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
2011.08639	Space-time budget allocation policy design for viral marketing	We address formally the problem of opinion dynamics when the agents of a social network (e.g., consumers) are not only influenced by their neighbors but also by an external influential entity referred to as a marketer. The influential entity tries to sway the overall opinion as close as possible to a desired opinion by...	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	206,940
1810.09309	Real-time Neural-based Input Method	The input method is an essential service on every mobile and desktop devices that provides text suggestions. It converts sequential keyboard inputs to the characters in its target language, which is indispensable for Japanese and Chinese users. Due to critical resource constraints and limited network bandwidth of the t...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	111,032
2312.13127	Pixel-to-Abundance Translation: Conditional Generative Adversarial Networks Based on Patch Transformer for Hyperspectral Unmixing	Spectral unmixing is a significant challenge in hyperspectral image processing. Existing unmixing methods utilize prior knowledge about the abundance distribution to solve the regularization optimization problem, where the difficulty lies in choosing appropriate prior knowledge and solving the complex regularization op...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,216
2306.10441	Image Harmonization with Diffusion Model	Image composition in image editing involves merging a foreground image with a background image to create a composite. Inconsistent lighting conditions between the foreground and background often result in unrealistic composites. Image harmonization addresses this challenge by adjusting illumination and color to achieve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	374,226
2204.05571	Speech Emotion Recognition with Global-Aware Fusion on Multi-scale Feature Representation	Speech Emotion Recognition (SER) is a fundamental task to predict the emotion label from speech data. Recent works mostly focus on using convolutional neural networks~(CNNs) to learn local attention map on fixed-scale feature representation by viewing time-varied spectral features as images. However, rich emotional fea...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	291,077
2303.01353	Penalising the biases in norm regularisation enforces sparsity	Controlling the parameters' norm often yields good generalisation when training neural networks. Beyond simple intuitions, the relation between regularising parameters' norm and obtained estimators remains theoretically misunderstood. For one hidden ReLU layer networks with unidimensional data, this work shows the para...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	348,939
1912.07358	Blind Denoising Autoencoder	The term blind denoising refers to the fact that the basis used for denoising is learnt from the noisy sample itself during denoising. Dictionary learning and transform learning based formulations for blind denoising are well known. But there has been no autoencoder based solution for the said blind denoising approach....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	157,584
2501.13080	Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment	Large Language Models (LLMs) have demonstrated powerful capabilities that render them valuable in different applications, including conversational AI products. It is paramount to ensure the security and reliability of these products by mitigating their vulnerabilities towards malicious user interactions, which can lead...	false	false	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	526,549
2206.11254	Langevin Monte Carlo for Contextual Bandits	We study the efficiency of Thompson sampling for contextual bandits. Existing Thompson sampling-based algorithms need to construct a Laplace approximation (i.e., a Gaussian distribution) of the posterior distribution, which is inefficient to sample in high dimensional applications for general covariance matrices. Moreo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	304,214
2202.04912	Random Forest Weighted Local Fr\'echet Regression with Random Objects	Statistical analysis is increasingly confronted with complex data from metric spaces. Petersen and M\"uller (2019) established a general paradigm of Fr\'echet regression with complex metric space valued responses and Euclidean predictors. However, the local approach therein involves nonparametric kernel smoothing and s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,713
2305.03610	The Role of Data Curation in Image Captioning	Image captioning models are typically trained by treating all samples equally, neglecting to account for mismatched or otherwise difficult data points. In contrast, recent work has shown the effectiveness of training models by scheduling the data using curriculum learning strategies. This paper contributes to this dire...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	362,455
2309.11445	SkeleTR: Towrads Skeleton-based Action Recognition in the Wild	We present SkeleTR, a new framework for skeleton-based action recognition. In contrast to prior work, which focuses mainly on controlled environments, we target more general scenarios that typically involve a variable number of people and various forms of interaction between people. SkeleTR works with a two-stage parad...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	393,409
2502.13474	Towards Lightweight, Adaptive and Attribute-Aware Multi-Aspect Controllable Text Generation with Large Language Models	Multi-aspect controllable text generation aims to control text generation in attributes from multiple aspects, making it a complex but powerful task in natural language processing. Supervised fine-tuning methods are often employed for this task due to their simplicity and effectiveness. However, they still have some li...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	535,381
2112.05660	DPU: DAG Processing Unit for Irregular Graphs with Precision-Scalable Posit Arithmetic in 28nm	Computation in several real-world applications like probabilistic machine learning, sparse linear algebra, and robotic navigation, can be modeled as irregular directed acyclic graphs (DAGs). The irregular data dependencies in DAGs pose challenges to parallel execution on general-purpose CPUs and GPUs, resulting in seve...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	270,914
2411.08253	Open-World Task and Motion Planning via Vision-Language Model Inferred Constraints	Foundation models trained on internet-scale data, such as Vision-Language Models (VLMs), excel at performing tasks involving common sense, such as visual question answering. Despite their impressive capabilities, these models cannot currently be directly applied to challenging robot manipulation problems that require c...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	507,820
2104.06650	Learning Semantic Person Image Generation by Region-Adaptive Normalization	Human pose transfer has received great attention due to its wide applications, yet is still a challenging task that is not well solved. Recent works have achieved great success to transfer the person image from the source to the target pose. However, most of them cannot well capture the semantic appearance, resulting i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	230,147
2403.06705	Multimodal Transformers for Real-Time Surgical Activity Prediction	Real-time recognition and prediction of surgical activities are fundamental to advancing safety and autonomy in robot-assisted surgery. This paper presents a multimodal transformer architecture for real-time recognition and prediction of surgical gestures and trajectories based on short segments of kinematic and video ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	436,571
2407.11788	Learning feasible transitions for efficient contact planning	In this paper, we propose an efficient contact planner for quadrupedal robots to navigate in extremely constrained environments such as stepping stones. The main difficulty in this setting stems from the mixed nature of the problem, namely discrete search over the steppable patches and continuous trajectory optimizatio...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	473,620
1801.06761	PU-Net: Point Cloud Upsampling Network	Learning and analyzing 3D point clouds with deep networks is challenging due to the sparseness and irregularity of the data. In this paper, we present a data-driven point cloud upsampling technique. The key idea is to learn multi-level features per point and expand the point set via a multi-branch convolution unit impl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	88,668
1904.07442	Decoupling Localization and Classification in Single Shot Temporal Action Detection	Video temporal action detection aims to temporally localize and recognize the action in untrimmed videos. Existing one-stage approaches mostly focus on unifying two subtasks, i.e., localization of action proposals and classification of each proposal through a fully shared backbone. However, such design of encapsulating...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	127,795
2410.17770	Small Singular Values Matter: A Random Matrix Analysis of Transformer Models	As large language models (LLMs) become increasingly central to AI applications, understanding their inner workings is essential. In this work, we analyze the spectra of weight matrices in pretrained transformer models through the lens of random matrix theory (RMT) to uncover learned structures. We find that certain reg...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	501,608
2208.03561	Study of detecting behavioral signatures within DeepFake videos	There is strong interest in the generation of synthetic video imagery of people talking for various purposes, including entertainment, communication, training, and advertisement. With the development of deep fake generation models, synthetic video imagery will soon be visually indistinguishable to the naked eye from a ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	311,822
2212.00268	Gaussian Process Barrier States for Safe Trajectory Optimization and Control	This paper proposes embedded Gaussian Process Barrier States (GP-BaS), a methodology to safely control unmodeled dynamics of nonlinear system using Bayesian learning. Gaussian Processes (GPs) are used to model the dynamics of the safety-critical system, which is subsequently used in the GP-BaS model. We derive the barr...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	333,997
1810.05045	Analysis of Noisy Evolutionary Optimization When Sampling Fails	In noisy evolutionary optimization, sampling is a common strategy to deal with noise. By the sampling strategy, the fitness of a solution is evaluated multiple times (called \emph{sample size}) independently, and its true fitness is then approximated by the average of these evaluations. Most previous studies on samplin...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	110,155
1907.02648	What is the Benefit of Code-domain NOMA in Massive MIMO?	In overloaded Massive MIMO systems, wherein the number K of user equipments (UEs) exceeds the number of base station antennas M, it has recently been shown that non-orthogonal multiple access (NOMA) can increase performance. This paper aims at identifying cases of the classical operating regime K < M, where code-domain...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	137,653
2103.04231	Quantum interpolating ensemble: Biorthogonal polynomials and average entropies	The density matrix formalism is a fundamental tool in studying various problems in quantum information processing. In the space of density matrices, the most well-known measures are the Hilbert-Schmidt and Bures-Hall ensembles. In this work, the averages of quantum purity and von Neumann entropy for an ensemble that in...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	223,563
1404.2071	Extracting a bilingual semantic grammar from FrameNet-annotated corpora	We present the creation of an English-Swedish FrameNet-based grammar in Grammatical Framework. The aim of this research is to make existing framenets computationally accessible for multilingual natural language applications via a common semantic grammar API, and to facilitate the porting of such grammar to other langua...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	32,174
2409.17550	A Simple but Strong Baseline for Sounding Video Generation: Effective Adaptation of Audio and Video Diffusion Models for Joint Generation	In this work, we build a simple but strong baseline for sounding video generation. Given base diffusion models for audio and video, we integrate them with additional modules into a single model and train it to make the model jointly generate audio and video. To enhance alignment between audio-video pairs, we introduce ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	491,862
2408.12133	Self-supervised Learning for Geospatial AI: A Survey	The proliferation of geospatial data in urban and territorial environments has significantly facilitated the development of geospatial artificial intelligence (GeoAI) across various urban applications. Given the vast yet inherently sparse labeled nature of geospatial data, there is a critical need for techniques that c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	482,604
1608.04694	Accelerating scientific codes by performance and accuracy modeling	Scientific software is often driven by multiple parameters that affect both accuracy and performance. Since finding the optimal configuration of these parameters is a highly complex task, it extremely common that the software is used suboptimally. In a typical scenario, accuracy requirements are imposed, and attained t...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	59,871
2208.04190	SA-NET.v2: Real-time vehicle detection from oblique UAV images with use of uncertainty estimation in deep meta-learning	In recent years, unmanned aerial vehicle (UAV) imaging is a suitable solution for real-time monitoring different vehicles on the urban scale. Real-time vehicle detection with the use of uncertainty estimation in deep meta-learning for the portable platforms (e.g., UAV) potentially improves video understanding in real-w...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	312,023
1508.07433	A General MIMO Framework for NOMA Downlink and Uplink Transmission Based on Signal Alignment	The application of multiple-input multiple-output (MIMO) techniques to non-orthogonal multiple access (NOMA) systems is important to enhance the performance gains of NOMA. In this paper, a novel MIMO-NOMA framework for downlink and uplink transmission is proposed by applying the concept of signal alignment. By using st...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	46,403
2310.11282	ChapGTP, ILLC's Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation	We present the submission of the ILLC at the University of Amsterdam to the BabyLM challenge (Warstadt et al., 2023), in the strict-small track. Our final model, ChapGTP, is a masked language model that was trained for 200 epochs, aided by a novel data augmentation technique called Automatic Task Formation. We discuss ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	400,584
2406.02506	An Open-Source Tool for Mapping War Destruction at Scale in Ukraine using Sentinel-1 Time Series	Access to detailed war impact assessments is crucial for humanitarian organizations to assist affected populations effectively. However, maintaining a comprehensive understanding of the situation on the ground is challenging, especially in widespread and prolonged conflicts. Here we present a scalable method for estima...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	460,796
1705.00487	Generalized orderless pooling performs implicit salient matching	Most recent CNN architectures use average pooling as a final feature encoding step. In the field of fine-grained recognition, however, recent global representations like bilinear pooling offer improved performance. In this paper, we generalize average and bilinear pooling to "alpha-pooling", allowing for learning the p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	72,692
2310.12556	An Efficient Algorithm for Counting Cycles in QC and APM LDPC Codes	In this paper, a new method is given for counting cycles in the Tanner graph of a (Type-I) quasi-cyclic (QC) low-density parity-check (LDPC) code which the complexity mainly is dependent on the base matrix, independent from the CPM-size of the constructed code. Interestingly, for large CPM-sizes, in comparison of the e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	401,067
2403.05801	Enhancing Multi-Hop Knowledge Graph Reasoning through Reward Shaping Techniques	In the realm of computational knowledge representation, Knowledge Graph Reasoning (KG-R) stands at the forefront of facilitating sophisticated inferential capabilities across multifarious domains. The quintessence of this research elucidates the employment of reinforcement learning (RL) strategies, notably the REINFORC...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	436,162
1507.01728	Equidistant subspace codes	In this paper we study equidistant subspace codes, i.e. subspace codes with the property that each two distinct codewords have the same distance. We provide an almost complete classification of such codes under the assumption that the cardinality of the ground field is large enough. More precisely, we prove that for mo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	44,900
2210.00221	Motion-inductive Self-supervised Object Discovery in Videos	In this paper, we consider the task of unsupervised object discovery in videos. Previous works have shown promising results via processing optical flows to segment objects. However, taking flow as input brings about two drawbacks. First, flow cannot capture sufficient cues when objects remain static or partially occlud...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	320,787
2407.08939	LightenDiffusion: Unsupervised Low-Light Image Enhancement with Latent-Retinex Diffusion Models	In this paper, we propose a diffusion-based unsupervised framework that incorporates physically explainable Retinex theory with diffusion models for low-light image enhancement, named LightenDiffusion. Specifically, we present a content-transfer decomposition network that performs Retinex decomposition within the laten...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,367
2406.01275	Lifting Factor Graphs with Some Unknown Factors	Lifting exploits symmetries in probabilistic graphical models by using a representative for indistinguishable objects, allowing to carry out query answering more efficiently while maintaining exact answers. In this paper, we investigate how lifting enables us to perform probabilistic inference for factor graphs contain...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	460,244
2401.09775	Controllable Decontextualization of Yes/No Question and Answers into Factual Statements	Yes/No or polar questions represent one of the main linguistic question categories. They consist of a main interrogative clause, for which the answer is binary (assertion or negation). Polar questions and answers (PQA) represent a valuable knowledge resource present in many community and other curated QA sources, such ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	422,381
2210.16118	Imitation Learning-based Implicit Semantic-aware Communication Networks: Multi-layer Representation and Collaborative Reasoning	Semantic communication has recently attracted significant interest from both industry and academia due to its potential to transform the existing data-focused communication architecture towards a more generally intelligent and goal-oriented semantic-aware networking system. Despite its promising potential, semantic com...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	true	327,231
2007.01272	RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces	We present RELATE, a model that learns to generate physically plausible scenes and videos of multiple interacting objects. Similar to other generative approaches, RELATE is trained end-to-end on raw, unlabeled data. RELATE combines an object-centric GAN formulation with a model that explicitly accounts for correlations...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	185,378
1104.0992	On the Degrees of Freedom Achievable Through Interference Alignment in a MIMO Interference Channel	Consider a K-user flat fading MIMO interference channel where the k-th transmitter (or receiver) is equipped with M_k (respectively N_k) antennas. If a large number of statistically independent channel extensions are allowed either across time or frequency, the recent work [1] suggests that the total achievable degrees...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,885
1706.01513	Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline	From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public healt...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	74,813
1408.2359	Gap-weighted subsequences for automatic cognate identification and phylogenetic inference	In this paper, we describe the problem of cognate identification and its relation to phylogenetic inference. We introduce subsequence based features for discriminating cognates from non-cognates. We show that subsequence based features perform better than the state-of-the-art string similarity measures for the purpose ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	35,292
2203.08213	HUMUS-Net: Hybrid unrolled multi-scale network architecture for accelerated MRI reconstruction	In accelerated MRI reconstruction, the anatomy of a patient is recovered from a set of under-sampled and noisy measurements. Deep learning approaches have been proven to be successful in solving this ill-posed inverse problem and are capable of producing very high quality reconstructions. However, current architectures...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	285,711
2408.05764	A robust baro-radar-inertial odometry m-estimator for multicopter navigation in cities and forests	Search and rescue operations require mobile robots to navigate unstructured indoor and outdoor environments. In particular, actively stabilized multirotor drones need precise movement data to balance and avoid obstacles. Combining radial velocities from on-chip radar with MEMS inertial sensing has proven to provide rob...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	479,926
1901.00952	Space Expansion of Feature Selection for Designing more Accurate Error Predictors	Approximate computing is being considered as a promising design paradigm to overcome the energy and performance challenges in computationally demanding applications. If the case where the accuracy can be configured, the quality level versus energy efficiency or delay also may be traded-off. For this technique to be use...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	117,886
1610.09638	Hybrid Analog and Digital Precoding: From Practical RF System Models to Information Theoretic Bounds	Hybrid analog-digital precoding is a key millimeter wave access technology, where an antenna array with reduced number of radio frequency (RF) chains is used with an RF precoding matrix to increase antenna gain at a reasonable cost. However, digital and RF precoder algorithms must be accompa- nied by a detailed system ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	63,095
2209.05156	Multiple Control Barrier Functions: An Application to Reactive Obstacle Avoidance for a Multi-steering Tractor-trailer System	Control barrier functions (CBFs) recently introduced a systematic way to guarantee the system's safety through set invariance. Together with a nominal control method, it establishes a safety-critical control mechanism. The resulting safety constraints can be enforced as hard constraints in quadratic programming (QP) op...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	317,013
2305.16791	On the Generalization and Approximation Capacities of Neural Controlled Differential Equations	Neural Controlled Differential Equations (NCDEs) are a state-of-the-art tool for supervised learning with irregularly sampled time series (Kidger, 2020). However, no theoretical analysis of their performance has been provided yet, and it remains unclear in particular how the irregularity of the time series affects thei...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	368,252
2302.02229	Entanglement capacity of fermionic Gaussian states	We study the capacity of entanglement as an alternative to entanglement entropies in estimating the degree of entanglement of quantum bipartite systems over fermionic Gaussian states. In particular, we derive the exact and asymptotic formulas of average capacity of two different cases - with and without particle number...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	343,912
2201.10436	Safe AI -- How is this Possible?	Ttraditional safety engineering is coming to a turning point moving from deterministic, non-evolving systems operating in well-defined contexts to increasingly autonomous and learning-enabled AI systems which are acting in largely unpredictable operating contexts. We outline some of underlying challenges of safe AI and...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	276,993
2006.05826	Transient Non-Stationarity and Generalisation in Deep Reinforcement Learning	Non-stationarity can arise in Reinforcement Learning (RL) even in stationary environments. For example, most RL algorithms collect new data throughout training, using a non-stationary behaviour policy. Due to the transience of this non-stationarity, it is often not explicitly addressed in deep RL and a single neural ne...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	181,211
2112.04042	Vision-Cloud Data Fusion for ADAS: A Lane Change Prediction Case Study	With the rapid development of intelligent vehicles and Advanced Driver-Assistance Systems (ADAS), a new trend is that mixed levels of human driver engagements will be involved in the transportation system. Therefore, necessary visual guidance for drivers is vitally important under this situation to prevent potential ri...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	270,403
2002.05227	Variational Autoencoders with Riemannian Brownian Motion Priors	Variational Autoencoders (VAEs) represent the given data in a low-dimensional latent space, which is generally assumed to be Euclidean. This assumption naturally leads to the common choice of a standard Gaussian prior over continuous latent variables. Recent work has, however, shown that this prior has a detrimental ef...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	163,834
2010.11807	Validation of non-negative matrix factorization for assessment of atomic pair-distribution function (PDF) data in a real-time streaming context	We validate the use of matrix factorization for the automatic identification of relevant components from atomic pair distribution function (PDF) data. We also present a newly developed software infrastructure for analyzing the PDF data arriving in streaming manner. We then apply two matrix factorization techniques, Pri...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,435
1903.09847	Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud	Monocular 3D scene understanding tasks, such as object size estimation, heading angle estimation and 3D localization, is challenging. Successful modern day methods for 3D scene understanding require the use of a 3D sensor. On the other hand, single image based methods have significantly worse performance. In this work,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	125,149
1803.04651	Compressive Sensing Based User Clustering for Downlink NOMA Systems with Decoding Power	This letter investigates joint power control and user clustering for downlink non-orthogonal multiple access systems. Our aim is to minimize the total power consumption by taking into account not only the conventional transmission power but also the decoding power of the users. To solve this optimization problem, it is...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	92,493
2409.16670	GraphLoRA: Structure-Aware Contrastive Low-Rank Adaptation for Cross-Graph Transfer Learning	Graph Neural Networks (GNNs) have demonstrated remarkable proficiency in handling a range of graph analytical tasks across various domains, such as e-commerce and social networks. Despite their versatility, GNNs face significant challenges in transferability, limiting their utility in real-world applications. Existing ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	491,450
1908.07553	Phrase Localization Without Paired Training Examples	Localizing phrases in images is an important part of image understanding and can be useful in many applications that require mappings between textual and visual information. Existing work attempts to learn these mappings from examples of phrase-image region correspondences (strong supervision) or from phrase-image pair...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	142,312
2411.13072	AMaze: An intuitive benchmark generator for fast prototyping of generalizable agents	Traditional approaches to training agents have generally involved a single, deterministic environment of minimal complexity to solve various tasks such as robot locomotion or computer vision. However, agents trained in static environments lack generalization capabilities, limiting their potential in broader scenarios. ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	509,666
1804.05259	Intrinsically motivated reinforcement learning for human-robot interaction in the real-world	For a natural social human-robot interaction, it is essential for a robot to learn the human-like social skills. However, learning such skills is notoriously hard due to the limited availability of direct instructions from people to teach a robot. In this paper, we propose an intrinsically motivated reinforcement learn...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	95,028
2207.09350	Riemannian Stochastic Gradient Method for Nested Composition Optimization	This work considers optimization of composition of functions in a nested form over Riemannian manifolds where each function contains an expectation. This type of problems is gaining popularity in applications such as policy evaluation in reinforcement learning or model customization in meta-learning. The standard Riema...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	308,877
1707.05154	Preliminary Exploration of Formula Embedding for Mathematical Information Retrieval: can mathematical formulae be embedded like a natural language?	While neural network approaches are achieving breakthrough performance in the natural language related fields, there have been few similar attempts at mathematical language related tasks. In this study, we explore the potential of applying neural representation techniques to Mathematical Information Retrieval (MIR) tas...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	77,175
1907.03564	Bounded Model Checking of Max-Plus Linear Systems via Predicate Abstractions	This paper introduces the abstraction of max-plus linear (MPL) systems via predicates. Predicates are automatically selected from system matrix, as well as from the specifications under consideration. We focus on verifying time-difference specifications, which encompass the relation between successive events in MPL sys...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	137,888
2401.16552	ONDA: ONline Database Architect	Database modeling is a key activity towards the fulfillment of storage requirements. Despite the availability of several database modeling tools for developers, these often come with associated costs, setup complexities, usability challenges, or dependency on specific operating systems. In this paper we present ONDA, a...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	424,871
2208.04803	Exploring the trade off between human driving imitation and safety for traffic simulation	Traffic simulation has gained a lot of interest for quantitative evaluation of self driving vehicles performance. In order for a simulator to be a valuable test bench, it is required that the driving policy animating each traffic agent in the scene acts as humans would do while maintaining minimal safety guarantees. Le...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	312,229
1906.07322	Whole-Body Control with (Self) Collision Avoidance using Vector Field Inequalities	This work uses vector field inequalities (VFI) to prevent robot self-collisions and collisions with the workspace. Differently from previous approaches, the method is suitable for both velocity and torque-actuated robots. We propose a new distance function and its corresponding Jacobian in order to generate a VFI to li...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	135,565
2301.06844	USER: Unified Semantic Enhancement with Momentum Contrast for Image-Text Retrieval	As a fundamental and challenging task in bridging language and vision domains, Image-Text Retrieval (ITR) aims at searching for the target instances that are semantically relevant to the given query from the other modality, and its key challenge is to measure the semantic similarity across different modalities. Althoug...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	340,754
1812.04429	Face-Focused Cross-Stream Network for Deception Detection in Videos	Automated deception detection (ADD) from real-life videos is a challenging task. It specifically needs to address two problems: (1) Both face and body contain useful cues regarding whether a subject is deceptive. How to effectively fuse the two is thus key to the effectiveness of an ADD model. (2) Real-life deceptive s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	116,219
2012.03902	Generative Adversarial User Privacy in Lossy Single-Server Information Retrieval	We propose to extend the concept of private information retrieval by allowing for distortion in the retrieval process and relaxing the perfect privacy requirement at the same time. In particular, we study the trade-off between download rate, distortion, and user privacy leakage, and show that in the limit of large file...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	210,294
2201.07657	Multiblock ADMM for nonsmooth nonconvex optimization with nonlinear coupling constraints	This paper proposes a multiblock alternating direction method of multipliers for solving a class of multiblock nonsmooth nonconvex optimization problem with nonlinear coupling constraints. We employ a majorization minimization procedure in the update of each block of the primal variables. Subsequential and global conve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	276,091
2112.13121	The Curse of Zero Task Diversity: On the Failure of Transfer Learning to Outperform MAML and their Empirical Equivalence	Recently, it has been observed that a transfer learning solution might be all we need to solve many few-shot learning benchmarks -- thus raising important questions about when and how meta-learning algorithms should be deployed. In this paper, we seek to clarify these questions by proposing a novel metric -- the divers...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	273,146
2403.17336	Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models	Recent advancements in generative AI have enabled ubiquitous access to large language models (LLMs). Empowered by their exceptional capabilities to understand and generate human-like text, these models are being increasingly integrated into our society. At the same time, there are also concerns on the potential misuse ...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	441,416
2406.13744	SRL-VIC: A Variable Stiffness-Based Safe Reinforcement Learning for Contact-Rich Robotic Tasks	Reinforcement learning (RL) has emerged as a promising paradigm in complex and continuous robotic tasks, however, safe exploration has been one of the main challenges, especially in contact-rich manipulation tasks in unstructured environments. Focusing on this issue, we propose SRL-VIC: a model-free safe RL framework c...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	465,982
1311.2903	Protocol Design and Stability Analysis of Cooperative Cognitive Radio Users	A single cognitive radio transmitter--receiver pair shares the spectrum with two primary users communicating with their respective receivers. Each primary user has a local traffic queue, whereas the cognitive user has three queues; one storing its own traffic while the other two are relaying queues used to store primar...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	28,365
2407.01126	Investigating the potential of Sparse Mixtures-of-Experts for multi-domain neural machine translation	We focus on multi-domain Neural Machine Translation, with the goal of developing efficient models which can handle data from various domains seen during training and are robust to domains unseen during training. We hypothesize that Sparse Mixture-of-Experts (SMoE) models are a good fit for this task, as they enable eff...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	469,164
2405.05369	Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory	Counterfactual explanations provide ways of achieving a favorable model outcome with minimum input perturbation. However, counterfactual explanations can also be leveraged to reconstruct the model by strategically training a surrogate model to give similar predictions as the original (target) model. In this work, we an...	false	false	false	false	false	false	true	false	false	true	false	false	true	true	false	false	false	false	452,891
2312.07609	IndoorGNN: A Graph Neural Network based approach for Indoor Localization using WiFi RSSI	Indoor localization is the process of determining the location of a person or object inside a building. Potential usage of indoor localization includes navigation, personalization, safety and security, and asset tracking. Commonly used technologies for indoor localization include WiFi, Bluetooth, RFID, and Ultra-wideba...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	414,994
2106.02775	Visual communication of object concepts at different levels of abstraction	People can produce drawings of specific entities (e.g., Garfield), as well as general categories (e.g., "cat"). What explains this ability to produce such varied drawings of even highly familiar object concepts? We hypothesized that drawing objects at different levels of abstraction depends on both sensory information ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	239,017
2408.01050	The Impact of Hyperparameters on Large Language Model Inference Performance: An Evaluation of vLLM and HuggingFace Pipelines	The recent surge of open-source large language models (LLMs) enables developers to create AI-based solutions while maintaining control over aspects such as privacy and compliance, thereby providing governance and ownership of the model deployment process. To utilize these LLMs, inference engines are needed. These engin...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	478,082
2412.07509	Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis	Autonomous Vehicles (AVs) use natural images and videos as input to understand the real world by overlaying and inferring digital elements, facilitating proactive detection in an effort to assure safety. A crucial aspect of this process is real-time, accurate object recognition through automatic scene analysis. While t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	515,693
1603.09382	Deep Networks with Stochastic Depth	Very deep convolutional networks with hundreds of layers have led to significant reductions in error on competitive benchmarks. Although the unmatched expressiveness of the many layers can be highly desirable at test time, training very deep networks comes with its own set of challenges. The gradients can vanish, the f...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	53,909
1407.2343	Fast Separable Non-Local Means	We propose a simple and fast algorithm called PatchLift for computing distances between patches (contiguous block of samples) extracted from a given one-dimensional signal. PatchLift is based on the observation that the patch distances can be efficiently computed from a matrix that is derived from the one-dimensional s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	34,518
2406.07328	Realistic Data Generation for 6D Pose Estimation of Surgical Instruments	Automation in surgical robotics has the potential to improve patient safety and surgical efficiency, but it is difficult to achieve due to the need for robust perception algorithms. In particular, 6D pose estimation of surgical instruments is critical to enable the automatic execution of surgical maneuvers based on vis...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	463,001
2210.07760	Lightweight Alpha Matting Network Using Distillation-Based Channel Pruning	Recently, alpha matting has received a lot of attention because of its usefulness in mobile applications such as selfies. Therefore, there has been a demand for a lightweight alpha matting model due to the limited computational resources of commercial portable devices. To this end, we suggest a distillation-based chann...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	323,853
2107.06749	Dynamic Event Camera Calibration	Camera calibration is an important prerequisite towards the solution of 3D computer vision problems. Traditional methods rely on static images of a calibration pattern. This raises interesting challenges towards the practical usage of event cameras, which notably require image change to produce sufficient measurements....	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	246,183
1907.10138	Reflective-AR Display: An Interaction Methodology for Virtual-Real Alignment in Medical Robotics	Robot-assisted minimally invasive surgery has shown to improve patient outcomes, as well as reduce complications and recovery time for several clinical applications. While increasingly configurable robotic arms can maximize reach and avoid collisions in cluttered environments, positioning them appropriately during surg...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	139,544
2203.03606	I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization	Graph Convolutional Networks (GCNs) have drawn tremendous attention in the past three years. Compared with other deep learning modalities, high-performance hardware acceleration of GCNs is as critical but even more challenging. The hurdles arise from the poor data locality and redundant computation due to the large siz...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	284,154
cmp-lg/9505038	Ubiquitous Talker: Spoken Language Interaction with Real World Objects	Augmented reality is a research area that tries to embody an electronic information space within the real world, through computational devices. A crucial issue within this area, is the recognition of real world objects or situations. In natural language processing, it is much easier to determine interpretations of ut...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,397
2406.11443	PrAViC: Probabilistic Adaptation Framework for Real-Time Video Classification	Video processing is generally divided into two main categories: processing of the entire video, which typically yields optimal classification outcomes, and real-time processing, where the objective is to make a decision as promptly as possible. The latter is often driven by the need to identify rapidly potential critic...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	464,894
1904.02679	Visualizing Attention in Transformer-Based Language Representation Models	We present an open-source tool for visualizing multi-head self-attention in Transformer-based language representation models. The tool extends earlier work by visualizing attention at three levels of granularity: the attention-head level, the model level, and the neuron level. We describe how each of these views can he...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,498
1706.00123	Diversified Top-k Partial MaxSAT Solving	We introduce a diversified top-k partial MaxSAT problem, a combination of partial MaxSAT problem and enumeration problem. Given a partial MaxSAT formula F and a positive integer k, the diversified top-k partial MaxSAT is to find k maximal solutions for F such that the k maximal solutions satisfy the maximum number of s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	74,567
1712.03898	Achieving Maximum Distance Separable Private Information Retrieval Capacity With Linear Codes	We propose three private information retrieval (PIR) protocols for distributed storage systems (DSSs) where data is stored using an arbitrary linear code. The first two protocols, named Protocol 1 and Protocol 2, achieve privacy for the scenario with noncolluding nodes. Protocol 1 requires a file size that is exponenti...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	86,516
2111.02212	Virtual reference feedback tuning with robustness constraints: A swarm intelligence solution	The simplified modeling of a complex system allied with a low-order controller structure can lead to poor closed-loop performance and robustness. A feasible solution is to avoid the necessity of a model by using data for the controller design. The Virtual Reference Feedback Tuning (VRFT) is a data-driven design method ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	264,803
2406.12536	ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection	With the rapid development of depth sensor, more and more RGB-D videos could be obtained. Identifying the foreground in RGB-D videos is a fundamental and important task. However, the existing salient object detection (SOD) works only focus on either static RGB-D images or RGB videos, ignoring the collaborating of RGB-D...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,453
1909.09569	Understanding Architectures Learnt by Cell-based Neural Architecture Search	Neural architecture search (NAS) searches architectures automatically for given tasks, e.g., image classification and language modeling. Improving the search efficiency and effectiveness have attracted increasing attention in recent years. However, few efforts have been devoted to understanding the generated architectu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	146,295

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