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
2312.06534	KPIs-Based Clustering and Visualization of HPC jobs: a Feature Reduction Approach	High-Performance Computing (HPC) systems need to be constantly monitored to ensure their stability. The monitoring systems collect a tremendous amount of data about different parameters or Key Performance Indicators (KPIs), such as resource usage, IO waiting time, etc. A proper analysis of this data, usually stored as ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	414,556
2111.07457	Attentive Federated Learning for Concept Drift in Distributed 5G Edge Networks	Machine learning (ML) is expected to play a major role in 5G edge computing. Various studies have demonstrated that ML is highly suitable for optimizing edge computing systems as rapid mobility and application-induced changes occur at the edge. For ML to provide the best solutions, it is important to continually train ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	266,378
1103.3794	Improved QPP Interleavers for LTE Standard	This paper proposes and proves a theorem which stipulates sufficient conditions the coefficients of two quadratic permutation polynomials (QPP) must satisfy, so that the permutations generated by them are identical. The result is used to reduce the search time of QPP interleavers with lengths given by Long Term Evoluti...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,676
2502.12118	Scaling Test-Time Compute Without Verification or RL is Suboptimal	Despite substantial advances in scaling test-time compute, an ongoing debate in the community is how it should be scaled up to enable continued and efficient improvements with scaling. There are largely two approaches: first, distilling successful search or thinking traces; and second, using verification (e.g., 0/1 out...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	534,693
2308.16082	SignDiff: Diffusion Models for American Sign Language Production	In this paper, we propose a dual-condition diffusion pre-training model named SignDiff that can generate human sign language speakers from a skeleton pose. SignDiff has a novel Frame Reinforcement Network called FR-Net, similar to dense human pose estimation work, which enhances the correspondence between text lexical ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,894
2304.00804	Two-layer adaptive trajectory tracking controller for quadruped robots on slippery terrains	Task space trajectory tracking for quadruped robots plays a crucial role on achieving dexterous maneuvers in unstructured environments. To fulfill the control objective, the robot should apply forces through the contact of the legs with the supporting surface, while maintaining its stability and controllability. In ord...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	355,823
2004.00490	Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness	In cellular federated edge learning (FEEL), multiple edge devices holding local data jointly train a neural network by communicating learning updates with an access point without exchanging their data samples. With very limited communication resources, it is beneficial to schedule the most informative local learning up...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	170,655
2407.11870	Fusion LiDAR-Inertial-Encoder data for High-Accuracy SLAM	In the realm of robotics, achieving simultaneous localization and mapping (SLAM) is paramount for autonomous navigation, especially in challenging environments like texture-less structures. This paper proposed a factor-graph-based model that tightly integrates IMU and encoder sensors to enhance positioning in such envi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	473,655
2010.04099	On Performance Characterization of Cascaded Multiwire-PLC/MIMO-RF Communication System	The flexibility of radio frequency (RF) systems and the omnipresence of power cables potentially make the cascaded power line communication (PLC)/RF system an efficient and cost-effective solution in terms of wide coverage and high-speed transmission. This letter proposes an opportunistic decode-and-forward (DF)-based ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	199,623
2406.12045	$\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains	Existing benchmarks do not test language agents on their interaction with human users or ability to follow domain-specific rules, both of which are vital for deploying them in real world applications. We propose $\tau$-bench, a benchmark emulating dynamic conversations between a user (simulated by language models) and ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	465,196
2306.01782	Capacity Constrained Influence Maximization in Social Networks	Influence maximization (IM) aims to identify a small number of influential individuals to maximize the information spread and finds applications in various fields. It was first introduced in the context of viral marketing, where a company pays a few influencers to promote the product. However, apart from the cost facto...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	370,603
1911.02390	Guiding Variational Response Generator to Exploit Persona	Leveraging persona information of users in Neural Response Generators (NRG) to perform personalized conversations has been considered as an attractive and important topic in the research of conversational agents over the past few years. Despite of the promising progresses achieved by recent studies in this field, perso...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	152,350
2402.17417	CARZero: Cross-Attention Alignment for Radiology Zero-Shot Classification	The advancement of Zero-Shot Learning in the medical domain has been driven forward by using pre-trained models on large-scale image-text pairs, focusing on image-text alignment. However, existing methods primarily rely on cosine similarity for alignment, which may not fully capture the complex relationship between med...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	432,982
1609.03415	Active Canny: Edge Detection and Recovery with Open Active Contour Models	We introduce an edge detection and recovery framework based on open active contour models (snakelets). This is motivated by the noisy or broken edges output by standard edge detection algorithms, like Canny. The idea is to utilize the local continuity and smoothness cues provided by strong edges and grow them to recove...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	60,874
2410.13039	A low complexity contextual stacked ensemble-learning approach for pedestrian intent prediction	Walking as a form of active travel is essential in promoting sustainable transport. It is thus crucial to accurately predict pedestrian crossing intention and avoid collisions, especially with the advent of autonomous and advanced driver-assisted vehicles. Current research leverages computer vision and machine learning...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	499,338
2001.09975	Optimal Selective Encoding for Timely Updates	We consider a system in which an information source generates independent and identically distributed status update packets from an observed phenomenon that takes $n$ possible values based on a given pmf. These update packets are encoded at the transmitter node to be sent to the receiver node. Instead of encoding all $...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	161,711
2010.01932	Is Information Theory Inherently a Theory of Causation?	Information theory gives rise to a novel method for causal skeleton discovery by expressing associations between variables as tensors. This tensor-based approach reduces the dimensionality of the data needed to test for conditional independence, e.g., for systems comprising three variables, the causal skeleton can be d...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	198,849
2305.11746	HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine Translation	Hallucinations in machine translation are translations that contain information completely unrelated to the input. Omissions are translations that do not include some of the input information. While both cases tend to be catastrophic errors undermining user trust, annotated data with these types of pathologies is extre...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	365,677
2411.02607	Towards Context-Aware Adaptation in Extended Reality: A Design Space for XR Interfaces and an Adaptive Placement Strategy	By converting the entire 3D space around the user into a screen, Extended Reality (XR) can ameliorate traditional displays' space limitations and facilitate the consumption of multiple pieces of information at a time. However, if designed inappropriately, these XR interfaces can overwhelm the user and complicate inform...	true	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	true	505,576
2311.10477	The Set of Pure Gaps at Several Rational Places in Function Fields	In this work, using maximal elements in generalized Weierstrass semigroups and its relationship with pure gaps, we extend the results in \cite{CMT2024} and provide a way to completely determine the set of pure gaps at several rational places in an arbitrary function field $F$ over a finite field and its cardinality. As...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	408,542
1511.02669	Enacting textual entailment and ontologies for automated essay grading in chemical domain	We propose a system for automated essay grading using ontologies and textual entailment. The process of textual entailment is guided by hypotheses, which are extracted from a domain ontology. Textual entailment checks if the truth of the hypothesis follows from a given text. We enact textual entailment to compare stude...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	48,671
2412.05897	Detecting Discrepancies Between AI-Generated and Natural Images Using Uncertainty	In this work, we propose a novel approach for detecting AI-generated images by leveraging predictive uncertainty to mitigate misuse and associated risks. The motivation arises from the fundamental assumption regarding the distributional discrepancy between natural and AI-generated images. The feasibility of distinguish...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	515,020
2404.07353	Addressing the Abstraction and Reasoning Corpus via Procedural Example Generation	This work presents code to procedurally generate examples for the ARC training tasks. For each of the 400 tasks, an example generator following the transformation logic of the original examples was created. In effect, the assumed underlying distribution of examples for any given task was reverse engineered by implement...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	445,800
2308.03514	Worker Activity Recognition in Manufacturing Line Using Near-body Electric Field	Manufacturing industries strive to improve production efficiency and product quality by deploying advanced sensing and control systems. Wearable sensors are emerging as a promising solution for achieving this goal, as they can provide continuous and unobtrusive monitoring of workers' activities in the manufacturing lin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	384,062
2408.08430	Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learning	Federated Learning(FL), in theory, preserves privacy of individual clients' data while producing quality machine learning models. However, attacks such as Deep Leakage from Gradients(DLG) severely question the practicality of FL. In this paper, we empirically evaluate the efficacy of four defensive methods against DLG:...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	480,986
2305.07421	Selective imitation on the basis of reward function similarity	Imitation is a key component of human social behavior, and is widely used by both children and adults as a way to navigate uncertain or unfamiliar situations. But in an environment populated by multiple heterogeneous agents pursuing different goals or objectives, indiscriminate imitation is unlikely to be an effective ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	363,895
1712.08707	Freebase-triples: A Methodology for Processing the Freebase Data Dumps	The Freebase knowledge base was a significant Semantic Web and linked data technology during its years of operations since 2007. Following its acquisition by Google in 2010 and its shutdown in 2016, Freebase data is contained in a data dump of billions of RDF triples. In this research, an exploration of the Freebase da...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	87,236
1911.11403	SemEval-2015 Task 3: Answer Selection in Community Question Answering	Community Question Answering (cQA) provides new interesting research directions to the traditional Question Answering (QA) field, e.g., the exploitation of the interaction between users and the structure of related posts. In this context, we organized SemEval-2015 Task 3 on "Answer Selection in cQA", which included two...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	155,117
1906.06863	A Generic Approach for Accelerating Belief Propagation based DCOP Algorithms via A Branch-and-Bound Technique	Belief propagation approaches, such as Max-Sum and its variants, are a kind of important methods to solve large-scale Distributed Constraint Optimization Problems (DCOPs). However, for problems with n-ary constraints, these algorithms face a huge challenge since their computational complexity scales exponentially with ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	135,442
2407.10250	Product and Ratio of Two $\alpha-\kappa-\mu$ Shadowed Random Variables and its Application to Wireless Communication	This work studies the product and ratio statistics of independent and non-identically distributed (i.n.i.d) $ \alpha-\kappa - \mu $ shadowed random variables. We derive the series expression for the probability density function (PDF), cumulative distribution function (CDF), and moment generating function (MGF) of the p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	472,903
2203.00538	Capability-based Frameworks for Industrial Robot Skills: a Survey	The research community is puzzled with words like skill, action, atomic unit and others when describing robots' capabilities. However, for giving the possibility to integrate capabilities in industrial scenarios, a standardization of these descriptions is necessary. This work uses a structured review approach to identi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	283,041
2309.07383	Rates of Convergence in Certain Native Spaces of Approximations used in Reinforcement Learning	This paper studies convergence rates for some value function approximations that arise in a collection of reproducing kernel Hilbert spaces (RKHS) $H(\Omega)$. By casting an optimal control problem in a specific class of native spaces, strong rates of convergence are derived for the operator equation that enables offli...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	391,755
2305.10412	AI Friends: A Design Framework for AI-Powered Creative Programming for Youth	What role can AI play in supporting and constraining creative coding by families? To investigate these questions, we built a Wizard of Oz platform to help families engage in creative coding in partnership with a researcher-operated AI Friend. We designed a 3 week series of programming activities with ten children, 7 to...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	365,044
2009.02713	Higher-order Quasi-Monte Carlo Training of Deep Neural Networks	We present a novel algorithmic approach and an error analysis leveraging Quasi-Monte Carlo points for training deep neural network (DNN) surrogates of Data-to-Observable (DtO) maps in engineering design. Our analysis reveals higher-order consistent, deterministic choices of training points in the input data space for d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	194,637
2409.19152	MASt3R-SfM: a Fully-Integrated Solution for Unconstrained Structure-from-Motion	Structure-from-Motion (SfM), a task aiming at jointly recovering camera poses and 3D geometry of a scene given a set of images, remains a hard problem with still many open challenges despite decades of significant progress. The traditional solution for SfM consists of a complex pipeline of minimal solvers which tends t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	492,558
2310.03777	PrIeD-KIE: Towards Privacy Preserved Document Key Information Extraction	In this paper, we introduce strategies for developing private Key Information Extraction (KIE) systems by leveraging large pretrained document foundation models in conjunction with differential privacy (DP), federated learning (FL), and Differentially Private Federated Learning (DP-FL). Through extensive experimentatio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	397,422
2402.09631	Representation Surgery: Theory and Practice of Affine Steering	Language models often exhibit undesirable behavior, e.g., generating toxic or gender-biased text. In the case of neural language models, an encoding of the undesirable behavior is often present in the model's representations. Thus, one natural (and common) approach to prevent the model from exhibiting undesirable behav...	false	false	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	429,605
2307.13429	Multi-Objective Optimisation of URLLC-Based Metaverse Services	Metaverse aims for building a fully immersive virtual shared space, where the users are able to engage in various activities. To successfully deploy the service for each user, the Metaverse service provider and network service provider generally localise the user first and then support the communication between the bas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	381,587
2403.04140	Contrastive Augmented Graph2Graph Memory Interaction for Few Shot Continual Learning	Few-Shot Class-Incremental Learning (FSCIL) has gained considerable attention in recent years for its pivotal role in addressing continuously arriving classes. However, it encounters additional challenges. The scarcity of samples in new sessions intensifies overfitting, causing incompatibility between the output featur...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	435,471
2402.03049	EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models	In recent years, instruction tuning has gained increasing attention and emerged as a crucial technique to enhance the capabilities of Large Language Models (LLMs). To construct high-quality instruction datasets, many instruction processing approaches have been proposed, aiming to achieve a delicate balance between data...	true	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	426,839
1812.05270	Joint Entity Extraction and Assertion Detection for Clinical Text	Negative medical findings are prevalent in clinical reports, yet discriminating them from positive findings remains a challenging task for information extraction. Most of the existing systems treat this task as a pipeline of two separate tasks, i.e., named entity recognition (NER) and rule-based negation detection. We ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	116,382
1703.00079	Fault Tolerant Thermal Control of Steam Turbine Shell Deflections	The metal-to-metal clearances of a steam turbine during full or part load operation are among the main drivers of efficiency. The requirement to add clearances is driven by a number of factors including the relative movements of the steam turbine shell and rotor during transient conditions such as startup and shutdown....	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	69,098
2412.18489	An Overview and Discussion of the Suitability of Existing Speech Datasets to Train Machine Learning Models for Collective Problem Solving	This report characterized the suitability of existing datasets for devising new Machine Learning models, decision making methods, and analysis algorithms to improve Collaborative Problem Solving and then enumerated requirements for future datasets to be devised. Problem solving was assumed to be performed in teams of a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	520,438
2108.10634	Learning to Arbitrate Human and Robot Control using Disagreement between Sub-Policies	In the context of teleoperation, arbitration refers to deciding how to blend between human and autonomous robot commands. We present a reinforcement learning solution that learns an optimal arbitration strategy that allocates more control authority to the human when the robot comes across a decision point in the task. ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	251,958
2305.11260	Constrained Environment Optimization for Prioritized Multi-Agent Navigation	Traditional approaches to the design of multi-agent navigation algorithms consider the environment as a fixed constraint, despite the influence of spatial constraints on agents' performance. Yet hand-designing conducive environment layouts is inefficient and potentially expensive. The goal of this paper is to consider ...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	true	false	false	false	365,447
2412.13115	Koopman Mode-Based Detection of Internal Short Circuits in Lithium-ion Battery Pack	Monitoring of internal short circuit (ISC) in Lithium-ion battery packs is imperative to safe operations, optimal performance, and extension of pack life. Since ISC in one of the modules inside a battery pack can eventually lead to thermal runaway, it is crucial to detect its early onset. However, the inaccuracy and ag...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	518,167
2303.15068	DQSOps: Data Quality Scoring Operations Framework for Data-Driven Applications	Data quality assessment has become a prominent component in the successful execution of complex data-driven artificial intelligence (AI) software systems. In practice, real-world applications generate huge volumes of data at speeds. These data streams require analysis and preprocessing before being permanently stored o...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	354,349
2310.17998	Closing the Gap Between the Upper Bound and the Lower Bound of Adam's Iteration Complexity	Recently, Arjevani et al. [1] established a lower bound of iteration complexity for the first-order optimization under an $L$-smooth condition and a bounded noise variance assumption. However, a thorough review of existing literature on Adam's convergence reveals a noticeable gap: none of them meet the above lower boun...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	403,365
2411.06883	Scalable Distributed Least Squares Algorithm for Linear Algebraic Equations via Scheduling	In this work, we propose a novel discrete-time distributed algorithm for finding least squares solutions of linear algebraic equations with a scheduling protocol to further enhance its scalability. Each agent in the network is assumed to know some rows of the coefficient matrix and the corresponding entries in the obse...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	507,314
2402.13950	Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought Reasoning	Large language models (LLMs) have been shown to perform better when asked to reason step-by-step before answering a question. However, it is unclear to what degree the model's final answer is faithful to the stated reasoning steps. In this paper, we perform a causal mediation analysis on twelve LLMs to examine how inte...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	431,476
2008.07178	Disentangled Item Representation for Recommender Systems	Item representations in recommendation systems are expected to reveal the properties of items. Collaborative recommender methods usually represent an item as one single latent vector. Nowadays the e-commercial platforms provide various kinds of attribute information for items (e.g., category, price and style of clothin...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	192,023
2001.11688	A study on the role of subsidiary information in replay attack spoofing detection	In this study, we analyze the role of various categories of subsidiary information in conducting replay attack spoofing detection: `Room Size', `Reverberation', `Speaker-to-ASV distance, `Attacker-to-Speaker distance', and `Replay Device Quality'. As a means of analyzing subsidiary information, we use two frameworks to...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,135
2103.11895	Deep learning on fundus images detects glaucoma beyond the optic disc	Although unprecedented sensitivity and specificity values are reported, recent glaucoma detection deep learning models lack in decision transparency. Here, we propose a methodology that advances explainable deep learning in the field of glaucoma detection and vertical cup-disc ratio (VCDR), an important risk factor. We...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	225,993
1907.03452	Deep splitting method for parabolic PDEs	In this paper we introduce a numerical method for nonlinear parabolic PDEs that combines operator splitting with deep learning. It divides the PDE approximation problem into a sequence of separate learning problems. Since the computational graph for each of the subproblems is comparatively small, the approach can handl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	137,867
1106.2819	Optimizing Constellations for Single-Subcarrier Intensity-Modulated Optical Systems	We optimize modulation formats for the additive white Gaussian noise channel with nonnegative input, also known as the intensity-modulated direct-detection channel, with and without confining them to a lattice structure. Our optimization criteria are the average electrical, average optical, and peak power. The nonnegat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,856
2203.08923	Towards True Detail Restoration for Super-Resolution: A Benchmark and a Quality Metric	Super-resolution (SR) has become a widely researched topic in recent years. SR methods can improve overall image and video quality and create new possibilities for further content analysis. But the SR mainstream focuses primarily on increasing the naturalness of the resulting image despite potentially losing context ac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,951
2106.05738	GBHT: Gradient Boosting Histogram Transform for Density Estimation	In this paper, we propose a density estimation algorithm called \textit{Gradient Boosting Histogram Transform} (GBHT), where we adopt the \textit{Negative Log Likelihood} as the loss function to make the boosting procedure available for the unsupervised tasks. From a learning theory viewpoint, we first prove fast conve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	240,209
1909.10080	Whole-Body Geometric Retargeting for Humanoid Robots	Humanoid robot teleoperation allows humans to integrate their cognitive capabilities with the apparatus to perform tasks that need high strength, manoeuvrability and dexterity. This paper presents a framework for teleoperation of humanoid robots using a novel approach for motion retargeting through inverse kinematics o...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	146,441
1607.03519	Common-Message Broadcast Channels with Feedback in the Nonasymptotic Regime: Stop Feedback	We investigate the maximum coding rate for a given average blocklength and error probability over a K-user discrete memoryless broadcast channel for the scenario where a common message is transmitted using variable-length stop-feedback codes. For the point-to-point case, Polyanskiy et al. (2011) demonstrated that varia...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	58,527
2302.07120	PrefixMol: Target- and Chemistry-aware Molecule Design via Prefix Embedding	Is there a unified model for generating molecules considering different conditions, such as binding pockets and chemical properties? Although target-aware generative models have made significant advances in drug design, they do not consider chemistry conditions and cannot guarantee the desired chemical properties. Unfo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	345,625
2309.13022	Graph Neural Network for Stress Predictions in Stiffened Panels Under Uniform Loading	Machine learning (ML) and deep learning (DL) techniques have gained significant attention as reduced order models (ROMs) to computationally expensive structural analysis methods, such as finite element analysis (FEA). Graph neural network (GNN) is a particular type of neural network which processes data that can be rep...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	394,010
2009.06824	Stratified and Time-aware Sampling based Adaptive Ensemble Learning for Streaming Recommendations	Recommender systems have played an increasingly important role in providing users with tailored suggestions based on their preferences. However, the conventional offline recommender systems cannot handle the ubiquitous data stream well. To address this issue, Streaming Recommender Systems (SRSs) have emerged in recent ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	195,757
1909.08263	Distributed Answer Set Coloring: Stable Models Computation via Graph Coloring	Answer Set Programming (ASP) is a famous logic language for knowledge representation, which has been really successful in the last years, as witnessed by the great interest into the development of efficient solvers for ASP. Yet, the great request of resources for certain types of problems, as the planning ones, still c...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	145,939
2411.09607	Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Framework	This report provides an initial look at partial results from the TREC 2024 Retrieval-Augmented Generation (RAG) Track. We have identified RAG evaluation as a barrier to continued progress in information access (and more broadly, natural language processing and artificial intelligence), and it is our hope that we can co...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	508,307
0906.3323	Adaptive Regularization of Ill-Posed Problems: Application to Non-rigid Image Registration	We introduce an adaptive regularization approach. In contrast to conventional Tikhonov regularization, which specifies a fixed regularization operator, we estimate it simultaneously with parameters. From a Bayesian perspective we estimate the prior distribution on parameters assuming that it is close to some given mode...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	3,909
2411.04263	Object Recognition in Human Computer Interaction:- A Comparative Analysis	Human-computer interaction (HCI) has been a widely researched area for many years, with continuous advancements in technology leading to the development of new techniques that change the way we interact with computers. With the recent advent of powerful computers, we recognize human actions and interact accordingly, th...	true	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	506,195
2003.00834	CALVIS: chest, waist and pelvis circumference from 3D human body meshes as ground truth for deep learning	In this paper we present CALVIS, a method to calculate $\textbf{C}$hest, w$\textbf{A}$ist and pe$\textbf{LVIS}$ circumference from 3D human body meshes. Our motivation is to use this data as ground truth for training convolutional neural networks (CNN). Previous work had used the large scale CAESAR dataset or determine...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	166,449
1703.06714	Generalized Compute-Compress-and-Forward	Compute-and-forward (CF) harnesses interference in wireless communications by exploiting structured coding. The key idea of CF is to compute integer combinations of codewords from multiple source nodes, rather than to decode individual codewords by treating others as noise. Compute-compress-and-forward (CCF) can furthe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	70,272
2102.11497	Controllable and Diverse Text Generation in E-commerce	In E-commerce, a key challenge in text generation is to find a good trade-off between word diversity and accuracy (relevance) in order to make generated text appear more natural and human-like. In order to improve the relevance of generated results, conditional text generators were developed that use input keywords or ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	221,443
2103.12609	Incrementally Zero-Shot Detection by an Extreme Value Analyzer	Human beings not only have the ability to recognize novel unseen classes, but also can incrementally incorporate the new classes to existing knowledge preserved. However, zero-shot learning models assume that all seen classes should be known beforehand, while incremental learning models cannot recognize unseen classes....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	226,236
1705.10413	Learning to Generate Chairs with Generative Adversarial Nets	Generative adversarial networks (GANs) has gained tremendous popularity lately due to an ability to reinforce quality of its predictive model with generated objects and the quality of the generative model with and supervised feedback. GANs allow to synthesize images with a high degree of realism. However, the learning ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,385
2301.11989	Practical Differentially Private Hyperparameter Tuning with Subsampling	Tuning the hyperparameters of differentially private (DP) machine learning (ML) algorithms often requires use of sensitive data and this may leak private information via hyperparameter values. Recently, Papernot and Steinke (2022) proposed a certain class of DP hyperparameter tuning algorithms, where the number of rand...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	342,340
2412.12406	Global SLAM in Visual-Inertial Systems with 5G Time-of-Arrival Integration	This paper presents a novel approach that integrates 5G Time of Arrival (ToA) measurements into ORB-SLAM3 to enable global localization and enhance mapping capabilities for indoor drone navigation. We extend ORB-SLAM3's optimization pipeline to jointly process ToA data from 5G base stations alongside visual and inertia...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	517,852
1909.13765	FNHSM_HRS: Hybrid recommender system using fuzzy clustering and heuristic similarity measure	Nowadays, Recommender Systems have become a comprehensive system for helping and guiding users in a huge amount of data on the Internet. Collaborative Filtering offers to active users based on the rating of a set of users. One of the simplest and most comprehensible and successful models is to find users with a taste i...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	147,511
2007.01126	A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning	Multi-task learning (MTL) optimizes several learning tasks simultaneously and leverages their shared information to improve generalization and the prediction of the model for each task. Auxiliary tasks can be added to the main task to ultimately boost the performance. In this paper, we provide a brief review on the rec...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	185,333
2405.10612	Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformers	Given the power of vision transformers, a new learning paradigm, pre-training and then prompting, makes it more efficient and effective to address downstream visual recognition tasks. In this paper, we identify a novel security threat towards such a paradigm from the perspective of backdoor attacks. Specifically, an ex...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	454,825
2204.03044	Fusing finetuned models for better pretraining	Pretrained models are the standard starting point for training. This approach consistently outperforms the use of a random initialization. However, pretraining is a costly endeavour that few can undertake. In this paper, we create better base models at hardly any cost, by fusing multiple existing fine tuned models in...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	290,166
2412.02210	CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy	Large Multimodal Models (LMMs) have demonstrated impressive performance in recognizing document images with natural language instructions. However, it remains unclear to what extent capabilities in literacy with rich structure and fine-grained visual challenges. The current landscape lacks a comprehensive benchmark to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,434
2202.04748	Estimation of Clinical Workload and Patient Activity using Deep Learning and Optical Flow	Contactless monitoring using thermal imaging has become increasingly proposed to monitor patient deterioration in hospital, most recently to detect fevers and infections during the COVID-19 pandemic. In this letter, we propose a novel method to estimate patient motion and observe clinical workload using a similar techn...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	279,649
2312.02941	Fast CT anatomic localization algorithm	Automatically determining the position of every slice in a CT scan is a basic yet powerful capability allowing fast retrieval of region of interest for visual inspection and automated analysis. Unlike conventional localization approaches which work at the slice level, we directly localize only a fraction of the slices ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	413,059
1611.07567	Feature Importance Measure for Non-linear Learning Algorithms	Complex problems may require sophisticated, non-linear learning methods such as kernel machines or deep neural networks to achieve state of the art prediction accuracies. However, high prediction accuracies are not the only objective to consider when solving problems using machine learning. Instead, particular scientif...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	64,366
1102.2891	Usage Bibliometrics	Scholarly usage data provides unique opportunities to address the known shortcomings of citation analysis. However, the collection, processing and analysis of usage data remains an area of active research. This article provides a review of the state-of-the-art in usage-based informetric, i.e. the use of usage data to s...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	9,185
1509.01698	HAMSI: A Parallel Incremental Optimization Algorithm Using Quadratic Approximations for Solving Partially Separable Problems	We propose HAMSI (Hessian Approximated Multiple Subsets Iteration), which is a provably convergent, second order incremental algorithm for solving large-scale partially separable optimization problems. The algorithm is based on a local quadratic approximation, and hence, allows incorporating curvature information to sp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	46,642
2303.00532	fpgaDDS: An Intra-FPGA Data Distribution Service for ROS 2 Robotics Applications	Modern computing platforms for robotics applications comprise a set of heterogeneous elements, e.g., multi-core CPUs, embedded GPUs, and FPGAs. FPGAs are reprogrammable hardware devices that allow for fast and energy-efficient computation of many relevant tasks in robotics. ROS is the de-facto programming standard for ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	348,632
2103.00051	Constructing Dampened LTI Systems Generating Polynomial Bases	We present an alternative derivation of the LTI system underlying the Legendre Delay Network (LDN). To this end, we first construct an LTI system that generates the Legendre polynomials. We then dampen the system by approximating a windowed impulse response, using what we call a "delay re-encoder". The resulting LTI sy...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	222,127
2308.11124	Constructive Equivariant Observer Design for Inertial Navigation	Inertial Navigation Systems (INS) are algorithms that fuse inertial measurements of angular velocity and specific acceleration with supplementary sensors including GNSS and magnetometers to estimate the position, velocity and attitude, or extended pose, of a vehicle. The industry-standard extended Kalman filter (EKF) d...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	387,012
2409.08765	Cross-Country Comparative Analysis of Climate Resilience and Localized Mapping in Data-Sparse Regions	Climate resilience across sectors varies significantly in low-income countries (LICs), with agriculture being the most vulnerable to climate change. Existing studies typically focus on individual countries, offering limited insights into broader cross-country patterns of adaptation and vulnerability. This paper address...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	488,047
1311.0810	On the emergence of an "intention field" for socially cohesive agents	We argue that when a social convergence mechanism exists and is strong enough, one should expect the emergence of a well defined "field", i.e. a slowly evolving, local quantity around which individual attributes fluctuate in a finite range. This condensation phenomenon is well illustrated by the Deffuant-Weisbuch opini...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	28,185
2204.09308	A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement	Neural networks are ubiquitous in many tasks, but trusting their predictions is an open issue. Uncertainty quantification is required for many applications, and disentangled aleatoric and epistemic uncertainties are best. In this paper, we generalize methods to produce disentangled uncertainties to work with different ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	292,390
1203.4031	FEAST Eigenvalue Solver v3.0 User Guide	The FEAST eigensolver package is a free high-performance numerical library for solving the Hermitian and non-Hermitian eigenvalue problems, and obtaining all the eigenvalues and (right/left) eigenvectors within a given search interval or arbitrary contour in the complex plane. Its originality lies with a new transforma...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	15,009
2306.02342	Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration	We propose an image restoration algorithm that can control the perceptual quality and/or the mean square error (MSE) of any pre-trained model, trading one over the other at test time. Our algorithm is few-shot: Given about a dozen images restored by the model, it can significantly improve the perceptual quality and/or ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	370,864
2004.13608	An Explainable Deep Learning-based Prognostic Model for Rotating Machinery	This paper develops an explainable deep learning model that estimates the remaining useful lives of rotating machinery. The model extracts high-level features from Fourier transform using an autoencoder. The features are used as input to a feedforward neural network to estimate the remaining useful lives. The paper exp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	174,606
2208.12327	DSR: Towards Drone Image Super-Resolution	Despite achieving remarkable progress in recent years, single-image super-resolution methods are developed with several limitations. Specifically, they are trained on fixed content domains with certain degradations (whether synthetic or real). The priors they learn are prone to overfitting the training configuration. T...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	314,689
2405.04897	Machine Learning-based NLP for Emotion Classification on a Cholera X Dataset	Recent social media posts on the cholera outbreak in Hammanskraal have highlighted the diverse range of emotions people experienced in response to such an event. The extent of people's opinions varies greatly depending on their level of knowledge and information about the disease. The documented re-search about Cholera...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	452,718
1811.01394	A method to construct exponential families by representation theory	In this paper, we give a method to construct "good" exponential families systematically by representation theory. More precisely, we consider a homogeneous space $G/H$ as a sample space and construct an exponential family invariant under the transformation group $G$ by using a representation of $G$. The method generate...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,355
2501.02825	Randomly Sampled Language Reasoning Problems Reveal Limits of LLMs	Can LLMs pick up language structure from examples? Evidence in prior work seems to indicate yes, as pretrained models repeatedly demonstrate the ability to adapt to new language structures and vocabularies. However, this line of research typically considers languages that are present within common pretraining datasets,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	522,652
2412.02574	Generating Critical Scenarios for Testing Automated Driving Systems	Autonomous vehicles (AVs) have demonstrated significant potential in revolutionizing transportation, yet ensuring their safety and reliability remains a critical challenge, especially when exposed to dynamic and unpredictable environments. Real-world testing of an Autonomous Driving System (ADS) is both expensive and r...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	true	513,586
2212.13638	Battling the Coronavirus Infodemic Among Social Media Users in Kenya and Nigeria	How can we induce social media users to be discerning when sharing information during a pandemic? An experiment on Facebook Messenger with users from Kenya (n = 7,498) and Nigeria (n = 7,794) tested interventions designed to decrease intentions to share COVID-19 misinformation without decreasing intentions to share fac...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	338,357
1906.11470	Automatically Extract the Semi-transparent Motion-blurred Hand from a Single Image	When we use video chat, video game, or other video applications, motion-blurred hands often appear. Accurately extracting these hands is very useful for video editing and behavior analysis. However, existing motion-blurred object extraction methods either need user interactions, such as user supplied trimaps and scribb...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	136,677
1507.08788	Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity	We study the convergence properties of the VR-PCA algorithm introduced by \cite{shamir2015stochastic} for fast computation of leading singular vectors. We prove several new results, including a formal analysis of a block version of the algorithm, and convergence from random initialization. We also make a few observatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	45,602

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