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
2411.09410	LLM-assisted Explicit and Implicit Multi-interest Learning Framework for Sequential Recommendation	Multi-interest modeling in current recommender systems (RS) is mainly based on user behavioral data, capturing user interest preferences from multiple dimensions. However, since behavioral data is implicit and often highly sparse, it is challenging to understand users' complex and diverse interests. Recent studies have...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	508,237
2405.16542	Mamba4KT:An Efficient and Effective Mamba-based Knowledge Tracing Model	Knowledge tracing (KT) enhances student learning by leveraging past performance to predict future performance. Current research utilizes models based on attention mechanisms and recurrent neural network structures to capture long-term dependencies and correlations between exercises, aiming to improve model accuracy. Du...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	457,480
2405.06227	MaskMatch: Boosting Semi-Supervised Learning Through Mask Autoencoder-Driven Feature Learning	Conventional methods in semi-supervised learning (SSL) often face challenges related to limited data utilization, mainly due to their reliance on threshold-based techniques for selecting high-confidence unlabeled data during training. Various efforts (e.g., FreeMatch) have been made to enhance data utilization by tweak...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	453,218
1808.06509	Optimized Rate-Adaptive Protograph-Based LDPC Codes for Source Coding with Side Information	This paper considers the problem of source coding with side information at the decoder, also called Slepian-Wolf source coding scheme. In practical applications of this coding scheme, the statistical relation between the source and the side information can vary from one data transmission to another, and there is a need...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	105,547
1812.11485	Partially Non-Recurrent Controllers for Memory-Augmented Neural Networks	Memory-Augmented Neural Networks (MANNs) are a class of neural networks equipped with an external memory, and are reported to be effective for tasks requiring a large long-term memory and its selective use. The core module of a MANN is called a controller, which is usually implemented as a recurrent neural network (RNN...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	117,574
2405.05187	A score-based particle method for homogeneous Landau equation	We propose a novel score-based particle method for solving the Landau equation in plasmas, that seamlessly integrates learning with structure-preserving particle methods [arXiv:1910.03080]. Building upon the Lagrangian viewpoint of the Landau equation, a central challenge stems from the nonlinear dependence of the velo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	452,827
2210.06728	On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood	We provide an efficient unified plug-in approach for estimating symmetric properties of distributions given $n$ independent samples. Our estimator is based on profile-maximum-likelihood (PML) and is sample optimal for estimating various symmetric properties when the estimation error $\epsilon \gg n^{-1/3}$. This result...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	323,417
2202.07021	QuadSim: A Quadcopter Rotational Dynamics Simulation Framework For Reinforcement Learning Algorithms	This study focuses on designing and developing a mathematically based quadcopter rotational dynamics simulation framework for testing reinforcement learning (RL) algorithms in many flexible configurations. The design of the simulation framework aims to simulate both linear and nonlinear representations of a quadcopter ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	280,398
2307.08104	Using Decision Trees for Interpretable Supervised Clustering	In this paper, we address an issue of finding explainable clusters of class-uniform data in labelled datasets. The issue falls into the domain of interpretable supervised clustering. Unlike traditional clustering, supervised clustering aims at forming clusters of labelled data with high probability densities. We are pa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	379,673
1710.08500	Are Multiagent Systems Resilient to Communication Failures?	A challenge in multiagent control systems is to ensure that they are appropriately resilient to communication failures between the various agents. In many common game-theoretic formulations of these types of systems, it is implicitly assumed that all agents have access to as much information about other agents' actions...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	true	83,086
2303.05780	TAKT: Target-Aware Knowledge Transfer for Whole Slide Image Classification	Transferring knowledge from a source domain to a target domain can be crucial for whole slide image classification, since the number of samples in a dataset is often limited due to high annotation costs. However, domain shift and task discrepancy between datasets can hinder effective knowledge transfer. In this paper, ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	350,600
2412.03055	Real-Time AIoT for UAV Antenna Interference Detection via Edge-Cloud Collaboration	In the fifth-generation (5G) era, eliminating communication interference sources is crucial for maintaining network performance. Interference often originates from unauthorized or malfunctioning antennas, and radio monitoring agencies must address numerous sources of such antennas annually. Unmanned aerial vehicles (UA...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,795
2103.00919	Computing the sampling performance of event-triggered control	In the context of networked control systems, event-triggered control (ETC) has emerged as a major topic due to its alleged resource usage reduction capabilities. However, this is mainly supported by numerical simulations, and very little is formally known about the traffic generated by ETC. This work devises a method t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	222,452
2206.11484	Towards WinoQueer: Developing a Benchmark for Anti-Queer Bias in Large Language Models	This paper presents exploratory work on whether and to what extent biases against queer and trans people are encoded in large language models (LLMs) such as BERT. We also propose a method for reducing these biases in downstream tasks: finetuning the models on data written by and/or about queer people. To measure anti-q...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	304,280
1702.00764	Symbolic, Distributed and Distributional Representations for Natural Language Processing in the Era of Deep Learning: a Survey	Natural language is inherently a discrete symbolic representation of human knowledge. Recent advances in machine learning (ML) and in natural language processing (NLP) seem to contradict the above intuition: discrete symbols are fading away, erased by vectors or tensors called distributed and distributional representat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	67,703
2407.18900	How Polarized are Online Conversations about Childhood?	2020 through 2023 were unusually tumultuous years for children in the United States, and children's welfare was prominent in political debate. Theories in moral psychology suggest that political parties would treat concerns for children using different moral frames, and that moral conflict might drive substantial polar...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	476,555
2409.13410	Sine Wave Normalization for Deep Learning-Based Tumor Segmentation in CT/PET Imaging	This report presents a normalization block for automated tumor segmentation in CT/PET scans, developed for the autoPET III Challenge. The key innovation is the introduction of the SineNormal, which applies periodic sine transformations to PET data to enhance lesion detection. By highlighting intensity variations and pr...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	489,982
2311.09748	Translation Aligned Sentence Embeddings for Turkish Language	Due to the limited availability of high quality datasets for training sentence embeddings in Turkish, we propose a training methodology and a regimen to develop a sentence embedding model. The central idea is simple but effective : is to fine-tune a pretrained encoder-decoder model in two consecutive stages, where the ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	408,274
2501.03937	A precise asymptotic analysis of learning diffusion models: theory and insights	In this manuscript, we consider the problem of learning a flow or diffusion-based generative model parametrized by a two-layer auto-encoder, trained with online stochastic gradient descent, on a high-dimensional target density with an underlying low-dimensional manifold structure. We derive a tight asymptotic character...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	523,047
2009.07635	The FaceChannel: A Fast & Furious Deep Neural Network for Facial Expression Recognition	Current state-of-the-art models for automatic Facial Expression Recognition (FER) are based on very deep neural networks that are effective but rather expensive to train. Given the dynamic conditions of FER, this characteristic hinders such models of been used as a general affect recognition. In this paper, we address ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	196,000
2407.12830	Knowledge-based Consistency Testing of Large Language Models	In this work, we systematically expose and measure the inconsistency and knowledge gaps of Large Language Models (LLMs). Specifically, we propose an automated testing framework (called KonTest) which leverages a knowledge graph to construct test cases. KonTest probes and measures the inconsistencies in the LLM's knowle...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	474,106
2201.07341	Learning grammar with a divide-and-concur neural network	We implement a divide-and-concur iterative projection approach to context-free grammar inference. Unlike most state-of-the-art models of natural language processing, our method requires a relatively small number of discrete parameters, making the inferred grammar directly interpretable -- one can read off from a soluti...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	275,995
2111.02709	Analog MIMO Communication for One-shot Distributed Principal Component Analysis	A fundamental algorithm for data analytics at the edge of wireless networks is distributed principal component analysis (DPCA), which finds the most important information embedded in a distributed high-dimensional dataset by distributed computation of a reduced-dimension data subspace, called principal components (PCs)...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	264,952
2308.14583	Learning to Read Analog Gauges from Synthetic Data	Manually reading and logging gauge data is time inefficient, and the effort increases according to the number of gauges available. We present a computer vision pipeline that automates the reading of analog gauges. We propose a two-stage CNN pipeline that identifies the key structural components of an analog gauge and o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,377
1907.05021	Optimal Feature Transport for Cross-View Image Geo-Localization	This paper addresses the problem of cross-view image geo-localization, where the geographic location of a ground-level street-view query image is estimated by matching it against a large scale aerial map (e.g., a high-resolution satellite image). State-of-the-art deep-learning based methods tackle this problem as deep ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	138,260
2208.14743	SimpleRecon: 3D Reconstruction Without 3D Convolutions	Traditionally, 3D indoor scene reconstruction from posed images happens in two phases: per-image depth estimation, followed by depth merging and surface reconstruction. Recently, a family of methods have emerged that perform reconstruction directly in final 3D volumetric feature space. While these methods have shown im...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	315,410
2408.08624	RealMedQA: A pilot biomedical question answering dataset containing realistic clinical questions	Clinical question answering systems have the potential to provide clinicians with relevant and timely answers to their questions. Nonetheless, despite the advances that have been made, adoption of these systems in clinical settings has been slow. One issue is a lack of question-answering datasets which reflect the real...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	481,072
1504.00532	A general framework for compressed sensing and parallel MRI using annihilating filter based low-rank Hankel matrix	Parallel MRI (pMRI) and compressed sensing MRI (CS-MRI) have been considered as two distinct reconstruction problems. Inspired by recent k-space interpolation methods, an annihilating filter based low-rank Hankel matrix approach (ALOHA) is proposed as a general framework for sparsity-driven k-space interpolation method...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,713
1503.06962	Probabilistic Binary-Mask Cocktail-Party Source Separation in a Convolutional Deep Neural Network	Separation of competing speech is a key challenge in signal processing and a feat routinely performed by the human auditory brain. A long standing benchmark of the spectrogram approach to source separation is known as the ideal binary mask. Here, we train a convolutional deep neural network, on a two-speaker cocktail p...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	41,423
2408.15778	LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models	Large Language Models (LLMs) have demonstrated notable capabilities across various tasks, showcasing complex problem-solving abilities. Understanding and executing complex rules, along with multi-step planning, are fundamental to logical reasoning and critical for practical LLM agents and decision-making systems. Howev...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	484,075
2405.14425	When predict can also explain: few-shot prediction to select better neural latents	Latent variable models serve as powerful tools to infer underlying dynamics from observed neural activity. Ideally, the inferred dynamics should align with true ones. However, due to the absence of ground truth data, prediction benchmarks are often employed as proxies. One widely-used method, co-smoothing, involves j...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	456,418
1909.12316	Preference-Based Learning for Exoskeleton Gait Optimization	This paper presents a personalized gait optimization framework for lower-body exoskeletons. Rather than optimizing numerical objectives such as the mechanical cost of transport, our approach directly learns from user preferences, e.g., for comfort. Building upon work in preference-based interactive learning, we present...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	147,089
1809.07887	Closeness of Solutions for Singularly Perturbed Systems via Averaging	This paper studies the behavior of singularly perturbed nonlinear differential equations with boundary-layer solutions that do not necessarily converge to an equilibrium. Using the average of the fast variable and assuming the boundary layer solutions converge to a bounded set, results on the closeness of solutions of ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	108,380
1911.07509	AI-based Pilgrim Detection using Convolutional Neural Networks	Pilgrimage represents the most important Islamic religious gathering in the world where millions of pilgrims visit the holy places of Makkah and Madinah to perform their rituals. The safety and security of pilgrims is the highest priority for the authorities. In Makkah, 5000 cameras are spread around the holy for monit...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	153,877
2012.03468	An Empirical Survey of Unsupervised Text Representation Methods on Twitter Data	The field of NLP has seen unprecedented achievements in recent years. Most notably, with the advent of large-scale pre-trained Transformer-based language models, such as BERT, there has been a noticeable improvement in text representation. It is, however, unclear whether these improvements translate to noisy user-gener...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	210,128
2207.05833	Earthformer: Exploring Space-Time Transformers for Earth System Forecasting	Conventionally, Earth system (e.g., weather and climate) forecasting relies on numerical simulation with complex physical models and are hence both expensive in computation and demanding on domain expertise. With the explosive growth of the spatiotemporal Earth observation data in the past decade, data-driven models th...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	307,678
2408.17428	CLOCR-C: Context Leveraging OCR Correction with Pre-trained Language Models	The digitisation of historical print media archives is crucial for increasing accessibility to contemporary records. However, the process of Optical Character Recognition (OCR) used to convert physical records to digital text is prone to errors, particularly in the case of newspapers and periodicals due to their comple...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	484,699
2007.00479	The Restricted Isometry of ReLU Networks: Generalization through Norm Concentration	While regression tasks aim at interpolating a relation on the entire input space, they often have to be solved with a limited amount of training data. Still, if the hypothesis functions can be sketched well with the data, one can hope for identifying a generalizing model. In this work, we introduce with the Neural Re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	185,128
2404.09480	Mitigating Hallucination in Abstractive Summarization with Domain-Conditional Mutual Information	A primary challenge in abstractive summarization is hallucination -- the phenomenon where a model generates plausible text that is absent in the source text. We hypothesize that the domain (or topic) of the source text triggers the model to generate text that is highly probable in the domain, neglecting the details of ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	446,694
2404.00495	Configurable Safety Tuning of Language Models with Synthetic Preference Data	State-of-the-art language model fine-tuning techniques, such as Direct Preference Optimization (DPO), restrict user control by hard-coding predefined behaviors into the model. To address this, we propose a novel method, Configurable Safety Tuning (CST), that augments DPO using synthetic preference data to facilitate fl...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	442,957
2405.09711	STAR: A Benchmark for Situated Reasoning in Real-World Videos	Reasoning in the real world is not divorced from situations. How to capture the present knowledge from surrounding situations and perform reasoning accordingly is crucial and challenging for machine intelligence. This paper introduces a new benchmark that evaluates the situated reasoning ability via situation abstracti...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	454,500
1605.03956	On the Convergent Properties of Word Embedding Methods	Do word embeddings converge to learn similar things over different initializations? How repeatable are experiments with word embeddings? Are all word embedding techniques equally reliable? In this paper we propose evaluating methods for learning word representations by their consistency across initializations. We propo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	55,812
1512.06868	Minimum distance functions of graded ideals and Reed-Muller-type codes	We introduce and study the minimum distance function of a graded ideal in a polynomial ring with coefficients in a field, and show that it generalizes the minimum distance of projective Reed-Muller-type codes over finite fields. This gives an algebraic formulation of the minimum distance of a projective Reed-Muller-typ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	50,357
2111.15129	Anonymization for Skeleton Action Recognition	Skeleton-based action recognition attracts practitioners and researchers due to the lightweight, compact nature of datasets. Compared with RGB-video-based action recognition, skeleton-based action recognition is a safer way to protect the privacy of subjects while having competitive recognition performance. However, du...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	268,821
2402.04469	IoT Network Traffic Analysis with Deep Learning	As IoT networks become more complex and generate massive amounts of dynamic data, it is difficult to monitor and detect anomalies using traditional statistical methods and machine learning methods. Deep learning algorithms can process and learn from large amounts of data and can also be trained using unsupervised learn...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	427,463
2311.02695	Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions	The task of inferring high-level causal variables from low-level observations, commonly referred to as causal representation learning, is fundamentally underconstrained. As such, recent works to address this problem focus on various assumptions that lead to identifiability of the underlying latent causal variables. A l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	405,544
1405.6033	Universal Bayesian Measures and Universal Histogram Sequences	Consider universal data compression: the length $l(x^n)$ of sequence $x^n\in A^n$ with finite alphabet $A$ and length $n$ satisfies Kraft's inequality over $A^n$, and $-\frac{1}{n}\log \frac{P^n(x^n)}{Q^n(x^n)}$ almost surely converges to zero as $n$ grows for the $Q^n(x^n)=2^{-l(x^n)}$ and any stationary ergodic sourc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	33,329
1607.01059	Improving Sparse Representation-Based Classification Using Local Principal Component Analysis	Sparse representation-based classification (SRC), proposed by Wright et al., seeks the sparsest decomposition of a test sample over the dictionary of training samples, with classification to the most-contributing class. Because it assumes test samples can be written as linear combinations of their same-class training s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	58,175
2308.10578	Weakly synchronous systems with three machines are Turing powerful	Communicating finite-state machines (CFMs) are a Turing powerful model of asynchronous message-passing distributed systems. In weakly synchronous systems, processes communicate through phases in which messages are first sent and then received, for each process. Such systems enjoy a limited form of synchronization, and ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	386,794
2108.07478	Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks	Instance segmentation in 3D scenes is fundamental in many applications of scene understanding. It is yet challenging due to the compound factors of data irregularity and uncertainty in the numbers of instances. State-of-the-art methods largely rely on a general pipeline that first learns point-wise features discriminat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	250,927
2404.13333	Parallel-in-Time Integration of Transient Phenomena in No-Insulation Superconducting Coils Using Parareal	High-temperature superconductors (HTS) have the potential to enable magnetic fields beyond the current limits of low-temperature superconductors in applications like accelerator magnets. However, the design of HTS-based magnets requires computationally demanding transient multi-physics simulations with highly non-linea...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	448,250
2411.03351	Tabular Data Synthesis with Differential Privacy: A Survey	Data sharing is a prerequisite for collaborative innovation, enabling organizations to leverage diverse datasets for deeper insights. In real-world applications like FinTech and Smart Manufacturing, transactional data, often in tabular form, are generated and analyzed for insight generation. However, such datasets typi...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	true	false	505,871
2210.04620	FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings	Federated Learning (FL) is a novel approach enabling several clients holding sensitive data to collaboratively train machine learning models, without centralizing data. The cross-silo FL setting corresponds to the case of few ($2$--$50$) reliable clients, each holding medium to large datasets, and is typically found in...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	322,529
2303.05101	Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics	Stochastic-gradient sampling methods are often used to perform Bayesian inference on neural networks. It has been observed that the methods in which notions of differential geometry are included tend to have better performances, with the Riemannian metric improving posterior exploration by accounting for the local curv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	350,340
2109.12722	Markerless Suture Needle 6D Pose Tracking with Robust Uncertainty Estimation for Autonomous Minimally Invasive Robotic Surgery	Suture needle localization is necessary for autonomous suturing. Previous approaches in autonomous suturing often relied on fiducial markers rather than markerless detection schemes for localizing a suture needle due to the inconsistency of markerless detections. However, fiducial markers are not practical for real-wor...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	257,391
1909.00392	Towards Robust Learning-Based Pose Estimation of Noncooperative Spacecraft	This work presents a novel Convolutional Neural Network (CNN) architecture and a training procedure to enable robust and accurate pose estimation of a noncooperative spacecraft. First, a new CNN architecture is introduced that has scored a fourth place in the recent Pose Estimation Challenge hosted by Stanford's Space ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	143,622
2404.06004	AiSAQ: All-in-Storage ANNS with Product Quantization for DRAM-free Information Retrieval	In approximate nearest neighbor search (ANNS) methods based on approximate proximity graphs, DiskANN achieves good recall-speed balance for large-scale datasets using both of RAM and storage. Despite it claims to save memory usage by loading compressed vectors by product quantization (PQ), its memory usage increases in...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	true	445,295
1903.07988	Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI	Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multi-sequence 3D imaging. This study demonstrates automated detection and segmentation of brain metastases on multi-sequence MRI using a deep learning approach based on a fully con...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	124,750
2102.06659	Leveraging Artificial Intelligence to Analyze Citizens' Opinions on Urban Green Space	Continued population growth and urbanization is shifting research to consider the quality of urban green space over the quantity of these parks, woods, and wetlands. The quality of urban green space has been hitherto measured by expert assessments, including in-situ observations, surveys, and remote sensing analyses. L...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	219,831
1907.05671	Justifying Diagnosis Decisions by Deep Neural Networks	An integrated approach is proposed across visual and textual data to both determine and justify a medical diagnosis by a neural network. As deep learning techniques improve, interest grows to apply them in medical applications. To enable a transition to workflows in a medical context that are aided by machine learning,...	true	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	138,426
2201.09433	Active Learning Polynomial Threshold Functions	We initiate the study of active learning polynomial threshold functions (PTFs). While traditional lower bounds imply that even univariate quadratics cannot be non-trivially actively learned, we show that allowing the learner basic access to the derivatives of the underlying classifier circumvents this issue and leads t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	276,674
2007.12236	Usability of a Robot's Realistic Facial Expressions and Peripherals in Autistic Children's Therapy	Robot-assisted therapy is an emerging form of therapy for autistic children, although designing effective robot behaviors is a challenge for effective implementation of such therapy. A series of usability tests assessed trends in the effectiveness of modelling a robot's facial expressions on realistic facial expression...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	188,766
1512.00743	Recognizing Semantic Features in Faces using Deep Learning	The human face constantly conveys information, both consciously and subconsciously. However, as basic as it is for humans to visually interpret this information, it is quite a big challenge for machines. Conventional semantic facial feature recognition and analysis techniques are already in use and are based on physiol...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	49,738
2103.01452	Social Profit Optimization with Demand Response Management in Electricity Market: A Multi-timescale Leader-following Approach	In the electricity market, it is quite common that the market participants make "selfish" strategies to harvest the maximum profits for themselves, which may cause the social benefit loss and impair the sustainability of the society in the long term. Regarding this issue, in this work, we will discuss how the social pr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	222,621
1907.02821	Benchmarking unsupervised near-duplicate image detection	Unsupervised near-duplicate detection has many practical applications ranging from social media analysis and web-scale retrieval, to digital image forensics. It entails running a threshold-limited query on a set of descriptors extracted from the images, with the goal of identifying all possible near-duplicates, while l...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	true	137,693
2305.00533	Guaranteed Evader Detection in Multi-Agent Search Tasks using Pincer Trajectories	Assume that inside an initial planar area there are smart mobile evaders attempting to avoid detection by a team of sweeping searching agents. All sweepers detect evaders with fan-shaped sensors, modeling the field of view of real cameras. Detection of all evaders is guaranteed with cooperative sweeping strategies, by ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	361,363
2305.02312	AG3D: Learning to Generate 3D Avatars from 2D Image Collections	While progress in 2D generative models of human appearance has been rapid, many applications require 3D avatars that can be animated and rendered. Unfortunately, most existing methods for learning generative models of 3D humans with diverse shape and appearance require 3D training data, which is limited and expensive t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	361,990
2402.01618	Style Vectors for Steering Generative Large Language Model	This research explores strategies for steering the output of large language models (LLMs) towards specific styles, such as sentiment, emotion, or writing style, by adding style vectors to the activations of hidden layers during text generation. We show that style vectors can be simply computed from recorded layer activ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	426,102
2407.01445	FastCLIP: A Suite of Optimization Techniques to Accelerate CLIP Training with Limited Resources	Existing studies of training state-of-the-art Contrastive Language-Image Pretraining (CLIP) models on large-scale data involve hundreds of or even thousands of GPUs due to the requirement of a large batch size. However, such a large amount of resources is not accessible to most people. While advanced compositional opti...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	469,300
2012.01405	Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization	We introduce a novel representation learning method to disentangle pose-dependent as well as view-dependent factors from 2D human poses. The method trains a network using cross-view mutual information maximization (CV-MIM) which maximizes mutual information of the same pose performed from different viewpoints in a cont...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	209,409
2408.09886	SAM-UNet:Enhancing Zero-Shot Segmentation of SAM for Universal Medical Images	Segment Anything Model (SAM) has demonstrated impressive performance on a wide range of natural image segmentation tasks. However, its performance significantly deteriorates when directly applied to medical domain, due to the remarkable differences between natural images and medical images. Some researchers have attemp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	481,633
2404.09365	Hierarchical Attention Models for Multi-Relational Graphs	We present Bi-Level Attention-Based Relational Graph Convolutional Networks (BR-GCN), unique neural network architectures that utilize masked self-attentional layers with relational graph convolutions, to effectively operate on highly multi-relational data. BR-GCN models use bi-level attention to learn node embeddings ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	446,640
2402.03319	Physical Reservoir Computing Enabled by Solitary Waves and Biologically-Inspired Nonlinear Transformation of Input Data	Reservoir computing (RC) systems can efficiently forecast chaotic time series using nonlinear dynamical properties of an artificial neural network of random connections. The versatility of RC systems has motivated further research on both hardware counterparts of traditional RC algorithms and more efficient RC-like sch...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	426,960
2007.13019	Feedback Loop and Bias Amplification in Recommender Systems	Recommendation algorithms are known to suffer from popularity bias; a few popular items are recommended frequently while the majority of other items are ignored. These recommendations are then consumed by the users, their reaction will be logged and added to the system: what is generally known as a feedback loop. In th...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	188,996
1704.06955	Superadditivity of the Classical Capacity with Limited Entanglement Assistance	Finding the optimal encoding strategies can be challenging for communication using quantum channels, as classical and quantum capacities may be superadditive. Entanglement assistance can often simplify this task, as the entanglement-assisted classical capacity for any channel is additive, making entanglement across cha...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	72,264
2108.09993	Image coding for machines: an end-to-end learned approach	Over recent years, deep learning-based computer vision systems have been applied to images at an ever-increasing pace, oftentimes representing the only type of consumption for those images. Given the dramatic explosion in the number of images generated per day, a question arises: how much better would an image codec ta...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	251,767
2501.02194	Ensemble-based Deep Multilayer Community Search	Multilayer graphs, consisting of multiple interconnected layers, are widely used to model diverse relationships in the real world. A community is a cohesive subgraph that offers valuable insights for analyzing (multilayer) graphs. Recently, there has been an emerging trend focused on searching query-driven communities ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	522,389
2107.09802	Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates	We study the problem of differentially private (DP) matrix completion under user-level privacy. We design a joint differentially private variant of the popular Alternating-Least-Squares (ALS) method that achieves: i) (nearly) optimal sample complexity for matrix completion (in terms of number of items, users), and ii) ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	247,129
1408.1600	Change Impact Analysis Based Regression Testing of Web Services	Reducing the effort required to make changes in web services is one of the primary goals in web service projects maintenance and evolution. Normally, functional and non-functional testing of a web service is performed by testing the operations specified in its WSDL. The regression testing is performed by identifying th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	35,191
2410.05805	PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling	Precipitation nowcasting plays a pivotal role in socioeconomic sectors, especially in severe convective weather warnings. Although notable progress has been achieved by approaches mining the spatiotemporal correlations with deep learning, these methods still suffer severe blurriness as the lead time increases, which ha...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	495,927
2002.10836	Gesture recognition with 60GHz 802.11 waveforms	Gesture recognition application over 802.11 ad/y waveforms is developed. Simultaneous gestures of slider-control and two-finger gesture for switching are detected based on Golay sequences of channel estimation fields of the packets.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	165,529
1702.08235	Variational Inference using Implicit Distributions	Generative adversarial networks (GANs) have given us a great tool to fit implicit generative models to data. Implicit distributions are ones we can sample from easily, and take derivatives of samples with respect to model parameters. These models are highly expressive and we argue they can prove just as useful for vari...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	68,947
2010.04430	Large-scale randomized experiment reveals machine learning helps people learn and remember more effectively	Machine learning has typically focused on developing models and algorithms that would ultimately replace humans at tasks where intelligence is required. In this work, rather than replacing humans, we focus on unveiling the potential of machine learning to improve how people learn and remember factual material. To this ...	true	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	199,741
1206.6409	Scaling Up Coordinate Descent Algorithms for Large $\ell_1$ Regularization Problems	We present a generic framework for parallel coordinate descent (CD) algorithms that includes, as special cases, the original sequential algorithms Cyclic CD and Stochastic CD, as well as the recent parallel Shotgun algorithm. We introduce two novel parallel algorithms that are also special cases---Thread-Greedy CD and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	16,944
2201.01819	Formal Analysis of Art: Proxy Learning of Visual Concepts from Style Through Language Models	We present a machine learning system that can quantify fine art paintings with a set of visual elements and principles of art. This formal analysis is fundamental for understanding art, but developing such a system is challenging. Paintings have high visual complexities, but it is also difficult to collect enough train...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	274,357
2309.07990	Leveraging Contextual Information for Effective Entity Salience Detection	In text documents such as news articles, the content and key events usually revolve around a subset of all the entities mentioned in a document. These entities, often deemed as salient entities, provide useful cues of the aboutness of a document to a reader. Identifying the salience of entities was found helpful in sev...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	391,988
2303.13760	Multiple Access Design for Symbiotic Radios: Facilitating Massive IoT Connections with Cellular Networks	Symbiotic radio (SR) has emerged as a spectrum- and energy-efficient paradigm to support massive Internet of Things (IoT) connections. Two multiple access schemes are proposed in this paper to facilitate the massive IoT connections using the cellular network based on the SR technique, namely, the simultaneous access (S...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	353,807
2402.01209	Solution of the Probabilistic Lambert's Problem: Optimal Transport Approach	The deterministic variant of the Lambert's problem was posed by Lambert in the 18th century and its solution for conic trajectory has been derived by many, including Euler, Lambert, Lagrange, Laplace, Gauss and Legendre. The solution amounts to designing velocity control for steering a spacecraft from a given initial t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	425,915
2006.12618	A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence	Emotion perception is essential to affective and cognitive development which involves distributed brain circuits. The ability of emotion identification begins in infancy and continues to develop throughout childhood and adolescence. Understanding the development of brain's emotion circuitry may help us explain the emot...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	183,643
1909.04142	DaTscan SPECT Image Classification for Parkinson's Disease	Parkinson's Disease (PD) is a neurodegenerative disease that currently does not have a cure. In order to facilitate disease management and reduce the speed of symptom progression, early diagnosis is essential. The current clinical, diagnostic approach is to have radiologists perform human visual analysis of the degener...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	144,707
2208.01849	Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation	Multi-types of behaviors (e.g., clicking, adding to cart, purchasing, etc.) widely exist in most real-world recommendation scenarios, which are beneficial to learn users' multi-faceted preferences. As dependencies are explicitly exhibited by the multiple types of behaviors, effectively modeling complex behavior depende...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	311,295
2304.10075	Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering	The rendering scheme in neural radiance field (NeRF) is effective in rendering a pixel by casting a ray into the scene. However, NeRF yields blurred rendering results when the training images are captured at non-uniform scales, and produces aliasing artifacts if the test images are taken in distant views. To address th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	359,282
1903.02165	Camera Obscurer: Generative Art for Design Inspiration	We investigate using generated decorative art as a source of inspiration for design tasks. Using a visual similarity search for image retrieval, the \emph{Camera Obscurer} app enables rapid searching of tens of thousands of generated abstract images of various types. The seed for a visual similarity search is a given i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	true	123,441
1909.00531	Improving Context-aware Neural Machine Translation with Target-side Context	In recent years, several studies on neural machine translation (NMT) have attempted to use document-level context by using a multi-encoder and two attention mechanisms to read the current and previous sentences to incorporate the context of the previous sentences. These studies concluded that the target-side context is...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	143,659
2409.11307	GS-Net: Generalizable Plug-and-Play 3D Gaussian Splatting Module	3D Gaussian Splatting (3DGS) integrates the strengths of primitive-based representations and volumetric rendering techniques, enabling real-time, high-quality rendering. However, 3DGS models typically overfit to single-scene training and are highly sensitive to the initialization of Gaussian ellipsoids, heuristically d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	489,100
1304.2347	Process, Structure, and Modularity in Reasoning with Uncertainty	Computational mechanisms for uncertainty management must support interactive and incremental problem formulation, inference, hypothesis testing, and decision making. However, most current uncertainty inference systems concentrate primarily on inference, and provide no support for the larger issues. We present a computa...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,655
1711.07240	MegDet: A Large Mini-Batch Object Detector	The improvements in recent CNN-based object detection works, from R-CNN [11], Fast/Faster R-CNN [10, 31] to recent Mask R-CNN [14] and RetinaNet [24], mainly come from new network, new framework, or novel loss design. But mini-batch size, a key factor in the training, has not been well studied. In this paper, we propos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,946
2104.14506	Explainable AI For COVID-19 CT Classifiers: An Initial Comparison Study	Artificial Intelligence (AI) has made leapfrogs in development across all the industrial sectors especially when deep learning has been introduced. Deep learning helps to learn the behaviour of an entity through methods of recognising and interpreting patterns. Despite its limitless potential, the mystery is how deep l...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	232,842
1203.4867	Multi-hop Analog Network Coding: An Amplify-and-Forward Approach	In this paper, we study the performance of an amplify-and-forward (AF) based analog network coding (ANC) relay scheme in a multi-hop wireless network under individual power constraints. In the first part, a unicast scenario is considered. The problem of finding the maximum achievable rate is formulated as an optimizati...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	15,063
1809.04317	Action Representations in Robotics: A Taxonomy and Systematic Classification	Understanding and defining the meaning of "action" is substantial for robotics research. This becomes utterly evident when aiming at equipping autonomous robots with robust manipulation skills for action execution. Unfortunately, to this day we still lack both a clear understanding of the concept of an action and a set...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	107,535

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