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
1405.0514	Complexity of Equivalence and Learning for Multiplicity Tree Automata	We consider the complexity of equivalence and learning for multiplicity tree automata, i.e., weighted tree automata over a field. We first show that the equivalence problem is logspace equivalent to polynomial identity testing, the complexity of which is a longstanding open problem. Secondly, we derive lower bounds on ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	32,769
2305.05454	Restormer-Plus for Real World Image Deraining: One State-of-the-Art Solution to the GT-RAIN Challenge (CVPR 2023 UG2+ Track 3)	This technical report presents our Restormer-Plus approach, which was submitted to the GT-RAIN Challenge (CVPR 2023 UG$^2$+ Track 3). Details regarding the challenge are available at http://cvpr2023.ug2challenge.org/track3.html. Restormer-Plus outperformed all other submitted solutions in terms of peak signal-to-noise ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	363,154
2501.03287	OpenLKA: an open dataset of lane keeping assist from market autonomous vehicles	The Lane Keeping Assist (LKA) system has become a standard feature in recent car models. While marketed as providing auto-steering capabilities, the system's operational characteristics and safety performance remain underexplored, primarily due to a lack of real-world testing and comprehensive data. To fill this gap, w...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	522,829
1505.06651	A Logic of Knowing How	In this paper, we propose a single-agent modal logic framework for reasoning about goal-direct "knowing how" based on ideas from linguistics, philosophy, modal logic and automated planning. We first define a modal language to express "I know how to guarantee phi given psi" with a semantics not based on standard epistem...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	43,459
2502.09541	Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics	Despite the high computational throughput of GPUs, limited memory capacity and bandwidth-limited CPU-GPU communication via PCIe links remain significant bottlenecks for accelerating large-scale data analytics workloads. This paper introduces Vortex, a GPU-accelerated framework designed for data analytics workloads that...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	533,484
2402.17319	A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge -- Multi-Task Robustness Track	In this report, we present our solution to the multi-task robustness track of the 1st Visual Continual Learning (VCL) Challenge at ICCV 2023 Workshop. We propose a vanilla framework named UniNet that seamlessly combines various visual perception algorithms into a multi-task model. Specifically, we choose DETR3D, Mask2F...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	432,941
2010.01729	Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch	Spiking Neural Networks (SNNs) have recently emerged as an alternative to deep learning owing to sparse, asynchronous and binary event (or spike) driven processing, that can yield huge energy efficiency benefits on neuromorphic hardware. However, training high-accuracy and low-latency SNNs from scratch suffers from non...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	false	198,763
1211.4150	Efficiently Learning from Revealed Preference	In this paper, we consider the revealed preferences problem from a learning perspective. Every day, a price vector and a budget is drawn from an unknown distribution, and a rational agent buys his most preferred bundle according to some unknown utility function, subject to the given prices and budget constraint. We wis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	19,782
0907.0229	A new model of artificial neuron: cyberneuron and its use	This article describes a new type of artificial neuron, called the authors "cyberneuron". Unlike classical models of artificial neurons, this type of neuron used table substitution instead of the operation of multiplication of input values for the weights. This allowed to significantly increase the information capacity...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	4,011
2302.12349	Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws	Specifying reward functions for complex tasks like object manipulation or driving is challenging to do by hand. Reward learning seeks to address this by learning a reward model using human feedback on selected query policies. This shifts the burden of reward specification to the optimal design of the queries. We propos...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	347,526
1405.5769	Descriptor Matching with Convolutional Neural Networks: a Comparison to SIFT	Latest results indicate that features learned via convolutional neural networks outperform previous descriptors on classification tasks by a large margin. It has been shown that these networks still work well when they are applied to datasets or recognition tasks different from those they were trained on. However, desc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	33,302
1109.0736	Compression Aware Physical Database Design	Modern RDBMSs support the ability to compress data using methods such as null suppression and dictionary encoding. Data compression offers the promise of significantly reducing storage requirements and improving I/O performance for decision support queries. However, compression can also slow down update and query perfo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	11,962
2008.08285	Scalable Blocking for Very Large Databases	In the field of database deduplication, the goal is to find approximately matching records within a database. Blocking is a typical stage in this process that involves cheaply finding candidate pairs of records that are potential matches for further processing. We present here Hashed Dynamic Blocking, a new approach to...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	192,376
1805.00357	Domain and Geometry Agnostic CNNs for Left Atrium Segmentation in 3D Ultrasound	Segmentation of the left atrium and deriving its size can help to predict and detect various cardiovascular conditions. Automation of this process in 3D Ultrasound image data is desirable, since manual delineations are time-consuming, challenging and observer-dependent. Convolutional neural networks have made improveme...	false	false	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	96,426
1807.11190	Distributed Stochastic Optimization in Networks with Low Informational Exchange	We consider a distributed stochastic optimization problem in networks with finite number of nodes. Each node adjusts its action to optimize the global utility of the network, which is defined as the sum of local utilities of all nodes. Gradient descent method is a common technique to solve the optimization problem, whi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	104,127
2301.13710	On the Initialisation of Wide Low-Rank Feedforward Neural Networks	The edge-of-chaos dynamics of wide randomly initialized low-rank feedforward networks are analyzed. Formulae for the optimal weight and bias variances are extended from the full-rank to low-rank setting and are shown to follow from multiplicative scaling. The principle second order effect, the variance of the input-out...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,003
2111.03047	A deep ensemble approach to X-ray polarimetry	X-ray polarimetry will soon open a new window on the high energy universe with the launch of NASA's Imaging X-ray Polarimetry Explorer (IXPE). Polarimeters are currently limited by their track reconstruction algorithms, which typically use linear estimators and do not consider individual event quality. We present a mod...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	265,039
2009.01062	Decentralized Source Localization without Sensor Parameters in Wireless Sensor Networks	This paper studies the source (event) localization problem in decentralized wireless sensor networks (WSNs) under the fault model without knowing the sensor parameters. Event localizations have many applications such as localizing intruders, Wifi hotspots and users, and faults in power systems. Previous studies assume ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	194,215
2406.17135	Testing network clustering algorithms with Natural Language Processing	The advent of online social networks has led to the development of an abundant literature on the study of online social groups and their relationship to individuals' personalities as revealed by their textual productions. Social structures are inferred from a wide range of social interactions. Those interactions form c...	false	false	false	true	false	false	false	false	true	false	false	false	false	true	false	false	false	false	467,435
2306.00861	Non-stationary Reinforcement Learning under General Function Approximation	General function approximation is a powerful tool to handle large state and action spaces in a broad range of reinforcement learning (RL) scenarios. However, theoretical understanding of non-stationary MDPs with general function approximation is still limited. In this paper, we make the first such an attempt. We first ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	370,191
1811.02320	Hierarchical Neural Network Architecture In Keyword Spotting	Keyword Spotting (KWS) provides the start signal of ASR problem, and thus it is essential to ensure a high recall rate. However, its real-time property requires low computation complexity. This contradiction inspires people to find a suitable model which is small enough to perform well in multi environments. To deal wi...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	112,564
2306.14145	DSE-TTS: Dual Speaker Embedding for Cross-Lingual Text-to-Speech	Although high-fidelity speech can be obtained for intralingual speech synthesis, cross-lingual text-to-speech (CTTS) is still far from satisfactory as it is difficult to accurately retain the speaker timbres(i.e. speaker similarity) and eliminate the accents from their first language(i.e. nativeness). In this paper, we...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	375,572
1005.1871	Subfield-Subcodes of Generalized Toric codes	We study subfield-subcodes of Generalized Toric (GT) codes over $\mathbb{F}_{p^s}$. These are the multidimensional analogues of BCH codes, which may be seen as subfield-subcodes of generalized Reed-Solomon codes. We identify polynomial generators for subfield-subcodes of GT codes which allows us to determine the dimens...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	6,464
1408.5265	A Bayesian Ensemble Regression Framework on the Angry Birds Game	An ensemble inference mechanism is proposed on the Angry Birds domain. It is based on an efficient tree structure for encoding and representing game screenshots, where it exploits its enhanced modeling capability. This has the advantage to establish an informative feature space and modify the task of game playing to a ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	35,525
1611.07641	Sparse Phase Retrieval via Truncated Amplitude Flow	This paper develops a novel algorithm, termed \emph{SPARse Truncated Amplitude flow} (SPARTA), to reconstruct a sparse signal from a small number of magnitude-only measurements. It deals with what is also known as sparse phase retrieval (PR), which is \emph{NP-hard} in general and emerges in many science and engineerin...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	64,384
cs/0611080	A Multi-server Scheduling Framework for Resource Allocation in Wireless Multi-carrier Networks	Multiuser resource allocation has recently been recognized as an effective methodology for enhancing the power and spectrum efficiency in OFDM (orthogonal frequency division multiplexing) systems. It is, however, not directly applicable to current packet-switched networks, because (i) most existing packet-scheduling sc...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	539,883
1307.7223	Universal Polar Codes	Polar codes, invented by Arikan in 2009, are known to achieve the capacity of any binary-input memoryless output-symmetric channel. One of the few drawbacks of the original polar code construction is that it is not universal. This means that the code has to be tailored to the channel if we want to transmit close to cap...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	26,081
2407.11873	Variance Norms for Kernelized Anomaly Detection	We present a unified theory for Mahalanobis-type anomaly detection on Banach spaces, using ideas from Cameron-Martin theory applied to non-Gaussian measures. This approach leads to a basis-free, data-driven notion of anomaly distance through the so-called variance norm of a probability measure, which can be consistentl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	473,656
2203.10611	Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis	Building an accurate computer-aided diagnosis system based on data-driven approaches requires a large amount of high-quality labeled data. In medical imaging analysis, multiple expert annotators often produce subjective estimates about "ground truth labels" during the annotation process, depending on their expertise an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,610
1911.11260	Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem	Order dispatching and driver repositioning (also known as fleet management) in the face of spatially and temporally varying supply and demand are central to a ride-sharing platform marketplace. Hand-crafting heuristic solutions that account for the dynamics in these resource allocation problems is difficult, and may be...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	155,063
2211.03363	Over-The-Air Clustered Wireless Federated Learning	Privacy and bandwidth constraints have led to the use of federated learning (FL) in wireless systems, where training a machine learning (ML) model is accomplished collaboratively without sharing raw data. While using bandwidth-constrained uplink wireless channels, over-the-air (OTA) FL is preferred since the clients ca...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	328,910
2307.12621	A Degree Bound For The c-Boomerang Uniformity Of Permutation Monomials	Let $\mathbb{F}_q$ be a finite field of characteristic $p$. In this paper we prove that the $c$-Boomerang Uniformity, $c \neq 0$, for all permutation monomials $x^d$, where $d > 1$ and $p \nmid d$, is bounded by $d^2$. Further, we utilize this bound to estimate the $c$-boomerang uniformity of a large class of Generaliz...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	381,325
2006.13863	Feedback Graph Attention Convolutional Network for Medical Image Enhancement	Artifacts, blur and noise are the common distortions degrading MRI images during the acquisition process, and deep neural networks have been demonstrated to help in improving image quality. To well exploit global structural information and texture details, we propose a novel biomedical image enhancement network, named ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	184,054
1909.04868	Is Heuristic Sampling Necessary in Training Deep Object Detectors?	To train accurate deep object detectors under the extreme foreground-background imbalance, heuristic sampling methods are always necessary, which either re-sample a subset of all training samples (hard sampling methods, \eg biased sampling, OHEM), or use all training samples but re-weight them discriminatively (soft sa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	144,926
2408.00323	A Novel Edge Laplacian-based Approach for Adaptive Formation Control of Uncertain Multi-agent Systems with Unified Relative Error Performance	For most existing prescribed performance formation control methods, performance requirements are not directly imposed on the relative states between agents but on the consensus error, which lacks a clear physical interpretation of their solution. In this paper, we propose a novel adaptive prescribed performance formati...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	477,793
2212.00937	StructVPR: Distill Structural Knowledge with Weighting Samples for Visual Place Recognition	Visual place recognition (VPR) is usually considered as a specific image retrieval problem. Limited by existing training frameworks, most deep learning-based works cannot extract sufficiently stable global features from RGB images and rely on a time-consuming re-ranking step to exploit spatial structural information fo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,248
2405.03177	Transformer-based RGB-T Tracking with Channel and Spatial Feature Fusion	How to better fuse cross-modal features is the core issue of RGB-T tracking. Some previous methods either insufficiently fuse RGB and TIR features, or depend on intermediaries containing information from both modalities to achieve cross-modal information interaction. The former does not fully exploit the potential of u...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	452,082
2001.00102	The Gambler's Problem and Beyond	We analyze the Gambler's problem, a simple reinforcement learning problem where the gambler has the chance to double or lose the bets until the target is reached. This is an early example introduced in the reinforcement learning textbook by Sutton and Barto (2018), where they mention an interesting pattern of the optim...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	159,132
1209.3113	Detection and Classification of Viewer Age Range Smart Signs at TV Broadcast	In this paper, the identification and classification of Viewer Age Range Smart Signs, designed by the Radio and Television Supreme Council of Turkey, to give age range information for the TV viewers, are realized. Therefore, the automatic detection at the broadcast will be possible, enabling the manufacturing of TV rec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	18,557
1810.03286	Guiding Intelligent Surveillance System by learning-by-synthesis gaze estimation	We describe a novel learning-by-synthesis method for estimating gaze direction of an automated intelligent surveillance system. Recently, progress in learning-by-synthesis has proposed training models on synthetic images, which can effectively reduce the cost of manpower and material resources. However, learning from s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	109,779
2011.01483	Design Paradigms Based on Spring Agonists for Underactuated Robot Hands: Concepts and Application	In this paper, we focus on a rarely used paradigm in the design of underactuated robot hands: the use of springs as agonists and tendons as antagonists. We formalize this approach in a design matrix also considering its interplay with the underactuation method used (one tendon for multiple joints vs. multiple tendons o...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	204,603
2403.03270	Bi-KVIL: Keypoints-based Visual Imitation Learning of Bimanual Manipulation Tasks	Visual imitation learning has achieved impressive progress in learning unimanual manipulation tasks from a small set of visual observations, thanks to the latest advances in computer vision. However, learning bimanual coordination strategies and complex object relations from bimanual visual demonstrations, as well as g...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	435,126
2408.14072	Hybrid SIC Aided Hybrid NOMA: A New Approach For Improving Energy Efficiency	Hybrid non-orthogonal multiple access (NOMA), which organically combines pure NOMA and conventional OMA, has recently received significant attention to be a promising multiple access framework for future wireless communication networks. However, most of the literatures on hybrid NOMA only consider fixed order of succes...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	483,410
2405.09955	Dual-band feature selection for maturity classification of specialty crops by hyperspectral imaging	The maturity classification of specialty crops such as strawberries and tomatoes is an essential agricultural downstream activity for selective harvesting and quality control (QC) at production and packaging sites. Recent advancements in Deep Learning (DL) have produced encouraging results in color images for maturity ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	454,598
2207.02739	Robust Counterfactual Explanations for Tree-Based Ensembles	Counterfactual explanations inform ways to achieve a desired outcome from a machine learning model. However, such explanations are not robust to certain real-world changes in the underlying model (e.g., retraining the model, changing hyperparameters, etc.), questioning their reliability in several applications, e.g., c...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	306,606
2108.02028	Incorporating Learnt Local and Global Embeddings into Monocular Visual SLAM	Traditional approaches for Visual Simultaneous Localization and Mapping (VSLAM) rely on low-level vision information for state estimation, such as handcrafted local features or the image gradient. While significant progress has been made through this track, under more challenging configuration for monocular VSLAM, e.g....	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	249,200
2407.05375	Online Drift Detection with Maximum Concept Discrepancy	Continuous learning from an immense volume of data streams becomes exceptionally critical in the internet era. However, data streams often do not conform to the same distribution over time, leading to a phenomenon called concept drift. Since a fixed static model is unreliable for inferring concept-drifted data streams,...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	470,949
2009.00089	Random Forest (RF) Kernel for Regression, Classification and Survival	Breiman's random forest (RF) can be interpreted as an implicit kernel generator,where the ensuing proximity matrix represents the data-driven RF kernel. Kernel perspective on the RF has been used to develop a principled framework for theoretical investigation of its statistical properties. However, practical utility of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,946
2303.16378	A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion	Despite the record-breaking performance in Text-to-Image (T2I) generation by Stable Diffusion, less research attention is paid to its adversarial robustness. In this work, we study the problem of adversarial attack generation for Stable Diffusion and ask if an adversarial text prompt can be obtained even in the absence...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,835
1803.06508	MergeNet: A Deep Net Architecture for Small Obstacle Discovery	We present here, a novel network architecture called MergeNet for discovering small obstacles for on-road scenes in the context of autonomous driving. The basis of the architecture rests on the central consideration of training with less amount of data since the physical setup and the annotation process for small obsta...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	92,850
2104.03391	Interpreting Verbal Metaphors by Paraphrasing	Metaphorical expressions are difficult linguistic phenomena, challenging diverse Natural Language Processing tasks. Previous works showed that paraphrasing a metaphor as its literal counterpart can help machines better process metaphors on downstream tasks. In this paper, we interpret metaphors with BERT and WordNet hy...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	229,047
2411.15180	Multi-layer matrix factorization for cancer subtyping using full and partial multi-omics dataset	Cancer, with its inherent heterogeneity, is commonly categorized into distinct subtypes based on unique traits, cellular origins, and molecular markers specific to each type. However, current studies primarily rely on complete multi-omics datasets for predicting cancer subtypes, often overlooking predictive performance...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	510,472
2412.12648	Exploring AI-Enabled Cybersecurity Frameworks: Deep-Learning Techniques, GPU Support, and Future Enhancements	Traditional rule-based cybersecurity systems have proven highly effective against known malware threats. However, they face challenges in detecting novel threats. To address this issue, emerging cybersecurity systems are incorporating AI techniques, specifically deep-learning algorithms, to enhance their ability to det...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	true	517,965
2208.10940	Evaluating Out-of-Distribution Detectors Through Adversarial Generation of Outliers	A reliable evaluation method is essential for building a robust out-of-distribution (OOD) detector. Current robustness evaluation protocols for OOD detectors rely on injecting perturbations to outlier data. However, the perturbations are unlikely to occur naturally or not relevant to the content of data, providing a li...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	314,260
2406.16086	SEAM: A Stochastic Benchmark for Multi-Document Tasks	Various tasks, such as summarization, multi-hop question answering, or coreference resolution, are naturally phrased over collections of real-world documents. Such tasks present a unique set of challenges, revolving around the lack of coherent narrative structure across documents, which often leads to contradiction, om...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	466,995
1901.09901	Asymptotic Performance Analysis of Generalized User Selection for Interference-Limited Multiuser Secondary Networks	We analyze the asymptotic performance of a generalized multiuser diversity scheme for an interference-limited secondary multiuser network of underlay cognitive radio systems. Assuming a large number of secondary users and that the noise at each secondary user's receiver is negligible compared to the interference from t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	119,875
2202.02172	Facebook's Architecture Undermines Vaccine Misinformation Removal Efforts	Misinformation promotes distrust in science, undermines public health, and may drive civil unrest. Vaccine misinformation, in particular, has stalled efforts to overcome the COVID-19 pandemic, prompting social media platforms' attempts to reduce it. Some have questioned whether "soft" content moderation remedies -- e.g...	false	false	false	true	false	false	false	false	false	false	true	false	false	true	false	false	false	false	278,720
1904.02536	Graph clustering in industrial networks	The present work investigates clustering of a graph-based representation of industrial connections derived from international trade data by Hidalgo et al (2007) and confirms existence of around ten industrial clusters that are reasonably consistent with expected historical patterns of diffusion of innovation and techno...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	126,457
2205.14756	EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction	High-resolution dense prediction enables many appealing real-world applications, such as computational photography, autonomous driving, etc. However, the vast computational cost makes deploying state-of-the-art high-resolution dense prediction models on hardware devices difficult. This work presents EfficientViT, a new...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	299,477
2301.09800	Improving Responsiveness to Robots for Tacit Human-Robot Interaction via Implicit and Naturalistic Team Status Projection	Fluent human-human teaming is often characterized by tacit interaction without explicit communication. This is because explicit communication, such as language utterances and gestures, are inherently interruptive. On the other hand, tacit interaction requires team situation awareness (TSA) to facilitate, which often re...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	341,609
2212.00479	Noisy Label Classification using Label Noise Selection with Test-Time Augmentation Cross-Entropy and NoiseMix Learning	As the size of the dataset used in deep learning tasks increases, the noisy label problem, which is a task of making deep learning robust to the incorrectly labeled data, has become an important task. In this paper, we propose a method of learning noisy label data using the label noise selection with test-time augmenta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,071
2206.13418	Belief-selective Propagation Detection for MIMO Systems	Compared to the linear MIMO detectors, the Belief Propagation (BP) detector has shown greater capabilities in achieving near optimal performance and better nature to iteratively cooperate with channel decoders. Aiming at real applications, recent works mainly fall into the category of reducing the complexity by simplif...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	304,962
2402.10001	Privacy Attacks in Decentralized Learning	Decentralized Gradient Descent (D-GD) allows a set of users to perform collaborative learning without sharing their data by iteratively averaging local model updates with their neighbors in a network graph. The absence of direct communication between non-neighbor nodes might lead to the belief that users cannot infer p...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	429,763
2004.07715	Taxonomy of Dual Block-Coordinate Ascent Methods for Discrete Energy Minimization	We consider the maximum-a-posteriori inference problem in discrete graphical models and study solvers based on the dual block-coordinate ascent rule. We map all existing solvers in a single framework, allowing for a better understanding of their design principles. We theoretically show that some block-optimizing update...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	172,857
2105.03979	Improving Patent Mining and Relevance Classification using Transformers	Patent analysis and mining are time-consuming and costly processes for companies, but nevertheless essential if they are willing to remain competitive. To face the overload induced by numerous patents, the idea is to automatically filter them, bringing only few to read to experts. This paper reports a successful applic...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	234,337
2205.05068	Secure and Private Source Coding with Private Key and Decoder Side Information	The problem of secure source coding with multiple terminals is extended by considering a remote source whose noisy measurements are the correlated random variables used for secure source reconstruction. The main additions to the problem include 1) all terminals noncausally observe a noisy measurement of the remote sour...	false	false	false	false	false	true	true	false	false	true	false	false	true	false	false	false	false	false	295,830
2411.01101	How Effective Is Self-Consistency for Long-Context Problems?	Self-consistency (SC) has been demonstrated to enhance the performance of large language models (LLMs) across various tasks and domains involving short content. However, does this evidence support its effectiveness for long-context problems? This study examines the role of SC in long-context scenarios, where LLMs often...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	504,910
1508.03720	Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Path	Relation classification is an important research arena in the field of natural language processing (NLP). In this paper, we present SDP-LSTM, a novel neural network to classify the relation of two entities in a sentence. Our neural architecture leverages the shortest dependency path (SDP) between two entities; multicha...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	46,032
2405.00611	Addressing Topic Granularity and Hallucination in Large Language Models for Topic Modelling	Large language models (LLMs) with their strong zero-shot topic extraction capabilities offer an alternative to probabilistic topic modelling and closed-set topic classification approaches. As zero-shot topic extractors, LLMs are expected to understand human instructions to generate relevant and non-hallucinated topics ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	450,985
2012.13658	Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards	A major challenge in reinforcement learning is the design of exploration strategies, especially for environments with sparse reward structures and continuous state and action spaces. Intuitively, if the reinforcement signal is very scarce, the agent should rely on some form of short-term memory in order to cover its en...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	213,286
2309.11528	Learning Complete Topology-Aware Correlations Between Relations for Inductive Link Prediction	Inductive link prediction -- where entities during training and inference stages can be different -- has shown great potential for completing evolving knowledge graphs in an entity-independent manner. Many popular methods mainly focus on modeling graph-level features, while the edge-level interactions -- especially the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	393,444
2212.00060	Capacity of an infinite family of networks related to the diamond network for fixed alphabet sizes	We consider the problem of error correction in a network where the errors can occur only on a proper subset of the network edges. For a generalization of the so-called Diamond Network we consider lower and upper bounds for the network's (1-shot) capacity for fixed alphabet sizes.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	333,936
2104.12106	Temp-Frustum Net: 3D Object Detection with Temporal Fusion	3D object detection is a core component of automated driving systems. State-of-the-art methods fuse RGB imagery and LiDAR point cloud data frame-by-frame for 3D bounding box regression. However, frame-by-frame 3D object detection suffers from noise, field-of-view obstruction, and sparsity. We propose a novel Temporal F...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,117
2407.04180	Slice-100K: A Multimodal Dataset for Extrusion-based 3D Printing	G-code (Geometric code) or RS-274 is the most widely used computer numerical control (CNC) and 3D printing programming language. G-code provides machine instructions for the movement of the 3D printer, especially for the nozzle, stage, and extrusion of material for extrusion-based additive manufacturing. Currently ther...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,455
2310.04714	Generalized Robust Test-Time Adaptation in Continuous Dynamic Scenarios	Test-time adaptation (TTA) adapts the pre-trained models to test distributions during the inference phase exclusively employing unlabeled test data streams, which holds great value for the deployment of models in real-world applications. Numerous studies have achieved promising performance on simplistic test streams, c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	397,783
1704.02914	Kinematic analysis of geared robotic mechanism using matroid and T-T graph methods	In this paper, the kinematic structure of the geared robotic mechanism (GRM) is investigated with the aid of two different methods which are based on directed graphs and the methods are compared. One of the methods is Matroid Method developed by Talpasanu and the other method is Tsai-Tokad (T-T) Graph method developed ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	71,537
2412.02646	Interpretable Generalized Additive Models for Datasets with Missing Values	Many important datasets contain samples that are missing one or more feature values. Maintaining the interpretability of machine learning models in the presence of such missing data is challenging. Singly or multiply imputing missing values complicates the model's mapping from features to labels. On the other hand, rea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	513,622
2111.11647	Inducing Functions through Reinforcement Learning without Task Specification	We report a bio-inspired framework for training a neural network through reinforcement learning to induce high level functions within the network. Based on the interpretation that animals have gained their cognitive functions such as object recognition - without ever being specifically trained for - as a result of maxi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	267,727
2411.14678	Reinterpreting PID Controller From the Perspective of State Feedback and Lumped Disturbance Compensation	This paper analyzes the motion of solutions to non-homogeneous linear differential equations. It further clarifies that a proportional-integral-derivative (PID) controller essentially comprises two parts: a homogeneous controller and a disturbance observer, which are responsible for stabilizing the homogeneous system a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	510,269
2410.13139	See Behind Walls in Real-time Using Aerial Drones and Augmented Reality	This work presents ARD2, a framework that enables real-time through-wall surveillance using two aerial drones and an augmented reality (AR) device. ARD2 consists of two main steps: target direction estimation and contour reconstruction. In the first stage, ARD2 leverages geometric relationships between the drones, the ...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	499,387
2408.02455	A Surprisingly Efficient Representation for Multi-Finger Grasping	The problem of grasping objects using a multi-finger hand has received significant attention in recent years. However, it remains challenging to handle a large number of unfamiliar objects in real and cluttered environments. In this work, we propose a representation that can be effectively mapped to the multi-finger gr...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	478,646
1406.3976	Handling non-compositionality in multilingual CNLs	In this paper, we describe methods for handling multilingual non-compositional constructions in the framework of GF. We specifically look at methods to detect and extract non-compositional phrases from parallel texts and propose methods to handle such constructions in GF grammars. We expect that the methods to handle n...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	33,896
2502.11986	Selective Task Group Updates for Multi-Task Optimization	Multi-task learning enables the acquisition of task-generic knowledge by training multiple tasks within a unified architecture. However, training all tasks together in a single architecture can lead to performance degradation, known as negative transfer, which is a main concern in multi-task learning. Previous works ha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	534,633
2112.10878	Enabling NAS with Automated Super-Network Generation	Recent Neural Architecture Search (NAS) solutions have produced impressive results training super-networks and then deriving subnetworks, a.k.a. child models that outperform expert-crafted models from a pre-defined search space. Efficient and robust subnetworks can be selected for resource-constrained edge devices, all...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	272,544
2205.07477	Manifold Characteristics That Predict Downstream Task Performance	Pretraining methods are typically compared by evaluating the accuracy of linear classifiers, transfer learning performance, or visually inspecting the representation manifold's (RM) lower-dimensional projections. We show that the differences between methods can be understood more clearly by investigating the RM directl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	296,618
1304.3118	On Implementing Usual Values	In many cases commonsense knowledge consists of knowledge of what is usual. In this paper we develop a system for reasoning with usual information. This system is based upon the fact that these pieces of commonsense information involve both a probabilistic aspect and a granular aspect. We implement this system with the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,834
2305.15728	A Tutorial on Holographic MIMO Communications--Part I: Channel Modeling and Channel Estimation	By integrating a nearly infinite number of reconfigurable elements into a finite space, a spatially continuous array aperture is formed for holographic multiple-input multiple-output (HMIMO) communications. This three-part tutorial aims for providing an overview of the latest advances in HMIMO communications. As Part I...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	367,747
0705.1399	A New Concept of Modular Parallel Mechanism for Machining Applications	The subject of this paper is the design of a new concept of modular parallel mechanisms for three, four or five-axis machining applications. Most parallel mechanisms are designed for three- or six-axis machining applications. In the last case, the position and the orientation of the tool are coupled and the shape of th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	215
2410.09761	ChartKG: A Knowledge-Graph-Based Representation for Chart Images	Chart images, such as bar charts, pie charts, and line charts, are explosively produced due to the wide usage of data visualizations. Accordingly, knowledge mining from chart images is becoming increasingly important, which can benefit downstream tasks like chart retrieval and knowledge graph completion. However, exist...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	497,760
2312.11770	Bridging the Gap: Generalising State-of-the-Art U-Net Models to Sub-Saharan African Populations	A critical challenge for tumour segmentation models is the ability to adapt to diverse clinical settings, particularly when applied to poor-quality neuroimaging data. The uncertainty surrounding this adaptation stems from the lack of representative datasets, leaving top-performing models without exposure to common arti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	416,704
1103.3174	A Longitudinal Study of Social Media Privacy Behavior	Existing constructs for privacy concerns and behaviors do not adequately model deviations between user attitudes and behaviors. Although a number of studies have examined supposed deviations from rationality by online users, true explanations for these behaviors may lie in factors not previously addressed in privacy co...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	9,637
2308.09921	Recap: Detecting Deepfake Video with Unpredictable Tampered Traces via Recovering Faces and Mapping Recovered Faces	The exploitation of Deepfake techniques for malicious intentions has driven significant research interest in Deepfake detection. Deepfake manipulations frequently introduce random tampered traces, leading to unpredictable outcomes in different facial regions. However, existing detection methods heavily rely on specific...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	386,486
2404.17302	Part-Guided 3D RL for Sim2Real Articulated Object Manipulation	Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots. Existing learning-based solutions mainly focus on visual affordance learning or other pre-trained visual models to guide manipulation policies, which face challenges for novel instances in real-world scen...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	449,813
2004.02804	Mapping individual differences in cortical architecture using multi-view representation learning	In neuroscience, understanding inter-individual differences has recently emerged as a major challenge, for which functional magnetic resonance imaging (fMRI) has proven invaluable. For this, neuroscientists rely on basic methods such as univariate linear correlations between single brain features and a score that quant...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	171,349
2408.13520	An Open, Cross-Platform, Web-Based Metaverse Using WebXR and A-Frame	The metaverse has received much attention in the literature and industry in the last few years, but the lack of an open and cross-platform architecture has led to many distinct metaverses that cannot communicate with each other. This work proposes a WebXR-based cross-platform architecture for developing spatial web app...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	483,178
1701.05432	Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition	Most successful deep learning algorithms for action recognition extend models designed for image-based tasks such as object recognition to video. Such extensions are typically trained for actions on single video frames or very short clips, and then their predictions from sliding-windows over the video sequence are pool...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	66,985
2009.00826	PANE: scalable and effective attributed network embedding	Given a graph G where each node is associated with a set of attributes, attributed network embedding (ANE) maps each node v in G to a compact vector Xv, which can be used in downstream machine learning tasks. Ideally, Xv should capture node v's affinity to each attribute, which considers not only v's own attribute asso...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	194,152
2010.00030	Fast Decomposition of Temporal Logic Specifications for Heterogeneous Teams	In this work, we focus on decomposing large multi-agent path planning problems with global temporal logic goals (common to all agents) into smaller sub-problems that can be solved and executed independently. Crucially, the sub-problems' solutions must jointly satisfy the common global mission specification. The agents'...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	198,159
2001.01026	Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings	We introduce a new video synthesis task: synthesizing time lapse videos depicting how a given painting might have been created. Artists paint using unique combinations of brushes, strokes, and colors. There are often many possible ways to create a given painting. Our goal is to learn to capture this rich range of possi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	159,379
2303.07582	Calibrated Teacher for Sparsely Annotated Object Detection	Fully supervised object detection requires training images in which all instances are annotated. This is actually impractical due to the high labor and time costs and the unavoidable missing annotations. As a result, the incomplete annotation in each image could provide misleading supervision and harm the training. Rec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,300

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