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
1209.4444	On the Construction of Polar Codes	We consider the problem of efficiently constructing polar codes over binary memoryless symmetric (BMS) channels. The complexity of designing polar codes via an exact evaluation of the polarized channels to find which ones are "good" appears to be exponential in the block length. In \cite{TV11}, Tal and Vardy show that ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,649
2305.19275	Automated spacing measurement of formwork system members with 3D point cloud data	The formwork system belonging to the temporary structure plays an important role in the smooth progress and successful completion of a construction project. Ensuring that the formwork system is installed as designed is essential for construction safety and quality. The current way to measure the spacing between formwor...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	369,454
1803.08810	Sneak into Devil's Colony- A study of Fake Profiles in Online Social Networks and the Cyber Law	Massive content about user's social, personal and professional life stored on Online Social Networks (OSNs) has attracted not only the attention of researchers and social analysts but also the cyber criminals. These cyber criminals penetrate illegally into an OSN by establishing fake profiles or by designing bots and e...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	93,343
2201.01760	Multi-Robot Collaborative Perception with Graph Neural Networks	Multi-robot systems such as swarms of aerial robots are naturally suited to offer additional flexibility, resilience, and robustness in several tasks compared to a single robot by enabling cooperation among the agents. To enhance the autonomous robot decision-making process and situational awareness, multi-robot system...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	274,340
2305.17024	Contouring by Unit Vector Field Regression	This work introduces a simple deep-learning based method to delineate contours by `walking' along learnt unit vector fields. We demonstrate the effectiveness of our pipeline on the unique case of open contours on the task of delineating the sacroiliac joints (SIJs) in spinal MRIs. We show that: (i) 95% of the time the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,380
2412.08300	Augmenting Sequential Recommendation with Balanced Relevance and Diversity	By generating new yet effective data, data augmentation has become a promising method to mitigate the data sparsity problem in sequential recommendation. Existing works focus on augmenting the original data but rarely explore the issue of imbalanced relevance and diversity for augmented data, leading to semantic drift ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	516,035
1604.06506	Online Action Detection	In online action detection, the goal is to detect the start of an action in a video stream as soon as it happens. For instance, if a child is chasing a ball, an autonomous car should recognize what is going on and respond immediately. This is a very challenging problem for four reasons. First, only partial actions are ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,945
1205.3225	Using Superposition Codebooks and Partial Decode and Forward in Low SNR Parallel Relay Networks	A new communication scheme for Gaussian parallel relay networks based on superposition coding and partial decoding at the relays is presented. Some specific examples are proposed in which two codebook layers are superimposed. The first level codebook is constructed with symbols from a binary or ternary alphabet while t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,007
1810.02266	Concept-drifting Data Streams are Time Series; The Case for Continuous Adaptation	Learning from data streams is an increasingly important topic in data mining, machine learning, and artificial intelligence in general. A major focus in the data stream literature is on designing methods that can deal with concept drift, a challenge where the generating distribution changes over time. A general assumpt...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,558
2211.05412	Desire Backpropagation: A Lightweight Training Algorithm for Multi-Layer Spiking Neural Networks based on Spike-Timing-Dependent Plasticity	Spiking neural networks (SNNs) are a viable alternative to conventional artificial neural networks when resource efficiency and computational complexity are of importance. A major advantage of SNNs is their binary information transfer through spike trains which eliminates multiplication operations. The training of SNNs...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	true	329,545
2108.02281	Context-Aware Environment Monitoring to Support LPWAN-based Battlefield Applications	The use of IoT-related technologies is growing in several areas. Applications of environmental monitoring, logistics, smart cities are examples of applications that benefit from advances in IoT. In the military context, IoT applications can support the decision-making process by delivering information collected directl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	249,267
2111.12911	Human and Scene Motion Deblurring using Pseudo-blur Synthesizer	Present-day deep learning-based motion deblurring methods utilize the pair of synthetic blur and sharp data to regress any particular framework. This task is designed for directly translating a blurry image input into its restored version as output. The aforementioned approach relies heavily on the quality of the synth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	268,121
1512.04509	On non-iterative training of a neural classifier	Recently an algorithm, was discovered, which separates points in n-dimension by planes in such a manner that no two points are left un-separated by at least one plane{[}1-3{]}. By using this new algorithm we show that there are two ways of classification by a neural network, for a large dimension feature space, both of...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	50,141
2212.07231	Cutting Plane Selection with Analytic Centers and Multiregression	Cutting planes are a crucial component of state-of-the-art mixed-integer programming solvers, with the choice of which subset of cuts to add being vital for solver performance. We propose new distance-based measures to qualify the value of a cut by quantifying the extent to which it separates relevant parts of the rela...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	336,348
2401.11383	Entropic Conditional Central Limit Theorem and Hadamard Compression	We make use of an entropic property to establish a convergence theorem (Main Theorem), which reveals that the conditional entropy measures the asymptotic Gaussianity. As an application, we establish the {\it entropic conditional central limit theorem} (CCLT), which is stronger than the classical CCLT. As another applic...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	422,975
1901.03904	A Speech Act Classifier for Persian Texts and its Application in Identifying Rumors	Speech Acts (SAs) are one of the important areas of pragmatics, which give us a better understanding of the state of mind of the people and convey an intended language function. Knowledge of the SA of a text can be helpful in analyzing that text in natural language processing applications. This study presents a diction...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	118,516
2310.12074	Towards Safer Operations: An Expert-involved Dataset of High-Pressure Gas Incidents for Preventing Future Failures	This paper introduces a new IncidentAI dataset for safety prevention. Different from prior corpora that usually contain a single task, our dataset comprises three tasks: named entity recognition, cause-effect extraction, and information retrieval. The dataset is annotated by domain experts who have at least six years o...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	400,894
0803.3608	The Category-Theoretic Arithmetic of Information	We highlight the underlying category-theoretic structure of measures of information flow. We present an axiomatic framework in which communication systems are represented as morphisms, and information flow is characterized by its behavior when communication systems are combined. Our framework includes a variety of disc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,483
2312.04494	AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making	With recent advances in multi-modal foundation models, the previously text-only large language models (LLM) have evolved to incorporate visual input, opening up unprecedented opportunities for various applications in visualization. Our work explores the utilization of the visual perception ability of multi-modal LLMs t...	true	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	413,692
1504.05662	Weakly Secure MDS Codes for Simple Multiple Access Networks	We consider a simple multiple access network (SMAN), where $k$ sources of unit rates transmit their data to a common sink via $n$ relays. Each relay is connected to the sink and to certain sources. A coding scheme (for the relays) is weakly secure if a passive adversary who eavesdrops on less than $k$ relay-sink links ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,302
2210.07845	Flame-state monitoring based on very low number of visible or infrared images via few-shot learning	The current success of machine learning on image-based combustion monitoring is based on massive data, which is costly even impossible for industrial applications. To address this conflict, we introduce few-shot learning in order to achieve combustion monitoring and classification for the first time. Two algorithms, Si...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	323,892
2310.18119	Towards a Unified Conversational Recommendation System: Multi-task Learning via Contextualized Knowledge Distillation	In Conversational Recommendation System (CRS), an agent is asked to recommend a set of items to users within natural language conversations. To address the need for both conversational capability and personalized recommendations, prior works have utilized separate recommendation and dialogue modules. However, such appr...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	403,400
2010.11264	An Efficient Real-Time NMPC for Quadrotor Position Control under Communication Time-Delay	The advances in computer processor technology have enabled the application of nonlinear model predictive control (NMPC) to agile systems, such as quadrotors. These systems are characterized by their underactuation, nonlinearities, bounded inputs, and time-delays. Classical control solutions fall short in overcoming the...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	202,172
2403.01926	IndicVoices: Towards building an Inclusive Multilingual Speech Dataset for Indian Languages	We present INDICVOICES, a dataset of natural and spontaneous speech containing a total of 7348 hours of read (9%), extempore (74%) and conversational (17%) audio from 16237 speakers covering 145 Indian districts and 22 languages. Of these 7348 hours, 1639 hours have already been transcribed, with a median of 73 hours p...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	434,639
1211.5735	Generalized Degrees of Freedom for Network-Coded Cognitive Interference Channel	We study a two-user cognitive interference channel (CIC) where one of the transmitters (primary) has knowledge of a linear combination (over an appropriate finite field) of the two information messages. We refer to this channel model as Network-Coded CIC, since the linear combination may be the result of some linear ne...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,916
2405.20117	Infinite 3D Landmarks: Improving Continuous 2D Facial Landmark Detection	In this paper, we examine 3 important issues in the practical use of state-of-the-art facial landmark detectors and show how a combination of specific architectural modifications can directly improve their accuracy and temporal stability. First, many facial landmark detectors require face normalization as a preprocessi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	459,205
1911.09126	Incompressibility of classical distributions	In blind compression of quantum states, a sender Alice is given a specimen of a quantum state $\rho$ drawn from a known ensemble (but without knowing what $\rho$ is), and she transmits sufficient quantum data to a receiver Bob so that he can decode a near perfect specimen of $\rho$. For many such states drawn iid from ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	154,410
2006.14004	Predicting First Passage Percolation Shapes Using Neural Networks	Many random growth models have the property that the set of discovered sites, scaled properly, converges to some deterministic set as time grows. Such results are known as shape theorems. Typically, not much is known about the shapes. For first passage percolation on $\mathbb{Z}^d$ we only know that the shape is convex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,092
2304.03093	Inductive Graph Unlearning	As a way to implement the "right to be forgotten" in machine learning, \textit{machine unlearning} aims to completely remove the contributions and information of the samples to be deleted from a trained model without affecting the contributions of other samples. Recently, many frameworks for machine unlearning have bee...	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	false	356,663
2404.02327	Robust Constrained Consensus and Inequality-constrained Distributed Optimization with Guaranteed Differential Privacy and Accurate Convergence	We address differential privacy for fully distributed optimization subject to a shared inequality constraint. By co-designing the distributed optimization mechanism and the differential-privacy noise injection mechanism, we propose the first distributed constrained optimization algorithm that can ensure both provable c...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	443,808
1801.02362	Acceleration of Mean Square Distance Calculations with Floating Close Structure in Metadynamics Simulations	Molecular dynamics simulates the~movements of atoms. Due to its high cost, many methods have been developed to "push the~simulation forward". One of them, metadynamics, can hasten the~molecular dynamics with the~help of variables describing the~simulated process. However, the~evaluation of these variables can include n...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	87,918
2410.11268	Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent	In-context learning has been recognized as a key factor in the success of Large Language Models (LLMs). It refers to the model's ability to learn patterns on the fly from provided in-context examples in the prompt during inference. Previous studies have demonstrated that the Transformer architecture used in LLMs can im...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	498,473
2501.15522	Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths	The committor functions are central to investigating rare but important events in molecular simulations. It is known that computing the committor function suffers from the curse of dimensionality. Recently, using neural networks to estimate the committor function has gained attention due to its potential for high-dimen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	527,597
2012.07450	FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health Monitoring	In-home health monitoring has attracted great attention for the ageing population worldwide. With the abundant user health data accessed by Internet of Things (IoT) devices and recent development in machine learning, smart healthcare has seen many successful stories. However, existing approaches for in-home health moni...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	211,458
1909.03198	Soft Policy Gradient Method for Maximum Entropy Deep Reinforcement Learning	Maximum entropy deep reinforcement learning (RL) methods have been demonstrated on a range of challenging continuous tasks. However, existing methods either suffer from severe instability when training on large off-policy data or cannot scale to tasks with very high state and action dimensionality such as 3D humanoid l...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	144,399
2005.07464	An Object Model for the Representation of Empirical Knowledge	We are currently designing an object oriented model which describes static and dynamical knowledge in diff{\'e}rent domains. It provides a twin conceptual level. The internal level proposes: the object structure composed of sub-objects hierarchy, structure evolution with dynamical functions, same type objects compariso...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	177,290
2011.00773	Using a Bi-directional LSTM Model with Attention Mechanism trained on MIDI Data for Generating Unique Music	Generating music is an interesting and challenging problem in the field of machine learning. Mimicking human creativity has been popular in recent years, especially in the field of computer vision and image processing. With the advent of GANs, it is possible to generate new similar images, based on trained data. But th...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	204,363
2102.11062	On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks	Bayesian neural networks (BNNs) are making significant progress in many research areas where decision-making needs to be accompanied by uncertainty estimation. Being able to quantify uncertainty while making decisions is essential for understanding when the model is over-/under-confident, and hence BNNs are attracting ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	221,315
2102.05047	Bounded Memory Active Learning through Enriched Queries	The explosive growth of easily-accessible unlabeled data has lead to growing interest in active learning, a paradigm in which data-hungry learning algorithms adaptively select informative examples in order to lower prohibitively expensive labeling costs. Unfortunately, in standard worst-case models of learning, the act...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,308
2308.14976	Efficient labeling of solar flux evolution videos by a deep learning model	Machine learning (ML) is becoming a critical tool for interrogation of large complex data. Labeling, defined as the process of adding meaningful annotations, is a crucial step of supervised ML. However, labeling datasets is time consuming. Here we show that convolutional neural networks (CNNs), trained on crudely label...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	388,515
2301.03774	How Data Scientists Review the Scholarly Literature	Keeping up with the research literature plays an important role in the workflow of scientists - allowing them to understand a field, formulate the problems they focus on, and develop the solutions that they contribute, which in turn shape the nature of the discipline. In this paper, we examine the literature review pra...	true	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	true	339,883
2312.03014	Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey	As artificial intelligence (AI) continues to rapidly evolve, the realm of Earth and atmospheric sciences is increasingly adopting data-driven models, powered by progressive developments in deep learning (DL). Specifically, DL techniques are extensively utilized to decode the chaotic and nonlinear aspects of Earth syste...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	413,093
1802.09700	Robust GANs against Dishonest Adversaries	Robustness of deep learning models is a property that has recently gained increasing attention. We explore a notion of robustness for generative adversarial models that is pertinent to their internal interactive structure, and show that, perhaps surprisingly, the GAN in its original form is not robust. Our notion of ro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	91,372
1704.05400	Waveform Design for Wireless Power Transfer with Limited Feedback	Waveform design is a key technique to jointly exploit a beamforming gain, the channel frequency-selectivity and the rectifier nonlinearity, so as to enhance the end-to-end power transfer efficiency of Wireless Power Transfer (WPT). Those waveforms have been designed assuming perfect channel state information at the tra...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	72,000
1904.12475	Over-the-Air Computation via Intelligent Reflecting Surfaces	Over-the-air computation (AirComp) becomes a promising approach for fast wireless data aggregation via exploiting the superposition property in a multiple access channel. To further overcome the unfavorable signal propagation conditions for AirComp, in this paper, we propose an intelligent reflecting surface (IRS) aide...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	129,122
1804.01405	R2RML Mappings in OBDA Systems: Enabling Comparison among OBDA Tools	In today's large enterprises there is a significant increasing trend in the amount of data that has to be stored and processed. To complicate this scenario the complexity of organizing and managing a large collection of data, structured according to a single, unified schema, makes so that there is almost never a single...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	94,218
2410.00683	Efficient Technical Term Translation: A Knowledge Distillation Approach for Parenthetical Terminology Translation	This paper addresses the challenge of accurately translating technical terms, which are crucial for clear communication in specialized fields. We introduce the Parenthetical Terminology Translation (PTT) task, designed to mitigate potential inaccuracies by displaying the original term in parentheses alongside its trans...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	493,460
2312.00467	Unfolder: Fast localization and image rectification of a document with a crease from folding in half	Presentation of folded documents is not an uncommon case in modern society. Digitizing such documents by capturing them with a smartphone camera can be tricky since a crease can divide the document contents into separate planes. To unfold the document, one could hold the edges potentially obscuring it in a captured ima...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,061
2406.03789	Enhancing Graph U-Nets for Mesh-Agnostic Spatio-Temporal Flow Prediction	This study aims to overcome the limitations of conventional deep-learning approaches based on convolutional neural networks in complex geometries and unstructured meshes by exploring the potential of Graph U-Nets for unsteady flow-field prediction. We present a comprehensive investigation of Graph U-Nets, originally de...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	461,390
2404.06657	Res-U2Net: Untrained Deep Learning for Phase Retrieval and Image Reconstruction	Conventional deep learning-based image reconstruction methods require a large amount of training data which can be hard to obtain in practice. Untrained deep learning methods overcome this limitation by training a network to invert a physical model of the image formation process. Here we present a novel untrained Res-U...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,539
2412.18464	MotifGPL: Motif-Enhanced Graph Prototype Learning for Deciphering Urban Social Segregation	Social segregation in cities, spanning racial, residential, and income dimensions, is becoming more diverse and severe. As urban spaces and social relations grow more complex, residents in metropolitan areas experience varying levels of social segregation. If left unaddressed, this could lead to increased crime rates, ...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	520,434
2308.01836	Subspace-Constrained Continuous Methane Leak Monitoring and Optimal Sensor Placement	This work presents a procedure that can quickly identify and isolate methane emission sources leading to expedient remediation. Minimizing the time required to identify a leak and the subsequent time to dispatch repair crews can significantly reduce the amount of methane released into the atmosphere. The procedure deve...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	383,383
1701.01930	Stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for Earth observation Level 2 product generation, Part 1 Theory	The European Space Agency (ESA) defines an Earth Observation (EO) Level 2 product as a multispectral (MS) image corrected for geometric, atmospheric, adjacency and topographic effects, stacked with its scene classification map (SCM), whose legend includes quality layers such as cloud and cloud-shadow. No ESA EO Level 2...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	66,475
2106.03734	Reveal of Vision Transformers Robustness against Adversarial Attacks	The major part of the vanilla vision transformer (ViT) is the attention block that brings the power of mimicking the global context of the input image. For better performance, ViT needs large-scale training data. To overcome this data hunger limitation, many ViT-based networks, or hybrid-ViT, have been proposed to incl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	239,427
2412.02474	F-SE-LSTM: A Time Series Anomaly Detection Method with Frequency Domain Information	With the development of society, time series anomaly detection plays an important role in network and IoT services. However, most existing anomaly detection methods directly analyze time series in the time domain and cannot distinguish some relatively hidden anomaly sequences. We attempt to analyze the impact of freque...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	513,551
1904.01739	SADIH: Semantic-Aware DIscrete Hashing	Due to its low storage cost and fast query speed, hashing has been recognized to accomplish similarity search in large-scale multimedia retrieval applications. Particularly supervised hashing has recently received considerable research attention by leveraging the label information to preserve the pairwise similarities ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	126,231
2411.00750	Mitigating Tail Narrowing in LLM Self-Improvement via Socratic-Guided Sampling	Self-improvement methods enable large language models (LLMs) to generate solutions themselves and iteratively train on filtered, high-quality rationales. This process proves effective and reduces the reliance on human supervision in LLMs' reasoning, but the performance soon plateaus. We delve into the process and find ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	504,730
2401.00523	Compressing Deep Image Super-resolution Models	Deep learning techniques have been applied in the context of image super-resolution (SR), achieving remarkable advances in terms of reconstruction performance. Existing techniques typically employ highly complex model structures which result in large model sizes and slow inference speeds. This often leads to high energ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	419,016
2410.08212	Learning Bipedal Walking for Humanoid Robots in Challenging Environments with Obstacle Avoidance	Deep reinforcement learning has seen successful implementations on humanoid robots to achieve dynamic walking. However, these implementations have been so far successful in simple environments void of obstacles. In this paper, we aim to achieve bipedal locomotion in an environment where obstacles are present using a po...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	497,009
2212.13899	Attentive Deep Neural Networks for Legal Document Retrieval	Legal text retrieval serves as a key component in a wide range of legal text processing tasks such as legal question answering, legal case entailment, and statute law retrieval. The performance of legal text retrieval depends, to a large extent, on the representation of text, both query and legal documents. Based on go...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	338,429
2207.00067	Rethinking Unsupervised Domain Adaptation for Semantic Segmentation	Unsupervised domain adaptation (UDA) adapts a model trained on one domain (called source) to a novel domain (called target) using only unlabeled data. Due to its high annotation cost, researchers have developed many UDA methods for semantic segmentation, which assume no labeled sample is available in the target domain....	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	305,624
1712.05231	Robust Estimation of Similarity Transformation for Visual Object Tracking	Most of existing correlation filter-based tracking approaches only estimate simple axis-aligned bounding boxes, and very few of them is capable of recovering the underlying similarity transformation. To tackle this challenging problem, in this paper, we propose a new correlation filter-based tracker with a novel robust...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	86,710
1805.11183	Semi-Implicit Variational Inference	Semi-implicit variational inference (SIVI) is introduced to expand the commonly used analytic variational distribution family, by mixing the variational parameter with a flexible distribution. This mixing distribution can assume any density function, explicit or not, as long as independent random samples can be generat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	98,855
2102.04951	MISO-wiLDCosts: Multi Information Source Optimization with Location Dependent Costs	This paper addresses black-box optimization over multiple information sources whose both fidelity and query cost change over the search space, that is they are location dependent. The approach uses: (i) an Augmented Gaussian Process, recently proposed in multi-information source optimization as a single model of the ob...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,277
2410.04906	Art2Mus: Bridging Visual Arts and Music through Cross-Modal Generation	Artificial Intelligence and generative models have revolutionized music creation, with many models leveraging textual or visual prompts for guidance. However, existing image-to-music models are limited to simple images, lacking the capability to generate music from complex digitized artworks. To address this gap, we in...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	495,490
1902.06385	Speeding up convolutional networks pruning with coarse ranking	Channel-based pruning has achieved significant successes in accelerating deep convolutional neural network, whose pipeline is an iterative three-step procedure: ranking, pruning and fine-tuning. However, this iterative procedure is computationally expensive. In this study, we present a novel computationally efficient c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	121,757
2309.07929	Prompting Segmentation with Sound Is Generalizable Audio-Visual Source Localizer	Never having seen an object and heard its sound simultaneously, can the model still accurately localize its visual position from the input audio? In this work, we concentrate on the Audio-Visual Localization and Segmentation tasks but under the demanding zero-shot and few-shot scenarios. To achieve this goal, different...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	391,964
2401.06197	Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications	We introduce Deformable Convolution v4 (DCNv4), a highly efficient and effective operator designed for a broad spectrum of vision applications. DCNv4 addresses the limitations of its predecessor, DCNv3, with two key enhancements: 1. removing softmax normalization in spatial aggregation to enhance its dynamic property a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	421,072
1910.06691	A 3D benchmark problem for crack propagation in brittle fracture	We propose a full 3D benchmark problem for brittle fracture based on experiments as well as a validation in the context of phase-field models. The example consists of a series of four-point bending tests on graphite specimens with sharp V-notches at different inclination angles. This simple setup leads to a mixed mode ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	149,408
2403.07748	Ariadne and Theseus: Exploration and Rendezvous with Two Mobile Agents in an Unknown Graph	We investigate two fundamental problems in mobile computing: exploration and rendezvous, with two distinct mobile agents in an unknown graph. The agents may communicate by reading and writing information on whiteboards that are located at all nodes. They both move along one adjacent edge at every time-step. In the expl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	437,013
2502.00047	HadamRNN: Binary and Sparse Ternary Orthogonal RNNs	Binary and sparse ternary weights in neural networks enable faster computations and lighter representations, facilitating their use on edge devices with limited computational power. Meanwhile, vanilla RNNs are highly sensitive to changes in their recurrent weights, making the binarization and ternarization of these wei...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	529,188
2307.01673	Disentanglement in a GAN for Unconditional Speech Synthesis	Can we develop a model that can synthesize realistic speech directly from a latent space, without explicit conditioning? Despite several efforts over the last decade, previous adversarial and diffusion-based approaches still struggle to achieve this, even on small-vocabulary datasets. To address this, we propose AudioS...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	377,433
2207.08799	Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit	There is mounting evidence of emergent phenomena in the capabilities of deep learning methods as we scale up datasets, model sizes, and training times. While there are some accounts of how these resources modulate statistical capacity, far less is known about their effect on the computational problem of model training....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	308,689
2407.02918	Free-SurGS: SfM-Free 3D Gaussian Splatting for Surgical Scene Reconstruction	Real-time 3D reconstruction of surgical scenes plays a vital role in computer-assisted surgery, holding a promise to enhance surgeons' visibility. Recent advancements in 3D Gaussian Splatting (3DGS) have shown great potential for real-time novel view synthesis of general scenes, which relies on accurate poses and point...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	469,945
2410.11133	3D-Prover: Diversity Driven Theorem Proving With Determinantal Point Processes	A key challenge in automated formal reasoning is the intractable search space, which grows exponentially with the depth of the proof. This branching is caused by the large number of candidate proof tactics which can be applied to a given goal. Nonetheless, many of these tactics are semantically similar or lead to an ex...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	498,401
2104.13923	Automated System for Ship Detection from Medium Resolution Satellite Optical Imagery	In this paper, we present a ship detection pipeline for low-cost medium resolution satellite optical imagery obtained from ESA Sentinel-2 and Planet Labs Dove constellations. This optical satellite imagery is readily available for any place on Earth and underutilized in the maritime domain, compared to existing solutio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,656
2203.08060	Seeking Commonness and Inconsistencies: A Jointly Smoothed Approach to Multi-view Subspace Clustering	Multi-view subspace clustering aims to discover the hidden subspace structures from multiple views for robust clustering, and has been attracting considerable attention in recent years. Despite significant progress, most of the previous multi-view subspace clustering algorithms are still faced with two limitations. Fir...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	285,662
1808.03733	Familia: A Configurable Topic Modeling Framework for Industrial Text Engineering	In the last decade, a variety of topic models have been proposed for text engineering. However, except Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation (LDA), most of existing topic models are seldom applied or considered in industrial scenarios. This phenomenon is caused by the fact that t...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	104,985
2006.03537	A Soft Humanoid Hand with In-Finger Visual Perception	We present a novel underactued humanoid five finger soft hand, the KIT \softhand, which is equipped with cameras in the fingertips and integrates a high performance embedded system for visual processing and control. We describe the actuation mechanism of the hand and the tendon-driven soft finger design with internally...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	180,344
2303.11616	HRDFuse: Monocular 360{\deg}Depth Estimation by Collaboratively Learning Holistic-with-Regional Depth Distributions	Depth estimation from a monocular 360{\deg} image is a burgeoning problem owing to its holistic sensing of a scene. Recently, some methods, \eg, OmniFusion, have applied the tangent projection (TP) to represent a 360{\deg}image and predicted depth values via patch-wise regressions, which are merged to get a depth map w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,925
2007.03014	Topic-based Community Search over Spatial-Social Networks (Technical Report)	Recently, the community search problem has attracted significant attention, due to its wide spectrum of real-world applications such as event organization, friend recommendation, advertisement in e-commence, and so on. Given a query vertex, the community search problem finds dense subgraph that contains the query verte...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	185,917
2306.02895	Evading Black-box Classifiers Without Breaking Eggs	Decision-based evasion attacks repeatedly query a black-box classifier to generate adversarial examples. Prior work measures the cost of such attacks by the total number of queries made to the classifier. We argue this metric is flawed. Most security-critical machine learning systems aim to weed out "bad" data (e.g., m...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	371,103
1607.03502	Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals	Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user's interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recomme...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	58,525
2202.10983	Tracking perovskite crystallization via deep learning-based feature detection on 2D X-ray scattering data	Understanding the processes of perovskite crystallization is essential for improving the properties of organic solar cells. In situ real-time grazing-incidence X-ray diffraction (GIXD) is a key technique for this task, but it produces large amounts of data, frequently exceeding the capabilities of traditional data proc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	281,737
1010.3172	CRT: A numerical tool for propagating ultra-high energy cosmic rays through Galactic magnetic field models	Deflection of ultra high energy cosmic rays (UHECRs) by the Galactic magnetic field (GMF) may be sufficiently strong to hinder identification of the UHECR source distribution. A common method for determining the effect of GMF models on source identification efforts is backtracking cosmic rays. We present the public num...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	7,916
2404.13378	Social Force Embedded Mixed Graph Convolutional Network for Multi-class Trajectory Prediction	Accurate prediction of agent motion trajectories is crucial for autonomous driving, contributing to the reduction of collision risks in human-vehicle interactions and ensuring ample response time for other traffic participants. Current research predominantly focuses on traditional deep learning methods, including convo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	448,272
2412.11803	UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models	Despite demonstrating impressive capabilities, Large Language Models (LLMs) still often struggle to accurately express the factual knowledge they possess, especially in cases where the LLMs' knowledge boundaries are ambiguous. To improve LLMs' factual expressions, we propose the UAlign framework, which leverages Uncert...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	517,589
2010.06122	Asking Crowdworkers to Write Entailment Examples: The Best of Bad Options	Large-scale natural language inference (NLI) datasets such as SNLI or MNLI have been created by asking crowdworkers to read a premise and write three new hypotheses, one for each possible semantic relationships (entailment, contradiction, and neutral). While this protocol has been used to create useful benchmark data, ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	200,373
2402.15552	Morphological Symmetries in Robotics	We present a comprehensive framework for studying and leveraging morphological symmetries in robotic systems. These are intrinsic properties of the robot's morphology, frequently observed in animal biology and robotics, which stem from the replication of kinematic structures and the symmetrical distribution of mass. We...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	432,185
2203.00417	Beam-Shape Effects and Noise Removal from THz Time-Domain Images in Reflection Geometry in the 0.25-6 THz Range	The increasing need of restoring high-resolution Hyper-Spectral (HS) images is determining a growing reliance on Computer Vision-based processing to enhance the clarity of the image content. HS images can, in fact, suffer from degradation effects or artefacts caused by instrument limitations. This paper focuses on a pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	282,991
2311.12489	Multilingual Word Embeddings for Low-Resource Languages using Anchors and a Chain of Related Languages	Very low-resource languages, having only a few million tokens worth of data, are not well-supported by multilingual NLP approaches due to poor quality cross-lingual word representations. Recent work showed that good cross-lingual performance can be achieved if a source language is related to the low-resource target lan...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	409,357
2209.12095	Identifying latent activity behaviors and lifestyles using mobility data to describe urban dynamics	Urbanization and its problems require an in-depth and comprehensive understanding of urban dynamics, especially the complex and diversified lifestyles in modern cities. Digitally acquired data can accurately capture complex human activity, but it lacks the interpretability of demographic data. In this paper, we study a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	319,413
1804.04273	VITAL: VIsual Tracking via Adversarial Learning	The tracking-by-detection framework consists of two stages, i.e., drawing samples around the target object in the first stage and classifying each sample as the target object or as background in the second stage. The performance of existing trackers using deep classification networks is limited by two aspects. First, t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,802
2406.16308	Anomaly Detection of Tabular Data Using LLMs	Large language models (LLMs) have shown their potential in long-context understanding and mathematical reasoning. In this paper, we study the problem of using LLMs to detect tabular anomalies and show that pre-trained LLMs are zero-shot batch-level anomaly detectors. That is, without extra distribution-specific model f...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	467,083
2106.13849	A CNN Segmentation-Based Approach to Object Detection and Tracking in Ultrasound Scans with Application to the Vagus Nerve Detection	Ultrasound scanning is essential in several medical diagnostic and therapeutic applications. It is used to visualize and analyze anatomical features and structures that influence treatment plans. However, it is both labor intensive, and its effectiveness is operator dependent. Real-time accurate and robust automatic de...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	243,199
2407.19794	Introducing a new hyper-parameter for RAG: Context Window Utilization	This paper introduces a new hyper-parameter for Retrieval-Augmented Generation (RAG) systems called Context Window Utilization. RAG systems enhance generative models by incorporating relevant information retrieved from external knowledge bases, improving the factual accuracy and contextual relevance of generated respon...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	476,928
2203.08421	WegFormer: Transformers for Weakly Supervised Semantic Segmentation	Although convolutional neural networks (CNNs) have achieved remarkable progress in weakly supervised semantic segmentation (WSSS), the effective receptive field of CNN is insufficient to capture global context information, leading to sub-optimal results. Inspired by the great success of Transformers in fundamental visi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,783
1904.07950	A Comprehensive Study of Alzheimer's Disease Classification Using Convolutional Neural Networks	A plethora of deep learning models have been developed for the task of Alzheimer's disease classification from brain MRI scans. Many of these models report high performance, achieving three-class classification accuracy of up to 95%. However, it is common for these studies to draw performance comparisons between models...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	127,918
1808.05258	Edge Coloring Technique to Remove Small Elementary Trapping Sets from Tanner Graph of QC-LDPC Codes with Column Weight 4	One of the phenomena that causes high decoding failure rates is trapping sets. Characterization of $(a,b)$ elementary trapping sets (ETSs), their graphical properties and the lower bounds on their size in variable regular LDPC codes with column weights 3, 4, 5 and 6, where $a$ is the size of the ETS and $b$ is the numb...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	105,314
1305.2440	Rate Region of the (4,3,3) Exact-Repair Regenerating Codes	Exact-repair regenerating codes are considered for the case (n,k,d)=(4,3,3), for which a complete characterization of the rate region is provided. This characterization answers in the affirmative the open question whether there exists a non-vanishing gap between the optimal bandwidth-storage tradeoff of the functional-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	24,515

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