput and latency in long contexts and large batch-size scenarios while preserving LLMs effectiveness. However, current methods have three unsolved issues: overlooking layer-wise sensitivity to KV cache quantization, high overhead of online f...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	531,156
2311.05602	Reconstructing Objects in-the-wild for Realistic Sensor Simulation	Reconstructing objects from real world data and rendering them at novel views is critical to bringing realism, diversity and scale to simulation for robotics training and testing. In this work, we present NeuSim, a novel approach that estimates accurate geometry and realistic appearance from sparse in-the-wild data cap...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	406,637
2007.06850	A model to support collective reasoning: Formalization, analysis and computational assessment	Inspired by e-participation systems, in this paper we propose a new model to represent human debates and methods to obtain collective conclusions from them. This model overcomes drawbacks of existing approaches by allowing users to introduce new pieces of information into the discussion, to relate them to existing piec...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	187,150
2403.16742	A Branch and Bound method for the exact parameter identification of the PK/PD model for anesthetic drugs	We address the problem of parameter identification for the standard pharmacokinetic/pharmacodynamic (PK/PD) model for anesthetic drugs. Our main contribution is the development of a global optimization method that guarantees finding the parameters that minimize the one-step ahead prediction error. The method is based o...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	441,174
2401.04722	U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation	Convolutional Neural Networks (CNNs) and Transformers have been the most popular architectures for biomedical image segmentation, but both of them have limited ability to handle long-range dependencies because of inherent locality or computational complexity. To address this challenge, we introduce U-Mamba, a general-p...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	420,515
1406.0085	Cooperative Control of Linear Multi-Agent Systems via Distributed Output Regulation and Transient Synchronization	A wide range of multi-agent coordination problems including reference tracking and disturbance rejection requirements can be formulated as a cooperative output regulation problem. The general framework captures typical problems such as output synchronization, leader-follower synchronization, and many more. In the prese...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	33,521
2011.01893	Iterative Best Response for Multi-Body Asset-Guarding Games	We present a numerical approach to finding optimal trajectories for players in a multi-body, asset-guarding game with nonlinear dynamics and non-convex constraints. Using the Iterative Best Response (IBR) scheme, we solve for each player's optimal strategy assuming the other players' trajectories are known and fixed. L...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	204,750
1705.09368	Pose Guided Person Image Generation	This paper proposes the novel Pose Guided Person Generation Network (PG$^2$) that allows to synthesize person images in arbitrary poses, based on an image of that person and a novel pose. Our generation framework PG$^2$ utilizes the pose information explicitly and consists of two key stages: pose integration and image ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,180
1809.09658	Non-native children speech recognition through transfer learning	This work deals with non-native children's speech and investigates both multi-task and transfer learning approaches to adapt a multi-language Deep Neural Network (DNN) to speakers, specifically children, learning a foreign language. The application scenario is characterized by young students learning English and German...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	108,750
2010.07002	Fast meningioma segmentation in T1-weighted MRI volumes using a lightweight 3D deep learning architecture	Automatic and consistent meningioma segmentation in T1-weighted MRI volumes and corresponding volumetric assessment is of use for diagnosis, treatment planning, and tumor growth evaluation. In this paper, we optimized the segmentation and processing speed performances using a large number of both surgically treated men...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	200,671
1503.00796	On the Convergence and Performance of MF Precoding in Distributed Massive MU-MIMO Systems	In this paper, we analyze both the rate of convergence and the performance of a matched-filter (MF) precoder in a massive multi-user (MU) multiple-input-multiple-output (MIMO) system, with the aim of determining the impact of distributing the transmit antennas into multiple clusters. We consider cases of transmit spati...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	40,751
2310.07794	CRITERIA: a New Benchmarking Paradigm for Evaluating Trajectory Prediction Models for Autonomous Driving	Benchmarking is a common method for evaluating trajectory prediction models for autonomous driving. Existing benchmarks rely on datasets, which are biased towards more common scenarios, such as cruising, and distance-based metrics that are computed by averaging over all scenarios. Following such a regiment provides a l...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	399,122
1805.00982	k-SVRG: Variance Reduction for Large Scale Optimization	Variance reduced stochastic gradient (SGD) methods converge significantly faster than the vanilla SGD counterpart. However, these methods are not very practical on large scale problems, as they either i) require frequent passes over the full data to recompute gradients---without making any progress during this time (li...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	96,554
2305.09584	Revisiting Proprioceptive Sensing for Articulated Object Manipulation	Robots that assist humans will need to interact with articulated objects such as cabinets or microwaves. Early work on creating systems for doing so used proprioceptive sensing to estimate joint mechanisms during contact. However, nowadays, almost all systems use only vision and no longer consider proprioceptive inform...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	364,692
2004.06957	Self-Supervised training for blind multi-frame video denoising	We propose a self-supervised approach for training multi-frame video denoising networks. These networks predict frame t from a window of frames around t. Our self-supervised approach benefits from the video temporal consistency by penalizing a loss between the predicted frame t and a neighboring target frame, which are...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	172,648
1711.04226	AON: Towards Arbitrarily-Oriented Text Recognition	Recognizing text from natural images is a hot research topic in computer vision due to its various applications. Despite the enduring research of several decades on optical character recognition (OCR), recognizing texts from natural images is still a challenging task. This is because scene texts are often in irregular ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,358
2406.05376	Adversarial flows: A gradient flow characterization of adversarial attacks	A popular method to perform adversarial attacks on neuronal networks is the so-called fast gradient sign method and its iterative variant. In this paper, we interpret this method as an explicit Euler discretization of a differential inclusion, where we also show convergence of the discretization to the associated gradi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	462,110
2402.05906	Risk-Sensitive Multi-Agent Reinforcement Learning in Network Aggregative Markov Games	Classical multi-agent reinforcement learning (MARL) assumes risk neutrality and complete objectivity for agents. However, in settings where agents need to consider or model human economic or social preferences, a notion of risk must be incorporated into the RL optimization problem. This will be of greater importance in...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	428,053
2204.09172	Node Deployment in Heterogeneous Rayleigh Fading Sensor Networks	We study a hierarchical heterogeneous Rayleigh fading wireless sensor network (WSN) in which sensor nodes surveil a region of interest (RoI) and use access points (APs) as relays to transmit their sensed information to base stations (BSs). By considering both large-scale path-loss signal attenuation and small-scale sig...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	292,338
2302.06025	Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits	We consider the sequential decision-making problem where the mean outcome is a non-linear function of the chosen action. Compared with the linear model, two curious phenomena arise in non-linear models: first, in addition to the "learning phase" with a standard parametric rate for estimation or regret, there is an "bur...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	345,259
2102.01767	Automatic analysis of artistic paintings using information-based measures	The artistic community is increasingly relying on automatic computational analysis for authentication and classification of artistic paintings. In this paper, we identify hidden patterns and relationships present in artistic paintings by analysing their complexity, a measure that quantifies the sum of characteristics o...	false	false	false	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	218,216
2007.12913	NoPropaganda at SemEval-2020 Task 11: A Borrowed Approach to Sequence Tagging and Text Classification	This paper describes our contribution to SemEval-2020 Task 11: Detection Of Propaganda Techniques In News Articles. We start with simple LSTM baselines and move to an autoregressive transformer decoder to predict long continuous propaganda spans for the first subtask. We also adopt an approach from relation extraction ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	188,961
2405.08486	Gradient Boosting Mapping for Dimensionality Reduction and Feature Extraction	A fundamental problem in supervised learning is to find a good set of features or distance measures. If the new set of features is of lower dimensionality and can be obtained by a simple transformation of the original data, they can make the model understandable, reduce overfitting, and even help to detect distribution...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	454,111
2112.14300	Time-Incremental Learning from Data Using Temporal Logics	Real-time and human-interpretable decision-making in cyber-physical systems is a significant but challenging task, which usually requires predictions of possible future events from limited data. In this paper, we introduce a time-incremental learning framework: given a dataset of labeled signal traces with a common tim...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	true	273,485
0808.0987	A new graph perspective on max-min fairness in Gaussian parallel channels	In this work we are concerned with the problem of achieving max-min fairness in Gaussian parallel channels with respect to a general performance function, including channel capacity or decoding reliability as special cases. As our central results, we characterize the laws which determine the value of the achievable max...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	2,175
2407.05645	OneDiff: A Generalist Model for Image Difference Captioning	In computer vision, Image Difference Captioning (IDC) is crucial for accurately describing variations between closely related images. Traditional IDC methods often rely on specialist models, which restrict their applicability across varied contexts. This paper introduces the OneDiff model, a novel generalist approach t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	471,069
2302.00358	Bandit Convex Optimisation Revisited: FTRL Achieves $\tilde{O}(t^{1/2})$ Regret	We show that a kernel estimator using multiple function evaluations can be easily converted into a sampling-based bandit estimator with expectation equal to the original kernel estimate. Plugging such a bandit estimator into the standard FTRL algorithm yields a bandit convex optimisation algorithm that achieves $\tilde...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,190
2004.04400	Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image Synthesis	Camera captured human pose is an outcome of several sources of variation. Performance of supervised 3D pose estimation approaches comes at the cost of dispensing with variations, such as shape and appearance, that may be useful for solving other related tasks. As a result, the learned model not only inculcates task-bia...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	171,871
1202.3753	Partial Order MCMC for Structure Discovery in Bayesian Networks	We present a new Markov chain Monte Carlo method for estimating posterior probabilities of structural features in Bayesian networks. The method draws samples from the posterior distribution of partial orders on the nodes; for each sampled partial order, the conditional probabilities of interest are computed exactly. We...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	14,425
2302.12563	Retrieved Sequence Augmentation for Protein Representation Learning	Protein language models have excelled in a variety of tasks, ranging from structure prediction to protein engineering. However, proteins are highly diverse in functions and structures, and current state-of-the-art models including the latest version of AlphaFold rely on Multiple Sequence Alignments (MSA) to feed in the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	347,614
2410.05711	TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation	Self-supervised learning has garnered increasing attention in time series analysis for benefiting various downstream tasks and reducing reliance on labeled data. Despite its effectiveness, existing methods often struggle to comprehensively capture both long-term dynamic evolution and subtle local patterns in a unified ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	495,873
2412.08843	Precise Asymptotics and Refined Regret of Variance-Aware UCB	In this paper, we study the behavior of the Upper Confidence Bound-Variance (UCB-V) algorithm for the Multi-Armed Bandit (MAB) problems, a variant of the canonical Upper Confidence Bound (UCB) algorithm that incorporates variance estimates into its decision-making process. More precisely, we provide an asymptotic chara...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	516,243

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