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
1311.2540	Asymmetric numeral systems: entropy coding combining speed of Huffman coding with compression rate of arithmetic coding	The modern data compression is mainly based on two approaches to entropy coding: Huffman (HC) and arithmetic/range coding (AC). The former is much faster, but approximates probabilities with powers of 2, usually leading to relatively low compression rates. The latter uses nearly exact probabilities - easily approaching...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	28,328
1909.05309	Annotation and Classification of Sentence-level Revision Improvement	Studies of writing revisions rarely focus on revision quality. To address this issue, we introduce a corpus of between-draft revisions of student argumentative essays, annotated as to whether each revision improves essay quality. We demonstrate a potential usage of our annotations by developing a machine learning model...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	145,051
1604.00861	Recurrent Neural Networks for Polyphonic Sound Event Detection in Real Life Recordings	In this paper we present an approach to polyphonic sound event detection in real life recordings based on bi-directional long short term memory (BLSTM) recurrent neural networks (RNNs). A single multilabel BLSTM RNN is trained to map acoustic features of a mixture signal consisting of sounds from multiple classes, to b...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	54,110
1809.06366	AUEB at BioASQ 6: Document and Snippet Retrieval	We present AUEB's submissions to the BioASQ 6 document and snippet retrieval tasks (parts of Task 6b, Phase A). Our models use novel extensions to deep learning architectures that operate solely over the text of the query and candidate document/snippets. Our systems scored at the top or near the top for all batches of ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	108,042
2406.12109	Can LLMs Learn Macroeconomic Narratives from Social Media?	This study empirically tests the $\textit{Narrative Economics}$ hypothesis, which posits that narratives (ideas that are spread virally and affect public beliefs) can influence economic fluctuations. We introduce two curated datasets containing posts from X (formerly Twitter) which capture economy-related narratives (D...	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	465,226
1911.12246	Do Attention Heads in BERT Track Syntactic Dependencies?	We investigate the extent to which individual attention heads in pretrained transformer language models, such as BERT and RoBERTa, implicitly capture syntactic dependency relations. We employ two methods---taking the maximum attention weight and computing the maximum spanning tree---to extract implicit dependency relat...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	155,344
1907.11563	Neural Dynamic Successive Cancellation Flip Decoding of Polar Codes	Dynamic successive cancellation flip (DSCF) decoding of polar codes is a powerful algorithm that can achieve the error correction performance of successive cancellation list (SCL) decoding, with a complexity that is close to that of successive cancellation (SC) decoding at practical signal-to-noise ratio (SNR) regimes....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	139,883
2304.07576	Guaranteed Stability Margins for Decentralized Linear Quadratic Regulators	It is well-known that linear quadratic regulators (LQR) enjoy guaranteed stability margins, whereas linear quadratic Gaussian regulators (LQG) do not. In this letter, we consider systems and compensators defined over directed acyclic graphs. In particular, there are multiple decision-makers, each with access to a diffe...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	358,402
2403.08782	Procedural terrain generation with style transfer	In this study we introduce a new technique for the generation of terrain maps, exploiting a combination of procedural generation and Neural Style Transfer. We consider our approach to be a viable alternative to competing generative models, with our technique achieving greater versatility, lower hardware requirements an...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	437,470
2408.10125	Video Object Segmentation via SAM 2: The 4th Solution for LSVOS Challenge VOS Track	Video Object Segmentation (VOS) task aims to segmenting a particular object instance throughout the entire video sequence given only the object mask of the first frame. Recently, Segment Anything Model 2 (SAM 2) is proposed, which is a foundation model towards solving promptable visual segmentation in images and videos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	481,725
2302.10197	Growing Steerable Neural Cellular Automata	Neural Cellular Automata (NCA) models have shown remarkable capacity for pattern formation and complex global behaviors stemming from local coordination. However, in the original implementation of NCA, cells are incapable of adjusting their own orientation, and it is the responsibility of the model designer to orient t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	346,709
2009.07310	Simultaneous Machine Translation with Visual Context	Simultaneous machine translation (SiMT) aims to translate a continuous input text stream into another language with the lowest latency and highest quality possible. The translation thus has to start with an incomplete source text, which is read progressively, creating the need for anticipation. In this paper, we seek t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	195,877
2109.01019	Extended Object Tracking Using Sets Of Trajectories with a PHD Filter	PHD filtering is a common and effective multiple object tracking (MOT) algorithm used in scenarios where the number of objects and their states are unknown. In scenarios where each object can generate multiple measurements per scan, some PHD filters can estimate the extent of the objects as well as their kinematic prop...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	253,317
2204.00325	CAT-Det: Contrastively Augmented Transformer for Multi-modal 3D Object Detection	In autonomous driving, LiDAR point-clouds and RGB images are two major data modalities with complementary cues for 3D object detection. However, it is quite difficult to sufficiently use them, due to large inter-modal discrepancies. To address this issue, we propose a novel framework, namely Contrastively Augmented Tra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	289,220
2312.07214	Exploring Large Language Models to Facilitate Variable Autonomy for Human-Robot Teaming	In a rapidly evolving digital landscape autonomous tools and robots are becoming commonplace. Recognizing the significance of this development, this paper explores the integration of Large Language Models (LLMs) like Generative pre-trained transformer (GPT) into human-robot teaming environments to facilitate variable a...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	414,841
2410.04191	Accelerating Diffusion Models with One-to-Many Knowledge Distillation	Significant advancements in image generation have been made with diffusion models. Nevertheless, when contrasted with previous generative models, diffusion models face substantial computational overhead, leading to failure in real-time generation. Recent approaches have aimed to accelerate diffusion models by reducing ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	495,164
1711.06055	Integrated Face Analytics Networks through Cross-Dataset Hybrid Training	Face analytics benefits many multimedia applications. It consists of a number of tasks, such as facial emotion recognition and face parsing, and most existing approaches generally treat these tasks independently, which limits their deployment in real scenarios. In this paper we propose an integrated Face Analytics Netw...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,703
2403.09977	EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba	Prior efforts in light-weight model development mainly centered on CNN and Transformer-based designs yet faced persistent challenges. CNNs adept at local feature extraction compromise resolution while Transformers offer global reach but escalate computational demands $\mathcal{O}(N^2)$. This ongoing trade-off between a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	437,985
2411.13597	Enhancing Bidirectional Sign Language Communication: Integrating YOLOv8 and NLP for Real-Time Gesture Recognition & Translation	The primary concern of this research is to take American Sign Language (ASL) data through real time camera footage and be able to convert the data and information into text. Adding to that, we are also putting focus on creating a framework that can also convert text into sign language in real time which can help us bre...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	509,850
2410.00059	IDEA: An Inverse Domain Expert Adaptation Based Active DNN IP Protection Method	Illegitimate reproduction, distribution and derivation of Deep Neural Network (DNN) models can inflict economic loss, reputation damage and even privacy infringement. Passive DNN intellectual property (IP) protection methods such as watermarking and fingerprinting attempt to prove the ownership upon IP violation, but t...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	false	false	false	false	493,216
1811.04133	Integrating Recurrence Dynamics for Speech Emotion Recognition	We investigate the performance of features that can capture nonlinear recurrence dynamics embedded in the speech signal for the task of Speech Emotion Recognition (SER). Reconstruction of the phase space of each speech frame and the computation of its respective Recurrence Plot (RP) reveals complex structures which can...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	113,000
2111.12819	MMSE Bound for MIMO Channel	Detailed derivations of two bounds of the minimum mean-square error (MMSE) of complex-valued multiple-input multiple-output (MIMO) systems are proposed for performance evaluation. Particularly, the lower bound is derived based on a genie-aided MMSE estimator, whereas the upper bound is derived based on a maximum-likeli...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	268,083
1903.08888	Tensor-Ring Nuclear Norm Minimization and Application for Visual Data Completion	Tensor ring (TR) decomposition has been successfully used to obtain the state-of-the-art performance in the visual data completion problem. However, the existing TR-based completion methods are severely non-convex and computationally demanding. In addition, the determination of the optimal TR rank is a tough work in pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	124,932
2306.01344	Adjustable Visual Appearance for Generalizable Novel View Synthesis	We present a generalizable novel view synthesis method which enables modifying the visual appearance of an observed scene so rendered views match a target weather or lighting condition without any scene specific training or access to reference views at the target condition. Our method is based on a pretrained generaliz...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	370,416
2108.06227	SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation	Automated segmentation in medical image analysis is a challenging task that requires a large amount of manually labeled data. However, most existing learning-based approaches usually suffer from limited manually annotated medical data, which poses a major practical problem for accurate and robust medical image segmenta...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	250,541
2303.10368	An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering	Large-scale pre-trained language models (PLMs) such as BERT have recently achieved great success and become a milestone in natural language processing (NLP). It is now the consensus of the NLP community to adopt PLMs as the backbone for downstream tasks. In recent works on knowledge graph question answering (KGQA), BER...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	352,414
1210.2126	Lists that are smaller than their parts: A coding approach to tunable secrecy	We present a new information-theoretic definition and associated results, based on list decoding in a source coding setting. We begin by presenting list-source codes, which naturally map a key length (entropy) to list size. We then show that such codes can be analyzed in the context of a novel information-theoretic met...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	18,990
1706.05101	On M-ary Distributed Detection for Power Constraint Wireless Sensor Networks	We consider a wireless sensor network (WSN), consisting of several sensors and a fusion center (FC), which is tasked with solving an M-ary hypothesis testing problem. Sensors make M-ary decisions and transmit their digitally modulated decisions over orthogonal channels, which are subject to Rayleigh fading and noise, t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	75,451
1303.5403	An Entropy-based Learning Algorithm of Bayesian Conditional Trees	This article offers a modification of Chow and Liu's learning algorithm in the context of handwritten digit recognition. The modified algorithm directs the user to group digits into several classes consisting of digits that are hard to distinguish and then constructing an optimal conditional tree representation for eac...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	23,091
2009.09011	Experimental Review of Neural-based approaches for Network Intrusion Management	The use of Machine Learning (ML) techniques in Intrusion Detection Systems (IDS) has taken a prominent role in the network security management field, due to the substantial number of sophisticated attacks that often pass undetected through classic IDSs. These are typically aimed at recognising attacks based on a specif...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	196,416
2108.02183	Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization	The crux of self-supervised video representation learning is to build general features from unlabeled videos. However, most recent works have mainly focused on high-level semantics and neglected lower-level representations and their temporal relationship which are crucial for general video understanding. To address the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	249,243
2112.00484	Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding	Although considerable progress has been made in semantic scene understanding under clear weather, it is still a tough problem under adverse weather conditions, such as dense fog, due to the uncertainty caused by imperfect observations. Besides, difficulties in collecting and labeling foggy images hinder the progress of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,150
2307.10563	FACADE: A Framework for Adversarial Circuit Anomaly Detection and Evaluation	We present FACADE, a novel probabilistic and geometric framework designed for unsupervised mechanistic anomaly detection in deep neural networks. Its primary goal is advancing the understanding and mitigation of adversarial attacks. FACADE aims to generate probabilistic distributions over circuits, which provide critic...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	380,596
2409.15277	A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor?	Large language models (LLMs) have exhibited remarkable capabilities across various domains and tasks, pushing the boundaries of our knowledge in learning and cognition. The latest model, OpenAI's o1, stands out as the first LLM with an internalized chain-of-thought technique using reinforcement learning strategies. Whi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	490,834
2207.08531	DID-M3D: Decoupling Instance Depth for Monocular 3D Object Detection	Monocular 3D detection has drawn much attention from the community due to its low cost and setup simplicity. It takes an RGB image as input and predicts 3D boxes in the 3D space. The most challenging sub-task lies in the instance depth estimation. Previous works usually use a direct estimation method. However, in this ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	308,617
1811.07153	Robust Website Fingerprinting Through the Cache Occupancy Channel	Website fingerprinting attacks, which use statistical analysis on network traffic to compromise user privacy, have been shown to be effective even if the traffic is sent over anonymity-preserving networks such as Tor. The classical attack model used to evaluate website fingerprinting attacks assumes an on-path adversar...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	113,688
2402.01410	XAI for Skin Cancer Detection with Prototypes and Non-Expert Supervision	Skin cancer detection through dermoscopy image analysis is a critical task. However, existing models used for this purpose often lack interpretability and reliability, raising the concern of physicians due to their black-box nature. In this paper, we propose a novel approach for the diagnosis of melanoma using an inter...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	426,009
2301.01984	The Evolutionary Computation Methods No One Should Use	The center-bias (or zero-bias) operator has recently been identified as one of the problems plaguing the benchmarking of evolutionary computation methods. This operator lets the methods that utilize it easily optimize functions that have their respective optima in the center of the feasible set. In this paper, we descr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	339,384
2405.07719	USP: A Unified Sequence Parallelism Approach for Long Context Generative AI	Sequence parallelism (SP), which divides the sequence dimension of input tensors across multiple computational devices, is becoming key to unlocking the long-context capabilities of generative AI models. This paper investigates the state-of-the-art SP approaches, i.e. DeepSpeed-Ulysses and Ring-Attention, and proposes ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	453,830
1907.06882	Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach	Majority of state-of-the-art monocular depth estimation methods are supervised learning approaches. The success of such approaches heavily depends on the high-quality depth labels which are expensive to obtain. Some recent methods try to learn depth networks by leveraging unsupervised cues from monocular videos which a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	138,731
2005.07293	Statistical Equity: A Fairness Classification Objective	Machine learning systems have been shown to propagate the societal errors of the past. In light of this, a wealth of research focuses on designing solutions that are "fair." Even with this abundance of work, there is no singular definition of fairness, mainly because fairness is subjective and context dependent. We pro...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	177,241
2003.11159	What is the people posting about symptoms related to Coronavirus in Bogota, Colombia?	During the last months, there is an increasing alarm about a new mutation of coronavirus, covid-19 coined by World Health Organization(WHO) with an impact in many areas: economy, health, politics and others. This situation was declared a pandemic by WHO, because of the fast expansion over many countries. At the same ti...	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	false	169,530
2208.02804	Cluster-to-adapt: Few Shot Domain Adaptation for Semantic Segmentation across Disjoint Labels	Domain adaptation for semantic segmentation across datasets consisting of the same categories has seen several recent successes. However, a more general scenario is when the source and target datasets correspond to non-overlapping label spaces. For example, categories in segmentation datasets change vastly depending on...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	311,573
1609.05929	Model reduction of cavity nonlinear optics for photonic logic: A quasi-principal components approach	Kerr nonlinear cavities displaying optical thresholding have been proposed for the realization of ultra-low power photonic logic gates. In the ultra-low photon number regime, corresponding to energy levels in the attojoule scale, quantum input-output models become important to study the effect of unavoidable quantum fl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	61,215
2501.04947	Seeing with Partial Certainty: Conformal Prediction for Robotic Scene Recognition in Built Environments	In assistive robotics serving people with disabilities (PWD), accurate place recognition in built environments is crucial to ensure that robots navigate and interact safely within diverse indoor spaces. Language interfaces, particularly those powered by Large Language Models (LLM) and Vision Language Models (VLM), hold...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	523,406
2109.12606	Autoregressive neural-network wavefunctions for ab initio quantum chemistry	In recent years, neural network quantum states (NNQS) have emerged as powerful tools for the study of quantum many-body systems. Electronic structure calculations are one such canonical many-body problem that have attracted significant research efforts spanning multiple decades, whilst only recently being attempted wit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	257,354
2012.01118	Neural Teleportation	In this paper, we explore a process called neural teleportation, a mathematical consequence of applying quiver representation theory to neural networks. Neural teleportation "teleports" a network to a new position in the weight space and preserves its function. This phenomenon comes directly from the definitions of rep...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	209,329
2212.08729	Distribution-aware Goal Prediction and Conformant Model-based Planning for Safe Autonomous Driving	The feasibility of collecting a large amount of expert demonstrations has inspired growing research interests in learning-to-drive settings, where models learn by imitating the driving behaviour from experts. However, exclusively relying on imitation can limit agents' generalisability to novel scenarios that are outsid...	false	false	false	false	true	false	true	true	false	false	true	true	false	false	false	false	false	false	336,851
2410.19560	Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning	In recent advancements in unsupervised visual representation learning, the Joint-Embedding Predictive Architecture (JEPA) has emerged as a significant method for extracting visual features from unlabeled imagery through an innovative masking strategy. Despite its success, two primary limitations have been identified: t...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	502,367
1908.09951	An Emotional Analysis of False Information in Social Media and News Articles	Fake news is risky since it has been created to manipulate the readers' opinions and beliefs. In this work, we compared the language of false news to the real one of real news from an emotional perspective, considering a set of false information types (propaganda, hoax, clickbait, and satire) from social media and onli...	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	false	142,980
2312.15903	An Incremental Update Framework for Online Recommenders with Data-Driven Prior	Online recommenders have attained growing interest and created great revenue for businesses. Given numerous users and items, incremental update becomes a mainstream paradigm for learning large-scale models in industrial scenarios, where only newly arrived data within a sliding window is fed into the model, meeting the ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	418,184
cs/0610011	Creation and use of Citations in the ADS	With over 20 million records, the ADS citation database is regularly used by researchers and librarians to measure the scientific impact of individuals, groups, and institutions. In addition to the traditional sources of citations, the ADS has recently added references extracted from the arXiv e-prints on a nightly bas...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	true	539,754
1511.05616	Learning Structured Inference Neural Networks with Label Relations	Images of scenes have various objects as well as abundant attributes, and diverse levels of visual categorization are possible. A natural image could be assigned with fine-grained labels that describe major components, coarse-grained labels that depict high level abstraction or a set of labels that reveal attributes. S...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	49,067
1602.06822	Understanding Visual Concepts with Continuation Learning	We introduce a neural network architecture and a learning algorithm to produce factorized symbolic representations. We propose to learn these concepts by observing consecutive frames, letting all the components of the hidden representation except a small discrete set (gating units) be predicted from the previous frame,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	52,428
1712.08858	Towards Collaborative Conceptual Exploration	In domains with high knowledge distribution a natural objective is to create principle foundations for collaborative interactive learning environments. We present a first mathematical characterization of a collaborative learning group, a consortium, based on closure systems of attribute sets and the well-known attribut...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	87,265
1803.06084	A Kernel Theory of Modern Data Augmentation	Data augmentation, a technique in which a training set is expanded with class-preserving transformations, is ubiquitous in modern machine learning pipelines. In this paper, we seek to establish a theoretical framework for understanding data augmentation. We approach this from two directions: First, we provide a general...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	92,769
2501.12938	Robust Hypothesis Testing with Abstention	We study the binary hypothesis testing problem where an adversary may potentially corrupt a fraction of the samples. The detector is, however, permitted to abstain from making a decision if (and only if) the adversary is present. We consider a few natural "contamination models" and characterize for them the trade-off b...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	526,492
1802.04784	MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means	Mean embeddings provide an extremely flexible and powerful tool in machine learning and statistics to represent probability distributions and define a semi-metric (MMD, maximum mean discrepancy; also called N-distance or energy distance), with numerous successful applications. The representation is constructed as the e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	90,306
2005.05495	Train and Deploy an Image Classifier for Disaster Response	With Deep Learning Image Classification becoming more powerful each year, it is apparent that its introduction to disaster response will increase the efficiency that responders can work with. Using several Neural Network Models, including AlexNet, ResNet, MobileNet, DenseNets, and 4-Layer CNN, we have classified flood ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	176,743
2106.07278	Which Mutual-Information Representation Learning Objectives are Sufficient for Control?	Mutual information maximization provides an appealing formalism for learning representations of data. In the context of reinforcement learning (RL), such representations can accelerate learning by discarding irrelevant and redundant information, while retaining the information necessary for control. Much of the prior w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	240,853
2112.14119	Robotic Perception of Object Properties using Tactile Sensing	The sense of touch plays a key role in enabling humans to understand and interact with surrounding environments. For robots, tactile sensing is also irreplaceable. While interacting with objects, tactile sensing provides useful information for the robot to understand the object, such as distributed pressure, temperatur...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	273,452
2403.16447	A Study on How Attention Scores in the BERT Model are Aware of Lexical Categories in Syntactic and Semantic Tasks on the GLUE Benchmark	This study examines whether the attention scores between tokens in the BERT model significantly vary based on lexical categories during the fine-tuning process for downstream tasks. Drawing inspiration from the notion that in human language processing, syntactic and semantic information is parsed differently, we catego...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	441,048
2501.18463	A Benchmark and Evaluation for Real-World Out-of-Distribution Detection Using Vision-Language Models	Out-of-distribution (OOD) detection is a task that detects OOD samples during inference to ensure the safety of deployed models. However, conventional benchmarks have reached performance saturation, making it difficult to compare recent OOD detection methods. To address this challenge, we introduce three novel OOD dete...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	528,714
2307.06337	Incomplete Utterance Rewriting as Sequential Greedy Tagging	The task of incomplete utterance rewriting has recently gotten much attention. Previous models struggled to extract information from the dialogue context, as evidenced by the low restoration scores. To address this issue, we propose a novel sequence tagging-based model, which is more adept at extracting information fro...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	379,039
2006.15789	A Benchmark dataset for both underwater image enhancement and underwater object detection	Underwater image enhancement is such an important vision task due to its significance in marine engineering and aquatic robot. It is usually work as a pre-processing step to improve the performance of high level vision tasks such as underwater object detection. Even though many previous works show the underwater image ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	184,626
2404.17174	Optimizing Cycle Life Prediction of Lithium-ion Batteries via a Physics-Informed Model	Accurately measuring the cycle lifetime of commercial lithium-ion batteries is crucial for performance and technology development. We introduce a novel hybrid approach combining a physics-based equation with a self-attention model to predict the cycle lifetimes of commercial lithium iron phosphate graphite cells via ea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	449,763
2208.13290	Domain Adaptation Principal Component Analysis: base linear method for learning with out-of-distribution data	Domain adaptation is a popular paradigm in modern machine learning which aims at tackling the problem of divergence (or shift) between the labeled training and validation datasets (source domain) and a potentially large unlabeled dataset (target domain). The task is to embed both datasets red into a common space in whi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	315,014
2006.05757	Data science on industrial data -- Today's challenges in brown field applications	Much research is done on data analytics and machine learning. In industrial processes large amounts of data are available and many researchers are trying to work with this data. In practical approaches one finds many pitfalls restraining the application of modern technologies especially in brown field applications. Wit...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	181,196
2310.08384	Towards Running Time Analysis of Interactive Multi-objective Evolutionary Algorithms	Evolutionary algorithms (EAs) are widely used for multi-objective optimization due to their population-based nature. Traditional multi-objective EAs (MOEAs) generate a large set of solutions to approximate the Pareto front, leaving a decision maker (DM) with the task of selecting a preferred solution. However, this pro...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	399,371
1609.06082	Learning Robust Representations of Text	Deep neural networks have achieved remarkable results across many language processing tasks, however these methods are highly sensitive to noise and adversarial attacks. We present a regularization based method for limiting network sensitivity to its inputs, inspired by ideas from computer vision, thus learning models ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	61,240
2411.15178	Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries	Partial Differential Equations (PDEs) underpin many scientific phenomena, yet traditional computational approaches often struggle with complex, nonlinear systems and irregular geometries. This paper introduces the AMG method, a Multi-Graph neural operator approach designed for efficiently solving PDEs on Arbitrary geom...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	510,470
1605.00480	Scalable Device-to-Device Communications For Frequency Reuse >> 1	Proximity based applications are becoming fast growing markets suggesting that Device-to-Device (D2D) communications is becoming an essential part of future mobile data networks. We propose scalable admission and power control methods for D2D communications underlay cellular networks to increase the reuse of frequency ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	55,350
1312.6173	Multilingual Distributed Representations without Word Alignment	Distributed representations of meaning are a natural way to encode covariance relationships between words and phrases in NLP. By overcoming data sparsity problems, as well as providing information about semantic relatedness which is not available in discrete representations, distributed representations have proven usef...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	29,336
2311.17026	When the Few Outweigh the Many: Illicit Content Recognition with Few-Shot Learning	The anonymity and untraceability benefits of the Dark web account for the exponentially-increased potential of its popularity while creating a suitable womb for many illicit activities, to date. Hence, in collaboration with cybersecurity and law enforcement agencies, research has provided approaches for recognizing and...	false	false	false	false	true	false	true	false	false	false	false	true	true	true	false	false	false	false	411,124
2204.09833	Sample-Based Bounds for Coherent Risk Measures: Applications to Policy Synthesis and Verification	The dramatic increase of autonomous systems subject to variable environments has given rise to the pressing need to consider risk in both the synthesis and verification of policies for these systems. This paper aims to address a few problems regarding risk-aware verification and policy synthesis, by first developing a ...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	292,575
2401.12275	Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation	Social robot navigation can be helpful in various contexts of daily life but requires safe human-robot interactions and efficient trajectory planning. While modeling pairwise relations has been widely studied in multi-agent interacting systems, the ability to capture larger-scale group-wise activities is limited. In th...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	true	false	false	false	423,332
2308.10424	Attenuation and Loss of Spatial Coherence Modeling for Atmospheric Turbulence in Terahertz UAV MIMO Channels	Terahertz (THz) wireless communications have the potential to realize ultra-high-speed and secure data transfer with miniaturized devices for unmanned aerial vehicle (UAV) communications. The atmospheric turbulence due to random airflow leads to spatial inhomogeneity of the communication medium, which is yet missing in...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	386,721
2107.14735	Neural Relighting and Expression Transfer On Video Portraits	Photo-realistic video portrait reenactment benefits virtual production and numerous VR/AR experiences. The task remains challenging as the reenacted expression should match the source while the lighting should be adjustable to new environments. We present a neural relighting and expression transfer technique to transfe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	248,552
1811.10066	Predicting Gender from Iris Texture May Be Harder Than It Seems	Predicting gender from iris images has been reported by several researchers as an application of machine learning in biometrics. Recent works on this topic have suggested that the preponderance of the gender cues is located in the periocular region rather than in the iris texture itself. This paper focuses on teasing o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,397
1601.07059	Permutation codes, source coding and a generalisation of Bollob\'as-Lubell-Yamamoto-Meshalkin and Kraft inequalities	We develop a general framework to prove Kraft-type inequalities for prefix-free permutation codes for source coding with various notions of permutation code and prefix. We also show that the McMillan-type converse theorem in most of these cases does not hold, and give a general form of a counterexample. Our approach is...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,374
2403.09865	Safety-Critical Control for Autonomous Systems: Control Barrier Functions via Reduced-Order Models	Modern autonomous systems, such as flying, legged, and wheeled robots, are generally characterized by high-dimensional nonlinear dynamics, which presents challenges for model-based safety-critical control design. Motivated by the success of reduced-order models in robotics, this paper presents a tutorial on constructiv...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	437,940
2111.06181	Multilingual and Multilabel Emotion Recognition using Virtual Adversarial Training	Virtual Adversarial Training (VAT) has been effective in learning robust models under supervised and semi-supervised settings for both computer vision and NLP tasks. However, the efficacy of VAT for multilingual and multilabel text classification has not been explored before. In this work, we explore VAT for multilabel...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	266,010
2106.04428	Noise Conditional Flow Model for Learning the Super-Resolution Space	Fundamentally, super-resolution is ill-posed problem because a low-resolution image can be obtained from many high-resolution images. Recent studies for super-resolution cannot create diverse super-resolution images. Although SRFlow tried to account for ill-posed nature of the super-resolution by predicting multiple hi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	239,719
2212.13715	MyI-Net: Fully Automatic Detection and Quantification of Myocardial Infarction from Cardiovascular MRI Images	A "heart attack" or myocardial infarction (MI), occurs when an artery supplying blood to the heart is abruptly occluded. The "gold standard" method for imaging MI is Cardiovascular Magnetic Resonance Imaging (MRI), with intravenously administered gadolinium-based contrast (late gadolinium enhancement). However, no "gol...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	338,384
2202.11046	A policy gradient approach for optimization of smooth risk measures	We propose policy gradient algorithms for solving a risk-sensitive reinforcement learning (RL) problem in on-policy as well as off-policy settings. We consider episodic Markov decision processes, and model the risk using the broad class of smooth risk measures of the cumulative discounted reward. We propose two templat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	281,755
2305.09511	Limit-behavior of a hybrid evolutionary algorithm for the Hasofer-Lind reliability index problem	In probabilistic structural mechanics, the Hasofer-Lind reliability index problem is a paradigmatic equality constrained problem of searching for the minimum distance from a point to a surface. In practical engineering problems, such surface is defined implicitly, requiring the solution of a boundary-value problem. Rec...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	364,662
2312.04043	Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes	In this paper, we democratise 3D content creation, enabling precise generation of 3D shapes from abstract sketches while overcoming limitations tied to drawing skills. We introduce a novel part-level modelling and alignment framework that facilitates abstraction modelling and cross-modal correspondence. Leveraging the ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	413,523
2403.10156	Cardiac valve event timing in echocardiography using deep learning and triplane recordings	Cardiac valve event timing plays a crucial role when conducting clinical measurements using echocardiography. However, established automated approaches are limited by the need of external electrocardiogram sensors, and manual measurements often rely on timing from different cardiac cycles. Recent methods have applied d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,080
2103.03937	Sampled-Data Stabilization with Control Lyapunov Functions via Quadratically Constrained Quadratic Programs	Controller design for nonlinear systems with Control Lyapunov Function (CLF) based quadratic programs has recently been successfully applied to a diverse set of difficult control tasks. These existing formulations do not address the gap between design with continuous time models and the discrete time sampled implementa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	223,461
2412.10231	SuperGSeg: Open-Vocabulary 3D Segmentation with Structured Super-Gaussians	3D Gaussian Splatting has recently gained traction for its efficient training and real-time rendering. While the vanilla Gaussian Splatting representation is mainly designed for view synthesis, more recent works investigated how to extend it with scene understanding and language features. However, existing methods lack...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,835
1110.6739	The Binary Perfect Phylogeny with Persistent characters	The binary perfect phylogeny model is too restrictive to model biological events such as back mutations. In this paper we consider a natural generalization of the model that allows a special type of back mutation. We investigate the problem of reconstructing a near perfect phylogeny over a binary set of characters wher...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	12,828
2209.02679	Risk Aware Adaptive Belief-dependent Probabilistically Constrained Continuous POMDP Planning	Although risk awareness is fundamental to an online operating agent, it has received less attention in the challenging continuous domain and under partial observability. This paper presents a novel formulation and solution for risk-averse belief-dependent probabilistically constrained continuous POMDP. We tackle a dema...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	316,275
2109.13964	An Accelerated Stochastic Gradient for Canonical Polyadic Decomposition	We consider the problem of structured canonical polyadic decomposition. If the size of the problem is very big, then stochastic gradient approaches are viable alternatives to classical methods, such as Alternating Optimization and All-At-Once optimization. We extend a recent stochastic gradient approach by employing an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	257,803
2410.14604	Learning to Control the Smoothness of Graph Convolutional Network Features	The pioneering work of Oono and Suzuki [ICLR, 2020] and Cai and Wang [arXiv:2006.13318] initializes the analysis of the smoothness of graph convolutional network (GCN) features. Their results reveal an intricate empirical correlation between node classification accuracy and the ratio of smooth to non-smooth feature com...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	500,098
2204.14007	Searching for Efficient Neural Architectures for On-Device ML on Edge TPUs	On-device ML accelerators are becoming a standard in modern mobile system-on-chips (SoC). Neural architecture search (NAS) comes to the rescue for efficiently utilizing the high compute throughput offered by these accelerators. However, existing NAS frameworks have several practical limitations in scaling to multiple t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	294,025
2410.06013	Characterization of input-to-output stability for infinite dimensional systems	We prove a superposition theorem for input-to-output stability (IOS) of a broad class of nonlinear infinite-dimensional systems with outputs including both continuous-time and discrete-time systems. It contains, as a special case, the superposition theorem for input-to-state stability (ISS) of infinite-dimensional syst...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	496,013
2402.17447	Deep Learning Based Named Entity Recognition Models for Recipes	Food touches our lives through various endeavors, including flavor, nourishment, health, and sustainability. Recipes are cultural capsules transmitted across generations via unstructured text. Automated protocols for recognizing named entities, the building blocks of recipe text, are of immense value for various applic...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	432,995
2004.11836	Convolutional Neural Network Array for Sign Language Recognition using Wearable IMUs	Advancements in gesture recognition algorithms have led to a significant growth in sign language translation. By making use of efficient intelligent models, signs can be recognized with precision. The proposed work presents a novel one-dimensional Convolutional Neural Network (CNN) array architecture for recognition of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	174,037
2008.10728	Constructive Spherical Codes by Hopf Foliations	We present a new systematic approach to constructing spherical codes in dimensions $2^k$, based on Hopf foliations. Using the fact that a sphere $S^{2n-1}$ is foliated by manifolds $S_{\cos\eta}^{n-1} \times S_{\sin\eta}^{n-1}$, $\eta\in[0,\pi/2]$, we distribute points in dimension $2^k$ via a recursive algorithm from ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	193,069
2106.08229	MICo: Improved representations via sampling-based state similarity for Markov decision processes	We present a new behavioural distance over the state space of a Markov decision process, and demonstrate the use of this distance as an effective means of shaping the learnt representations of deep reinforcement learning agents. While existing notions of state similarity are typically difficult to learn at scale due to...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	241,225

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