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
1209.2794	Protecting oracle pl/sql source code from a dba user	In this paper we are presenting a new way to disable DDL statements on some specific PL/SQL procedures to a dba user in the Oracle database. Nowadays dba users have access to a lot of data and source code even if they do not have legal permissions to see or modify them. With this method we can disable the ability to ex...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	18,537
1901.10088	Subspace Stabilization Analysis for Non-Markovian Open Quantum Systems	Studied in this article is non-Markovian open quantum systems parametrized by Hamiltonian H, coupling operator L, and memory kernel function {\gamma}, which is a proper candidate for describing the dynamics of various solid-state quantum information processing devices. We look into the subspace stabilization problem of...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	119,924
1611.08512	Person Re-Identification by Unsupervised Video Matching	Most existing person re-identification (ReID) methods rely only on the spatial appearance information from either one or multiple person images, whilst ignore the space-time cues readily available in video or image-sequence data. Moreover, they often assume the availability of exhaustively labelled cross-view pairwise ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	64,514
2406.16935	Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex	We characterized the generalization capabilities of DNN-based encoding models when predicting neuronal responses from the visual cortex. We collected \textit{MacaqueITBench}, a large-scale dataset of neural population responses from the macaque inferior temporal (IT) cortex to over $300,000$ images, comprising $8,233$ ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	467,351
1512.08301	Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency	In this paper, we propose a novel neural network structure, namely \emph{feedforward sequential memory networks (FSMN)}, to model long-term dependency in time series without using recurrent feedback. The proposed FSMN is a standard fully-connected feedforward neural network equipped with some learnable memory blocks in...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	50,505
0812.2458	Square Complex Orthogonal Designs with no Zero Entry for any $2^m$ Antennas	Space-time block codes from square complex orthogonal designs (SCOD) have been extensively studied and most of the existing SCODs contain large number of zeros. The zeros in the designs result in high peak-to-average power ratio and also impose a severe constraint on hardware implementation of the code while turning of...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,791
1504.02957	Intelligent Implementation Processor Design for Oracle Distributed Databases System	Despite the increasing need for modeling and implementing Distributed Databases (DDB), distributed database management systems are still quite far from helping the designer to directly implement its BDD. Indeed, the fundamental principle of implementation of a DDB is to make the database appear as a centralized databas...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	41,979
2302.08997	Designing and Evaluating Interfaces that Highlight News Coverage Diversity Using Discord Questions	Modern news aggregators do the hard work of organizing a large news stream, creating collections for a given news story with tens of source options. This paper shows that navigating large source collections for a news story can be challenging without further guidance. In this work, we design three interfaces -- the Ann...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	346,260
2408.06400	MetMamba: Regional Weather Forecasting with Spatial-Temporal Mamba Model	Deep Learning based Weather Prediction (DLWP) models have been improving rapidly over the last few years, surpassing state of the art numerical weather forecasts by significant margins. While much of the optimization effort is focused on training curriculum to extend forecast range in the global context, two aspects re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	480,198
1703.00835	Autonomous Skill-centric Testing using Deep Learning	Software testing is an important tool to ensure software quality. This is a hard task in robotics due to dynamic environments and the expensive development and time-consuming execution of test cases. Most testing approaches use model-based and / or simulation-based testing to overcome these problems. We propose model-f...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	69,236
2210.02964	Designing a Robust Low-Level Agnostic Controller for a Quadrotor with Actor-Critic Reinforcement Learning	Purpose: Real-life applications using quadrotors introduce a number of disturbances and time-varying properties that pose a challenge to flight controllers. We observed that, when a quadrotor is tasked with picking up and dropping a payload, traditional PID and RL-based controllers found in literature struggle to maint...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	321,842
2410.24162	Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-trained and Finetuned Attention-Driven Neural Operators	This paper proposes a new data-driven methodology for predicting intervals of post-fault voltage trajectories in power systems. We begin by introducing the Quantile Attention-Fourier Deep Operator Network (QAF-DeepONet), designed to capture the complex dynamics of voltage trajectories and reliably estimate quantiles of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,354
2301.13446	Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments	We study variance-dependent regret bounds for Markov decision processes (MDPs). Algorithms with variance-dependent regret guarantees can automatically exploit environments with low variance (e.g., enjoying constant regret on deterministic MDPs). The existing algorithms are either variance-independent or suboptimal. We ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,922
1603.08273	Collective Influence Algorithm to find influencers via optimal percolation in massively large social media	We elaborate on a linear time implementation of the Collective Influence (CI) algorithm introduced by Morone, Makse, Nature 524, 65 (2015) to find the minimal set of influencers in a network via optimal percolation. We show that the computational complexity of CI is O(N log N) when removing nodes one-by-one, with N the...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	53,758
2012.09605	Sparsifying networks by traversing Geodesics	The geometry of weight spaces and functional manifolds of neural networks play an important role towards 'understanding' the intricacies of ML. In this paper, we attempt to solve certain open questions in ML, by viewing them through the lens of geometry, ultimately relating it to the discovery of points or paths of equ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	212,116
1008.4161	Percolation and Connectivity in the Intrinsically Secure Communications Graph	The ability to exchange secret information is critical to many commercial, governmental, and military networks. The intrinsically secure communications graph (iS-graph) is a random graph which describes the connections that can be securely established over a large-scale network, by exploiting the physical properties of...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	7,358
1706.00130	Teaching Machines to Describe Images via Natural Language Feedback	Robots will eventually be part of every household. It is thus critical to enable algorithms to learn from and be guided by non-expert users. In this paper, we bring a human in the loop, and enable a human teacher to give feedback to a learning agent in the form of natural language. We argue that a descriptive sentence ...	true	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	74,568
1610.00384	Covert Single-hop Communication in a Wireless Network with Distributed Artificial Noise Generation	Covert communication, also known as low probability of detection (LPD) communication, prevents the adversary from knowing that a communication is taking place. Recent work has demonstrated that, in a three-party scenario with a transmitter (Alice), intended recipient (Bob), and adversary (Warden Willie), the maximum nu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	61,831
2207.00416	Energy Efficient Routing For Underwater Acoustic Sensor Network Using Genetic Algorithm	In underwater acoustic sensor networks (UWASN), energy-reliable data transmission is a challenging task. This is due to acoustic transmission disturbances caused by excessive noise, exceptionally long propagation delays, a high bit error rate, limited bandwidth capability, and interference. One of the most important is...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	true	305,746
2211.15556	Attack on Unfair ToS Clause Detection: A Case Study using Universal Adversarial Triggers	Recent work has demonstrated that natural language processing techniques can support consumer protection by automatically detecting unfair clauses in the Terms of Service (ToS) Agreement. This work demonstrates that transformer-based ToS analysis systems are vulnerable to adversarial attacks. We conduct experiments att...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	333,317
2106.02559	Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing	Analysing whether neural language models encode linguistic information has become popular in NLP. One method of doing so, which is frequently cited to support the claim that models like BERT encode syntax, is called probing; probes are small supervised models trained to extract linguistic information from another model...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	238,920
1602.05537	Whither probabilistic security management for real-time operation of power systems ?	This paper investigates the stakes of introducing probabilistic approaches for the management of power system's security. In real-time operation, the aim is to arbitrate in a rational way between preventive and corrective control, while taking into account i) the prior probabilities of contingencies, ii) the possible f...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	52,269
2411.12758	An exploration of the effect of quantisation on energy consumption and inference time of StarCoder2	This study examines quantisation and pruning strategies to reduce energy consumption in code Large Language Models (LLMs) inference. Using StarCoder2, we observe increased energy demands with quantization due to lower throughput and some accuracy losses. Conversely, pruning reduces energy usage but impairs performance....	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	509,527
2107.07789	Wasserstein Distances, Geodesics and Barycenters of Merge Trees	This paper presents a unified computational framework for the estimation of distances, geodesics and barycenters of merge trees. We extend recent work on the edit distance [106] and introduce a new metric, called the Wasserstein distance between merge trees, which is purposely designed to enable efficient computations ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	246,531
2404.00681	CoUDA: Coherence Evaluation via Unified Data Augmentation	Coherence evaluation aims to assess the organization and structure of a discourse, which remains challenging even in the era of large language models. Due to the scarcity of annotated data, data augmentation is commonly used for training coherence evaluation models. However, previous augmentations for this task primari...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,063
1802.08380	On Abruptly-Changing and Slowly-Varying Multiarmed Bandit Problems	We study the non-stationary stochastic multiarmed bandit (MAB) problem and propose two generic algorithms, namely, the limited memory deterministic sequencing of exploration and exploitation (LM-DSEE) and the Sliding-Window Upper Confidence Bound# (SW-UCB#). We rigorously analyze these algorithms in abruptly-changing a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	91,094
1812.05869	The Coherent Point Drift for Clustered Point Sets	The problem of non-rigid point set registration is a key problem for many computer vision tasks. In many cases the nature of the data or capabilities of the point detection algorithms can give us some prior information on point sets distribution. In non-rigid case this information is able to drastically improve registr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	116,498
2409.11436	Analysis of flexible traffic control method in SDN	The aim of this paper is to analyze methods of flexible control in SDN networks and to propose a self-developed solution that will enable intelligent adaptation of SDN controller performance. This work aims not only to review existing solutions, but also to develop an approach that will increase the efficiency and adap...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	489,156
1505.02759	How Resilient Are Our Societies? Analyses, Models, and Preliminary Results	Traditional social organizations such as those for the management of healthcare and civil defence are the result of designs and realizations that matched well with an operational context considerably different from the one we are experiencing today: A simpler world, characterized by a greater amount of resources to mat...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	42,998
1606.03021	Feature-based Recursive Observer Design for Homography Estimation	This paper presents a new algorithm for online estimation of a sequence of homographies applicable to image sequences obtained from robotic vehicles equipped with vision sensors. The approach taken exploits the underlying Special Linear group structure of the set of homographies along with gyroscope measurements and di...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	57,046
2409.05122	PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation	Semi-supervised learning has emerged as a widely adopted technique in the field of medical image segmentation. The existing works either focuses on the construction of consistency constraints or the generation of pseudo labels to provide high-quality supervisory signals, whose main challenge mainly comes from how to ke...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	486,643
2406.11280	ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO	Iterative self-improvement, a concept extending beyond personal growth, has found powerful applications in machine learning, particularly in transforming weak models into strong ones. While recent advances in natural language processing have shown its efficacy through iterative preference optimization, applying this ap...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	464,818
2202.03238	Towards an Analytical Definition of Sufficient Data	We show that, for each of five datasets of increasing complexity, certain training samples are more informative of class membership than others. These samples can be identified a priori to training by analyzing their position in reduced dimensional space relative to the classes' centroids. Specifically, we demonstrate ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	279,130
2411.09168	Theory of Mind Enhances Collective Intelligence	Collective Intelligence plays a central role in a large variety of fields, from economics and evolutionary theory to neural networks and eusocial insects, and it is also core to much of the work on emergence and self-organisation in complex systems theory. However, in human collective intelligence there is still much m...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	true	508,152
1912.10589	Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction	Reconstruction of a 3D shape from a single 2D image is a classical computer vision problem, whose difficulty stems from the inherent ambiguity of recovering occluded or only partially observed surfaces. Recent methods address this challenge through the use of largely unstructured neural networks that effectively distil...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	158,357
2106.09022	A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection	Mahalanobis distance (MD) is a simple and popular post-processing method for detecting out-of-distribution (OOD) inputs in neural networks. We analyze its failure modes for near-OOD detection and propose a simple fix called relative Mahalanobis distance (RMD) which improves performance and is more robust to hyperparame...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	241,522
2305.16636	DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions	Modern machine learning relies on datasets to develop and validate research ideas. Given the growth of publicly available data, finding the right dataset to use is increasingly difficult. Any research question imposes explicit and implicit constraints on how well a given dataset will enable researchers to answer this q...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	true	368,183
2404.11256	MMCBE: Multi-modality Dataset for Crop Biomass Prediction and Beyond	Crop biomass, a critical indicator of plant growth, health, and productivity, is invaluable for crop breeding programs and agronomic research. However, the accurate and scalable quantification of crop biomass remains inaccessible due to limitations in existing measurement methods. One of the obstacles impeding the adva...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	447,437
2404.17877	PromptCL: Improving Event Representation via Prompt Template and Contrastive Learning	The representation of events in text plays a significant role in various NLP tasks. Recent research demonstrates that contrastive learning has the ability to improve event comprehension capabilities of Pre-trained Language Models (PLMs) and enhance the performance of event representation learning. However, the efficacy...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	450,040
1111.2430	Achievable Rates for a Two-Relay Network with Relays-Transmitter Feedbacks	We consider a relay network with two relays and two feedback links from the relays to the sender. To obtain the achievability results, we use the compress-and-forward and the decode-and-forward strategies to superimpose facility and cooperation analogue to what proposed by Cover and El Gamal for a relay channel. In add...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,981
2301.04634	Street-View Image Generation from a Bird's-Eye View Layout	Bird's-Eye View (BEV) Perception has received increasing attention in recent years as it provides a concise and unified spatial representation across views and benefits a diverse set of downstream driving applications. At the same time, data-driven simulation for autonomous driving has been a focal point of recent rese...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	340,125
2311.02734	ISAR: A Benchmark for Single- and Few-Shot Object Instance Segmentation and Re-Identification	Most object-level mapping systems in use today make use of an upstream learned object instance segmentation model. If we want to teach them about a new object or segmentation class, we need to build a large dataset and retrain the system. To build spatial AI systems that can quickly be taught about new objects, we need...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	405,555
2201.00204	Low-Density Spreading Design Based on an Algebraic Scheme for NOMA Systems	NOMA) technique based on an algebraic design is studied. We propose an improved low-density spreading (LDS) sequence design based on projective geometry. In terms of its bit error rate (BER) performance, our proposed improved LDS code set outperforms the existing LDS designs over the frequency nonselective Rayleigh fad...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	273,895
1911.01155	Learning based Methods for Code Runtime Complexity Prediction	Predicting the runtime complexity of a programming code is an arduous task. In fact, even for humans, it requires a subtle analysis and comprehensive knowledge of algorithms to predict time complexity with high fidelity, given any code. As per Turing's Halting problem proof, estimating code complexity is mathematically...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	152,027
2406.16956	Data-Driven Computing Methods for Nonlinear Physics Systems with Geometric Constraints	In a landscape where scientific discovery is increasingly driven by data, the integration of machine learning (ML) with traditional scientific methodologies has emerged as a transformative approach. This paper introduces a novel, data-driven framework that synergizes physics-based priors with advanced ML techniques to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	467,361
1906.07556	Determination of Metamaterial Parameters by Means of a Homogenization Approach Based on Asymptotic Analysis	Owing to additive manufacturing techniques, a structure at millimeter length scale (macroscale) can be produced by using a lattice substructure at micrometer length scale (microscale). Such a system is called a metamaterial at the macroscale as the mechanical characteristics deviate from the characteristics at the micr...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	135,627
2502.02362	Premise-Augmented Reasoning Chains Improve Error Identification in Math reasoning with LLMs	Chain-of-Thought (CoT) prompting enhances mathematical reasoning in large language models (LLMs) by enabling detailed step-by-step solutions. However, due to the verbosity of LLMs, the resulting reasoning chains can be long, making it harder to verify the reasoning steps and trace issues resulting from dependencies bet...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	530,280
1709.03943	Support Spinor Machine	We generalize a support vector machine to a support spinor machine by using the mathematical structure of wedge product over vector machine in order to extend field from vector field to spinor field. The separated hyperplane is extended to Kolmogorov space in time series data which allow us to extend a structure of sup...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	80,568
2501.00987	Search Plurality	In light of Phillips' contention regarding the impracticality of Search Neutrality, asserting that non-epistemic factors presently dictate result prioritization, our objective in this study is to confront this constraint by questioning prevailing design practices in search engines. We posit that the concept of prioriti...	true	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	521,875
1311.2850	Virtual Modules in Discrete-Event Systems: Achieving Modular Diagnosability	This paper deals with the problem of enforcing modular diagnosability for discrete-event systems that don't satisfy this property by their natural modularity. We introduce an approach to achieve this property combining existing modules into new virtual modules. An underlining mathematical problem is to find a partition...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	28,355
2109.07764	Meeting-Merging-Mission: A Multi-robot Coordinate Framework for Large-Scale Communication-Limited Exploration	This letter presents a complete framework Meeting-Merging-Mission for multi-robot exploration under communication restriction. Considering communication is limited in both bandwidth and range in the real world, we propose a lightweight environment presentation method and an efficient cooperative exploration strategy. F...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	255,646
2005.12597	Perceptual Extreme Super Resolution Network with Receptive Field Block	Perceptual Extreme Super-Resolution for single image is extremely difficult, because the texture details of different images vary greatly. To tackle this difficulty, we develop a super resolution network with receptive field block based on Enhanced SRGAN. We call our network RFB-ESRGAN. The key contributions are listed...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	178,783
2309.06922	Hydra: Multi-head Low-rank Adaptation for Parameter Efficient Fine-tuning	The recent surge in large-scale foundation models has spurred the development of efficient methods for adapting these models to various downstream tasks. Low-rank adaptation methods, such as LoRA, have gained significant attention due to their outstanding parameter efficiency and no additional inference latency. This p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,590
2308.12914	3D Pose Nowcasting: Forecast the Future to Improve the Present	Technologies to enable safe and effective collaboration and coexistence between humans and robots have gained significant importance in the last few years. A critical component useful for realizing this collaborative paradigm is the understanding of human and robot 3D poses using non-invasive systems. Therefore, in thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,717
2009.00776	Models of benthic bipedalism	Walking is a common bipedal and quadrupedal gait and is often associated with terrestrial and aquatic organisms. Inspired by recent evidence of the neural underpinnings of primitive aquatic walking in the little skate Leucoraja erinacea, we introduce a theoretical model of aquatic walking that reveals robust and effici...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	194,134
2302.10144	Stabilising and accelerating light gated recurrent units for automatic speech recognition	The light gated recurrent units (Li-GRU) is well-known for achieving impressive results in automatic speech recognition (ASR) tasks while being lighter and faster to train than a standard gated recurrent units (GRU). However, the unbounded nature of its rectified linear unit on the candidate recurrent gate induces an i...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	346,684
2408.08106	Adaptation of uncertainty-penalized Bayesian information criterion for parametric partial differential equation discovery	Data-driven discovery of partial differential equations (PDEs) has emerged as a promising approach for deriving governing physics when domain knowledge about observed data is limited. Despite recent progress, the identification of governing equations and their parametric dependencies using conventional information crit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	480,861
2407.19895	Culsans: An Efficient Snoop-based Coherency Unit for the CVA6 Open Source RISC-V application processor	Symmetric Multi-Processing (SMP) based on cache coherency is crucial for high-end embedded systems like automotive applications. RISC-V is gaining traction, and open-source hardware (OSH) platforms offer solutions to issues such as IP costs and vendor dependency. Existing multi-core cache-coherent RISC-V platforms are ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	476,975
2106.04130	EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation	3D complete renal structures(CRS) segmentation targets on segmenting the kidneys, tumors, renal arteries and veins in one inference. Once successful, it will provide preoperative plans and intraoperative guidance for laparoscopic partial nephrectomy(LPN), playing a key role in the renal cancer treatment. However, no su...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	239,596
2407.00742	PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility Graph	Polygon representation learning is essential for diverse applications, encompassing tasks such as shape coding, building pattern classification, and geographic question answering. While recent years have seen considerable advancements in this field, much of the focus has been on single polygons, overlooking the intrica...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	468,992
1605.05369	Audio Features Affected by Music Expressiveness	Within a Music Information Retrieval perspective, the goal of the study presented here is to investigate the impact on sound features of the musician's affective intention, namely when trying to intentionally convey emotional contents via expressiveness. A preliminary experiment has been performed involving $10$ tuba p...	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	55,994
2405.05478	Using Machine Translation to Augment Multilingual Classification	An all-too-present bottleneck for text classification model development is the need to annotate training data and this need is multiplied for multilingual classifiers. Fortunately, contemporary machine translation models are both easily accessible and have dependable translation quality, making it possible to translate...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	452,930
2005.09643	An Innovative Approach to Determine Rebar Depth and Size by Comparing GPR Data with a Theoretical Database	Ground penetrating radar (GPR) is an efficient technique used for rapidly recognizing embedded rebar in concrete structures. However, due to the difficulty in extracting signals from GPR data and the intrinsic coupling between the rebar depth and size showing in the data, simultaneously determining rebar depth and size...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	177,974
2005.00948	Optimal Detection Interval for Absorbing Receivers in Molecular Communication Systems with Interference	We consider a molecular communication system comprised of a transmitter, an absorbing receiver, and an interference source. Assuming amplitude modulation, we analyze the dependence of the bit error rate (BER) on the detection interval, which is the time within one transmission symbol interval during which the receiver ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	175,439
2007.10916	On the Convergence of Reinforcement Learning with Monte Carlo Exploring Starts	A basic simulation-based reinforcement learning algorithm is the Monte Carlo Exploring States (MCES) method, also known as optimistic policy iteration, in which the value function is approximated by simulated returns and a greedy policy is selected at each iteration. The convergence of this algorithm in the general set...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	188,415
1908.01204	Private Sequential Function Computation	Consider a system, including a user, $N$ servers, and $K$ basic functions which are known at all of the servers. Using the combination of those basic functions, it is possible to construct a wide class of functions. The user wishes to compute a particular combination of the basic functions, by offloading the computatio...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	140,699
2210.14346	New wrapper method based on normalized mutual information for dimension reduction and classification of hyperspectral images	Feature selection is one of the most important problems in hyperspectral images classification. It consists to choose the most informative bands from the entire set of input datasets and discard the noisy, redundant and irrelevant ones. In this context, we propose a new wrapper method based on normalized mutual informa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	326,503
2201.00162	MLOps -- Definitions, Tools and Challenges	This paper is an overview of the Machine Learning Operations (MLOps) area. Our aim is to define the operation and the components of such systems by highlighting the current problems and trends. In this context, we present the different tools and their usefulness in order to provide the corresponding guidelines. Moreove...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	273,883
1907.10453	Detecting Stable Communities in Link Streams at Multiple Temporal Scales	Link streams model interactions over time in a wide range of fields. Under this model, the challenge is to mine efficiently both temporal and topological structures. Community detection and change point detection are one of the most powerful tools to analyze such evolving interactions. In this paper, we build on both t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	139,628
2312.14657	Deep Non-Parametric Time Series Forecaster	This paper presents non-parametric baseline models for time series forecasting. Unlike classical forecasting models, the proposed approach does not assume any parametric form for the predictive distribution and instead generates predictions by sampling from the empirical distribution according to a tunable strategy. By...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	417,714
2312.05733	DevBots can co-design APIs	DevBots are automated tools that perform various tasks in order to support software development. They are a growing trend and have been used in repositories to automate repetitive tasks, as code generators, and as collaborators in eliciting requirements and defining architectures. In this study, we analyzed 24 articles...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	414,206
2210.11884	Sum Capacity Maximization in Multi-Hop Mobile Networks with Flying Base Stations	Deployment of multi-hop network of unmanned aerial vehicles (UAVs) acting as flying base stations (FlyBSs) presents a remarkable potential to effectively enhance the performance of wireless networks. Such potential enhancement, however, relies on an efficient positioning of the FlyBSs as well as a management of resourc...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	325,492
2204.08472	Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Transport	Recent advances in deep learning, such as powerful generative models and joint text-image embeddings, have provided the computational creativity community with new tools, opening new perspectives for artistic pursuits. Text-to-image synthesis approaches that operate by generating images from text cues provide a case in...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	292,098
2204.13097	Learning to Borrow -- Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion	Prior work on integrating text corpora with knowledge graphs (KGs) to improve Knowledge Graph Embedding (KGE) have obtained good performance for entities that co-occur in sentences in text corpora. Such sentences (textual mentions of entity-pairs) are represented as Lexicalised Dependency Paths (LDPs) between two entit...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	293,704
1905.00572	Argument Identification in Public Comments from eRulemaking	Administrative agencies in the United States receive millions of comments each year concerning proposed agency actions during the eRulemaking process. These comments represent a diversity of arguments in support and opposition of the proposals. While agencies are required to identify and respond to substantive comments...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	129,511
1001.2767	Universally Optimal Privacy Mechanisms for Minimax Agents	A scheme that publishes aggregate information about sensitive data must resolve the trade-off between utility to information consumers and privacy of the database participants. Differential privacy is a well-established definition of privacy--this is a universal guarantee against all attackers, whatever their side-info...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	true	5,415
2203.07596	Task-Agnostic Robust Representation Learning	It has been reported that deep learning models are extremely vulnerable to small but intentionally chosen perturbations of its input. In particular, a deep network, despite its near-optimal accuracy on the clean images, often mis-classifies an image with a worst-case but humanly imperceptible perturbation (so-called ad...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	285,484
1507.03196	DeepFont: Identify Your Font from An Image	As font is one of the core design concepts, automatic font identification and similar font suggestion from an image or photo has been on the wish list of many designers. We study the Visual Font Recognition (VFR) problem, and advance the state-of-the-art remarkably by developing the DeepFont system. First of all, we bu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,060
1604.01537	Generating Chinese Classical Poems with RNN Encoder-Decoder	We take the generation of Chinese classical poem lines as a sequence-to-sequence learning problem, and build a novel system based on the RNN Encoder-Decoder structure to generate quatrains (Jueju in Chinese), with a topic word as input. Our system can jointly learn semantic meaning within a single line, semantic releva...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	54,211
2408.12599	Controllable Text Generation for Large Language Models: A Survey	In Natural Language Processing (NLP), Large Language Models (LLMs) have demonstrated high text generation quality. However, in real-world applications, LLMs must meet increasingly complex requirements. Beyond avoiding misleading or inappropriate content, LLMs are also expected to cater to specific user needs, such as i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	482,798
2411.15514	CellPilot: A unified approach to automatic and interactive segmentation in histopathology	Histopathology, the microscopic study of diseased tissue, is increasingly digitized, enabling improved visualization and streamlined workflows. An important task in histopathology is the segmentation of cells and glands, essential for determining shape and frequencies that can serve as indicators of disease. Deep learn...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,645
2010.03022	Resource-Enhanced Neural Model for Event Argument Extraction	Event argument extraction (EAE) aims to identify the arguments of an event and classify the roles that those arguments play. Despite great efforts made in prior work, there remain many challenges: (1) Data scarcity. (2) Capturing the long-range dependency, specifically, the connection between an event trigger and a dis...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	199,240
2003.01540	On the Effectiveness of Virtual Reality-based Training for Robotic Setup	Virtual Reality (VR) is rapidly increasing in popularity as a teaching tool. It allows for the creation of a highly immersive, three-dimensional virtual environment intended to simulate real-life environments. With more robots saturating the industry - from manufacturing to healthcare, there is a need to train end-user...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	166,683
1403.3084	Emerging archetypes in massive artificial societies for literary purposes using genetic algorithms	The creation of fictional stories is a very complex task that usually implies a creative process where the author has to combine characters, conflicts and plots to create an engaging narrative. This work presents a simulated environment with hundreds of characters that allows the study of coherent and interesting liter...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	31,539
2305.16433	Neural Machine Translation for Mathematical Formulae	We tackle the problem of neural machine translation of mathematical formulae between ambiguous presentation languages and unambiguous content languages. Compared to neural machine translation on natural language, mathematical formulae have a much smaller vocabulary and much longer sequences of symbols, while their tran...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	368,087
2409.13903	CI-Bench: Benchmarking Contextual Integrity of AI Assistants on Synthetic Data	Advances in generative AI point towards a new era of personalized applications that perform diverse tasks on behalf of users. While general AI assistants have yet to fully emerge, their potential to share personal data raises significant privacy challenges. This paper introduces CI-Bench, a comprehensive synthetic benc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	490,223
2105.09386	Surprisingly Popular Voting Recovers Rankings, Surprisingly!	The wisdom of the crowd has long become the de facto approach for eliciting information from individuals or experts in order to predict the ground truth. However, classical democratic approaches for aggregating individual \emph{votes} only work when the opinion of the majority of the crowd is relatively accurate. A cle...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	236,043
2406.18908	A Universal Railway Obstacle Detection System based on Semi-supervised Segmentation And Optical Flow	Detecting obstacles in railway scenarios is both crucial and challenging due to the wide range of obstacle categories and varying ambient conditions such as weather and light. Given the impossibility of encompassing all obstacle categories during the training stage, we address this out-of-distribution (OOD) issue with ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	468,226
1710.08894	Conformal predictive distributions with kernels	This paper reviews the checkered history of predictive distributions in statistics and discusses two developments, one from recent literature and the other new. The first development is bringing predictive distributions into machine learning, whose early development was so deeply influenced by two remarkable groups at ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	83,141
1903.08561	Sequential Optimization of Speed, Thermal Load, and Power Split in Connected HEVs	The emergence of connected and automated vehicles (CAVs) provides an unprecedented opportunity to capitalize on these technologies well beyond their original designed intents. While abundant evidence has been accumulated showing substantial fuel economy improvement benefits achieved through advanced powertrain control,...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	124,856
2104.09874	Boosting Masked Face Recognition with Multi-Task ArcFace	In this paper, we address the problem of face recognition with masks. Given the global health crisis caused by COVID-19, mouth and nose-covering masks have become an essential everyday-clothing-accessory. This sanitary measure has put the state-of-the-art face recognition models on the ropes since they have not been de...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	231,387
2006.08109	NeuroCard: One Cardinality Estimator for All Tables	Query optimizers rely on accurate cardinality estimates to produce good execution plans. Despite decades of research, existing cardinality estimators are inaccurate for complex queries, due to making lossy modeling assumptions and not capturing inter-table correlations. In this work, we show that it is possible to lear...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	182,070
2012.04855	Reconstruction of Backbone Curves for Snake Robots	Snake robots composed of alternating single-axis pitch and yaw joints have many internal degrees of freedom, which make them capable of versatile three-dimensional locomotion. In motion planning process, snake robot motions are often designed kinematically by a chronological sequence of continuous backbone curves that ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	210,592
2312.10730	Mixed Distillation Helps Smaller Language Model Better Reasoning	While large language models (LLMs) have demonstrated exceptional performance in recent natural language processing (NLP) tasks, their deployment poses substantial challenges due to high computational and memory demands in real-world applications. Recent studies have focused on enhancing smaller models through knowledge...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	416,297
2109.06093	Direct Advantage Estimation	The predominant approach in reinforcement learning is to assign credit to actions based on the expected return. However, we show that the return may depend on the policy in a way which could lead to excessive variance in value estimation and slow down learning. Instead, we show that the advantage function can be interp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	255,043
2212.11071	Can a Robot Shoot an Olympic Recurve Bow? A preliminary study	The field of robotics, and more especially humanoid robotics, has several established competitions with research oriented goals in mind. Challenging the robots in a handful of tasks, these competitions provide a way to gauge the state of the art in robotic design, as well as an indicator for how far we are from reachin...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	337,682
2309.10109	AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation	Test-time adaptation is a promising research direction that allows the source model to adapt itself to changes in data distribution without any supervision. Yet, current methods are usually evaluated on benchmarks that are only a simplification of real-world scenarios. Hence, we propose to validate test-time adaptation...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	392,861
2111.07494	Federated Learning for Internet of Things: Applications, Challenges, and Opportunities	Billions of IoT devices will be deployed in the near future, taking advantage of faster Internet speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the growth of IoT devices, vast quantities of data that may contain users' private information will be generated. The high communication...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,392
2501.05990	Constraining constructions with WordNet: pros and cons for the semantic annotation of fillers in the Italian Constructicon	The paper discusses the role of WordNet-based semantic classification in the formalization of constructions, and more specifically in the semantic annotation of schematic fillers, in the Italian Constructicon. We outline how the Italian Constructicon project uses Open Multilingual WordNet topics to represent semantic f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	523,794
0708.0905	Permutation Decoding and the Stopping Redundancy Hierarchy of Cyclic and Extended Cyclic Codes	We introduce the notion of the stopping redundancy hierarchy of a linear block code as a measure of the trade-off between performance and complexity of iterative decoding for the binary erasure channel. We derive lower and upper bounds for the stopping redundancy hierarchy via Lovasz's Local Lemma and Bonferroni-type i...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	531

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