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
2409.00106	Zero-Shot Visual Reasoning by Vision-Language Models: Benchmarking and Analysis	Vision-language models (VLMs) have shown impressive zero- and few-shot performance on real-world visual question answering (VQA) benchmarks, alluding to their capabilities as visual reasoning engines. However, the benchmarks being used conflate "pure" visual reasoning with world knowledge, and also have questions that ...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	484,780
1609.06616	Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text	We compare policy differences across institutions by embedding representations of the entire legal corpus of each institution and the vocabulary shared across all corpora into a continuous vector space. We apply our method, Gov2Vec, to Supreme Court opinions, Presidential actions, and official summaries of Congressiona...	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	true	false	false	61,321
2103.11318	Language-Agnostic Representation Learning of Source Code from Structure and Context	Source code (Context) and its parsed abstract syntax tree (AST; Structure) are two complementary representations of the same computer program. Traditionally, designers of machine learning models have relied predominantly either on Structure or Context. We propose a new model, which jointly learns on Context and Structu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	225,760
2306.15762	Toward Mesh-Invariant 3D Generative Deep Learning with Geometric Measures	3D generative modeling is accelerating as the technology allowing the capture of geometric data is developing. However, the acquired data is often inconsistent, resulting in unregistered meshes or point clouds. Many generative learning algorithms require correspondence between each point when comparing the predicted sh...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	376,140
2109.05767	Computation Rate Maximum for Mobile Terminals in UAV-assisted Wireless Powered MEC Networks with Fairness Constraint	This paper investigates an unmanned aerial vehicle (UAV)-assisted wireless powered mobile-edge computing (MEC) system, where the UAV powers the mobile terminals by wireless power transfer (WPT) and provides computation service for them. We aim to maximize the computation rate of terminals while ensuring fairness among ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	254,935
2409.14262	GND: Global Navigation Dataset with Multi-Modal Perception and Multi-Category Traversability in Outdoor Campus Environments	Navigating large-scale outdoor environments requires complex reasoning in terms of geometric structures, environmental semantics, and terrain characteristics, which are typically captured by onboard sensors such as LiDAR and cameras. While current mobile robots can navigate such environments using pre-defined, high-pre...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	490,395
2303.11954	Bayesian Optimization for Function Compositions with Applications to Dynamic Pricing	Bayesian Optimization (BO) is used to find the global optima of black box functions. In this work, we propose a practical BO method of function compositions where the form of the composition is known but the constituent functions are expensive to evaluate. By assuming an independent Gaussian process (GP) model for each...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	353,082
0704.2644	Joint universal lossy coding and identification of stationary mixing sources	The problem of joint universal source coding and modeling, treated in the context of lossless codes by Rissanen, was recently generalized to fixed-rate lossy coding of finitely parametrized continuous-alphabet i.i.d. sources. We extend these results to variable-rate lossy block coding of stationary ergodic sources and ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	68
2309.08674	Fake News Detectors are Biased against Texts Generated by Large Language Models	The spread of fake news has emerged as a critical challenge, undermining trust and posing threats to society. In the era of Large Language Models (LLMs), the capability to generate believable fake content has intensified these concerns. In this study, we present a novel paradigm to evaluate fake news detectors in scena...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	392,278
1808.10705	Bayesian Classifier for Route Prediction with Markov Chains	We present here a general framework and a specific algorithm for predicting the destination, route, or more generally a pattern, of an ongoing journey, building on the recent work of [Y. Lassoued, J. Monteil, Y. Gu, G. Russo, R. Shorten, and M. Mevissen, "Hidden Markov model for route and destination prediction," in IE...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	106,435
2307.04323	Optimal $(2,\delta)$ Locally Repairable Codes via Punctured Simplex Codes	Locally repairable codes (LRCs) have attracted a lot of attention due to their applications in distributed storage systems. In this paper, we provide new constructions of optimal $(2, \delta)$-LRCs over $\mathbb{F}_q$ with flexible parameters. Firstly, employing techniques from finite geometry, we introduce a simple ye...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	378,358
1504.05369	Key-Pose Prediction in Cyclic Human Motion	In this paper we study the problem of estimating innercyclic time intervals within repetitive motion sequences of top-class swimmers in a swimming channel. Interval limits are given by temporal occurrences of key-poses, i.e. distinctive postures of the body. A key-pose is defined by means of only one or two specific fe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	42,262
2306.08818	Pragmatic Inference with a CLIP Listener for Contrastive Captioning	We propose a simple yet effective and robust method for contrastive captioning: generating discriminative captions that distinguish target images from very similar alternative distractor images. Our approach is built on a pragmatic inference procedure that formulates captioning as a reference game between a speaker, wh...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	373,555
2310.08817	Exploring the relationship between response time sequence in scale answering process and severity of insomnia: a machine learning approach	Objectives: The study aims to investigate the relationship between insomnia and response time. Additionally, it aims to develop a machine learning model to predict the presence of insomnia in participants using response time data. Methods: A mobile application was designed to administer scale tests and collect response...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	399,547
2103.10948	The Shape of Learning Curves: a Review	Learning curves provide insight into the dependence of a learner's generalization performance on the training set size. This important tool can be used for model selection, to predict the effect of more training data, and to reduce the computational complexity of model training and hyperparameter tuning. This review re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	225,612
1911.11679	The problem with DDPG: understanding failures in deterministic environments with sparse rewards	In environments with continuous state and action spaces, state-of-the-art actor-critic reinforcement learning algorithms can solve very complex problems, yet can also fail in environments that seem trivial, but the reason for such failures is still poorly understood. In this paper, we contribute a formal explanation of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,194
2303.14608	Analyzing Effects of Mixed Sample Data Augmentation on Model Interpretability	Data augmentation strategies are actively used when training deep neural networks (DNNs). Recent studies suggest that they are effective at various tasks. However, the effect of data augmentation on DNNs' interpretability is not yet widely investigated. In this paper, we explore the relationship between interpretabilit...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	354,168
2106.06041	Adversarial purification with Score-based generative models	While adversarial training is considered as a standard defense method against adversarial attacks for image classifiers, adversarial purification, which purifies attacked images into clean images with a standalone purification model, has shown promises as an alternative defense method. Recently, an Energy-Based Model (...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	240,324
2107.09070	Dim but not entirely dark: Extracting the Galactic Center Excess' source-count distribution with neural nets	The two leading hypotheses for the Galactic Center Excess (GCE) in the $\textit{Fermi}$ data are an unresolved population of faint millisecond pulsars (MSPs) and dark-matter (DM) annihilation. The dichotomy between these explanations is typically reflected by modeling them as two separate emission components. However, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	246,921
2210.09153	Face Pasting Attack	Cujo AI and Adversa AI hosted the MLSec face recognition challenge. The goal was to attack a black box face recognition model with targeted attacks. The model returned the confidence of the target class and a stealthiness score. For an attack to be considered successful the target class has to have the highest confiden...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	324,437
2305.03237	Out-of-Domain Intent Detection Considering Multi-Turn Dialogue Contexts	Out-of-Domain (OOD) intent detection is vital for practical dialogue systems, and it usually requires considering multi-turn dialogue contexts. However, most previous OOD intent detection approaches are limited to single dialogue turns. In this paper, we introduce a context-aware OOD intent detection (Caro) framework t...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	362,315
2101.02115	Adversarial Robustness by Design through Analog Computing and Synthetic Gradients	We propose a new defense mechanism against adversarial attacks inspired by an optical co-processor, providing robustness without compromising natural accuracy in both white-box and black-box settings. This hardware co-processor performs a nonlinear fixed random transformation, where the parameters are unknown and impos...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	214,529
1810.02501	High-Dimensional Poisson DAG Model Learning Using $\ell_1$-Regularized Regression	In this paper, we develop a new approach to learning high-dimensional Poisson directed acyclic graphical (DAG) models from only observational data without strong assumptions such as faithfulness and strong sparsity. A key component of our method is to decouple the ordering estimation or parent search where the problems...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,602
2312.06177	Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems	We propose a physics-informed machine learning method for uncertainty quantification in high-dimensional inverse problems. In this method, the states and parameters of partial differential equations (PDEs) are approximated with truncated conditional Karhunen-Lo\`eve expansions (CKLEs), which, by construction, match the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	414,407
2303.17611	Transformer-based Self-supervised Multimodal Representation Learning for Wearable Emotion Recognition	Recently, wearable emotion recognition based on peripheral physiological signals has drawn massive attention due to its less invasive nature and its applicability in real-life scenarios. However, how to effectively fuse multimodal data remains a challenging problem. Moreover, traditional fully-supervised based approach...	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	355,281
1910.14353	Transfer Learning from Transformers to Fake News Challenge Stance Detection (FNC-1) Task	In this paper, we report improved results of the Fake News Challenge Stage 1 (FNC-1) stance detection task. This gain in performance is due to the generalization power of large language models based on Transformer architecture, invented, trained and publicly released over the last two years. Specifically (1) we improve...	false	false	false	true	false	true	true	false	true	false	false	false	false	false	false	false	false	false	151,628
1810.04040	Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning	Person-Job Fit is the process of matching the right talent for the right job by identifying talent competencies that are required for the job. While many qualitative efforts have been made in related fields, it still lacks of quantitative ways of measuring talent competencies as well as the job's talent requirements. T...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	109,955
2011.01682	Cross-lingual Word Embeddings beyond Zero-shot Machine Translation	We explore the transferability of a multilingual neural machine translation model to unseen languages when the transfer is grounded solely on the cross-lingual word embeddings. Our experimental results show that the translation knowledge can transfer weakly to other languages and that the degree of transferability depe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	204,670
2401.12557	Balancing the AI Strength of Roles in Self-Play Training with Regret Matching+	When training artificial intelligence for games encompassing multiple roles, the development of a generalized model capable of controlling any character within the game presents a viable option. This strategy not only conserves computational resources and time during the training phase but also reduces resource require...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	423,425
1603.00295	Hybrid Feedback Path Following for Robotic Walkers via Bang-Bang Control Actions	We show a control algorithm to guide a robotic walking assistant along a planned path. The control strategy exploits the electromechanical brakes mounted on the back wheels of the walker. In order to reduce the hardware requirements we adopt a Bang Bang approach relying of four actions (with saturated value for the bra...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	52,763
2307.07378	Defect Classification in Additive Manufacturing Using CNN-Based Vision Processing	The development of computer vision and in-situ monitoring using visual sensors allows the collection of large datasets from the additive manufacturing (AM) process. Such datasets could be used with machine learning techniques to improve the quality of AM. This paper examines two scenarios: first, using convolutional ne...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	379,384
1909.10204	New Sets of Optimal Odd-length Binary Z-Complementary Pairs	A pair of sequences is called a Z-complementary pair (ZCP) if it has zero aperiodic autocorrelation sums (AACSs) for time-shifts within a certain region, called zero correlation zone (ZCZ). Optimal odd-length binary ZCPs (OB-ZCPs) display closest correlation properties to Golay complementary pairs (GCPs) in that each O...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	146,477
1312.6802	Suffix Stripping Problem as an Optimization Problem	Stemming or suffix stripping, an important part of the modern Information Retrieval systems, is to find the root word (stem) out of a given cluster of words. Existing algorithms targeting this problem have been developed in a haphazard manner. In this work, we model this problem as an optimization problem. An Integer P...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	29,400
2409.01502	AMG: Avatar Motion Guided Video Generation	Human video generation task has gained significant attention with the advancement of deep generative models. Generating realistic videos with human movements is challenging in nature, due to the intricacies of human body topology and sensitivity to visual artifacts. The extensively studied 2D media generation methods t...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	485,357
2010.10600	Misleading Repurposing on Twitter	We present the first in-depth and large-scale study of misleading repurposing, in which a malicious user changes the identity of their social media account via, among other things, changes to the profile attributes in order to use the account for a new purpose while retaining their followers. We propose a definition fo...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	201,926
2107.04226	Multi-path Convolutional Neural Networks Efficiently Improve Feature Extraction in Continuous Adventitious Lung Sound Detection	We previously established a large lung sound database, HF_Lung_V2 (Lung_V2). We trained convolutional-bidirectional gated recurrent unit (CNN-BiGRU) networks for detecting inhalation, exhalation, continuous adventitious sound (CAS) and discontinuous adventitious sound at the recording level on the basis of Lung_V2. How...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	245,389
2011.00826	PV-NAS: Practical Neural Architecture Search for Video Recognition	Recently, deep learning has been utilized to solve video recognition problem due to its prominent representation ability. Deep neural networks for video tasks is highly customized and the design of such networks requires domain experts and costly trial and error tests. Recent advance in network architecture search has ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	204,390
2205.13857	TrackNet: A Triplet metric-based method for Multi-Target Multi-Camera Vehicle Tracking	We present TrackNet, a method for Multi-Target Multi-Camera (MTMC) vehicle tracking from traffic video sequences. Cross-camera vehicle tracking has proved to be a challenging task due to perspective, scale and speed variance, as well occlusions and noise conditions. Our method is based on a modular approach that first ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	299,117
2405.01614	A probabilistic estimation of remaining useful life from censored time-to-event data	Predicting the remaining useful life (RUL) of ball bearings plays an important role in predictive maintenance. A common definition of the RUL is the time until a bearing is no longer functional, which we denote as an event, and many data-driven methods have been proposed to predict the RUL. However, few studies have ad...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	451,436
2312.01999	SRTransGAN: Image Super-Resolution using Transformer based Generative Adversarial Network	Image super-resolution aims to synthesize high-resolution image from a low-resolution image. It is an active area to overcome the resolution limitations in several applications like low-resolution object-recognition, medical image enhancement, etc. The generative adversarial network (GAN) based methods have been the st...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,655
1803.07278	Text Detection and Recognition in images: A survey	Text Detection and recognition is a one of the important aspect of image processing. This paper analyzes and compares the methods to handle this task. It summarizes the fundamental problems and enumerates factors that need consideration when addressing these problems. Existing techniques are categorized as either stepw...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,005
2211.01573	Resource Allocation in MIMO setup	In a multi-input multi-output (MIMO) setup, where one side of the link comprises a linear antenna array, data can be transmitted over the direction of incident rays. Channel capacity for this setup is studied in this paper. We define two different setups; one when the energy is constant and equal over all rays, and one...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	328,274
2408.14469	Grounded Multi-Hop VideoQA in Long-Form Egocentric Videos	This paper considers the problem of Multi-Hop Video Question Answering (MH-VidQA) in long-form egocentric videos. This task not only requires to answer visual questions, but also to localize multiple relevant time intervals within the video as visual evidences. We develop an automated pipeline to create multi-hop quest...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	483,546
2105.06643	Monash Time Series Forecasting Archive	Many businesses and industries nowadays rely on large quantities of time series data making time series forecasting an important research area. Global forecasting models that are trained across sets of time series have shown a huge potential in providing accurate forecasts compared with the traditional univariate forec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	235,189
2403.19844	Expanding Chemical Representation with k-mers and Fragment-based Fingerprints for Molecular Fingerprinting	This study introduces a novel approach, combining substruct counting, $k$-mers, and Daylight-like fingerprints, to expand the representation of chemical structures in SMILES strings. The integrated method generates comprehensive molecular embeddings that enhance discriminative power and information content. Experimenta...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	442,493
2502.04407	Illuminating Spaces: Deep Reinforcement Learning and Laser-Wall Partitioning for Architectural Layout Generation	Space layout design (SLD), occurring in the early stages of the design process, nonetheless influences both the functionality and aesthetics of the ultimate architectural outcome. The complexity of SLD necessitates innovative approaches to efficiently explore vast solution spaces. While image-based generative AI has em...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	531,145
2306.06376	Enjoy the Silence: Analysis of Stochastic Petri Nets with Silent Transitions	Capturing stochastic behaviors in business and work processes is essential to quantitatively understand how nondeterminism is resolved when taking decisions within the process. This is of special interest in process mining, where event data tracking the actual execution of the process are related to process models, and...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	372,580
2409.08181	Enhancing Canine Musculoskeletal Diagnoses: Leveraging Synthetic Image Data for Pre-Training AI-Models on Visual Documentations	The examination of the musculoskeletal system in dogs is a challenging task in veterinary practice. In this work, a novel method has been developed that enables efficient documentation of a dog's condition through a visual representation. However, since the visual documentation is new, there is no existing training dat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,800
1510.01077	Nonlinear Spectral Analysis via One-homogeneous Functionals - Overview and Future Prospects	We present in this paper the motivation and theory of nonlinear spectral representations, based on convex regularizing functionals. Some comparisons and analogies are drawn to the fields of signal processing, harmonic analysis and sparse representations. The basic approach, main results and initial applications are sho...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	47,577
2211.00112	Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Bandits	We study the problem of planning restless multi-armed bandits (RMABs) with multiple actions. This is a popular model for multi-agent systems with applications like multi-channel communication, monitoring and machine maintenance tasks, and healthcare. Whittle index policies, which are based on Lagrangian relaxations, ar...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	327,759
2308.13392	Self-Supervised Representation Learning with Cross-Context Learning between Global and Hypercolumn Features	Whilst contrastive learning yields powerful representations by matching different augmented views of the same instance, it lacks the ability to capture the similarities between different instances. One popular way to address this limitation is by learning global features (after the global pooling) to capture inter-inst...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,900
2103.14703	Model-Free Optimal Voltage Control via Continuous-Time Zeroth-Order Methods	In power distribution systems, the growing penetration of renewable energy resources brings new challenges to maintaining voltage safety, which is further complicated by the limited model information of distribution systems. To address these challenges, we develop a model-free optimal voltage control algorithm based on...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	226,941
2303.09800	GOOD: General Optimization-based Fusion for 3D Object Detection via LiDAR-Camera Object Candidates	3D object detection serves as the core basis of the perception tasks in autonomous driving. Recent years have seen the rapid progress of multi-modal fusion strategies for more robust and accurate 3D object detection. However, current researches for robust fusion are all learning-based frameworks, which demand a large a...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	352,195
2401.15235	CascadedGaze: Efficiency in Global Context Extraction for Image Restoration	Image restoration tasks traditionally rely on convolutional neural networks. However, given the local nature of the convolutional operator, they struggle to capture global information. The promise of attention mechanisms in Transformers is to circumvent this problem, but it comes at the cost of intensive computational ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	424,363
2104.06585	A Novel Generalised Meta-Heuristic Framework for Dynamic Capacitated Arc Routing Problems	The capacitated arc routing problem (CARP) is a challenging combinatorial optimisation problem abstracted from many real-world applications, such as waste collection, road gritting and mail delivery. However, few studies considered dynamic changes during the vehicles' service, which can cause the original schedule infe...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	230,119
2501.15090	Speech Translation Refinement using Large Language Models	Recent advancements in large language models (LLMs) have demonstrated their remarkable capabilities across various language tasks. Inspired by the success of text-to-text translation refinement, this paper investigates how LLMs can improve the performance of speech translation by introducing a joint refinement process....	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	527,402
2204.03610	Unified Contrastive Learning in Image-Text-Label Space	Visual recognition is recently learned via either supervised learning on human-annotated image-label data or language-image contrastive learning with webly-crawled image-text pairs. While supervised learning may result in a more discriminative representation, language-image pretraining shows unprecedented zero-shot rec...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	290,367
2409.12140	MoRAG -- Multi-Fusion Retrieval Augmented Generation for Human Motion	We introduce MoRAG, a novel multi-part fusion based retrieval-augmented generation strategy for text-based human motion generation. The method enhances motion diffusion models by leveraging additional knowledge obtained through an improved motion retrieval process. By effectively prompting large language models (LLMs),...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	489,454
1808.02733	Debugging Neural Machine Translations	In this paper, we describe a tool for debugging the output and attention weights of neural machine translation (NMT) systems and for improved estimations of confidence about the output based on the attention. The purpose of the tool is to help researchers and developers find weak and faulty example translations that th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	104,820
2103.01306	Scalable Scene Flow from Point Clouds in the Real World	Autonomous vehicles operate in highly dynamic environments necessitating an accurate assessment of which aspects of a scene are moving and where they are moving to. A popular approach to 3D motion estimation, termed scene flow, is to employ 3D point cloud data from consecutive LiDAR scans, although such approaches have...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	222,574
1502.02558	K2-ABC: Approximate Bayesian Computation with Kernel Embeddings	Complicated generative models often result in a situation where computing the likelihood of observed data is intractable, while simulating from the conditional density given a parameter value is relatively easy. Approximate Bayesian Computation (ABC) is a paradigm that enables simulation-based posterior inference in su...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	40,058
2410.20475	Optimal Hardening Strategy for Electricity-Hydrogen Networks with Hydrogen Leakage Risk Control against Extreme Weather	Defense hardening can effectively enhance the resilience of distribution networks against extreme weather disasters. Currently, most existing hardening strategies focus on reducing load shedding. However, for electricity-hydrogen distribution networks (EHDNs), the leakage risk of hydrogen should be controlled to avoid ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	502,827
1603.03236	Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation	Optimization on manifolds is a class of methods for optimization of an objective function, subject to constraints which are smooth, in the sense that the set of points which satisfy the constraints admits the structure of a differentiable manifold. While many optimization problems are of the described form, technicalit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	53,096
2407.12451	Across Platforms and Languages: Dutch Influencers and Legal Disclosures on Instagram, YouTube and TikTok	Content monetization on social media fuels a growing influencer economy. Influencer marketing remains largely undisclosed or inappropriately disclosed on social media. Non-disclosure issues have become a priority for national and supranational authorities worldwide, who are starting to impose increasingly harsher sanct...	false	false	false	true	false	false	false	false	true	false	false	false	false	true	false	false	false	false	473,937
2310.10467	Stance Detection with Collaborative Role-Infused LLM-Based Agents	Stance detection automatically detects the stance in a text towards a target, vital for content analysis in web and social media research. Despite their promising capabilities, LLMs encounter challenges when directly applied to stance detection. First, stance detection demands multi-aspect knowledge, from deciphering e...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	400,237
2202.13072	Adversarial Contrastive Self-Supervised Learning	Recently, learning from vast unlabeled data, especially self-supervised learning, has been emerging and attracted widespread attention. Self-supervised learning followed by the supervised fine-tuning on a few labeled examples can significantly improve label efficiency and outperform standard supervised training using f...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	282,469
2002.05545	Sampling and Update Frequencies in Proximal Variance-Reduced Stochastic Gradient Methods	Variance-reduced stochastic gradient methods have gained popularity in recent times. Several variants exist with different strategies for the storing and sampling of gradients and this work concerns the interactions between these two aspects. We present a general proximal variance-reduced gradient method and analyze it...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	163,935
2008.03655	Global Optimum Search in Quantum Deep Learning	This paper aims to solve machine learning optimization problem by using quantum circuit. Two approaches, namely the average approach and the Partial Swap Test Cut-off method (PSTC) was proposed to search for the global minimum/maximum of two different objective functions. The current cost is $O(\sqrt{\|\Theta\|} N)$, but...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	190,984
2202.02666	Simulation-to-Reality domain adaptation for offline 3D object annotation on pointclouds with correlation alignment	Annotating objects with 3D bounding boxes in LiDAR pointclouds is a costly human driven process in an autonomous driving perception system. In this paper, we present a method to semi-automatically annotate real-world pointclouds collected by deployment vehicles using simulated data. We train a 3D object detector model ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	278,900
2309.14145	Feedback Increases the Capacity of Queues with Bounded Service Times	In the "Bits Through Queues" paper, it was hypothesized that full feedback always increases the capacity of first-in-first-out queues, except when the service time distribution is memoryless. More recently, a non-explicit sufficient condition under which feedback increases capacity was provided, along with simple examp...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	394,484
2209.04439	Improved Masked Image Generation with Token-Critic	Non-autoregressive generative transformers recently demonstrated impressive image generation performance, and orders of magnitude faster sampling than their autoregressive counterparts. However, optimal parallel sampling from the true joint distribution of visual tokens remains an open challenge. In this paper we intro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	316,785
2105.06361	Forensic Analysis of Video Files Using Metadata	The unprecedented ease and ability to manipulate video content has led to a rapid spread of manipulated media. The availability of video editing tools greatly increased in recent years, allowing one to easily generate photo-realistic alterations. Such manipulations can leave traces in the metadata embedded in video fil...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	235,101
2111.03290	Maillard Sampling: Boltzmann Exploration Done Optimally	The PhD thesis of Maillard (2013) presents a rather obscure algorithm for the $K$-armed bandit problem. This less-known algorithm, which we call Maillard sampling (MS), computes the probability of choosing each arm in a \textit{closed form}, which is not true for Thompson sampling, a widely-adopted bandit algorithm in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,121
2410.03090	UNComp: Uncertainty-Aware Long-Context Compressor for Efficient Large Language Model Inference	Deploying large language models (LLMs) is challenging due to their high memory and computational demands, especially during long-context inference. While key-value (KV) caching accelerates inference by reusing previously computed keys and values, it also introduces significant memory overhead. Existing KV cache compres...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	494,614
2303.16948	Cooperative Lane Changing in Mixed Traffic can be Robust to Human Driver Behavior	We derive time and energy-optimal control policies for a Connected Autonomous Vehicle (CAV) to complete lane change maneuvers in mixed traffic. The interaction between CAVs and Human-Driven Vehicles (HDVs) requires designing the best possible response of a CAV to actions by its neighboring HDVs. This interaction is for...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	355,049
1708.01938	A Framework for Visually Realistic Multi-robot Simulation in Natural Environment	This paper presents a generalized framework for the simulation of multiple robots and drones in highly realistic models of natural environments. The proposed simulation architecture uses the Unreal Engine4 for generating both optical and depth sensor outputs from any position and orientation within the environment and ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	78,488
2305.11901	Long-lead forecasts of wintertime air stagnation index in southern China using oceanic memory effects	Stagnant weather condition is one of the major contributors to air pollution as it is favorable for the formation and accumulation of pollutants. To measure the atmosphere's ability to dilute air pollutants, Air Stagnation Index (ASI) has been introduced as an important meteorological index. Therefore, making long-lead...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	365,747
2408.10620	Fast Grid Emissions Sensitivities using Parallel Decentralized Implicit Differentiation	Marginal emissions rates -- the sensitivity of carbon emissions to electricity demand -- are important for evaluating the impact of emissions mitigation measures. Like locational marginal prices, locational marginal emissions rates (LMEs) can vary geographically, even between nearby locations, and may be coupled across...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	481,944
2101.00939	CRSLab: An Open-Source Toolkit for Building Conversational Recommender System	In recent years, conversational recommender system (CRS) has received much attention in the research community. However, existing studies on CRS vary in scenarios, goals and techniques, lacking unified, standardized implementation or comparison. To tackle this challenge, we propose an open-source CRS toolkit CRSLab, wh...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	214,241
2210.10276	CLIP-Driven Fine-grained Text-Image Person Re-identification	TIReID aims to retrieve the image corresponding to the given text query from a pool of candidate images. Existing methods employ prior knowledge from single-modality pre-training to facilitate learning, but lack multi-modal correspondences. Besides, due to the substantial gap between modalities, existing methods embed ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	324,857
2211.05929	Structured Singular Value of a Repeated Complex Full-Block Uncertainty	The structured singular value (SSV), or mu, is used to assess the robust stability and performance of an uncertain linear time-invariant system. Existing algorithms compute upper and lower bounds on the SSV for structured uncertainties that contain repeated (real or complex) scalars and/or non-repeated complex full blo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	329,711
2410.19855	Personalized Recommendation Systems using Multimodal, Autonomous, Multi Agent Systems	This paper describes a highly developed personalised recommendation system using multimodal, autonomous, multi-agent systems. The system focuses on the incorporation of futuristic AI tech and LLMs like Gemini-1.5- pro and LLaMA-70B to improve customer service experiences especially within e-commerce. Our approach uses ...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	true	false	false	false	502,532
2310.08233	The Impact of Time Step Frequency on the Realism of Robotic Manipulation Simulation for Objects of Different Scales	This work evaluates the impact of time step frequency and component scale on robotic manipulation simulation accuracy. Increasing the time step frequency for small-scale objects is shown to improve simulation accuracy. This simulation, demonstrating pre-assembly part picking for two object geometries, serves as a start...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	399,319
2105.11259	PTR: Prompt Tuning with Rules for Text Classification	Fine-tuned pre-trained language models (PLMs) have achieved awesome performance on almost all NLP tasks. By using additional prompts to fine-tune PLMs, we can further stimulate the rich knowledge distributed in PLMs to better serve downstream tasks. Prompt tuning has achieved promising results on some few-class classif...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	236,641
2310.04431	Can neural networks count digit frequency?	In this research, we aim to compare the performance of different classical machine learning models and neural networks in identifying the frequency of occurrence of each digit in a given number. It has various applications in machine learning and computer vision, e.g. for obtaining the frequency of a target object in a...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	397,648
1604.06083	Automatic Graphic Logo Detection via Fast Region-based Convolutional Networks	Brand recognition is a very challenging topic with many useful applications in localization recognition, advertisement and marketing. In this paper we present an automatic graphic logo detection system that robustly handles unconstrained imaging conditions. Our approach is based on Fast Region-based Convolutional Netwo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,895
1711.03726	Saliency Prediction for Mobile User Interfaces	We introduce models for saliency prediction for mobile user interfaces. A mobile interface may include elements like buttons, text, etc. in addition to natural images which enable performing a variety of tasks. Saliency in natural images is a well studied area. However, given the difference in what constitutes a mobile...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	84,269
2012.12101	Estimating Crop Primary Productivity with Sentinel-2 and Landsat 8 using Machine Learning Methods Trained with Radiative Transfer Simulations	Satellite remote sensing has been widely used in the last decades for agricultural applications, {both for assessing vegetation condition and for subsequent yield prediction.} Existing remote sensing-based methods to estimate gross primary productivity (GPP), which is an important variable to indicate crop photosynthet...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	212,823
2203.16910	End-to-End Trajectory Distribution Prediction Based on Occupancy Grid Maps	In this paper, we aim to forecast a future trajectory distribution of a moving agent in the real world, given the social scene images and historical trajectories. Yet, it is a challenging task because the ground-truth distribution is unknown and unobservable, while only one of its samples can be applied for supervising...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	288,969
2407.09285	MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results	The increasing interest in computer vision applications for nutrition and dietary monitoring has led to the development of advanced 3D reconstruction techniques for food items. However, the scarcity of high-quality data and limited collaboration between industry and academia have constrained progress in this field. Bui...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,519
2411.14627	Generative AI for Music and Audio	Generative AI has been transforming the way we interact with technology and consume content. In the next decade, AI technology will reshape how we create audio content in various media, including music, theater, films, games, podcasts, and short videos. In this dissertation, I introduce the three main directions of my ...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	510,252
2403.02473	When do Convolutional Neural Networks Stop Learning?	Convolutional Neural Networks (CNNs) have demonstrated outstanding performance in computer vision tasks such as image classification, detection, segmentation, and medical image analysis. In general, an arbitrary number of epochs is used to train such neural networks. In a single epoch, the entire training data -- divid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	434,812
2412.16114	The Content Moderator's Dilemma: Removal of Toxic Content and Distortions to Online Discourse	There is an ongoing debate about how to moderate toxic speech on social media and how content moderation affects online discourse. We propose and validate a methodology for measuring the content-moderation-induced distortions in online discourse using text embeddings from computational linguistics. We test our measure ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	519,362
2008.09748	Multidomain Multimodal Fusion For Human Action Recognition Using Inertial Sensors	One of the major reasons for misclassification of multiplex actions during action recognition is the unavailability of complementary features that provide the semantic information about the actions. In different domains these features are present with different scales and intensities. In existing literature, features a...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	192,811
2405.05678	Beyond Prompts: Learning from Human Communication for Enhanced AI Intent Alignment	AI intent alignment, ensuring that AI produces outcomes as intended by users, is a critical challenge in human-AI interaction. The emergence of generative AI, including LLMs, has intensified the significance of this problem, as interactions increasingly involve users specifying desired results for AI systems. In order ...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	453,017
0712.4103	On the Monotonicity of the Generalized Marcum and Nuttall Q-Functions	Monotonicity criteria are established for the generalized Marcum Q-function, $\emph{Q}_{M}$, the standard Nuttall Q-function, $\emph{Q}_{M,N}$, and the normalized Nuttall Q-function, $\mathcal{Q}_{M,N}$, with respect to their real order indices M,N. Besides, closed-form expressions are derived for the computation of th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,085
2409.14327	Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining	This paper introduces a novel spatiotemporal feature representation model designed to address the limitations of traditional methods in multidimensional time series (MTS) analysis. The proposed approach converts MTS into one-dimensional sequences of spatially evolving events, preserving the complex coupling relationshi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	490,424
2010.01662	Learning from Home: A Mixed-Methods Analysis of Live Streaming Based Remote Education Experience in Chinese Colleges During the COVID-19 Pandemic	The COVID-19 global pandemic and resulted lockdown policies have forced education in nearly every country to switch from a traditional co-located paradigm to a pure online 'distance learning from home' paradigm. Lying in the center of this learning paradigm shift is the emergence and wide adoption of distance communica...	true	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	198,729
2412.10288	Performance evaluation of predictive AI models to support medical decisions: Overview and guidance	A myriad of measures to illustrate performance of predictive artificial intelligence (AI) models have been proposed in the literature. Selecting appropriate performance measures is essential for predictive AI models that are developed to be used in medical practice, because poorly performing models may harm patients an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	516,857
2302.00845	Coordinating Distributed Example Orders for Provably Accelerated Training	Recent research on online Gradient Balancing (GraB) has revealed that there exist permutation-based example orderings for SGD that are guaranteed to outperform random reshuffling (RR). Whereas RR arbitrarily permutes training examples, GraB leverages stale gradients from prior epochs to order examples -- achieving a pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	343,367

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