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
2105.00310	MARL: Multimodal Attentional Representation Learning for Disease Prediction	Existing learning models often utilise CT-scan images to predict lung diseases. These models are posed by high uncertainties that affect lung segmentation and visual feature learning. We introduce MARL, a novel Multimodal Attentional Representation Learning model architecture that learns useful features from multimodal...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	233,169
2011.09567	Predicting metrical patterns in Spanish poetry with language models	In this paper, we compare automated metrical pattern identification systems available for Spanish against extensive experiments done by fine-tuning language models trained on the same task. Despite being initially conceived as a model suitable for semantic tasks, our results suggest that BERT-based models retain enough...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	207,226
1603.02514	Variational Autoencoders for Semi-supervised Text Classification	Although semi-supervised variational autoencoder (SemiVAE) works in image classification task, it fails in text classification task if using vanilla LSTM as its decoder. From a perspective of reinforcement learning, it is verified that the decoder's capability to distinguish between different categorical labels is esse...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	53,019
2403.16205	Blur2Blur: Blur Conversion for Unsupervised Image Deblurring on Unknown Domains	This paper presents an innovative framework designed to train an image deblurring algorithm tailored to a specific camera device. This algorithm works by transforming a blurry input image, which is challenging to deblur, into another blurry image that is more amenable to deblurring. The transformation process, from one...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,924
2306.08424	Selective Concept Models: Permitting Stakeholder Customisation at Test-Time	Concept-based models perform prediction using a set of concepts that are interpretable to stakeholders. However, such models often involve a fixed, large number of concepts, which may place a substantial cognitive load on stakeholders. We propose Selective COncept Models (SCOMs) which make predictions using only a subs...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	373,410
2406.14594	Age of Information Versions: a Semantic View of Markov Source Monitoring	We consider the problem of real-time remote monitoring of a two-state Markov process, where a sensor observes the state of the source and makes a decision on whether to transmit the status updates over an unreliable channel or not. We introduce a modified randomized stationary sampling and transmission policy where the...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	true	466,389
2411.07503	A Novel Automatic Real-time Motion Tracking Method for Magnetic Resonance Imaging-guided Radiotherapy: Leveraging the Enhanced Tracking-Learning-Detection Framework with Automatic Segmentation	Background and Purpose: Accurate motion tracking in MRI-guided Radiotherapy (MRIgRT) is essential for effective treatment delivery. This study aimed to enhance motion tracking precision in MRIgRT through an automatic real-time markerless tracking method using an enhanced Tracking-Learning-Detection (ETLD) framework wit...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	507,553
2010.14492	Asymptotic Bounds on the Rate of Locally Repairable Codes	New asymptotic upper bounds are presented on the rate of sequences of locally repairable codes (LRCs) with a prescribed relative minimum distance and locality over a finite field $F$. The bounds apply to LRCs in which the recovery functions are linear; in particular, the bounds apply to linear LRCs over $F$. The new bo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	203,462
2306.04299	Timing Process Interventions with Causal Inference and Reinforcement Learning	The shift from the understanding and prediction of processes to their optimization offers great benefits to businesses and other organizations. Precisely timed process interventions are the cornerstones of effective optimization. Prescriptive process monitoring (PresPM) is the sub-field of process mining that concentra...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	371,687
1603.09429	Ordinal Conditional Functions for Nearly Counterfactual Revision	We are interested in belief revision involving conditional statements where the antecedent is almost certainly false. To represent such problems, we use Ordinal Conditional Functions that may take infinite values. We model belief change in this context through simple arithmetical operations that allow us to capture the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	53,915
2211.15081	Mitigating Overfitting in Graph Neural Networks via Feature and Hyperplane Perturbation	Graph neural networks (GNNs) are commonly used in semi-supervised settings. Previous research has primarily focused on finding appropriate graph filters (e.g. aggregation methods) to perform well on both homophilic and heterophilic graphs. While these methods are effective, they can still suffer from the sparsity of no...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	333,112
1910.00838	Data-Driven Identification of Rayleigh-Damped Second-Order Systems	In this paper, we present a data-driven approach to identify second-order systems, having internal Rayleigh damping. This means that the damping matrix is given as a linear combination of the mass and stiffness matrices. These systems typically appear when performing various engineering studies, e.g., vibrational and s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	147,776
2308.08148	Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series	Learning directed acyclic graphs (DAGs) to identify causal relations underlying observational data is crucial but also poses significant challenges. Recently, topology-based methods have emerged as a two-step approach to discovering DAGs by first learning the topological ordering of variables and then eliminating redun...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	385,781
0903.0735	Modeling the Experience of Emotion	Affective computing has proven to be a viable field of research comprised of a large number of multidisciplinary researchers resulting in work that is widely published. The majority of this work consists of computational models of emotion recognition, computational modeling of causal factors of emotion and emotion expr...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	3,285
1908.02435	Improved Adversarial Robustness by Reducing Open Space Risk via Tent Activations	Adversarial examples contain small perturbations that can remain imperceptible to human observers but alter the behavior of even the best performing deep learning models and yield incorrect outputs. Since their discovery, adversarial examples have drawn significant attention in machine learning: researchers try to reve...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	141,002
2310.12544	Neural Likelihood Approximation for Integer Valued Time Series Data	Stochastic processes defined on integer valued state spaces are popular within the physical and biological sciences. These models are necessary for capturing the dynamics of small systems where the individual nature of the populations cannot be ignored and stochastic effects are important. The inference of the paramete...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	401,063
1905.11293	Underactuation Design for Tendon-driven Hands via Optimization of Mechanically Realizable Manifolds in Posture and Torque Spaces	Grasp synergies represent a useful idea to reduce grasping complexity without compromising versatility. Synergies describe coordination patterns between joints, either in terms of position (joint angles) or effort (joint torques). In both of these cases, a grasp synergy can be represented as a low-dimensional manifold ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	132,385
1912.07195	Fingerprint Synthesis: Search with 100 Million Prints	Evaluation of large-scale fingerprint search algorithms has been limited due to lack of publicly available datasets. To address this problem, we utilize a Generative Adversarial Network (GAN) to synthesize a fingerprint dataset consisting of 100 million fingerprint images. In contrast to existing fingerprint synthesis ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,541
2408.03626	On the choice of the non-trainable internal weights in random feature maps	The computationally cheap machine learning architecture of random feature maps can be viewed as a single-layer feedforward network in which the weights of the hidden layer are random but fixed and only the outer weights are learned via linear regression. The internal weights are typically chosen from a prescribed distr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	479,095
2412.15224	Multi-Branch Mutual-Distillation Transformer for EEG-Based Seizure Subtype Classification	Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in precise epilepsy diagnostics. Deep learning is a promising solution, due to its ability to automatically extract latent patterns. However, it usually requires a large amount of training data, which may not always be avail...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	518,993
2311.08933	Design and Implementation of a Hybrid Wireless Power and Communication System for Medical Implants	Data collection and analysis from multiple implant nodes in humans can provide targeted medicine and treatment strategies that can prevent many chronic diseases. This data can be collected for a long time and processed using artificial intelligence (AI) techniques in a medical network for early detection and prevention...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	407,922
2206.12291	A Design of A Simple Yet Effective Exercise Recommendation System in K-12 Online Learning	We propose a simple but effective method to recommend exercises with high quality and diversity for students. Our method is made up of three key components: (1) candidate generation module; (2) diversity-promoting module; and (3) scope restriction module. The proposed method improves the overall recommendation performa...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	304,543
2401.00393	Generative Model-Driven Synthetic Training Image Generation: An Approach to Cognition in Rail Defect Detection	Recent advancements in cognitive computing, with the integration of deep learning techniques, have facilitated the development of intelligent cognitive systems (ICS). This is particularly beneficial in the context of rail defect detection, where the ICS would emulate human-like analysis of image data for defect pattern...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	418,973
1501.04232	Maximum Entropy Models of Shortest Path and Outbreak Distributions in Networks	Properties of networks are often characterized in terms of features such as node degree distributions, average path lengths, diameters, or clustering coefficients. Here, we study shortest path length distributions. On the one hand, average as well as maximum distances can be determined therefrom; on the other hand, the...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	39,339
2408.05676	A Decoding Acceleration Framework for Industrial Deployable LLM-based Recommender Systems	Recently, increasing attention has been paid to LLM-based recommender systems, but their deployment is still under exploration in the industry. Most deployments utilize LLMs as feature enhancers, generating augmentation knowledge in the offline stage. However, in recommendation scenarios, involving numerous users and i...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	479,885
1910.07860	Can I teach a robot to replicate a line art	Line art is arguably one of the fundamental and versatile modes of expression. We propose a pipeline for a robot to look at a grayscale line art and redraw it. The key novel elements of our pipeline are: a) we propose a novel task of mimicking line drawings, b) to solve the pipeline we modify the Quick-draw dataset to ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	149,725
2412.14615	Additive codes attaining the Griesmer bound	Additive codes may have better parameters than linear codes. However, still very few cases are known and the explicit construction of such codes is a challenging problem. Here we show that a Griesmer type bound for the length of additive codes can always be attained with equality if the minimum distance is sufficiently...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	518,790
2305.12534	BertRLFuzzer: A BERT and Reinforcement Learning Based Fuzzer	We present a novel tool BertRLFuzzer, a BERT and Reinforcement Learning (RL) based fuzzer aimed at finding security vulnerabilities for Web applications. BertRLFuzzer works as follows: given a set of seed inputs, the fuzzer performs grammar-adhering and attack-provoking mutation operations on them to generate candidate...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	366,047
2410.00432	Scalable Multi-Task Transfer Learning for Molecular Property Prediction	Molecules have a number of distinct properties whose importance and application vary. Often, in reality, labels for some properties are hard to achieve despite their practical importance. A common solution to such data scarcity is to use models of good generalization with transfer learning. This involves domain experts...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	493,377
2305.10167	Pragmatic Reasoning in Structured Signaling Games	In this work we introduce a structured signaling game, an extension of the classical signaling game with a similarity structure between meanings in the context, along with a variant of the Rational Speech Act (RSA) framework which we call structured-RSA (sRSA) for pragmatic reasoning in structured domains. We explore t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	364,939
2206.14255	Target alignment in truncated kernel ridge regression	Kernel ridge regression (KRR) has recently attracted renewed interest due to its potential for explaining the transient effects, such as double descent, that emerge during neural network training. In this work, we study how the alignment between the target function and the kernel affects the performance of the KRR. We ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,218
0812.1560	Achievable Rates and Training Optimization for Fading Relay Channels with Memory	In this paper, transmission over time-selective, flat fading relay channels is studied. It is assumed that channel fading coefficients are not known a priori. Transmission takes place in two phases: network training phase and data transmission phase. In the training phase, pilot symbols are sent and the receivers emplo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,765
2110.14895	Pipeline Parallelism for Inference on Heterogeneous Edge Computing	Deep neural networks with large model sizes achieve state-of-the-art results for tasks in computer vision (CV) and natural language processing (NLP). However, these large-scale models are too compute- or memory-intensive for resource-constrained edge devices. Prior works on parallel and distributed execution primarily ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	263,685
2410.11924	A Prompt-Guided Spatio-Temporal Transformer Model for National-Wide Nuclear Radiation Forecasting	Nuclear radiation (NR), which refers to the energy emitted from atomic nuclei during decay, poses substantial risks to human health and environmental safety. Accurate forecasting of nuclear radiation levels is crucial for informed decision-making by both individuals and governments. However, this task is challenging du...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,782
1608.05204	Refining Geometry from Depth Sensors using IR Shading Images	We propose a method to refine geometry of 3D meshes from a consumer level depth camera, e.g. Kinect, by exploiting shading cues captured from an infrared (IR) camera. A major benefit to using an IR camera instead of an RGB camera is that the IR images captured are narrow band images that filter out most undesired ambie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,946
1310.0307	Using the Random Sprays Retinex Algorithm for Global Illumination Estimation	In this paper the use of Random Sprays Retinex (RSR) algorithm for global illumination estimation is proposed and its feasibility tested. Like other algorithms based on the Retinex model, RSR also provides local illumination estimation and brightness adjustment for each pixel and it is faster than other path-wise Retin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	27,472
2203.00826	Using Geographic Load Shifting to Reduce Carbon Emissions	An increasing focus on the electricity use and carbon emissions associated with computing has lead to pledges by major cloud computing companies to lower their carbon footprint. Data centers have a unique ability to shift computing load between different geographical locations, giving rise to geographic load flexibilit...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	283,135
2006.10864	PEREGRiNN: Penalized-Relaxation Greedy Neural Network Verifier	Neural Networks (NNs) have increasingly apparent safety implications commensurate with their proliferation in real-world applications: both unanticipated as well as adversarial misclassifications can result in fatal outcomes. As a consequence, techniques of formal verification have been recognized as crucial to the des...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	183,024
2406.16568	Star+: A New Multi-Domain Model for CTR Prediction	In this paper, we introduce Star+, a novel multi-domain model for click-through rate (CTR) prediction inspired by the Star model. Traditional single-domain approaches and existing multi-task learning techniques face challenges in multi-domain environments due to their inability to capture domain-specific data distribut...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	467,186
1801.09031	Improving Word Vector with Prior Knowledge in Semantic Dictionary	Using low dimensional vector space to represent words has been very effective in many NLP tasks. However, it doesn't work well when faced with the problem of rare and unseen words. In this paper, we propose to leverage the knowledge in semantic dictionary in combination with some morphological information to build an e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	89,031
2309.10546	Mean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies	This paper investigates the issue of an adequate loss function in the optimization of machine learning models used in the forecasting of financial time series for the purpose of algorithmic investment strategies (AIS) construction. We propose the Mean Absolute Directional Loss (MADL) function, solving important problem...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	393,056
2309.10772	Interactive Distillation of Large Single-Topic Corpora of Scientific Papers	Highly specific datasets of scientific literature are important for both research and education. However, it is difficult to build such datasets at scale. A common approach is to build these datasets reductively by applying topic modeling on an established corpus and selecting specific topics. A more robust but time-co...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	true	393,145
1707.08951	Handwritten character recognition using some (anti)-diagonal structural features	In this paper, we present a methodology for off-line handwritten character recognition. The proposed methodology relies on a new feature extraction technique based on structural characteristics, histograms and profiles. As novelty, we propose the extraction of new eight histograms and four profiles from the $32\times 3...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	77,924
2408.07648	See It All: Contextualized Late Aggregation for 3D Dense Captioning	3D dense captioning is a task to localize objects in a 3D scene and generate descriptive sentences for each object. Recent approaches in 3D dense captioning have adopted transformer encoder-decoder frameworks from object detection to build an end-to-end pipeline without hand-crafted components. However, these approache...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	480,674
2409.01389	CV-Probes: Studying the interplay of lexical and world knowledge in visually grounded verb understanding	This study investigates the ability of various vision-language (VL) models to ground context-dependent and non-context-dependent verb phrases. To do that, we introduce the CV-Probes dataset, designed explicitly for studying context understanding, containing image-caption pairs with context-dependent verbs (e.g., "beg")...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	485,319
1809.05361	Advanced Soccer Skills and Team Play of RoboCup 2017 TeenSize Winner NimbRo	In order to pursue the vision of the RoboCup Humanoid League of beating the soccer world champion by 2050, new rules and competitions are added or modified each year fostering novel technological advances. In 2017, the number of players in the TeenSize class soccer games was increase to 3 vs. 3, which allowed for more ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	107,779
2209.15368	Inharmonious Region Localization by Magnifying Domain Discrepancy	Inharmonious region localization aims to localize the region in a synthetic image which is incompatible with surrounding background. The inharmony issue is mainly attributed to the color and illumination inconsistency produced by image editing techniques. In this work, we tend to transform the input image to another co...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	320,580
2212.06905	Query Time Optimized Deep Learning Based Video Inference System	This is a project report about how we tune Focus[1], a video inference system that provides low cost and low latency, through two phases. In this report, we will decrease the query time by saving the middle layer output of the neural network. This is a trade-off strategy that involves using more space to save time. We ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	336,243
0905.4163	Cyclic Codes over Some Finite Rings	In this paper cyclic codes are established with respect to the Mannheim metric over some finite rings by using Gaussian integers and the decoding algorithm for these codes is given.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,771
2207.07915	On Curating Responsible and Representative Healthcare Video Recommendations for Patient Education and Health Literacy: An Augmented Intelligence Approach	Studies suggest that one in three US adults use the Internet to diagnose or learn about a health concern. However, such access to health information online could exacerbate the disparities in health information availability and use. Health information seeking behavior (HISB) refers to the ways in which individuals seek...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	308,372
2501.18965	The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training	We show that learning-rate schedules for large model training behave surprisingly similar to a performance bound from non-smooth convex optimization theory. We provide a bound for the constant schedule with linear cooldown; in particular, the practical benefit of cooldown is reflected in the bound due to the absence of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	528,943
2206.00772	On the reversibility of adversarial attacks	Adversarial attacks modify images with perturbations that change the prediction of classifiers. These modified images, known as adversarial examples, expose the vulnerabilities of deep neural network classifiers. In this paper, we investigate the predictability of the mapping between the classes predicted for original ...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	300,242
1607.02613	New approach to Bayesian high-dimensional linear regression	Consider the problem of estimating parameters $X^n \in \mathbb{R}^n $, generated by a stationary process, from $m$ response variables $Y^m = AX^n+Z^m$, under the assumption that the distribution of $X^n$ is known. This is the most general version of the Bayesian linear regression problem. The lack of computationally fe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	58,382
1805.08594	Neural Generative Models for Global Optimization with Gradients	The aim of global optimization is to find the global optimum of arbitrary classes of functions, possibly highly multimodal ones. In this paper we focus on the subproblem of global optimization for differentiable functions and we propose an Evolutionary Search-inspired solution where we model point search distributions ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	98,185
0705.4485	Mixed membership stochastic blockmodels	Observations consisting of measurements on relationships for pairs of objects arise in many settings, such as protein interaction and gene regulatory networks, collections of author-recipient email, and social networks. Analyzing such data with probabilisic models can be delicate because the simple exchangeability assu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	294
2004.05155	Learning to Explore using Active Neural SLAM	This work presents a modular and hierarchical approach to learn policies for exploring 3D environments, called `Active Neural SLAM'. Our approach leverages the strengths of both classical and learning-based methods, by using analytical path planners with learned SLAM module, and global and local policies. The use of le...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	172,106
2309.03904	Exploring Sparse MoE in GANs for Text-conditioned Image Synthesis	Due to the difficulty in scaling up, generative adversarial networks (GANs) seem to be falling from grace on the task of text-conditioned image synthesis. Sparsely-activated mixture-of-experts (MoE) has recently been demonstrated as a valid solution to training large-scale models with limited computational resources. I...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,555
1904.10699	The VIA Annotation Software for Images, Audio and Video	In this paper, we introduce a simple and standalone manual annotation tool for images, audio and video: the VGG Image Annotator (VIA). This is a light weight, standalone and offline software package that does not require any installation or setup and runs solely in a web browser. The VIA software allows human annotator...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,692
2106.08905	Structure First Detail Next: Image Inpainting with Pyramid Generator	Recent deep generative models have achieved promising performance in image inpainting. However, it is still very challenging for a neural network to generate realistic image details and textures, due to its inherent spectral bias. By our understanding of how artists work, we suggest to adopt a `structure first detail n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	241,474
1912.11464	Attack-Resistant Federated Learning with Residual-based Reweighting	Federated learning has a variety of applications in multiple domains by utilizing private training data stored on different devices. However, the aggregation process in federated learning is highly vulnerable to adversarial attacks so that the global model may behave abnormally under attacks. To tackle this challenge, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	158,571
2301.05494	Multilingual Detection of Check-Worthy Claims using World Languages and Adapter Fusion	Check-worthiness detection is the task of identifying claims, worthy to be investigated by fact-checkers. Resource scarcity for non-world languages and model learning costs remain major challenges for the creation of models supporting multilingual check-worthiness detection. This paper proposes cross-training adapters ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	340,362
2309.10886	GelSight Svelte Hand: A Three-finger, Two-DoF, Tactile-rich, Low-cost Robot Hand for Dexterous Manipulation	This paper presents GelSight Svelte Hand, a novel 3-finger 2-DoF tactile robotic hand that is capable of performing precision grasps, power grasps, and intermediate grasps. Rich tactile signals are obtained from one camera on each finger, with an extended sensing area similar to the full length of a human finger. Each ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	393,186
2110.15444	10 Security and Privacy Problems in Large Foundation Models	Foundation models--such as GPT, CLIP, and DINO--have achieved revolutionary progress in the past several years and are commonly believed to be a promising approach for general-purpose AI. In particular, self-supervised learning is adopted to pre-train a foundation model using a large amount of unlabeled data. A pre-tra...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	263,881
2206.03183	Risk Measures and Upper Probabilities: Coherence and Stratification	Machine learning typically presupposes classical probability theory which implies that aggregation is built upon expectation. There are now multiple reasons to motivate looking at richer alternatives to classical probability theory as a mathematical foundation for machine learning. We systematically examine a powerful ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	301,173
2104.06022	Lessons on Parameter Sharing across Layers in Transformers	We propose a parameter sharing method for Transformers (Vaswani et al., 2017). The proposed approach relaxes a widely used technique, which shares parameters for one layer with all layers such as Universal Transformers (Dehghani et al., 2019), to increase the efficiency in the computational time. We propose three strat...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	229,937
1909.10031	LuNet: A Deep Neural Network for Network Intrusion Detection	Network attack is a significant security issue for modern society. From small mobile devices to large cloud platforms, almost all computing products, used in our daily life, are networked and potentially under the threat of network intrusion. With the fast-growing network users, network intrusions become more and more ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	146,429
2305.20065	Latent Exploration for Reinforcement Learning	In Reinforcement Learning, agents learn policies by exploring and interacting with the environment. Due to the curse of dimensionality, learning policies that map high-dimensional sensory input to motor output is particularly challenging. During training, state of the art methods (SAC, PPO, etc.) explore the environmen...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	369,802
1011.5124	Delay Constrained Utility Maximization in Multihop Random Access Networks	Multi-hop random access networks have received much attention due to their distributed nature which facilitates deploying many new applications over the sensor and computer networks. Recently, utility maximization framework is applied in order to optimize performance of such networks, however proposed algorithms result...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	true	8,314
2310.16960	Privately Aligning Language Models with Reinforcement Learning	Positioned between pre-training and user deployment, aligning large language models (LLMs) through reinforcement learning (RL) has emerged as a prevailing strategy for training instruction following-models such as ChatGPT. In this work, we initiate the study of privacy-preserving alignment of LLMs through Differential ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	402,935
2203.01652	Informative Path Planning for Active Learning in Aerial Semantic Mapping	Semantic segmentation of aerial imagery is an important tool for mapping and earth observation. However, supervised deep learning models for segmentation rely on large amounts of high-quality labelled data, which is labour-intensive and time-consuming to generate. To address this, we propose a new approach for using un...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	283,466
2204.09437	Search-based Methods for Multi-Cloud Configuration	Multi-cloud computing has become increasingly popular with enterprises looking to avoid vendor lock-in. While most cloud providers offer similar functionality, they may differ significantly in terms of performance and/or cost. A customer looking to benefit from such differences will naturally want to solve the multi-cl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	292,441
2402.01481	Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains	In recent years, there has been a surge in the development of 3D structure-based pre-trained protein models, representing a significant advancement over pre-trained protein language models in various downstream tasks. However, most existing structure-based pre-trained models primarily focus on the residue level, i.e., ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	426,042
2306.14237	A Safe Genetic Algorithm Approach for Energy Efficient Federated Learning in Wireless Communication Networks	Federated Learning (FL) has emerged as a decentralized technique, where contrary to traditional centralized approaches, devices perform a model training in a collaborative manner, while preserving data privacy. Despite the existing efforts made in FL, its environmental impact is still under investigation, since several...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	375,601
2401.09471	Brain Tumor Radiogenomic Classification	The RSNA-MICCAI brain tumor radiogenomic classification challenge aimed to predict MGMT biomarker status in glioblastoma through binary classification on Multi parameter mpMRI scans: T1w, T1wCE, T2w and FLAIR. The dataset is splitted into three main cohorts: training set, validation set which were used during training,...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	422,275
2001.03573	Should Artificial Intelligence Governance be Centralised? Design Lessons from History	Can effective international governance for artificial intelligence remain fragmented, or is there a need for a centralised international organisation for AI? We draw on the history of other international regimes to identify advantages and disadvantages in centralising AI governance. Some considerations, such as efficie...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	160,014
0903.5054	Flow of Activity in the Ouroboros Model	The Ouroboros Model is a new conceptual proposal for an algorithmic structure for efficient data processing in living beings as well as for artificial agents. Its central feature is a general repetitive loop where one iteration cycle sets the stage for the next. Sensory input activates data structures (schemata) with s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	3,435
2309.05380	Collective PV-RCNN: A Novel Fusion Technique using Collective Detections for Enhanced Local LiDAR-Based Perception	Comprehensive perception of the environment is crucial for the safe operation of autonomous vehicles. However, the perception capabilities of autonomous vehicles are limited due to occlusions, limited sensor ranges, or environmental influences. Collective Perception (CP) aims to mitigate these problems by enabling the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,065
2407.19435	ASI-Seg: Audio-Driven Surgical Instrument Segmentation with Surgeon Intention Understanding	Surgical instrument segmentation is crucial in surgical scene understanding, thereby facilitating surgical safety. Existing algorithms directly detected all instruments of pre-defined categories in the input image, lacking the capability to segment specific instruments according to the surgeon's intention. During diffe...	true	false	false	false	true	false	false	true	true	false	false	true	false	false	false	false	false	false	476,785
1901.07871	Analysis of the $(\mu/\mu_I,\lambda)$-CSA-ES with Repair by Projection Applied to a Conically Constrained Problem	Theoretical analyses of evolution strategies are indispensable for gaining a deep understanding of their inner workings. For constrained problems, rather simple problems are of interest in the current research. This work presents a theoretical analysis of a multi-recombinative evolution strategy with cumulative step si...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	119,324
1903.11891	AED-Net: An Abnormal Event Detection Network	It is challenging to detect the anomaly in crowded scenes for quite a long time. In this paper, a self-supervised framework, abnormal event detection network (AED-Net), which is composed of PCAnet and kernel principal component analysis (kPCA), is proposed to address this problem. Using surveillance video sequences of ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	125,604
1312.3986	Correlations between user voting data, budget, and box office for films in the Internet Movie Database	The Internet Movie Database (IMDb) is one of the most-visited websites in the world and the premier source for information on films. Like Wikipedia, much of IMDb's information is user contributed. IMDb also allows users to voice their opinion on the quality of films through voting. We investigate whether there is a con...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	29,086
1708.01654	Better Together: Joint Reasoning for Non-rigid 3D Reconstruction with Specularities and Shading	We demonstrate the use of shape-from-shading (SfS) to improve both the quality and the robustness of 3D reconstruction of dynamic objects captured by a single camera. Unlike previous approaches that made use of SfS as a post-processing step, we offer a principled integrated approach that solves dynamic object tracking ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,422
2112.06953	Controlled Cue Generation for Play Scripts	In this paper, we use a large-scale play scripts dataset to propose the novel task of theatrical cue generation from dialogues. Using over one million lines of dialogue and cues, we approach the problem of cue generation as a controlled text generation task, and show how cues can be used to enhance the impact of dialog...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	271,334
2403.09380	Impact of Synthetic Images on Morphing Attack Detection Using a Siamese Network	This paper evaluated the impact of synthetic images on Morphing Attack Detection (MAD) using a Siamese network with a semi-hard-loss function. Intra and cross-dataset evaluations were performed to measure synthetic image generalisation capabilities using a cross-dataset for evaluation. Three different pre-trained netwo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	437,743
2110.00669	Expanding the Design Space for Electrically-Driven Soft Robots through Handed Shearing Auxetics	Handed Shearing Auxetics (HSA) are a promising structure for making electrically driven robots with distributed compliance that convert a motors rotation and torque into extension and force. We overcame past limitations on the range of actuation, blocked force, and stiffness by focusing on two key design parameters: th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	258,480
1901.04167	Age-Delay Tradeoffs in Single Server Systems	Information freshness and low latency communication is important to many emerging applications. While Age of Information (AoI) serves as a metric of information freshness, packet delay is a traditional metric of communication latency. We prove that there is a natural tradeoff between the AoI and packet delay. We consid...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	118,558
1205.5024	Analytical Study of Hexapod miRNAs using Phylogenetic Methods	MicroRNAs (miRNAs) are a class of non-coding RNAs that regulate gene expression. Identification of total number of miRNAs even in completely sequenced organisms is still an open problem. However, researchers have been using techniques that can predict limited number of miRNA in an organism. In this paper, we have used ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	16,138
2306.09855	Runtime Construction of Large-Scale Spiking Neuronal Network Models on GPU Devices	Simulation speed matters for neuroscientific research: this includes not only how quickly the simulated model time of a large-scale spiking neuronal network progresses, but also how long it takes to instantiate the network model in computer memory. On the hardware side, acceleration via highly parallel GPUs is being in...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	373,994
1602.03936	Study of Interference Cancellation and Relay Selection Algorithms Using Greedy Techniques for Cooperative DS-CDMA Systems	In this work, we study interference cancellation techniques and a multi-relay selection algorithm based on greedy methods for the uplink of cooperative direct-sequence code-division multiple access (DS-CDMA) systems. We first devise low-cost list-based successive interference cancellation (GL-SIC) and parallel interfer...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	52,066
2412.13179	A Pipeline and NIR-Enhanced Dataset for Parking Lot Segmentation	Discussions of minimum parking requirement policies often include maps of parking lots, which are time consuming to construct manually. Open source datasets for such parking lots are scarce, particularly for US cities. This paper introduces the idea of using Near-Infrared (NIR) channels as input and several post-proces...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	518,196
1803.10136	Comprehending Real Numbers: Development of Bengali Real Number Speech Corpus	Speech recognition has received a less attention in Bengali literature due to the lack of a comprehensive dataset. In this paper, we describe the development process of the first comprehensive Bengali speech dataset on real numbers. It comprehends all the possible words that may arise in uttering any Bengali real numbe...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	93,650
2412.20903	WalkVLM:Aid Visually Impaired People Walking by Vision Language Model	Approximately 200 million individuals around the world suffer from varying degrees of visual impairment, making it crucial to leverage AI technology to offer walking assistance for these people. With the recent progress of vision-language models (VLMs), employing VLMs to improve this field has emerged as a popular rese...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	521,397
2408.04840	mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models	Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities in executing instructions for a variety of single-image tasks. Despite this progress, significant challenges remain in modeling long image sequences. In this work, we introduce the versatile multi-modal large language model, mPLUG-Owl3,...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	479,551
1308.2572	Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs	Stochastic simulation techniques employed for the analysis of portfolios of insurance/reinsurance risk, often referred to as `Aggregate Risk Analysis', can benefit from exploiting state-of-the-art high-performance computing platforms. In this paper, parallel methods to speed-up aggregate risk analysis for supporting re...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	26,393
1901.04654	Reducing Age-of-Information for Computation-Intensive Messages via Packet Replacement	Freshness of data is an important performance metric for real-time applications, which can be measured by age-of-information. For computation-intensive messages, the embedded information is not available until being computed. In this paper, we study the age-of-information for computation-intensive messages, which are f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	118,637
2002.12041	Attention-guided Chained Context Aggregation for Semantic Segmentation	The way features propagate in Fully Convolutional Networks is of momentous importance to capture multi-scale contexts for obtaining precise segmentation masks. This paper proposes a novel series-parallel hybrid paradigm called the Chained Context Aggregation Module (CAM) to diversify feature propagation. CAM gains feat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	165,912
1807.11182	End-to-End Deep Kronecker-Product Matching for Person Re-identification	Person re-identification aims to robustly measure similarities between person images. The significant variation of person poses and viewing angles challenges for accurate person re-identification. The spatial layout and correspondences between query person images are vital information for tackling this problem but are ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,126
1906.04043	GLTR: Statistical Detection and Visualization of Generated Text	The rapid improvement of language models has raised the specter of abuse of text generation systems. This progress motivates the development of simple methods for detecting generated text that can be used by and explained to non-experts. We develop GLTR, a tool to support humans in detecting whether a text was generate...	true	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	134,585
2407.11138	Lessons from a human-in-the-loop machine learning approach for identifying vacant, abandoned, and deteriorated properties in Savannah, Georgia	Addressing strategies for managing vacant, abandoned, and deteriorated (VAD) properties is important for maintaining healthy communities. Yet, the process of identifying these properties can be difficult. Here, we create a human-in-the-loop machine learning (HITLML) model called VADecide and apply it to a parcel-level ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	473,319
2103.16493	Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training	Data augmentation has proved extremely useful by increasing training data variance to alleviate overfitting and improve deep neural networks' generalization performance. In medical image analysis, a well-designed augmentation policy usually requires much expert knowledge and is difficult to generalize to multiple tasks...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	227,600

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