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
2501.16050	Skeleton-Guided-Translation: A Benchmarking Framework for Code Repository Translation with Fine-Grained Quality Evaluation	The advancement of large language models has intensified the need to modernize enterprise applications and migrate legacy systems to secure, versatile languages. However, existing code translation benchmarks primarily focus on individual functions, overlooking the complexities involved in translating entire repositorie...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	527,800
2103.14066	Beyond permutation equivariance in graph networks	In this draft paper, we introduce a novel architecture for graph networks which is equivariant to the Euclidean group in $n$-dimensions. The model is designed to work with graph networks in their general form and can be shown to include particular variants as special cases. Thanks to its equivariance properties, we exp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	226,710
2411.08003	Can adversarial attacks by large language models be attributed?	Attributing outputs from Large Language Models (LLMs) in adversarial settings-such as cyberattacks and disinformation-presents significant challenges that are likely to grow in importance. We investigate this attribution problem using formal language theory, specifically language identification in the limit as introduc...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	true	507,745
2206.06706	An analysis of retracted papers in Computer Science	Context: The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent. Objective: The aim is to assess: (i) the extent and nature of retracted research in Computer Science ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	302,468
2408.16899	Network-aware Recommender System via Online Feedback Optimization	Personalized content on social platforms can exacerbate negative phenomena such as polarization, partly due to the feedback interactions between recommendations and the users. In this paper, we present a control-theoretic recommender system that explicitly accounts for this feedback loop to mitigate polarization. Our a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	484,495
2312.00914	Optimizing Information Freshness over a Channel that Wears Out	A sensor samples and transmits status updates to a destination through a wireless channel that wears out over time and with every use. At each time slot, the sensor can decide to sample and transmit a fresh status update, restore the initial quality of the channel, or remain silent. The actions impose different costs o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	412,230
2003.11420	Fast and resilient manipulation planning for target retrieval in clutter	This paper presents a task and motion planning (TAMP) framework for a robotic manipulator in order to retrieve a target object from clutter. We consider a configuration of objects in a confined space with a high density so no collision-free path to the target exists. The robot must relocate some objects to retrieve the...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	169,598
1911.00171	PODNet: A Neural Network for Discovery of Plannable Options	Learning from demonstration has been widely studied in machine learning but becomes challenging when the demonstrated trajectories are unstructured and follow different objectives. This short-paper proposes PODNet, Plannable Option Discovery Network, addressing how to segment an unstructured set of demonstrated traject...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	151,744
1606.07829	Unsupervised Topic Modeling Approaches to Decision Summarization in Spoken Meetings	We present a token-level decision summarization framework that utilizes the latent topic structures of utterances to identify "summary-worthy" words. Concretely, a series of unsupervised topic models is explored and experimental results show that fine-grained topic models, which discover topics at the utterance-level r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	57,788
2401.03500	Quadrotor Stabilization with Safety Guarantees: A Universal Formula Approach	Safe stabilization is a significant challenge for quadrotors, which involves reaching a goal position while avoiding obstacles. Most of the existing solutions for this problem rely on optimization-based methods, demanding substantial onboard computational resources. This paper introduces a novel approach to address thi...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	420,129
1805.04690	New Embedded Representations and Evaluation Protocols for Inferring Transitive Relations	Beyond word embeddings, continuous representations of knowledge graph (KG) components, such as entities, types and relations, are widely used for entity mention disambiguation, relation inference and deep question answering. Great strides have been made in modeling general, asymmetric or antisymmetric KG relations usin...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	97,289
2501.15165	A* Based Algorithm for Reduced Complexity ML Decoding of Tailbiting Codes	The A* algorithm is a graph search algorithm which has shown good results in terms of computational complexity for Maximum Likelihood (ML) decoding of tailbiting convolutional codes. The decoding of tailbiting codes with this algorithm is performed in two phases. In the first phase, a typical Viterbi decoding is employ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	527,433
1805.06197	A Structural Representation Learning for Multi-relational Networks	Most of the existing multi-relational network embedding methods, e.g., TransE, are formulated to preserve pair-wise connectivity structures in the networks. With the observations that significant triangular connectivity structures and parallelogram connectivity structures found in many real multi-relational networks ar...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	97,555
2202.03874	Combining Intra-Risk and Contagion Risk for Enterprise Bankruptcy Prediction Using Graph Neural Networks	Predicting the bankruptcy risk of small and medium-sized enterprises (SMEs) is an important step for financial institutions when making decisions about loans. Existing studies in both finance and AI research fields, however, tend to only consider either the intra-risk or contagion risk of enterprises, ignoring their in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,373
2012.02757	Playing Text-Based Games with Common Sense	Text based games are simulations in which an agent interacts with the world purely through natural language. They typically consist of a number of puzzles interspersed with interactions with common everyday objects and locations. Deep reinforcement learning agents can learn to solve these puzzles. However, the everyday...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	209,870
cs/0509071	CP-nets and Nash equilibria	We relate here two formalisms that are used for different purposes in reasoning about multi-agent systems. One of them are strategic games that are used to capture the idea that agents interact with each other while pursuing their own interest. The other are CP-nets that were introduced to express qualitative and condi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	538,972
2407.10003	A Dynamic Algorithm for Weighted Submodular Cover Problem	We initiate the study of the submodular cover problem in dynamic setting where the elements of the ground set are inserted and deleted. In the classical submodular cover problem, we are given a monotone submodular function $f : 2^{V} \to \mathbb{R}^{\ge 0}$ and the goal is to obtain a set $S \subseteq V$ that minimiz...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	472,803
2407.13437	FREST: Feature RESToration for Semantic Segmentation under Multiple Adverse Conditions	Robust semantic segmentation under adverse conditions is crucial in real-world applications. To address this challenging task in practical scenarios where labeled normal condition images are not accessible in training, we propose FREST, a novel feature restoration framework for source-free domain adaptation (SFDA) of s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	474,381
2403.13627	Efficient exploration of high-Tc superconductors by a gradient-based composition design	We propose a material design method via gradient-based optimization on compositions, overcoming the limitations of traditional methods: exhaustive database searches and conditional generation models. It optimizes inputs via backpropagation, aligning the model's output closely with the target property and facilitating t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	439,705
2406.16416	Multilingual Knowledge Editing with Language-Agnostic Factual Neurons	Multilingual knowledge editing (MKE) aims to simultaneously update factual knowledge across multiple languages within large language models (LLMs). Previous research indicates that the same knowledge across different languages within LLMs exhibits a degree of shareability. However, most existing MKE methods overlook th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	467,121
1803.04842	A Learning-Based Visual Saliency Prediction Model for Stereoscopic 3D Video (LBVS-3D)	Over the past decade, many computational saliency prediction models have been proposed for 2D images and videos. Considering that the human visual system has evolved in a natural 3D environment, it is only natural to want to design visual attention models for 3D content. Existing monocular saliency models are not able ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,529
2404.01049	A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification	This paper introduces a novel sector-based methodology for star-galaxy classification, leveraging the latest Sloan Digital Sky Survey data (SDSS-DR18). By strategically segmenting the sky into sectors aligned with SDSS observational patterns and employing a dedicated convolutional neural network (CNN), we achieve state...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	443,226
2312.09434	Task Tree Retrieval For Robotic Cooking	This paper is based on developing different algorithms, which generate the task tree planning for the given goal node(recipe). The knowledge representation of the dishes is called FOON. It contains the different objects and their between them with respective to the motion node The graphical representation of FOON is ma...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	415,718
2306.07850	Exact Mean Square Linear Stability Analysis for SGD	The dynamical stability of optimization methods at the vicinity of minima of the loss has recently attracted significant attention. For gradient descent (GD), stable convergence is possible only to minima that are sufficiently flat w.r.t. the step size, and those have been linked with favorable properties of the traine...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	373,166
2211.02592	A Large-Scale Study of a Sleep Tracking and Improving Device with Closed-loop and Personalized Real-time Acoustic Stimulation	Various intervention therapies ranging from pharmaceutical to hi-tech tailored solutions have been available to treat difficulty in falling asleep commonly caused by insomnia in modern life. However, current techniques largely remain ill-suited, ineffective, and unreliable due to their lack of precise real-time sleep t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	328,624
2102.03739	Infinite-channel deep stable convolutional neural networks	The interplay between infinite-width neural networks (NNs) and classes of Gaussian processes (GPs) is well known since the seminal work of Neal (1996). While numerous theoretical refinements have been proposed in the recent years, the interplay between NNs and GPs relies on two critical distributional assumptions on th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	218,850
1511.03703	Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures	Quantifying simulation uncertainties is a critical component of rigorous predictive simulation. A key component of this is forward propagation of uncertainties in simulation input data to output quantities of interest. Typical approaches involve repeated sampling of the simulation over the uncertain input data, and can...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	48,786
2402.13250	Video ReCap: Recursive Captioning of Hour-Long Videos	Most video captioning models are designed to process short video clips of few seconds and output text describing low-level visual concepts (e.g., objects, scenes, atomic actions). However, most real-world videos last for minutes or hours and have a complex hierarchical structure spanning different temporal granularitie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	431,172
2105.11088	Towards Book Cover Design via Layout Graphs	Book covers are intentionally designed and provide an introduction to a book. However, they typically require professional skills to design and produce the cover images. Thus, we propose a generative neural network that can produce book covers based on an easy-to-use layout graph. The layout graph contains objects such...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	236,591
2201.05026	Fantastic Data and How to Query Them	It is commonly acknowledged that the availability of the huge amount of (training) data is one of the most important factors for many recent advances in Artificial Intelligence (AI). However, datasets are often designed for specific tasks in narrow AI sub areas and there is no unified way to manage and access them. Thi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	true	false	275,261
2407.19660	A Causally Informed Pretraining Approach for Multimodal Foundation Models: Applications in Remote Sensing	Self-supervised learning has emerged as a powerful paradigm for pretraining foundation models using large-scale data. Existing pretraining approaches predominantly rely on masked reconstruction or next-token prediction strategies, demonstrating strong performance across various downstream tasks, including geoscience ap...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	476,870
1204.2035	Wireless Information Transfer with Opportunistic Energy Harvesting	Energy harvesting is a promising solution to prolong the operation of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the n...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	15,376
1201.1192	Formalization of semantic network of image constructions in electronic content	A formal theory based on a binary operator of directional associative relation is constructed in the article and an understanding of an associative normal form of image constructions is introduced. A model of a commutative semigroup, which provides a presentation of a sentence as three components of an interrogative li...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	13,698
2006.04451	Novel Adaptive Binary Search Strategy-First Hybrid Pyramid- and Clustering-Based CNN Filter Pruning Method without Parameters Setting	Pruning redundant filters in CNN models has received growing attention. In this paper, we propose an adaptive binary search-first hybrid pyramid- and clustering-based (ABSHPC-based) method for pruning filters automatically. In our method, for each convolutional layer, initially a hybrid pyramid data structure is constr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	180,697
2405.02538	AdaFPP: Adapt-Focused Bi-Propagating Prototype Learning for Panoramic Activity Recognition	Panoramic Activity Recognition (PAR) aims to identify multi-granularity behaviors performed by multiple persons in panoramic scenes, including individual activities, group activities, and global activities. Previous methods 1) heavily rely on manually annotated detection boxes in training and inference, hindering furth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	451,800
2102.07158	Distributed Second Order Methods with Fast Rates and Compressed Communication	We develop several new communication-efficient second-order methods for distributed optimization. Our first method, NEWTON-STAR, is a variant of Newton's method from which it inherits its fast local quadratic rate. However, unlike Newton's method, NEWTON-STAR enjoys the same per iteration communication cost as gradient...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	220,013
2403.13632	Extremality of stabilizer states	We investigate the extremality of stabilizer states to reveal their exceptional role in the space of all $n$-qubit/qudit states. We establish uncertainty principles for the characteristic function and the Wigner function of states, respectively. We find that only stabilizer states achieve saturation in these principles...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	439,707
2406.04129	LenslessFace: An End-to-End Optimized Lensless System for Privacy-Preserving Face Verification	Lensless cameras, innovatively replacing traditional lenses for ultra-thin, flat optics, encode light directly onto sensors, producing images that are not immediately recognizable. This compact, lightweight, and cost-effective imaging solution offers inherent privacy advantages, making it attractive for privacy-sensiti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	461,531
2306.03761	Generalised Impedance Model of Wireless Links Assisted by Reconfigurable Intelligent Surfaces	We devise an end-to-end communication channel model that describes the performance of RIS-assisted MIMO wireless links. The model borrows the impedance (interaction) matrix formalism from the Method of Moments and provides a physics-based communication model. In configurations where the transmit and receive antenna arr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	371,467
2402.01796	Speech foundation models in healthcare: Effect of layer selection on pathological speech feature prediction	Accurately extracting clinical information from speech is critical to the diagnosis and treatment of many neurological conditions. As such, there is interest in leveraging AI for automatic, objective assessments of clinical speech to facilitate diagnosis and treatment of speech disorders. We explore transfer learning u...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	426,228
2206.11970	Learning quantum symmetries with interactive quantum-classical variational algorithms	A symmetry of a state $\vert \psi \rangle$ is a unitary operator of which $\vert \psi \rangle$ is an eigenvector. When $\vert \psi \rangle$ is an unknown state supplied by a black-box oracle, the state's symmetries provide key physical insight into the quantum system; symmetries also boost many crucial quantum learning...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	304,431
1904.01987	Hybrid Cosine Based Convolutional Neural Networks	Convolutional neural networks (CNNs) have demonstrated their capability to solve different kind of problems in a very huge number of applications. However, CNNs are limited for their computational and storage requirements. These limitations make difficult to implement these kind of neural networks on embedded devices s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,298
1801.01552	Asymptotic bounds for spherical codes	The set of all error-correcting codes C over a fixed finite alphabet F of cardinality q determines the set of code points in the unit square with coordinates (R(C), delta (C)):= (relative transmission rate, relative minimal distance). The central problem of the theory of such codes consists in maximizing simultaneously...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,745
2403.18870	SugarcaneNet: An Optimized Ensemble of LASSO-Regularized Pre-trained Models for Accurate Disease Classification	Sugarcane, a key crop for the world's sugar industry, is prone to several diseases that have a substantial negative influence on both its yield and quality. To effectively manage and implement preventative initiatives, diseases must be detected promptly and accurately. In this study, we present a unique model called su...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	442,113
2006.08131	An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks	With the widespread use of deep neural networks (DNNs) in high-stake applications, the security problem of the DNN models has received extensive attention. In this paper, we investigate a specific security problem called trojan attack, which aims to attack deployed DNN systems relying on the hidden trigger patterns ins...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	182,075
2206.05618	Synthetic PET via Domain Translation of 3D MRI	Historically, patient datasets have been used to develop and validate various reconstruction algorithms for PET/MRI and PET/CT. To enable such algorithm development, without the need for acquiring hundreds of patient exams, in this paper we demonstrate a deep learning technique to generate synthetic but realistic whole...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	302,069
2404.02912	Probabilistic Generating Circuits -- Demystified	Zhang et al. (ICML 2021, PLMR 139, pp. 12447-1245) introduced probabilistic generating circuits (PGCs) as a probabilistic model to unify probabilistic circuits (PCs) and determinantal point processes (DPPs). At a first glance, PGCs store a distribution in a very different way, they compute the probability generating po...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	444,049
2006.07064	Indexing Data on the Web: A Comparison of Schema-level Indices for Data Search -- Extended Technical Report	Indexing the Web of Data offers many opportunities, in particular, to find and explore data sources. One major design decision when indexing the Web of Data is to find a suitable index model, i.e., how to index and summarize data. Various efforts have been conducted to develop specific index models for a given task. Wi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	181,676
1809.03216	Multimodal feedback for active robot-object interaction	In this work, we present a multimodal system for active robot-object interaction using laser-based SLAM, RGBD images, and contact sensors. In the object manipulation task, the robot adjusts its initial pose with respect to obstacles and target objects through RGBD data so it can perform object grasping in different con...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	107,271
2405.04760	Large Language Models for Cyber Security: A Systematic Literature Review	The rapid advancement of Large Language Models (LLMs) has opened up new opportunities for leveraging artificial intelligence in various domains, including cybersecurity. As the volume and sophistication of cyber threats continue to grow, there is an increasing need for intelligent systems that can automatically detect ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	452,669
1511.03260	A Hierarchical Spectral Method for Extreme Classification	Extreme classification problems are multiclass and multilabel classification problems where the number of outputs is so large that straightforward strategies are neither statistically nor computationally viable. One strategy for dealing with the computational burden is via a tree decomposition of the output space. Whil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	48,737
1410.3596	Detection of cheating by decimation algorithm	We expand the item response theory to study the case of "cheating students" for a set of exams, trying to detect them by applying a greedy algorithm of inference. This extended model is closely related to the Boltzmann machine learning. In this paper we aim to infer the correct biases and interactions of our model by c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	36,719
2208.10536	A Meta-Analysis of Solar Forecasting Based on Skill Score	We conduct the first comprehensive meta-analysis of deterministic solar forecasting based on skill score, screening 1,447 papers from Google Scholar and reviewing the full texts of 320 papers for data extraction. A database of 4,687 points was built and analyzed with multivariate adaptive regression spline modelling, p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	314,096
1912.11430	TF3P: Three-dimensional Force Fields Fingerprint Learned by Deep Capsular Network	Molecular fingerprints are the workhorse in ligand-based drug discovery. In recent years, an increasing number of research papers reported fascinating results on using deep neural networks to learn 2D molecular representations as fingerprints. It is anticipated that the integration of deep learning would also contribut...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	158,566
2310.20363	CAFE: Conflict-Aware Feature-wise Explanations	Feature attribution methods are widely used to explain neural models by determining the influence of individual input features on the models' outputs. We propose a novel feature attribution method, CAFE (Conflict-Aware Feature-wise Explanations), that addresses three limitations of the existing methods: their disregard...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,364
0712.4099	Digital Ecosystems: Optimisation by a Distributed Intelligence	Can intelligence optimise Digital Ecosystems? How could a distributed intelligence interact with the ecosystem dynamics? Can the software components that are part of genetic selection be intelligent in themselves, as in an adaptive technology? We consider the effect of a distributed intelligence mechanism on the evolut...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	1,082
2312.07624	A dynamical clipping approach with task feedback for Proximal Policy Optimization	Proximal Policy Optimization (PPO) has been broadly applied to robotics learning, showcasing stable training performance. However, the fixed clipping bound setting may limit the performance of PPO. Specifically, there is no theoretical proof that the optimal clipping bound remains consistent throughout the entire train...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	415,000
2501.03475	Reading with Intent -- Neutralizing Intent	Queries to large language models (LLMs) can be divided into two parts: the instruction/question and the accompanying context. The context for retrieval-augmented generation (RAG) systems in most benchmarks comes from Wikipedia or Wikipedia-like texts which are written in a neutral and factual tone. However, when RAG sy...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	522,886
1903.10180	git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories	Data from software repositories have become an important foundation for the empirical study of software engineering processes. A recurring theme in the repository mining literature is the inference of developer networks capturing e.g. collaboration, coordination, or communication from the commit history of projects. Mo...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	true	125,223
2403.20222	Shallow Cross-Encoders for Low-Latency Retrieval	Transformer-based Cross-Encoders achieve state-of-the-art effectiveness in text retrieval. However, Cross-Encoders based on large transformer models (such as BERT or T5) are computationally expensive and allow for scoring only a small number of documents within a reasonably small latency window. However, keeping search...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	442,667
1910.02653	Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization	We formalize the problem of trading-off DNN training time and memory requirements as the tensor rematerialization optimization problem, a generalization of prior checkpointing strategies. We introduce Checkmate, a system that solves for optimal rematerialization schedules in reasonable times (under an hour) using off-t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	148,306
2408.14101	Estimating Causal Effects from Learned Causal Networks	The standard approach to answering an identifiable causal-effect query (e.g., $P(Y\|do(X)$) when given a causal diagram and observational data is to first generate an estimand, or probabilistic expression over the observable variables, which is then evaluated using the observational data. In this paper, we propose an al...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	483,419
2211.08168	Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems	Event detection in power systems aims to identify triggers and event types, which helps relevant personnel respond to emergencies promptly and facilitates the optimization of power supply strategies. However, the limited length of short electrical record texts causes severe information sparsity, and numerous domain-spe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	330,502
1904.04154	Bayesian Neural Networks at Finite Temperature	We recapitulate the Bayesian formulation of neural network based classifiers and show that, while sampling from the posterior does indeed lead to better generalisation than is obtained by standard optimisation of the cost function, even better performance can in general be achieved by sampling finite temperature ($T$) ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,951
2202.12230	Sample Efficiency of Data Augmentation Consistency Regularization	Data augmentation is popular in the training of large neural networks; currently, however, there is no clear theoretical comparison between different algorithmic choices on how to use augmented data. In this paper, we take a step in this direction - we first present a simple and novel analysis for linear regression wit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	282,154
2309.16702	Prediction and Interpretation of Vehicle Trajectories in the Graph Spectral Domain	This work provides a comprehensive analysis and interpretation of the graph spectral representation of traffic scenarios. Based on a spatio-temporal vehicle interaction graph, an observed traffic scenario can be transformed into the graph spectral domain by means of the multidimensional Graph Fourier Transformation. Si...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	395,462
2408.02883	"Sharing, Not Showing Off": How BeReal Approaches Authentic Self-Presentation on Social Media Through Its Design	Adolescents are particularly vulnerable to the pressures created by social media, such as heightened self-consciousness and the need for extensive self-presentation. In this study, we investigate how BeReal, a social media platform designed to counter some of these pressures, influences adolescents' self-presentation b...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	478,803
2201.05890	Robust uncertainty estimates with out-of-distribution pseudo-inputs training	Probabilistic models often use neural networks to control their predictive uncertainty. However, when making out-of-distribution (OOD)} predictions, the often-uncontrollable extrapolation properties of neural networks yield poor uncertainty predictions. Such models then don't know what they don't know, which directly l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	275,536
1205.6376	Analysis and study on text representation to improve the accuracy of the Normalized Compression Distance	The huge amount of information stored in text form makes methods that deal with texts really interesting. This thesis focuses on dealing with texts using compression distances. More specifically, the thesis takes a small step towards understanding both the nature of texts and the nature of compression distances. Broadl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,220
2109.07556	Unit Selection with Causal Diagram	The unit selection problem aims to identify a set of individuals who are most likely to exhibit a desired mode of behavior, for example, selecting individuals who would respond one way if encouraged and a different way if not encouraged. Using a combination of experimental and observational data, Li and Pearl derived t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	255,560
2406.11316	Improved Algorithms for Contextual Dynamic Pricing	In contextual dynamic pricing, a seller sequentially prices goods based on contextual information. Buyers will purchase products only if the prices are below their valuations. The goal of the seller is to design a pricing strategy that collects as much revenue as possible. We focus on two different valuation models. Th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	464,838
2208.14775	Modified Froelich's Equation for Modelling of a Three Phase Self-Excited Synchronous Generator	With advancement in design and analysis of electro-mechanical and electromagnetic devices, the modelling of magnetic saturation of a synchronous generator has emerged to be a subject of interest in number of publications. Most of the existing electrical machine modelling methods does ignore the saturation effect for si...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	315,414
1307.3419	Pleasantly Consuming Linked Data with RDF Data Descriptions	Although the intention of RDF is to provide an open, minimally constraining way for representing information, there exists an increasing number of applications for which guarantees on the structure and values of an RDF data set become desirable if not essential. What is missing in this respect are mechanisms to tie RDF...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	25,801
2501.06122	NDOB-Based Control of a UAV with Delta-Arm Considering Manipulator Dynamics	Aerial Manipulators (AMs) provide a versatile platform for various applications, including 3D printing, architecture, and aerial grasping missions. However, their operational speed is often sacrificed to uphold precision. Existing control strategies for AMs often regard the manipulator as a disturbance and employ robus...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	523,846
1901.05112	An Exponential Lower Bound on the Sub-Packetization of MSR Codes	An $(n,k,\ell)$-vector MDS code is a $\mathbb{F}$-linear subspace of $(\mathbb{F}^\ell)^n$ (for some field $\mathbb{F}$) of dimension $k\ell$, such that any $k$ (vector) symbols of the codeword suffice to determine the remaining $r=n-k$ (vector) symbols. The length $\ell$ of each codeword symbol is called the sub-packe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	118,728
2301.09544	Learning to View: Decision Transformers for Active Object Detection	Active perception describes a broad class of techniques that couple planning and perception systems to move the robot in a way to give the robot more information about the environment. In most robotic systems, perception is typically independent of motion planning. For example, traditional object detection is passive: ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	341,530
2211.01877	Convex Clustering through MM: An Efficient Algorithm to Perform Hierarchical Clustering	Convex clustering is a modern method with both hierarchical and $k$-means clustering characteristics. Although convex clustering can capture complex clustering structures hidden in data, the existing convex clustering algorithms are not scalable to large data sets with sample sizes greater than several thousands. Moreo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	328,396
2108.00045	Multi-Head Self-Attention via Vision Transformer for Zero-Shot Learning	Zero-Shot Learning (ZSL) aims to recognise unseen object classes, which are not observed during the training phase. The existing body of works on ZSL mostly relies on pretrained visual features and lacks the explicit attribute localisation mechanism on images. In this work, we propose an attention-based model in the pr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	248,577
1806.08015	Stability of Scattering Decoder For Nonlinear Diffractive Imaging	The problem of image reconstruction under multiple light scattering is usually formulated as a regularized non-convex optimization. A deep learning architecture, Scattering Decoder (ScaDec), was recently proposed to solve this problem in a purely data-driven fashion. The proposed method was shown to substantially outpe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	101,069
1711.01991	Mitigating Adversarial Effects Through Randomization	Convolutional neural networks have demonstrated high accuracy on various tasks in recent years. However, they are extremely vulnerable to adversarial examples. For example, imperceptible perturbations added to clean images can cause convolutional neural networks to fail. In this paper, we propose to utilize randomizati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	83,984
2410.10681	A System Parameterization for Direct Data-Driven Estimator Synthesis	This paper introduces a novel parameterization to characterize unknown linear time-invariant systems using noisy data. The presented parameterization describes exactly the set of all systems consistent with the available data. We then derive verifiable conditions, when the consistency constraint reduces the set to the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	498,185
2009.14261	Abusive Language Detection and Characterization of Twitter Behavior	In this work, abusive language detection in online content is performed using Bidirectional Recurrent Neural Network (BiRNN) method. Here the main objective is to focus on various forms of abusive behaviors on Twitter and to detect whether a speech is abusive or not. The results are compared for various abusive behavio...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	197,977
1411.6757	Echo State Condition at the Critical Point	Recurrent networks with transfer functions that fulfill the Lipschitz continuity with K=1 may be echo state networks if certain limitations on the recurrent connectivity are applied. It has been shown that it is sufficient if the largest singular value of the recurrent connectivity is smaller than 1. The main achieveme...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	37,869
2412.17263	VarAD: Lightweight High-Resolution Image Anomaly Detection via Visual Autoregressive Modeling	This paper addresses a practical task: High-Resolution Image Anomaly Detection (HRIAD). In comparison to conventional image anomaly detection for low-resolution images, HRIAD imposes a heavier computational burden and necessitates superior global information capture capacity. To tackle HRIAD, this paper translates imag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	519,897
2205.11121	A normal approximation for joint frequency estimatation under Local Differential Privacy	In the recent years, Local Differential Privacy (LDP) has been one of the corner stone of privacy preserving data analysis. However, many challenges still opposes its widespread application. One of these problems is the scalability of LDP to high dimensional data, in particular for estimating joint-distributions. In th...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	298,009
0908.3544	On the Second Order Statistics of the Multihop Rayleigh Fading Channel	Second order statistics provides a dynamic representation of a fading channel and plays an important role in the evaluation and design of the wireless communication systems. In this paper, we present a novel analytical framework for the evaluation of important second order statistical parameters, as the level crossing ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,329
2004.09677	Approximate exploitability: Learning a best response in large games	Researchers have demonstrated that neural networks are vulnerable to adversarial examples and subtle environment changes, both of which one can view as a form of distribution shift. To humans, the resulting errors can look like blunders, eroding trust in these agents. In prior games research, agent evaluation often foc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,412
2012.15397	FREA-Unet: Frequency-aware U-net for Modality Transfer	While Positron emission tomography (PET) imaging has been widely used in diagnosis of number of diseases, it has costly acquisition process which involves radiation exposure to patients. However, magnetic resonance imaging (MRI) is a safer imaging modality that does not involve patient's exposure to radiation. Therefor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	213,766
0905.1386	Selective-Fading Multiple-Access MIMO Channels: Diversity-Multiplexing Tradeoff and Dominant Outage Event Regions	We establish the optimal diversity-multiplexing (DM) tradeoff for coherent selective-fading multiple-access MIMO channels and provide corresponding code design criteria. As a byproduct, on the conceptual level, we find an interesting relation between the DM tradeoff framework and the notion of dominant error event regi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,657
2008.07475	Absorption in Time-Varying Markov Chains: Graph-Based Conditions	We investigate absorption, i.e., almost sure convergence to an absorbing state, in time-varying (non-homogeneous) discrete-time Markov chains with finite state space. We consider systems that can switch among a finite set of transition matrices, which we call the modes. Our analysis is focused on two properties: 1) alm...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	192,122
2407.17869	EllipBench: A Large-scale Benchmark for Machine-learning based Ellipsometry Modeling	Ellipsometry is used to indirectly measure the optical properties and thickness of thin films. However, solving the inverse problem of ellipsometry is time-consuming since it involves human expertise to apply the data fitting techniques. Many studies use traditional machine learning-based methods to model the complex m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	476,154
2203.10472	Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs	As wireless standards evolve, more complex functionalities are introduced to address the increasing requirements in terms of throughput, latency, security, and efficiency. To unleash the potential of such new features, artificial intelligence (AI) and machine learning (ML) are currently being exploited for deriving mod...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	286,552
1809.02850	Rate-Adaptive Neural Networks for Spatial Multiplexers	In resource-constrained environments, one can employ spatial multiplexing cameras to acquire a small number of measurements of a scene, and perform effective reconstruction or high-level inference using purely data-driven neural networks. However, once trained, the measurement matrix and the network are valid only for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	107,154
2209.02518	Sequential Cross Attention Based Multi-task Learning	In multi-task learning (MTL) for visual scene understanding, it is crucial to transfer useful information between multiple tasks with minimal interferences. In this paper, we propose a novel architecture that effectively transfers informative features by applying the attention mechanism to the multi-scale features of t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	316,235
2312.05803	Transformer-based Selective Super-Resolution for Efficient Image Refinement	Conventional super-resolution methods suffer from two drawbacks: substantial computational cost in upscaling an entire large image, and the introduction of extraneous or potentially detrimental information for downstream computer vision tasks during the refinement of the background. To solve these issues, we propose a ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	414,248
1102.0033	Control of Multi-Agent Formations with Only Shape Constraints	This paper considers a novel problem of how to choose an appropriate geometry for a group of agents with only shape constraints but with a flexible scale. Instead of assigning the formation system with a specific geometry, here the only requirement on the desired geometry is a shape without any location, rotation and, ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	8,981
1801.02254	Theory of Deep Learning IIb: Optimization Properties of SGD	In Theory IIb we characterize with a mix of theory and experiments the optimization of deep convolutional networks by Stochastic Gradient Descent. The main new result in this paper is theoretical and experimental evidence for the following conjecture about SGD: SGD concentrates in probability -- like the classical Lang...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	87,893
2403.17236	Neural Image Compression with Quantization Rectifier	Neural image compression has been shown to outperform traditional image codecs in terms of rate-distortion performance. However, quantization introduces errors in the compression process, which can degrade the quality of the compressed image. Existing approaches address the train-test mismatch problem incurred during q...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	441,371
2012.06346	Distant Domain Transfer Learning for Medical Imaging	Medical image processing is one of the most important topics in the field of the Internet of Medical Things (IoMT). Recently, deep learning methods have carried out state-of-the-art performances on medical image tasks. However, conventional deep learning have two main drawbacks: 1) insufficient training data and 2) the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	211,087
2402.10010	Enhancing signal detectability in learning-based CT reconstruction with a model observer inspired loss function	Deep neural networks used for reconstructing sparse-view CT data are typically trained by minimizing a pixel-wise mean-squared error or similar loss function over a set of training images. However, networks trained with such pixel-wise losses are prone to wipe out small, low-contrast features that are critical for scre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	429,767

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