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
1707.02029	LoopInvGen: A Loop Invariant Generator based on Precondition Inference	We describe the LoopInvGen tool for generating loop invariants that can provably guarantee correctness of a program with respect to a given specification. LoopInvGen is an efficient implementation of the inference technique originally proposed in our earlier work on PIE (https://doi.org/10.1145/2908080.2908099). In c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	76,635
2204.04831	Cello: Efficient Computer Systems Optimization with Predictive Early Termination and Censored Regression	Sample-efficient machine learning (SEML) has been widely applied to find optimal latency and power tradeoffs for configurable computer systems. Instead of randomly sampling from the configuration space, SEML reduces the search cost by dramatically reducing the number of configurations that must be sampled to optimize s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	290,803
2304.11526	How to Control Hydrodynamic Force on Fluidic Pinball via Deep Reinforcement Learning	Deep reinforcement learning (DRL) for fluidic pinball, three individually rotating cylinders in the uniform flow arranged in an equilaterally triangular configuration, can learn the efficient flow control strategies due to the validity of self-learning and data-driven state estimation for complex fluid dynamic problems...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	359,852
2205.06231	The Experimental Multi-Arm Pendulum on a Cart: A Benchmark System for Chaos, Learning, and Control	The single, double, and triple pendulum has served as an illustrative experimental benchmark system for scientists to study dynamical behavior for more than four centuries. The pendulum system exhibits a wide range of interesting behaviors, from simple harmonic motion in the single pendulum to chaotic dynamics in multi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	296,180
2112.15462	Quaternary linear codes and related binary subfield codes	In this paper, we mainly study quaternary linear codes and their binary subfield codes. First we obtain a general explicit relationship between quaternary linear codes and their binary subfield codes in terms of generator matrices and defining sets. Second, we construct quaternary linear codes via simplicial complexes ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	273,794
2410.02810	StateAct: State Tracking and Reasoning for Acting and Planning with Large Language Models	Planning and acting to solve `real' tasks using large language models (LLMs) in interactive environments has become a new frontier for AI methods. While recent advances allowed LLMs to interact with online tools, solve robotics tasks and many more, long range reasoning tasks remain a problem for LLMs. Existing methods ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	494,475
2407.07972	Deconstructing What Makes a Good Optimizer for Language Models	Training language models becomes increasingly expensive with scale, prompting numerous attempts to improve optimization efficiency. Despite these efforts, the Adam optimizer remains the most widely used, due to a prevailing view that it is the most effective approach. We aim to compare several optimization algorithms, ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	471,962
2410.09293	EasyHeC++: Fully Automatic Hand-Eye Calibration with Pretrained Image Models	Hand-eye calibration plays a fundamental role in robotics by directly influencing the efficiency of critical operations such as manipulation and grasping. In this work, we present a novel framework, EasyHeC++, designed for fully automatic hand-eye calibration. In contrast to previous methods that necessitate manual cal...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	497,519
2412.18719	Using Large Language Models for Automated Grading of Student Writing about Science	Assessing writing in large classes for formal or informal learners presents a significant challenge. Consequently, most large classes, particularly in science, rely on objective assessment tools such as multiple-choice quizzes, which have a single correct answer. The rapid development of AI has introduced the possibili...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	520,539
2206.05589	Determinable and interpretable network representation for link prediction	As an intuitive description of complex physical, social, or brain systems, complex networks have fascinated scientists for decades. Recently, to abstract a network's structural and dynamical attributes for utilization, network representation has been one focus, mapping a network or its substructures (like nodes) into a...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	302,059
1405.7812	Duality of a Source Coding Problem and the Semi-Deterministic Broadcast Channel with Rate-Limited Cooperation	The Wyner-Ahlswede-K\"orner (WAK) empirical-coordination problem where the encoders cooperate via a finite-capacity one-sided link is considered. The coordination-capacity region is derived by combining several source coding techniques, such as Wyner-Ziv (WZ) coding, binning and superposition coding. Furthermore, a sem...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	33,497
2502.05650	Incongruence Identification in Eyewitness Testimony	Incongruence detection in eyewitness narratives is critical for understanding the reliability of testimonies, yet traditional approaches often fail to address the nuanced inconsistencies inherent in such accounts. In this paper, we introduce a novel task of incongruence detection in eyewitness testimonies. Given a pair...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	531,705
2001.09322	Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation	We present a novel approach to category-level 6D object pose and size estimation. To tackle intra-class shape variations, we learn canonical shape space (CASS), a unified representation for a large variety of instances of a certain object category. In particular, CASS is modeled as the latent space of a deep generative...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	161,535
1602.07873	CNN for License Plate Motion Deblurring	In this work we explore the previously proposed approach of direct blind deconvolution and denoising with convolutional neural networks in a situation where the blur kernels are partially constrained. We focus on blurred images from a real-life traffic surveillance system, on which we, for the first time, demonstrate t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	52,577
2210.08340	Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution	Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI. A core component of this is the embodied Turing test, which challenges AI animal models to interact with the sensorimotor world at ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	324,100
1607.07234	Doubly Massive mmWave MIMO Systems: Using Very Large Antenna Arrays at Both Transmitter and Receiver	One of the key features of next generation wireless communication systems will be the use of frequencies in the range 10-100GHz (aka mmWave band) in densely populated indoor and outdoor scenarios. Due to the reduced wavelength, antenna arrays with a large number of antennas can be packed in very small volumes, making t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	58,993
2502.04467	Efficient variable-length hanging tether parameterization for marsupial robot planning in 3D environments	This paper presents a novel approach to efficiently parameterize and estimate the state of a hanging tether for path and trajectory planning of a UGV tied to a UAV in a marsupial configuration. Most implementations in the state of the art assume a taut tether or make use of the catenary curve to model the shape of the ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	531,165
1511.05318	Asymptotic Performance Analysis for 1-bit Bayesian Smoothing	Energy-efficient signal processing systems require estimation methods operating on data collected with low-complexity devices. Using analog-to-digital converters (ADC) with $1$-bit amplitude resolution has been identified as a possible option in order to obtain low power consumption. The $1$-bit performance loss, in co...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	49,034
2501.15070	Unifying Prediction and Explanation in Time-Series Transformers via Shapley-based Pretraining	In this paper, we propose ShapTST, a framework that enables time-series transformers to efficiently generate Shapley-value-based explanations alongside predictions in a single forward pass. Shapley values are widely used to evaluate the contribution of different time-steps and features in a test sample, and are commonl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	527,389
1704.01515	On application of OMP and CoSaMP algorithms for DOA estimation problem	Remarkable properties of Compressed sensing (CS) has led researchers to utilize it in various other fields where a solution to an underdetermined system of linear equations is needed. One such application is in the area of array signal processing e.g. in signal denoising and Direction of Arrival (DOA) estimation. From ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	71,278
2003.02689	EPINE: Enhanced Proximity Information Network Embedding	Unsupervised homogeneous network embedding (NE) represents every vertex of networks into a low-dimensional vector and meanwhile preserves the network information. Adjacency matrices retain most of the network information, and directly charactrize the first-order proximity. In this work, we devote to mining valuable inf...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	167,014
2203.16867	Snapshot Visualization of Complex Graphs with Force-Directed Algorithms	Force-directed algorithms are widely used for visualizing graphs. However, these algorithms are computationally expensive in producing good quality layouts for complex graphs. The layout quality is largely influenced by execution time and methods' input parameters especially for large complex graphs. The snapshots of v...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	288,955
2206.05398	E2PN: Efficient SE(3)-Equivariant Point Network	This paper proposes a convolution structure for learning SE(3)-equivariant features from 3D point clouds. It can be viewed as an equivariant version of kernel point convolutions (KPConv), a widely used convolution form to process point cloud data. Compared with existing equivariant networks, our design is simple, light...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	301,989
2305.12951	Cross-functional Analysis of Generalisation in Behavioural Learning	In behavioural testing, system functionalities underrepresented in the standard evaluation setting (with a held-out test set) are validated through controlled input-output pairs. Optimising performance on the behavioural tests during training (behavioural learning) would improve coverage of phenomena not sufficiently r...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	366,268
2012.13944	ROS for Human-Robot Interaction	Integrating real-time, complex social signal processing into robotic systems -- especially in real-world, multi-party interaction situations -- is a challenge faced by many in the Human-Robot Interaction (HRI) community. The difficulty is compounded by the lack of any standard model for human representation that would ...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	213,366
2305.02334	Structures of Neural Network Effective Theories	We develop a diagrammatic approach to effective field theories (EFTs) corresponding to deep neural networks at initialization, which dramatically simplifies computations of finite-width corrections to neuron statistics. The structures of EFT calculations make it transparent that a single condition governs criticality o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	362,002
2302.07477	Optimal Sample Complexity of Reinforcement Learning for Mixing Discounted Markov Decision Processes	We consider the optimal sample complexity theory of tabular reinforcement learning (RL) for maximizing the infinite horizon discounted reward in a Markov decision process (MDP). Optimal worst-case complexity results have been developed for tabular RL problems in this setting, leading to a sample complexity dependence o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	345,747
1808.09479	Residualized Factor Adaptation for Community Social Media Prediction Tasks	Predictive models over social media language have shown promise in capturing community outcomes, but approaches thus far largely neglect the socio-demographic context (e.g. age, education rates, race) of the community from which the language originates. For example, it may be inaccurate to assume people in Mobile, Alab...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	106,196
2411.02125	Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning	Obtaining effective representations of DNA sequences is crucial for genome analysis. Metagenomic binning, for instance, relies on genome representations to cluster complex mixtures of DNA fragments from biological samples with the aim of determining their microbial compositions. In this paper, we revisit k-mer-based re...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	505,364
2010.04408	Dirichlet Graph Variational Autoencoder	Graph Neural Networks (GNNs) and Variational Autoencoders (VAEs) have been widely used in modeling and generating graphs with latent factors. However, there is no clear explanation of what these latent factors are and why they perform well. In this work, we present Dirichlet Graph Variational Autoencoder (DGVAE) with g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	199,730
2303.15414	Learnable Graph Matching: A Practical Paradigm for Data Association	Data association is at the core of many computer vision tasks, e.g., multiple object tracking, image matching, and point cloud registration. however, current data association solutions have some defects: they mostly ignore the intra-view context information; besides, they either train deep association models in an end-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,481
1706.07582	Fundamental Limits of Universal Variable-to-Fixed Length Coding of Parametric Sources	Universal variable-to-fixed (V-F) length coding of $d$-dimensional exponential family of distributions is considered. We propose an achievable scheme consisting of a dictionary, used to parse the source output stream, making use of the previously-introduced notion of quantized types. The quantized type class of a seque...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	75,870
2411.16657	DreamRunner: Fine-Grained Storytelling Video Generation with Retrieval-Augmented Motion Adaptation	Storytelling video generation (SVG) has recently emerged as a task to create long, multi-motion, multi-scene videos that consistently represent the story described in the input text script. SVG holds great potential for diverse content creation in media and entertainment; however, it also presents significant challenge...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	511,105
2106.03245	Verification in the Loop: Correct-by-Construction Control Learning with Reach-avoid Guarantees	In the current control design of safety-critical autonomous systems, formal verification techniques are typically applied after the controller is designed to evaluate whether the required properties (e.g., safety) are satisfied. However, due to the increasing system complexity and the fundamental hardness of designing ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	239,241
2011.15028	The LDBC Graphalytics Benchmark	In this document, we describe LDBC Graphalytics, an industrial-grade benchmark for graph analysis platforms. The main goal of Graphalytics is to enable the fair and objective comparison of graph analysis platforms. Due to the diversity of bottlenecks and performance issues such platforms need to address, Graphalytics c...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	208,964
2403.13864	Optimal Transport for Fairness: Archival Data Repair using Small Research Data Sets	With the advent of the AI Act and other regulations, there is now an urgent need for algorithms that repair unfairness in training data. In this paper, we define fairness in terms of conditional independence between protected attributes ($S$) and features ($X$), given unprotected attributes ($U$). We address the import...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	439,826
2310.15952	Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensembles	Ensemble deep learning has been shown to achieve high predictive accuracy and uncertainty estimation in a wide variety of medical imaging contexts. However, perturbations in the input images at test time (e.g. noise, domain shifts) can still lead to significant performance degradation, posing challenges for trustworthy...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	402,515
1110.5870	Universal and efficient compressed sensing by spread spectrum and application to realistic Fourier imaging techniques	We advocate a compressed sensing strategy that consists of multiplying the signal of interest by a wide bandwidth modulation before projection onto randomly selected vectors of an orthonormal basis. Firstly, in a digital setting with random modulation, considering a whole class of sensing bases including the Fourier ba...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,780
2303.10833	Linear Codes Constructed From Two Weakly Regular Plateaued Functions with Index (p-1)/2	Linear codes are the most important family of codes in cryptography and coding theory. Some codes have only a few weights and are widely used in many areas, such as authentication codes, secret sharing schemes and strongly regular graphs. By setting $ p\equiv 1 \pmod 4 $, we construct an infinite family of linear codes...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	352,596
2305.12121	ACA-Net: Towards Lightweight Speaker Verification using Asymmetric Cross Attention	In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetric Cross Attention (ACA) to replace temporal pooling. ACA is able to distill large, variable-length sequences into small, fixed-sized latents...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	365,847
2306.09237	One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support	Recent strides in Large Language Models (LLMs) have saturated many Natural Language Processing (NLP) benchmarks, emphasizing the need for more challenging ones to properly assess LLM capabilities. However, domain-specific and multilingual benchmarks are rare because they require in-depth expertise to develop. Still, mo...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	373,727
2410.23107	Decoupling Semantic Similarity from Spatial Alignment for Neural Networks	What representation do deep neural networks learn? How similar are images to each other for neural networks? Despite the overwhelming success of deep learning methods key questions about their internal workings still remain largely unanswered, due to their internal high dimensionality and complexity. To address this, o...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	503,903
1805.06621	Generative networks as inverse problems with Scattering transforms	Generative Adversarial Nets (GANs) and Variational Auto-Encoders (VAEs) provide impressive image generations from Gaussian white noise, but the underlying mathematics are not well understood. We compute deep convolutional network generators by inverting a fixed embedding operator. Therefore, they do not require to be o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	97,652
2202.13871	Wastewater Pipe Rating Model Using Natural Language Processing	Closed-circuit video (CCTV) inspection has been the most popular technique for visually evaluating the interior status of pipelines in recent decades. Certified inspectors prepare the pipe repair document based on the CCTV inspection. The traditional manual method of assessing sewage structural conditions from pipe rep...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	282,778
2103.15972	Deep Compression for PyTorch Model Deployment on Microcontrollers	Neural network deployment on low-cost embedded systems, hence on microcontrollers (MCUs), has recently been attracting more attention than ever. Since MCUs have limited memory capacity as well as limited compute-speed, it is critical that we employ model compression, which reduces both memory and compute-speed requirem...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	227,399
2008.12289	Hope Amid of a Pandemic: Is Psychological Distress Alleviating in South America while Coronavirus is still on Surge?	As of July 31, 2020, the COVID-19 pandemic has over 17 million reported cases, causing more than 667,000 deaths. Countries irrespective of economic status have succumbed to this pandemic. Many aspects of the lives, including health, economy, freedom of movement have been negatively affected by the coronavirus outbreak....	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	193,534
1811.02932	Supervisor Obfuscation Against Actuator Enablement Attack	In this paper, we propose and address the problem of supervisor obfuscation against actuator enablement attack, in a common setting where the actuator attacker can eavesdrop the control commands issued by the supervisor. We propose a method to obfuscate an (insecure) supervisor to make it resilient against actuator ena...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	112,720
2108.04692	Automated Audio Captioning using Transfer Learning and Reconstruction Latent Space Similarity Regularization	In this paper, we examine the use of Transfer Learning using Pretrained Audio Neural Networks (PANNs), and propose an architecture that is able to better leverage the acoustic features provided by PANNs for the Automated Audio Captioning Task. We also introduce a novel self-supervised objective, Reconstruction Latent S...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	250,086
1908.10738	Modular Verification of Autonomous Space Robotics	Ensuring that autonomous space robot control software behaves as it should is crucial, particularly as software failure in space often equates to mission failure and could potentially endanger nearby astronauts and costly equipment. To minimise mission failure caused by software errors, we can utilise a variety of tool...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	143,199
2404.02117	Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners	Few-Shot Class Incremental Learning (FSCIL) is a task that requires a model to learn new classes incrementally without forgetting when only a few samples for each class are given. FSCIL encounters two significant challenges: catastrophic forgetting and overfitting, and these challenges have driven prior studies to prim...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	443,728
1703.05381	3D Vision Guided Robotic Charging Station for Electric and Plug-in Hybrid Vehicles	Electric vehicles (EVs) and plug-in hybrid vehicles (PHEVs) are rapidly gaining popularity on our roads. Besides a comparatively high purchasing price, the main two problems limiting their use are the short driving range and inconvenient charging process. In this paper we address the following by presenting an automati...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	70,067
2203.00947	KC-TSS: An Algorithm for Heterogeneous Robot Teams Performing Resilient Target Search	This paper proposes KC-TSS: K-Clustered-Traveling Salesman Based Search, a failure resilient path planning algorithm for heterogeneous robot teams performing target search in human environments. We separate the sample path generation problem into Heterogeneous Clustering and multiple Traveling Salesman Problems. This a...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	283,193
2501.19066	Concept Steerers: Leveraging K-Sparse Autoencoders for Controllable Generations	Despite the remarkable progress in text-to-image generative models, they are prone to adversarial attacks and inadvertently generate unsafe, unethical content. Existing approaches often rely on fine-tuning models to remove specific concepts, which is computationally expensive, lack scalability, and/or compromise genera...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	528,993
2309.01656	Building Footprint Extraction in Dense Areas using Super Resolution and Frame Field Learning	Despite notable results on standard aerial datasets, current state-of-the-arts fail to produce accurate building footprints in dense areas due to challenging properties posed by these areas and limited data availability. In this paper, we propose a framework to address such issues in polygonal building extraction. Firs...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	389,757
2007.10985	PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding	Arguably one of the top success stories of deep learning is transfer learning. The finding that pre-training a network on a rich source set (eg., ImageNet) can help boost performance once fine-tuned on a usually much smaller target set, has been instrumental to many applications in language and vision. Yet, very little...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,438
2006.01629	Give Me Something to Eat: Referring Expression Comprehension with Commonsense Knowledge	Conventional referring expression comprehension (REF) assumes people to query something from an image by describing its visual appearance and spatial location, but in practice, we often ask for an object by describing its affordance or other non-visual attributes, especially when we do not have a precise target. For ex...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	179,827
2105.07914	Large-Scale Unsupervised Person Re-Identification with Contrastive Learning	Existing public person Re-Identification~(ReID) datasets are small in modern terms because of labeling difficulty. Although unlabeled surveillance video is abundant and relatively easy to obtain, it is unclear how to leverage these footage to learn meaningful ReID representations. In particular, most existing unsupervi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	235,596
2409.11726	Revealing the Challenge of Detecting Character Knowledge Errors in LLM Role-Playing	Large language model (LLM) role-playing has gained widespread attention, where the authentic character knowledge is crucial for constructing realistic LLM role-playing agents. However, existing works usually overlook the exploration of LLMs' ability to detect characters' known knowledge errors (KKE) and unknown knowled...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	489,294
2110.01871	Emerging trends and collaboration patterns unveil the scientific production in blockchain technology: A bibliometric and network analysis from 2014-2020	Significant attention in the financial industry has paved the way for blockchain technology to spread across other industries, resulting in a plethora of literature on the subject. This study approaches the subject through bibliometrics and network analysis of 6790 records extracted from the Web of Science from 2014-20...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	258,925
1909.00526	An Abstraction-Free Method for Multi-Robot Temporal Logic Optimal Control Synthesis	The majority of existing Linear Temporal Logic (LTL) planning methods rely on the construction of a discrete product automaton, that combines a discrete abstraction of robot mobility and a B$\ddot{\text{u}}$chi automaton that captures the LTL specification. Representing this product automaton as a graph and using graph...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	143,658
1408.3877	FESTUNG: A MATLAB / GNU Octave toolbox for the discontinuous Galerkin method. Part I: Diffusion operator	This is the first in a series of papers on implementing a discontinuous Galerkin method as a MATLAB / GNU Octave toolbox. The main goal is the development of techniques that deliver optimized computational performance combined with a compact, user-friendly interface. Our implementation relies on fully vectorized matrix...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	35,422
2308.16464	MaintainoMATE: A GitHub App for Intelligent Automation of Maintenance Activities	Software development projects rely on issue tracking systems at the core of tracking maintenance tasks such as bug reports, and enhancement requests. Incoming issue-reports on these issue tracking systems must be managed in an effective manner. First, they must be labelled and then assigned to a particular developer wi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	388,991
2105.05610	A Statistical Threshold for Adversarial Classification in Laplace Mechanisms	This paper studies the statistical characterization of detecting an adversary who wants to harm some computation such as machine learning models or aggregation by altering the output of a differentially private mechanism in addition to discovering some information about the underlying dataset. An adversary who is able ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	234,869
2403.01631	TreeTracker Join: Simple, Optimal, Fast	Inspired by the TreeTracker algorithm used in Constraint Satisfaction we present a novel linear-time join algorithm, TreeTracker Join (TTJ). TTJ is very similar to a standard binary hash join, but introduces a test that identifies when a tuple is dangling and removes that tuple from its relation. The test is to simply ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	434,509
1612.09433	Curiosity-Aware Bargaining	Opponent modeling consists in modeling the strategy or preferences of an agent thanks to the data it provides. In the context of automated negotiation and with machine learning, it can result in an advantage so overwhelming that it may restrain some casual agents to be part of the bargaining process. We qualify as "cur...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	66,187
2011.04491	Masked Proxy Loss For Text-Independent Speaker Verification	Open-set speaker recognition can be regarded as a metric learning problem, which is to maximize inter-class variance and minimize intra-class variance. Supervised metric learning can be categorized into entity-based learning and proxy-based learning. Most of the existing metric learning objectives like Contrastive, Tri...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	205,606
2109.11304	Deep Learning Strategies for Industrial Surface Defect Detection Systems	Deep learning methods have proven to outperform traditional computer vision methods in various areas of image processing. However, the application of deep learning in industrial surface defect detection systems is challenging due to the insufficient amount of training data, the expensive data generation process, the sm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	256,900
1706.10209	Storage, Communication, and Load Balancing Trade-off in Distributed Cache Networks	We consider load balancing in a network of caching servers delivering contents to end users. Randomized load balancing via the so-called power of two choices is a well-known approach in parallel and distributed systems. In this framework, we investigate the tension between storage resources, communication cost, and loa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	76,262
2409.04363	RCNet: Deep Recurrent Collaborative Network for Multi-View Low-Light Image Enhancement	Scene observation from multiple perspectives would bring a more comprehensive visual experience. However, in the context of acquiring multiple views in the dark, the highly correlated views are seriously alienated, making it challenging to improve scene understanding with auxiliary views. Recent single image-based enha...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	486,367
2312.08176	ASC: Adaptive Scale Feature Map Compression for Deep Neural Network	Deep-learning accelerators are increasingly in demand; however, their performance is constrained by the size of the feature map, leading to high bandwidth requirements and large buffer sizes. We propose an adaptive scale feature map compression technique leveraging the unique properties of the feature map. This techniq...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	415,219
1905.10921	On the Commitment Capacity of Unfair Noisy Channels	Noisy channels are a valuable resource from a cryptographic point of view. They can be used for exchanging secret-keys as well as realizing other cryptographic primitives such as commitment and oblivious transfer. To be really useful, noisy channels have to be consider in the scenario where a cheating party has some de...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	132,254
2208.00319	Robust Planning for Multi-stage Forceful Manipulation	Multi-step forceful manipulation tasks, such as opening a push-and-twist childproof bottle, require a robot to make various planning choices that are substantially impacted by the requirement to exert force during the task. The robot must reason over discrete and continuous choices relating to the sequence of actions, ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	310,812
2310.00076	Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks	In light of recent advancements in generative AI models, it has become essential to distinguish genuine content from AI-generated one to prevent the malicious usage of fake materials as authentic ones and vice versa. Various techniques have been introduced for identifying AI-generated images, with watermarking emerging...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	395,808
1511.05622	Predicting distributions with Linearizing Belief Networks	Conditional belief networks introduce stochastic binary variables in neural networks. Contrary to a classical neural network, a belief network can predict more than the expected value of the output $Y$ given the input $X$. It can predict a distribution of outputs $Y$ which is useful when an input can admit multiple out...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	49,069
2004.11349	Personalized Automatic Sleep Staging with Single-Night Data: a Pilot Study with KL-Divergence Regularization	Brain waves vary between people. An obvious way to improve automatic sleep staging for longitudinal sleep monitoring is personalization of algorithms based on individual characteristics extracted from the first night of data. As a single night is a very small amount of data to train a sleep staging model, we propose a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,884
2201.03473	Macroprogramming: Concepts, State of the Art, and Opportunities of Macroscopic Behaviour Modelling	Macroprogramming refers to the theory and practice of conveniently expressing the macro(scopic) behaviour of a system using a single program. Macroprogramming approaches are motivated by the need of effectively capturing global/system-level aspects and the collective behaviour of a set of interacting components, while ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	true	274,862
2003.05870	Natural Language Interaction to Facilitate Mental Models of Remote Robots	Increasingly complex and autonomous robots are being deployed in real-world environments with far-reaching consequences. High-stakes scenarios, such as emergency response or offshore energy platform and nuclear inspections, require robot operators to have clear mental models of what the robots can and can't do. However...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	167,970
1009.5346	A Novel Approach for Cardiac Disease Prediction and Classification Using Intelligent Agents	The goal is to develop a novel approach for cardiac disease prediction and diagnosis using intelligent agents. Initially the symptoms are preprocessed using filter and wrapper based agents. The filter removes the missing or irrelevant symptoms. Wrapper is used to extract the data in the data set according to the thresh...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	7,696
1910.06995	Reduced-Order Modeling of Deep Neural Networks	We introduce a new method for speeding up the inference of deep neural networks. It is somewhat inspired by the reduced-order modeling techniques for dynamical systems.The cornerstone of the proposed method is the maximum volume algorithm. We demonstrate efficiency on neural networks pre-trained on different datasets. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,497
2207.04497	One-shot Neural Backdoor Erasing via Adversarial Weight Masking	Recent studies show that despite achieving high accuracy on a number of real-world applications, deep neural networks (DNNs) can be backdoored: by injecting triggered data samples into the training dataset, the adversary can mislead the trained model into classifying any test data to the target class as long as the tri...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	307,217
2109.09991	Learning Kernel-Smoothed Machine Translation with Retrieved Examples	How to effectively adapt neural machine translation (NMT) models according to emerging cases without retraining? Despite the great success of neural machine translation, updating the deployed models online remains a challenge. Existing non-parametric approaches that retrieve similar examples from a database to guide th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	256,470
2409.12972	TRACE: Transformer-based user Representations from Attributed Clickstream Event sequences	For users navigating travel e-commerce websites, the process of researching products and making a purchase often results in intricate browsing patterns that span numerous sessions over an extended period of time. The resulting clickstream data chronicle these user journeys and present valuable opportunities to derive i...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	489,798
2105.05037	BikNN: Anomaly Estimation in Bilateral Domains with k-Nearest Neighbors	In this paper, a novel framework for anomaly estimation is proposed. The basic idea behind our method is to reduce the data into a two-dimensional space and then rank each data point in the reduced space. We attempt to estimate the degree of anomaly in both spatial and density domains. Specifically, we transform the da...	false	false	false	false	false	true	true	false	false	false	false	true	false	false	false	false	false	false	234,699
2211.00065	Artificial Intelligence and Arms Control	Potential advancements in artificial intelligence (AI) could have profound implications for how countries research and develop weapons systems, and how militaries deploy those systems on the battlefield. The idea of AI-enabled military systems has motivated some activists to call for restrictions or bans on some weapon...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	327,738
2408.17083	Focus-Consistent Multi-Level Aggregation for Compositional Zero-Shot Learning	To transfer knowledge from seen attribute-object compositions to recognize unseen ones, recent compositional zero-shot learning (CZSL) methods mainly discuss the optimal classification branches to identify the elements, leading to the popularity of employing a three-branch architecture. However, these methods mix up th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	484,572
2010.12083	Language-Conditioned Imitation Learning for Robot Manipulation Tasks	Imitation learning is a popular approach for teaching motor skills to robots. However, most approaches focus on extracting policy parameters from execution traces alone (i.e., motion trajectories and perceptual data). No adequate communication channel exists between the human expert and the robot to describe critical a...	false	false	false	false	false	false	true	true	true	false	false	true	false	false	false	false	false	false	202,552
2303.11139	Opportunities and Challenges to Integrate Artificial Intelligence into Manufacturing Systems: Thoughts from a Panel Discussion	Rapid advances in artificial intelligence (AI) have the potential to significantly increase the productivity, quality, and profitability in future manufacturing systems. Traditional mass-production will give way to personalized production, with each item made to order, at the low cost and high-quality consumers have co...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	352,720
1609.01176	The Player Kernel: Learning Team Strengths Based on Implicit Player Contributions	In this work, we draw attention to a connection between skill-based models of game outcomes and Gaussian process classification models. The Gaussian process perspective enables a) a principled way of dealing with uncertainty and b) rich models, specified through kernel functions. Using this connection, we tackle the pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	60,562
2406.09983	Epidemic-induced local awareness behavior inferred from surveys and genetic sequence data	Behavior-disease models suggest that if individuals are aware and take preventive actions when the prevalence of the disease increases among their close contacts, then the pandemic can be contained in a cost-effective way. To measure the true impact of local awareness behavior on epidemic spreading, we propose an effic...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	464,176
2308.11485	Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Features	Given a query composed of a reference image and a relative caption, the Composed Image Retrieval goal is to retrieve images visually similar to the reference one that integrates the modifications expressed by the caption. Given that recent research has demonstrated the efficacy of large-scale vision and language pre-tr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,158
2408.12760	Hierarchical Attention and Parallel Filter Fusion Network for Multi-Source Data Classification	Hyperspectral image (HSI) and synthetic aperture radar (SAR) data joint classification is a crucial and yet challenging task in the field of remote sensing image interpretation. However, feature modeling in existing methods is deficient to exploit the abundant global, spectral, and local features simultaneously, leadin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	482,865
2011.00633	Aspect-Based Argument Mining	Computational Argumentation in general and Argument Mining in particular are important research fields. In previous works, many of the challenges to automatically extract and to some degree reason over natural language arguments were addressed. The tools to extract argument units are increasingly available and further ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	204,307
1807.09406	Estimating group properties in online social networks with a classifier	We consider the problem of obtaining unbiased estimates of group properties in social networks when using a classifier for node labels. Inference for this problem is complicated by two factors: the network is not known and must be crawled, and even high-performance classifiers provide biased estimates of group proporti...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	103,714
2205.15462	Causal Explanations for Sequential Decision Making Under Uncertainty	We introduce a novel framework for causal explanations of stochastic, sequential decision-making systems built on the well-studied structural causal model paradigm for causal reasoning. This single framework can identify multiple, semantically distinct explanations for agent actions -- something not previously possible...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	299,734
0808.0037	An Energy-Based Comparison of Long-Hop and Short-Hop Routing in MIMO Networks	This paper considers the problem of selecting either routes that consist of long hops or routes that consist of short hops in a network of multiple-antenna nodes, where each transmitting node employs spatial multiplexing. This distance-dependent route selection problem is approached from the viewpoint of energy efficie...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,148
1407.4206	Mobile Camera Array Calibration for Light Field Acquisition	The light field camera is useful for computer graphics and vision applications. Calibration is an essential step for these applications. After calibration, we can rectify the captured image by using the calibrated camera parameters. However, the large camera array calibration method, which assumes that all cameras are ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	34,688
2205.08106	Computerized Tomography Pulmonary Angiography Image Simulation using Cycle Generative Adversarial Network from Chest CT imaging in Pulmonary Embolism Patients	The purpose of this research is to develop a system that generates simulated computed tomography pulmonary angiography (CTPA) images clinically for pulmonary embolism diagnoses. Nowadays, CTPA images are the gold standard computerized detection method to determine and identify the symptoms of pulmonary embolism (PE), a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	296,822
2101.02330	Copula Quadrant Similarity for Anomaly Scores	Practical anomaly detection requires applying numerous approaches due to the inherent difficulty of unsupervised learning. Direct comparison between complex or opaque anomaly detection algorithms is intractable; we instead propose a framework for associating the scores of multiple methods. Our aim is to answer the ques...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	214,584
2212.01539	Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping	Differentially private deep learning has recently witnessed advances in computational efficiency and privacy-utility trade-off. We explore whether further improvements along the two axes are possible and provide affirmative answers leveraging two instantiations of \emph{group-wise clipping}. To reduce the compute time ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	334,466
1910.12717	Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset	This paper tackles the challenge presented by small-data to the task of Bayesian inference. A novel methodology, based on manifold learning and manifold sampling, is proposed for solving this computational statistics problem under the following assumptions: 1) neither the prior model nor the likelihood function are Gau...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	151,177

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