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
1802.04592	A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems	Bike sharing provides an environment-friendly way for traveling and is booming all over the world. Yet, due to the high similarity of user travel patterns, the bike imbalance problem constantly occurs, especially for dockless bike sharing systems, causing significant impact on service quality and company revenue. Thus,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	90,254
2308.09026	LesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation	Data augmentation has become a de facto component of deep learning-based medical image segmentation methods. Most data augmentation techniques used in medical imaging focus on spatial and intensity transformations to improve the diversity of training images. They are often designed at the image level, augmenting the fu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	386,122
2210.09236	ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization	Recent advances on large-scale pre-training have shown great potentials of leveraging a large set of Pre-Trained Models (PTMs) for improving Out-of-Distribution (OoD) generalization, for which the goal is to perform well on possible unseen domains after fine-tuning on multiple training domains. However, maximally explo...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	324,467
2005.02342	Heuristic-Based Weak Learning for Automated Decision-Making	Machine learning systems impact many stakeholders and groups of users, often disparately. Prior studies have reconciled conflicting user preferences by aggregating a high volume of manually labeled pairwise comparisons, but this technique may be costly or impractical. How can we lower the barrier to participation in al...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	175,848
1505.04394	Analysis and perturbation of degree correlation in complex networks	Degree correlation is an important topological property common to many real-world networks. In this paper, the statistical measures for characterizing the degree correlation in networks are investigated analytically. We give an exact proof of the consistency for the statistical measures, reveal the general linear relat...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	43,183
2501.16309	Evaluating The Performance of Using Large Language Models to Automate Summarization of CT Simulation Orders in Radiation Oncology	Purpose: This study aims to use a large language model (LLM) to automate the generation of summaries from the CT simulation orders and evaluate its performance. Materials and Methods: A total of 607 CT simulation orders for patients were collected from the Aria database at our institution. A locally hosted Llama 3.1 ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	527,899
1903.04579	Reprogrammable Electro-Optic Nonlinear Activation Functions for Optical Neural Networks	We introduce an electro-optic hardware platform for nonlinear activation functions in optical neural networks. The optical-to-optical nonlinearity operates by converting a small portion of the input optical signal into an analog electric signal, which is used to intensity-modulate the original optical signal with no re...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	124,001
2312.14808	A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential	In this paper, we present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar. The model is used in a Model Predictive Controller in which we included a micro-steps discretization approach to accurately linearize the dynamics and produce a predic...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	417,757
2212.00735	xTrimoABFold: De novo Antibody Structure Prediction without MSA	In the field of antibody engineering, an essential task is to design a novel antibody whose paratopes bind to a specific antigen with correct epitopes. Understanding antibody structure and its paratope can facilitate a mechanistic understanding of its function. Therefore, antibody structure prediction from its sequence...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	334,168
2105.01510	Multipath Graph Convolutional Neural Networks	Graph convolution networks have recently garnered a lot of attention for representation learning on non-Euclidean feature spaces. Recent research has focused on stacking multiple layers like in convolutional neural networks for the increased expressive power of graph convolution networks. However, simply stacking multi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	233,542
2309.10200	Harnessing Kernel Regression for Stochastic State Estimation in Solar-Integrated Power Grids	The paper presents a Gaussian/kernel process regression method for real-time state estimation and forecasting of phase angle and angular speed in systems with a high penetration of solar generation units, operating under a sparse measurements regime on both sunny and cloudy days. The method treats unknown terms in the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	392,903
2007.03085	Wasserstein Distances for Stereo Disparity Estimation	Existing approaches to depth or disparity estimation output a distribution over a set of pre-defined discrete values. This leads to inaccurate results when the true depth or disparity does not match any of these values. The fact that this distribution is usually learned indirectly through a regression loss causes furth...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	185,941
2112.06769	Multi-objective simulation optimization of the adhesive bonding process of materials	Automotive companies are increasingly looking for ways to make their products lighter, using novel materials and novel bonding processes to join these materials together. Finding the optimal process parameters for such adhesive bonding process is challenging. In this research, we successfully applied Bayesian optimizat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	271,295
1907.02124	Non-Structured DNN Weight Pruning -- Is It Beneficial in Any Platform?	Large deep neural network (DNN) models pose the key challenge to energy efficiency due to the significantly higher energy consumption of off-chip DRAM accesses than arithmetic or SRAM operations. It motivates the intensive research on model compression with two main approaches. Weight pruning leverages the redundancy i...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	137,530
1412.7932	Home Automation Using SSVEP & Eye-Blink Detection Based Brain-Computer Interface	In this paper, we present a novel brain computer interface based home automation system using two responses - Steady State Visually Evoked Potential (SSVEP) and the eye-blink artifact, which is augmented by a Bluetooth based indoor localization system, to greatly increase the number of controllable devices. The hardwar...	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	38,865
2409.11844	MEOW: MEMOry Supervised LLM Unlearning Via Inverted Facts	Large Language Models (LLMs) can memorize sensitive information, raising concerns about potential misuse. LLM Unlearning, a post-hoc approach to remove this information from trained LLMs, offers a promising solution to mitigate these risks. However, previous practices face three key challenges: 1. Utility: successful u...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	489,339
1709.00954	Virtual Borders: Accurate Definition of a Mobile Robot's Workspace Using Augmented Reality	We address the problem of interactively controlling the workspace of a mobile robot to ensure a human-aware navigation. This is especially of relevance for non-expert users living in human-robot shared spaces, e.g. home environments, since they want to keep the control of their mobile robots, such as vacuum cleaning or...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	80,000
2108.04892	Fun-SAT: Functional Corruptibility-Guided SAT-Based Attack on Sequential Logic Encryption	The SAT attack has shown to be efficient against most combinational logic encryption methods. It can be extended to attack sequential logic encryption techniques by leveraging circuit unrolling and model checking methods. However, with no guidance on the number of times that a circuit needs to be unrolled to find the c...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	250,140
2002.10546	Parsing Early Modern English for Linguistic Search	We investigate the question of whether advances in NLP over the last few years make it possible to vastly increase the size of data usable for research in historical syntax. This brings together many of the usual tools in NLP - word embeddings, tagging, and parsing - in the service of linguistic queries over automatica...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	165,432
2312.17111	Online Tensor Inference	Recent technological advances have led to contemporary applications that demand real-time processing and analysis of sequentially arriving tensor data. Traditional offline learning, involving the storage and utilization of all data in each computational iteration, becomes impractical for high-dimensional tensor data du...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	418,622
2102.11764	Quantum Entropic Causal Inference	The class of problems in causal inference which seeks to isolate causal correlations solely from observational data even without interventions has come to the forefront of machine learning, neuroscience and social sciences. As new large scale quantum systems go online, it opens interesting questions of whether a quantu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	221,519
2306.13786	Runtime optimization of acquisition trajectories for X-ray computed tomography with a robotic sample holder	Tomographic imaging systems are expected to work with a wide range of samples that house complex structures and challenging material compositions, which can influence image quality in a bad way. Complex samples increase total measurement duration and may introduce beam-hardening artifacts that lead to poor reconstructi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	375,398
2311.06654	Unsupervised and semi-supervised co-salient object detection via segmentation frequency statistics	In this paper, we address the detection of co-occurring salient objects (CoSOD) in an image group using frequency statistics in an unsupervised manner, which further enable us to develop a semi-supervised method. While previous works have mostly focused on fully supervised CoSOD, less attention has been allocated to de...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	407,022
2012.03206	MVHM: A Large-Scale Multi-View Hand Mesh Benchmark for Accurate 3D Hand Pose Estimation	Estimating 3D hand poses from a single RGB image is challenging because depth ambiguity leads the problem ill-posed. Training hand pose estimators with 3D hand mesh annotations and multi-view images often results in significant performance gains. However, existing multi-view datasets are relatively small with hand join...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	210,033
1705.04909	Full-Duplex Massive MIMO Relaying Systems with Low-Resolution ADCs	This paper considers a multipair amplify-and-forward massive MIMO relaying system with low-resolution ADCs at both the relay and destinations. The channel state information (CSI) at the relay is obtained via pilot training, which is then utilized to perform simple maximum-ratio combining/maximum-ratio transmission proc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	73,396
2407.12519	Causality-inspired Discriminative Feature Learning in Triple Domains for Gait Recognition	Gait recognition is a biometric technology that distinguishes individuals by their walking patterns. However, previous methods face challenges when accurately extracting identity features because they often become entangled with non-identity clues. To address this challenge, we propose CLTD, a causality-inspired discri...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,968
2306.02868	Explicit Construction of q-ary 2-deletion Correcting Codes with Low Redundancy	We consider the problem of efficient construction of q-ary 2-deletion correcting codes with low redundancy. We show that our construction requires less redundancy than any existing efficiently encodable q-ary 2-deletion correcting codes. Precisely speaking, we present an explicit construction of a q-ary 2-deletion corr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	371,091
1805.06627	Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures	Embedding methods which enforce a partial order or lattice structure over the concept space, such as Order Embeddings (OE) (Vendrov et al., 2016), are a natural way to model transitive relational data (e.g. entailment graphs). However, OE learns a deterministic knowledge base, limiting expressiveness of queries and the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	97,654
2502.12563	Evaluating Language Models on Grooming Risk Estimation Using Fuzzy Theory	Encoding implicit language presents a challenge for language models, especially in high-risk domains where maintaining high precision is important. Automated detection of online child grooming is one such critical domain, where predators manipulate victims using a combination of explicit and implicit language to convey...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	534,940
1308.0239	Rapid rise and decay in petition signing	Contemporary collective action, much of which involves social media and other Internet-based platforms, leaves a digital imprint which may be harvested to better understand the dynamics of mobilization. Petition signing is an example of collective action which has gained in popularity with rising use of social media an...	true	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	26,209
1405.0941	Towards a Benchmark of Natural Language Arguments	The connections among natural language processing and argumentation theory are becoming stronger in the latest years, with a growing amount of works going in this direction, in different scenarios and applying heterogeneous techniques. In this paper, we present two datasets we built to cope with the combination of the ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	32,827
2208.07531	FeedLens: Polymorphic Lenses for Personalizing Exploratory Search over Knowledge Graphs	The vast scale and open-ended nature of knowledge graphs (KGs) make exploratory search over them cognitively demanding for users. We introduce a new technique, polymorphic lenses, that improves exploratory search over a KG by obtaining new leverage from the existing preference models that KG-based systems maintain for ...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	313,073
1610.07108	Fast and Reliable Parameter Estimation from Nonlinear Observations	In this paper we study the problem of recovering a structured but unknown parameter ${\bf{\theta}}^$ from $n$ nonlinear observations of the form $y_i=f(\langle {\bf{x}}_i,{\bf{\theta}}^\rangle)$ for $i=1,2,\ldots,n$. We develop a framework for characterizing time-data tradeoffs for a variety of parameter estimation a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	62,740
1904.11340	Enhanced IoV Security Network by Using Blockchain Governance Game	This paper deals with the design of the secure network in an Enhanced Internet of Vehicles by using the Blockchain Governance Game (BGG). The BGG is a system model of a stochastic game to find best strategies towards preparation of preventing a network malfunction by an attacker and the paper applies this game model in...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	true	128,840
2502.00663	Enhanced Convolutional Neural Networks for Improved Image Classification	Image classification is a fundamental task in computer vision with diverse applications, ranging from autonomous systems to medical imaging. The CIFAR-10 dataset is a widely used benchmark to evaluate the performance of classification models on small-scale, multi-class datasets. Convolutional Neural Networks (CNNs) hav...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	529,484
2205.15473	Free-Space Ellipsoid Graphs for Multi-Agent Target Monitoring	We apply a novel framework for decomposing and reasoning about free space in an environment to a multi-agent persistent monitoring problem. Our decomposition method represents free space as a collection of ellipsoids associated with a weighted connectivity graph. The same ellipsoids used for reasoning about connectivit...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	299,739
1810.09274	From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference	Nonlinearity is crucial to the performance of a deep (neural) network (DN). To date there has been little progress understanding the menagerie of available nonlinearities, but recently progress has been made on understanding the r\^ole played by piecewise affine and convex nonlinearities like the ReLU and absolute valu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,027
2303.13002	Planning Goals for Exploration	Dropped into an unknown environment, what should an agent do to quickly learn about the environment and how to accomplish diverse tasks within it? We address this question within the goal-conditioned reinforcement learning paradigm, by identifying how the agent should set its goals at training time to maximize explorat...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	353,497
2106.02851	SURPRISE! and When to Schedule It	Information flow measures, over the duration of a game, the audience's belief of who will win, and thus can reflect the amount of surprise in a game. To quantify the relationship between information flow and audiences' perceived quality, we conduct a case study where subjects watch one of the world's biggest esports ev...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	239,060
2409.19740	When Molecular GAN Meets Byte-Pair Encoding	Deep generative models, such as generative adversarial networks (GANs), are pivotal in discovering novel drug-like candidates via de novo molecular generation. However, traditional character-wise tokenizers often struggle with identifying novel and complex sub-structures in molecular data. In contrast, alternative toke...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	492,828
2010.12866	Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards	In this paper, we consider stochastic multi-armed bandits (MABs) with heavy-tailed rewards, whose $p$-th moment is bounded by a constant $\nu_{p}$ for $1<p\leq2$. First, we propose a novel robust estimator which does not require $\nu_{p}$ as prior information, while other existing robust estimators demand prior knowled...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,898
2206.06602	Deep Isolation Forest for Anomaly Detection	Isolation forest (iForest) has been emerging as arguably the most popular anomaly detector in recent years due to its general effectiveness across different benchmarks and strong scalability. Nevertheless, its linear axis-parallel isolation method often leads to (i) failure in detecting hard anomalies that are difficul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,430
2406.09598	Introducing HOT3D: An Egocentric Dataset for 3D Hand and Object Tracking	We introduce HOT3D, a publicly available dataset for egocentric hand and object tracking in 3D. The dataset offers over 833 minutes (more than 3.7M images) of multi-view RGB/monochrome image streams showing 19 subjects interacting with 33 diverse rigid objects, multi-modal signals such as eye gaze or scene point clouds...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	463,999
2405.13711	VAE-Var: Variational-Autoencoder-Enhanced Variational Assimilation	Data assimilation refers to a set of algorithms designed to compute the optimal estimate of a system's state by refining the prior prediction (known as background states) using observed data. Variational assimilation methods rely on the maximum likelihood approach to formulate a variational cost, with the optimal state...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	456,046
2212.09234	Real-Time Deformable-Contact-Aware Model Predictive Control for Force-Modulated Manipulation	Force modulation of robotic manipulators has been extensively studied for several decades. However, it is not yet commonly used in safety-critical applications due to a lack of accurate interaction contact modeling and weak performance guarantees - a large proportion of them concerning the modulation of interaction for...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	337,035
2107.09123	Latency-Memory Optimized Splitting of Convolution Neural Networks for Resource Constrained Edge Devices	With the increasing reliance of users on smart devices, bringing essential computation at the edge has become a crucial requirement for any type of business. Many such computations utilize Convolution Neural Networks (CNNs) to perform AI tasks, having high resource and computation requirements, that are infeasible for ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	246,935
2310.11346	Towards Generalizable Multi-Camera 3D Object Detection via Perspective Debiasing	Detecting objects in 3D space using multiple cameras, known as Multi-Camera 3D Object Detection (MC3D-Det), has gained prominence with the advent of bird's-eye view (BEV) approaches. However, these methods often struggle when faced with unfamiliar testing environments due to the lack of diverse training data encompassi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	400,607
2406.17265	Image-Guided Outdoor LiDAR Perception Quality Assessment for Autonomous Driving	LiDAR is one of the most crucial sensors for autonomous vehicle perception. However, current LiDAR-based point cloud perception algorithms lack comprehensive and rigorous LiDAR quality assessment methods, leading to uncertainty in detection performance. Additionally, existing point cloud quality assessment algorithms a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	467,495
2305.00807	A comparison of methods to eliminate regularization weight tuning from data-enabled predictive control	Data-enabled predictive control (DeePC) is a recently established form of Model Predictive Control (MPC), based on behavioral systems theory. While eliminating the need to explicitly identify a model, it requires an additional regularization with a corresponding weight to function well with noisy data. The tuning of th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	361,461
1903.09739	Ultra-Reliable and Low-Latency Communications Using Proactive Multi-cell Association	Attaining reliable communications traditionally relies on a closed-loop methodology but inevitably incurs a good amount of networking latency thanks to complicated feedback mechanism and signaling storm. Such a closed-loop methodology thus shackles the current cellular network with a tradeoff between high reliability a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	125,113
2311.07421	Robust semi-supervised segmentation with timestep ensembling diffusion models	Medical image segmentation is a challenging task, made more difficult by many datasets' limited size and annotations. Denoising diffusion probabilistic models (DDPM) have recently shown promise in modelling the distribution of natural images and were successfully applied to various medical imaging tasks. This work focu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	407,312
2003.11774	Image Generation Via Minimizing Fr\'echet Distance in Discriminator Feature Space	For a given image generation problem, the intrinsic image manifold is often low dimensional. We use the intuition that it is much better to train the GAN generator by minimizing the distributional distance between real and generated images in a small dimensional feature space representing such a manifold than on the or...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	169,720
1707.04682	Rethinking Reprojection: Closing the Loop for Pose-aware ShapeReconstruction from a Single Image	An emerging problem in computer vision is the reconstruction of 3D shape and pose of an object from a single image. Hitherto, the problem has been addressed through the application of canonical deep learning methods to regress from the image directly to the 3D shape and pose labels. These approaches, however, are probl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	77,093
2403.01265	Smooth Computation without Input Delay: Robust Tube-Based Model Predictive Control for Robot Manipulator Planning	Model Predictive Control (MPC) has exhibited remarkable capabilities in optimizing objectives and meeting constraints. However, the substantial computational burden associated with solving the Optimal Control Problem (OCP) at each triggering instant introduces significant delays between state sampling and control appli...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	434,335
2410.18678	Ali-AUG: Innovative Approaches to Labeled Data Augmentation using One-Step Diffusion Model	This paper introduces Ali-AUG, a novel single-step diffusion model for efficient labeled data augmentation in industrial applications. Our method addresses the challenge of limited labeled data by generating synthetic, labeled images with precise feature insertion. Ali-AUG utilizes a stable diffusion architecture enhan...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	501,989
1311.2236	Fast Distribution To Real Regression	We study the problem of distribution to real-value regression, where one aims to regress a mapping $f$ that takes in a distribution input covariate $P\in \mathcal{I}$ (for a non-parametric family of distributions $\mathcal{I}$) and outputs a real-valued response $Y=f(P) + \epsilon$. This setting was recently studied, a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	28,299
2501.13992	Dual-Branch HNSW Approach with Skip Bridges and LID-Driven Optimization	The Hierarchical Navigable Small World (HNSW) algorithm is widely used for approximate nearest neighbor (ANN) search, leveraging the principles of navigable small-world graphs. However, it faces some limitations. The first is the local optima problem, which arises from the algorithm's greedy search strategy, selecting ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	526,934
2104.01459	A surrogate loss function for optimization of $F_\beta$ score in binary classification with imbalanced data	The $F_\beta$ score is a commonly used measure of classification performance, which plays crucial roles in classification tasks with imbalanced data sets. However, the $F_\beta$ score cannot be used as a loss function by gradient-based learning algorithms for optimizing neural network parameters due to its non-differen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	228,356
2410.08048	VerifierQ: Enhancing LLM Test Time Compute with Q-Learning-based Verifiers	Recent advancements in test time compute, particularly through the use of verifier models, have significantly enhanced the reasoning capabilities of Large Language Models (LLMs). This generator-verifier approach closely resembles the actor-critic framework in reinforcement learning (RL). However, current verifier model...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	496,925
2010.05687	Semantic Change Detection with Asymmetric Siamese Networks	Given two multi-temporal aerial images, semantic change detection aims to locate the land-cover variations and identify their change types with pixel-wise boundaries. This problem is vital in many earth vision related tasks, such as precise urban planning and natural resource management. Existing state-of-the-art algor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	200,224
1305.1502	Willingness Optimization for Social Group Activity	Studies show that a person is willing to join a social group activity if the activity is interesting, and if some close friends also join the activity as companions. The literature has demonstrated that the interests of a person and the social tightness among friends can be effectively derived and mined from social net...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	24,448
2306.05873	Detecting Adversarial Directions in Deep Reinforcement Learning to Make Robust Decisions	Learning in MDPs with highly complex state representations is currently possible due to multiple advancements in reinforcement learning algorithm design. However, this incline in complexity, and furthermore the increase in the dimensions of the observation came at the cost of volatility that can be taken advantage of v...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	372,368
2410.08731	Developing a Pragmatic Benchmark for Assessing Korean Legal Language Understanding in Large Language Models	Large language models (LLMs) have demonstrated remarkable performance in the legal domain, with GPT-4 even passing the Uniform Bar Exam in the U.S. However their efficacy remains limited for non-standardized tasks and tasks in languages other than English. This underscores the need for careful evaluation of LLMs within...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	497,247
1806.08894	Deep Reinforcement Learning: An Overview	In recent years, a specific machine learning method called deep learning has gained huge attraction, as it has obtained astonishing results in broad applications such as pattern recognition, speech recognition, computer vision, and natural language processing. Recent research has also been shown that deep learning tech...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	101,243
2209.11959	TransPOS: Transformers for Consolidating Different POS Tagset Datasets	In hope of expanding training data, researchers often want to merge two or more datasets that are created using different labeling schemes. This paper considers two datasets that label part-of-speech (POS) tags under different tagging schemes and leverage the supervised labels of one dataset to help generate labels for...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	319,363
2306.01301	Nonholonomic Motion Planning as Efficient as Piano Mover's	We present an algorithm for non-holonomic motion planning (or 'parking a car') that is as computationally efficient as a simple approach to solving the famous Piano-mover's problem, where the non-holonomic constraints are ignored. The core of the approach is a graph-discretization of the problem. The graph-discretizati...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	370,392
1504.01218	Instantly Decodable Network Coding for Real-Time Scalable Video Broadcast over Wireless Networks	In this paper, we study a real-time scalable video broadcast over wireless networks in instantly decodable network coded (IDNC) systems. Such real-time scalable video has a hard deadline and imposes a decoding order on the video layers.We first derive the upper bound on the probability that the individual completion ti...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,787
1503.01180	All Who Wander: On the Prevalence and Characteristics of Multi-community Engagement	Although analyzing user behavior within individual communities is an active and rich research domain, people usually interact with multiple communities both on- and off-line. How do users act in such multi-community environments? Although there are a host of intriguing aspects to this question, it has received much les...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	40,794
0907.4561	Fact Sheet on Semantic Web	The report gives an overview about activities on the topic Semantic Web. It has been released as technical report for the project "KTweb -- Connecting Knowledge Technologies Communities" in 2003.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	4,163
1907.05447	Grounding Value Alignment with Ethical Principles	An important step in the development of value alignment (VA) systems in AI is understanding how values can interrelate with facts. Designers of future VA systems will need to utilize a hybrid approach in which ethical reasoning and empirical observation interrelate successfully in machine behavior. In this article we i...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	138,369
2308.03301	What has ChatGPT read? The origins of archaeological citations used by a generative artificial intelligence application	The public release of ChatGPT has resulted in considerable publicity and has led to wide-spread discussion of the usefulness and capabilities of generative AI language models. Its ability to extract and summarise data from textual sources and present them as human-like contextual responses makes it an eminently suitabl...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	383,987
2105.04396	Stability Constrained Mobile Manipulation Planning on Rough Terrain	This paper presents a framework that allows online dynamic-stability-constrained optimal trajectory planning of a mobile manipulator robot working on rough terrain. First, the kinematics model of a mobile manipulator robot, and the Zero Moment Point (ZMP) stability measure are presented as theoretical background. Then,...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	234,494
2408.14154	Investigating the effect of Mental Models in User Interaction with an Adaptive Dialog Agent	Mental models play an important role in whether user interaction with intelligent systems, such as dialog systems is successful or not. Adaptive dialog systems present the opportunity to align a dialog agent's behavior with heterogeneous user expectations. However, there has been little research into what mental models...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	483,439
2309.16535	KLoB: a Benchmark for Assessing Knowledge Locating Methods in Language Models	Recently, Locate-Then-Edit paradigm has emerged as one of the main approaches in changing factual knowledge stored in the Language models. However, there is a lack of research on whether present locating methods can pinpoint the exact parameters embedding the desired knowledge. Moreover, although many researchers have ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	395,386
2202.02005	BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning	In this paper, we study the problem of enabling a vision-based robotic manipulation system to generalize to novel tasks, a long-standing challenge in robot learning. We approach the challenge from an imitation learning perspective, aiming to study how scaling and broadening the data collected can facilitate such genera...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	278,675
1312.1142	ADI iteration for Lyapunov equations: a tangential approach and adaptive shift selection	A new version of the alternating directions implicit (ADI) iteration for the solution of large-scale Lyapunov equations is introduced. It generalizes the hitherto existing iteration, by incorporating tangential directions in the way they are already available for rational Krylov subspaces. Additionally, first strategie...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	28,842
1901.04668	Distributed Stochastic Gradient Descent Using LDGM Codes	We consider a distributed learning problem in which the computation is carried out on a system consisting of a master node and multiple worker nodes. In such systems, the existence of slow-running machines called stragglers will cause a significant decrease in performance. Recently, coding theoretic framework, which is...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	118,639
2409.05494	An Atmospheric Correction Integrated LULC Segmentation Model for High-Resolution Satellite Imagery	The integration of fine-scale multispectral imagery with deep learning models has revolutionized land use and land cover (LULC) classification. However, the atmospheric effects present in Top-of-Atmosphere sensor measured Digital Number values must be corrected to retrieve accurate Bottom-of-Atmosphere surface reflecta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	486,796
2312.04724	Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models	This paper presents CyberSecEval, a comprehensive benchmark developed to help bolster the cybersecurity of Large Language Models (LLMs) employed as coding assistants. As what we believe to be the most extensive unified cybersecurity safety benchmark to date, CyberSecEval provides a thorough evaluation of LLMs in two cr...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	413,794
2010.15157	Panoster: End-to-end Panoptic Segmentation of LiDAR Point Clouds	Panoptic segmentation has recently unified semantic and instance segmentation, previously addressed separately, thus taking a step further towards creating more comprehensive and efficient perception systems. In this paper, we present Panoster, a novel proposal-free panoptic segmentation method for LiDAR point clouds. ...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	203,679
2406.11241	Reconfigurable Intelligent Surface Equipped UAV in Emergency Wireless Communications: A New Fading-Shadowing Model and Performance Analysis	Communication infrastructure is often severely disrupted in post-disaster areas, which interrupts communications and impedes rescue. Recently, the technology of reconfigurable intelligent surface (RIS)-equipped-UAV has been investigated as a feasible approach to assist communication under such conditions. However, the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	464,787
2404.02588	Large Language Models for Expansion of Spoken Language Understanding Systems to New Languages	Spoken Language Understanding (SLU) models are a core component of voice assistants (VA), such as Alexa, Bixby, and Google Assistant. In this paper, we introduce a pipeline designed to extend SLU systems to new languages, utilizing Large Language Models (LLMs) that we fine-tune for machine translation of slot-annotated...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,927
2303.01778	FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training	Federated Learning (FL) enables collaborations among clients for train machine learning models while protecting their data privacy. Existing FL simulation platforms that are designed from the perspectives of traditional distributed training, suffer from laborious code migration between simulation and production, low ef...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	349,106
1605.01194	IISCNLP at SemEval-2016 Task 2: Interpretable STS with ILP based Multiple Chunk Aligner	Interpretable semantic textual similarity (iSTS) task adds a crucial explanatory layer to pairwise sentence similarity. We address various components of this task: chunk level semantic alignment along with assignment of similarity type and score for aligned chunks with a novel system presented in this paper. We propose...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	55,450
2307.00123	How Do Human Users Teach a Continual Learning Robot in Repeated Interactions?	Continual learning (CL) has emerged as an important avenue of research in recent years, at the intersection of Machine Learning (ML) and Human-Robot Interaction (HRI), to allow robots to continually learn in their environments over long-term interactions with humans. Most research in continual learning, however, has be...	true	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	376,875
1605.08197	Centrality in the Global Network of Corporate Control	Corporations across the world are highly interconnected in a large global network of corporate control. This paper investigates the global board interlock network, covering 400,000 firms linked through 1,700,000 edges representing shared directors between these firms. The main focus is on the concept of centrality, whi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	56,400
1610.04627	Joint CoMP-Cell Selection and Resource Allocation with Fronthaul-Constrained C-RAN	Cloud-based Radio Access Network (C-RAN) is a promising architecture for future cellular networks, in which Baseband Units (BBUs) are placed at a centralized location, with capacity-constrained fronthaul connected to multiple distributed Remote Radio Units (RRHs) that are far away from the BBUs. The centralization of s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	62,415
2409.08426	A Deep Reinforcement Learning Framework For Financial Portfolio Management	In this research paper, we investigate into a paper named "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" [arXiv:1706.10059]. It is a portfolio management problem which is solved by deep learning techniques. The original paper proposes a financial-model-free reinforcement learni...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	487,902
2001.06303	Detection and Tracking Meet Drones Challenge	Drones, or general UAVs, equipped with cameras have been fast deployed with a wide range of applications, including agriculture, aerial photography, and surveillance. Consequently, automatic understanding of visual data collected from drones becomes highly demanding, bringing computer vision and drones more and more cl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	160,770
2202.00343	Interactive configurator with FO(.) and IDP-Z3	Industry abounds with interactive configuration problems, i.e., constraint solving problems interactively solved by persons with the assistance of a computer. The computer program, called a configurator, needs to perform a variety of reasoning tasks with the (often incomplete) information that the user provides. Impera...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	278,107
2311.11312	Optimizing rgb-d semantic segmentation through multi-modal interaction and pooling attention	Semantic segmentation of RGB-D images involves understanding the appearance and spatial relationships of objects within a scene, which requires careful consideration of various factors. However, in indoor environments, the simple input of RGB and depth images often results in a relatively limited acquisition of semanti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,901
2204.07079	Cohesive zone modelling of hydrogen assisted fatigue crack growth: the role of trapping	We investigate the influence of microstructural traps in hydrogen-assisted fatigue crack growth. To this end, a new formulation combining multi-trap stress-assisted diffusion, mechanism-based strain gradient plasticity and a hydrogen- and fatigue-dependent cohesive zone model is presented and numerically implemented. T...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	291,559
2004.07437	Non-Autoregressive Machine Translation with Latent Alignments	This paper presents two strong methods, CTC and Imputer, for non-autoregressive machine translation that model latent alignments with dynamic programming. We revisit CTC for machine translation and demonstrate that a simple CTC model can achieve state-of-the-art for single-step non-autoregressive machine translation, c...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	172,781
2003.00248	Tightly Robust Optimization via Empirical Domain Reduction	Data-driven decision-making is performed by solving a parameterized optimization problem, and the optimal decision is given by an optimal solution for unknown true parameters. We often need a solution that satisfies true constraints even though these are unknown. Robust optimization is employed to obtain such a solutio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	166,241
2208.03238	Learning programs with magic values	A magic value in a program is a constant symbol that is essential for the execution of the program but has no clear explanation for its choice. Learning programs with magic values is difficult for existing program synthesis approaches. To overcome this limitation, we introduce an inductive logic programming approach to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	311,721
2108.08052	Moser Flow: Divergence-based Generative Modeling on Manifolds	We are interested in learning generative models for complex geometries described via manifolds, such as spheres, tori, and other implicit surfaces. Current extensions of existing (Euclidean) generative models are restricted to specific geometries and typically suffer from high computational costs. We introduce Moser Fl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	251,123
1807.07255	Towards Explainable and Controllable Open Domain Dialogue Generation with Dialogue Acts	We study open domain dialogue generation with dialogue acts designed to explain how people engage in social chat. To imitate human behavior, we propose managing the flow of human-machine interactions with the dialogue acts as policies. The policies and response generation are jointly learned from human-human conversati...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	103,283
2103.07052	Improving Authorship Verification using Linguistic Divergence	We propose an unsupervised solution to the Authorship Verification task that utilizes pre-trained deep language models to compute a new metric called DV-Distance. The proposed metric is a measure of the difference between the two authors comparing against pre-trained language models. Our design addresses the problem of...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	224,478
2305.09535	What's the Problem, Linda? The Conjunction Fallacy as a Fairness Problem	The field of Artificial Intelligence (AI) is focusing on creating automated decision-making (ADM) systems that operate as close as possible to human-like intelligence. This effort has pushed AI researchers into exploring cognitive fields like psychology. The work of Daniel Kahneman and the late Amos Tversky on biased h...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	364,672
2208.07969	A Sensor-Based Simulation Method for Spatiotemporal Event Detection	Human movements in urban areas are essential to understand human-environment interactions. However, activities and associated movements are full of uncertainties due to the complexity of a city. In this paper, we propose a novel sensor-based approach for spatiotemporal event detection based on the Discrete Empirical In...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	313,199

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