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
1906.05062	Unified Semantic Parsing with Weak Supervision	Semantic parsing over multiple knowledge bases enables a parser to exploit structural similarities of programs across the multiple domains. However, the fundamental challenge lies in obtaining high-quality annotations of (utterance, program) pairs across various domains needed for training such models. To overcome this...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	134,918
2307.11729	OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples	Large Language Models (LLMs) have achieved human-level fluency in text generation, making it difficult to distinguish between human-written and LLM-generated texts. This poses a growing risk of misuse of LLMs and demands the development of detectors to identify LLM-generated texts. However, existing detectors lack robu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	381,003
2109.07260	Evaluation of Distributed Databases in Hybrid Clouds and Edge Computing: Energy, Bandwidth, and Storage Consumption	A benchmark study of modern distributed databases is an important source of information to select the right technology for managing data in the cloud-edge paradigms. To make the right decision, it is required to conduct an extensive experimental study on a variety of hardware infrastructures. While most of the state-of...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	255,456
2203.14155	How Do We Fail? Stress Testing Perception in Autonomous Vehicles	Autonomous vehicles (AVs) rely on environment perception and behavior prediction to reason about agents in their surroundings. These perception systems must be robust to adverse weather such as rain, fog, and snow. However, validation of these systems is challenging due to their complexity and dependence on observation...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	287,901
2405.07291	Robust Beamforming with Gradient-based Liquid Neural Network	Millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication with the advanced beamforming technologies is a key enabler to meet the growing demands of future mobile communication. However, the dynamic nature of cellular channels in large-scale urban mmWave MIMO communication scenarios brings substantia...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	453,652
2202.03400	Private Read Update Write (PRUW) with Storage Constrained Databases	We investigate the problem of private read update write (PRUW) in relation to federated submodel learning (FSL) with storage constrained databases. In PRUW, a user privately reads a submodel from a system of $N$ databases containing $M$ submodels, updates it locally, and writes the update back to the databases without ...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	279,190
2111.04157	Extractors: Low Entropy Requirements Colliding With Non-Malleability	The known constructions of negligible error (non-malleable) two-source extractors can be broadly classified in three categories: (1) Constructions where one source has min-entropy rate about $1/2$, the other source can have small min-entropy rate, but the extractor doesn't guarantee non-malleability. (2) Constructi...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	265,405
1705.00018	Stochastic Block Model Reveals the Map of Citation Patterns and Their Evolution in Time	In this study we map out the large-scale structure of citation networks of science journals and follow their evolution in time by using stochastic block models (SBMs). The SBM fitting procedures are principled methods that can be used to find hierarchical grouping of journals into blocks that show similar incoming and ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	72,613
1908.02571	Linking Physicians to Medical Research Results via Knowledge Graph Embeddings and Twitter	Informing professionals about the latest research results in their field is a particularly important task in the field of health care, since any development in this field directly improves the health status of the patients. Meanwhile, social media is an infrastructure that allows public instant sharing of information, ...	false	false	false	true	true	true	true	false	false	false	false	false	false	false	false	false	false	false	141,035
2004.03188	Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing	The Tsetlin Machine (TM) is a machine learning algorithm founded on the classical Tsetlin Automaton (TA) and game theory. It further leverages frequent pattern mining and resource allocation principles to extract common patterns in the data, rather than relying on minimizing output error, which is prone to overfitting....	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	171,481
2409.06445	Learning Generative Interactive Environments By Trained Agent Exploration	World models are increasingly pivotal in interpreting and simulating the rules and actions of complex environments. Genie, a recent model, excels at learning from visually diverse environments but relies on costly human-collected data. We observe that their alternative method of using random agents is too limited to ex...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	487,129
2405.06289	Look Once to Hear: Target Speech Hearing with Noisy Examples	In crowded settings, the human brain can focus on speech from a target speaker, given prior knowledge of how they sound. We introduce a novel intelligent hearable system that achieves this capability, enabling target speech hearing to ignore all interfering speech and noise, but the target speaker. A naive approach is ...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	453,245
1212.5352	On the Adaptability of Neural Network Image Super-Resolution	In this paper, we described and developed a framework for Multilayer Perceptron (MLP) to work on low level image processing, where MLP will be used to perform image super-resolution. Meanwhile, MLP are trained with different types of images from various categories, hence analyse the behaviour and performance of the neu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	20,543
2208.02205	Large-scale Building Damage Assessment using a Novel Hierarchical Transformer Architecture on Satellite Images	This paper presents \dahitra, a novel deep-learning model with hierarchical transformers to classify building damages based on satellite images in the aftermath of natural disasters. Satellite imagery provides real-time and high-coverage information and offers opportunities to inform large-scale post-disaster building ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	311,406
2012.08074	An exact solution in Markov decision process with multiplicative rewards as a general framework	We develop an exactly solvable framework of Markov decision process with a finite horizon, and continuous state and action spaces. We first review the exact solution of conventional linear quadratic regulation with a linear transition and a Gaussian noise, whose optimal policy does not depend on the Gaussian noise, whi...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	211,648
2111.00781	Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure	Multi-agent reinforcement learning (MARL) problems are challenging due to information asymmetry. To overcome this challenge, existing methods often require high level of coordination or communication between the agents. We consider two-agent multi-armed bandits (MABs) and Markov decision processes (MDPs) with a hierarc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	264,340
2407.08583	The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective	The rapid development of large language models (LLMs) has been witnessed in recent years. Based on the powerful LLMs, multi-modal LLMs (MLLMs) extend the modality from text to a broader spectrum of domains, attracting widespread attention due to the broader range of application scenarios. As LLMs and MLLMs rely on vast...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	472,224
1407.0822	Reducing Offline Evaluation Bias in Recommendation Systems	Recommendation systems have been integrated into the majority of large online systems. They tailor those systems to individual users by filtering and ranking information according to user profiles. This adaptation process influences the way users interact with the system and, as a consequence, increases the difficulty ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	34,370
1510.03353	Performance Analysis of Underlay Cognitive Radio Systems: Estimation-Throughput Tradeoff	In this letter, we study the performance of cognitive Underlay Systems (USs) that employ power control mechanism at the Secondary Transmitter (ST). Existing baseline models considered for the performance analysis either assume the knowledge of involved channels at the ST or retrieve this information by means of a feedb...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	47,830
2309.00369	Bayesian estimation and reconstruction of marine surface contaminant dispersion	Discharge of hazardous substances into the marine environment poses a substantial risk to both public health and the ecosystem. In such incidents, it is imperative to accurately estimate the release strength of the source and reconstruct the spatio-temporal dispersion of the substances based on the collected measuremen...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	389,288
1804.05990	Learning Joint Semantic Parsers from Disjoint Data	We present a new approach to learning semantic parsers from multiple datasets, even when the target semantic formalisms are drastically different, and the underlying corpora do not overlap. We handle such "disjoint" data by treating annotations for unobserved formalisms as latent structured variables. Building on state...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	95,195
2404.10772	Gaussian Opacity Fields: Efficient Adaptive Surface Reconstruction in Unbounded Scenes	Recently, 3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis results, while allowing the rendering of high-resolution images in real-time. However, leveraging 3D Gaussians for surface reconstruction poses significant challenges due to the explicit and disconnected nature of 3D Gaussians. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	447,246
2209.11223	UniColor: A Unified Framework for Multi-Modal Colorization with Transformer	We propose the first unified framework UniColor to support colorization in multiple modalities, including both unconditional and conditional ones, such as stroke, exemplar, text, and even a mix of them. Rather than learning a separate model for each type of condition, we introduce a two-stage colorization framework for...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	319,115
1905.11590	A Review of Semi Supervised Learning Theories and Recent Advances	Semi-supervised learning, which has emerged from the beginning of this century, is a new type of learning method between traditional supervised learning and unsupervised learning. The main idea of semi-supervised learning is to introduce unlabeled samples into the model training process to avoid performance (or model) ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,475
2412.09564	Improving the Reliability of Cable Broadband Networks via Proactive Network Maintenance	Cable broadband networks are one of the few "last-mile" broadband technologies widely available in the U.S. Unfortunately, they have poor reliability after decades of deployment. The cable industry proposed a framework called Proactive Network Maintenance (PNM) to diagnose the cable networks. However, there is little p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	516,529
2412.04665	ProPLIKS: Probablistic 3D human body pose estimation	We present a novel approach for 3D human pose estimation by employing probabilistic modeling. This approach leverages the advantages of normalizing flows in non-Euclidean geometries to address uncertain poses. Specifically, our method employs normalizing flow tailored to the SO(3) rotational group, incorporating a coup...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,507
1910.13466	Ordered Memory	Stack-augmented recurrent neural networks (RNNs) have been of interest to the deep learning community for some time. However, the difficulty of training memory models remains a problem obstructing the widespread use of such models. In this paper, we propose the Ordered Memory architecture. Inspired by Ordered Neurons (...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	151,397
2310.19590	Operator Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Characterized by Sharp Solutions	Physics-informed Neural Networks (PINNs) have been shown as a promising approach for solving both forward and inverse problems of partial differential equations (PDEs). Meanwhile, the neural operator approach, including methods such as Deep Operator Network (DeepONet) and Fourier neural operator (FNO), has been introdu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	404,050
2409.09354	PeriGuru: A Peripheral Robotic Mobile App Operation Assistant based on GUI Image Understanding and Prompting with LLM	Smartphones have significantly enhanced our daily learning, communication, and entertainment, becoming an essential component of modern life. However, certain populations, including the elderly and individuals with disabilities, encounter challenges in utilizing smartphones, thus necessitating mobile app operation assi...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	488,286
2007.04796	Training of Deep Learning Neuro-Skin Neural Network	In this brief paper, a learning algorithm is developed for Deep Learning Neuro-Skin Neural Network to improve their learning properties. Neuroskin is a new type of neural network presented recently by the authors. It is comprised of a cellular membrane which has a neuron attached to each cell. The neuron is the cells n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	186,478
2112.05536	Rapid manufacturing of color-based hemispherical soft tactile fingertips	Tactile sensing can provide access to information about the contact (i.e. slippage, surface feature, friction), which is out of reach of vision but crucial for manipulation. To access this information, a dense measurement of the deformation of soft fingertips is necessary. Recently, tactile sensors that rely on a camer...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	270,871
2311.11483	A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records	Foundation models hold promise for transforming AI in healthcare by providing modular components that are easily adaptable to downstream healthcare tasks, making AI development more scalable and cost-effective. Structured EHR foundation models, trained on coded medical records from millions of patients, demonstrated be...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	408,965
1909.08549	Knowledge representation and diagnostic inference using Bayesian networks in the medical discourse	For the diagnostic inference under uncertainty Bayesian networks are investigated. The method is based on an adequate uniform representation of the necessary knowledge. This includes both generic and experience-based specific knowledge, which is stored in a knowledge base. For knowledge processing, a combination of the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	146,004
2406.01375	D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models	Continual Pre-Training (CPT) on Large Language Models (LLMs) has been widely used to expand the model's fundamental understanding of specific downstream domains (e.g., math and code). For the CPT on domain-specific LLMs, one important question is how to choose the optimal mixture ratio between the general-corpus (e.g.,...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	460,287
2210.00166	Automated segmentation of microvessels in intravascular OCT images using deep learning	To analyze this characteristic of vulnerability, we developed an automated deep learning method for detecting microvessels in intravascular optical coherence tomography (IVOCT) images. A total of 8,403 IVOCT image frames from 85 lesions and 37 normal segments were analyzed. Manual annotation was done using a dedicated ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	320,760
2401.15668	Lips Are Lying: Spotting the Temporal Inconsistency between Audio and Visual in Lip-Syncing DeepFakes	In recent years, DeepFake technology has achieved unprecedented success in high-quality video synthesis, but these methods also pose potential and severe security threats to humanity. DeepFake can be bifurcated into entertainment applications like face swapping and illicit uses such as lip-syncing fraud. However, lip-f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,541
2111.13981	Kilometer-scale autonomous navigation in subarctic forests: challenges and lessons learned	Challenges inherent to autonomous wintertime navigation in forests include lack of reliable a Global Navigation Satellite System (GNSS) signal, low feature contrast, high illumination variations and changing environment. This type of off-road environment is an extreme case of situations autonomous cars could encounter ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	268,451
1909.04724	CalBehav: A Machine Learning based Personalized Calendar Behavioral Model using Time-Series Smartphone Data	The electronic calendar is a valuable resource nowadays for managing our daily life appointments or schedules, also known as events, ranging from professional to highly personal. Researchers have studied various types of calendar events to predict smartphone user behavior for incoming mobile communications. However, th...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	144,875
2311.07217	Troubles and Failures in Interactional Language. Towards a Linguistically Informed Taxonomy	The goal of this talk is to introduce a systematic research agenda which aims to understand the nature of interaction between humans and artificial conversational agents (CA) (henceforth humanmachine interaction, HMI). Specifically, we shall take an explicit linguistic perspective focusing on linguistically defined var...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	407,244
2104.03313	SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks	We present SCANimate, an end-to-end trainable framework that takes raw 3D scans of a clothed human and turns them into an animatable avatar. These avatars are driven by pose parameters and have realistic clothing that moves and deforms naturally. SCANimate does not rely on a customized mesh template or surface mesh reg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	229,030
2303.05267	Quantum memory error correction computation based on Chamon model	Quantum error correction codes play a central role in the realisation of fault-tolerant quantum computing. Chamon model is a 3D generalization of the toric code. The error correction computation on this model has not been explored so far. In this work, the Chamon model is turned to a non-CSS error correction code. Logi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	350,404
2410.17143	Empowering the Grid: Decentralized Autonomous Control for Effective Utilization and Resilience	With the emergence of low-inertia microgrids powered by inverter-based generation, there remains a concern about the operational resilience of these systems. Grid-forming inverters (GFMs), enabled by various device-level (primary) and system-level (secondary) control methods, are poised to play a significant role in ac...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	501,328
2102.02413	On Single-User Interactive Beam Alignment in Millimeter Wave Systems: Impact of Feedback Delay	Narrow beams are key to wireless communications in millimeter wave frequency bands. Beam alignment (BA) allows the base station (BS) to adjust the direction and width of the beam used for communication. During BA, the BS transmits a number of scanning beams covering different angular regions. The goal is to minimize th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	218,400
1401.2113	Latent Sentiment Detection in Online Social Networks: A Communications-oriented View	In this paper, we consider the problem of latent sentiment detection in Online Social Networks such as Twitter. We demonstrate the benefits of using the underlying social network as an Ising prior to perform network aided sentiment detection. We show that the use of the underlying network results in substantially lower...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	29,715
2402.18703	Zero-error communication under discrete-time Markovian dynamics	Consider an open quantum system with (discrete-time) Markovian dynamics. Our task is to store information in the system in such a way that it can be retrieved perfectly, even after the system is left to evolve for an arbitrarily long time. We show that this is impossible for classical (resp. quantum) information precis...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	433,525
2302.03323	Towards Efficient Trajectory Generation for Ground Robots beyond 2D Environment	With the development of robotics, ground robots are no longer limited to planar motion. Passive height variation due to complex terrain and active height control provided by special structures on robots require a more general navigation planning framework beyond 2D. Existing methods rarely considers both simultaneously...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	344,302
2212.00059	Single Slice Thigh CT Muscle Group Segmentation with Domain Adaptation and Self-Training	Objective: Thigh muscle group segmentation is important for assessment of muscle anatomy, metabolic disease and aging. Many efforts have been put into quantifying muscle tissues with magnetic resonance (MR) imaging including manual annotation of individual muscles. However, leveraging publicly available annotations in ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	333,935
1810.00204	Stochastic 2-D Motion Planning with a POMDP Framework	Motion planning is challenging when it comes to the case of imperfect state information. Decision should be made based on belief state which evolves according to the noise from the system dynamics and sensor measurement. In this paper, we propose the QV-Tree Search algorithm which combines the state-of-art offline and ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	109,119
1803.00233	Scalable Dense Non-rigid Structure-from-Motion: A Grassmannian Perspective	This paper addresses the task of dense non-rigid structure-from-motion (NRSfM) using multiple images. State-of-the-art methods to this problem are often hurdled by scalability, expensive computations, and noisy measurements. Further, recent methods to NRSfM usually either assume a small number of sparse feature points ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	91,634
2307.13466	Integrating processed-based models and machine learning for crop yield prediction	Crop yield prediction typically involves the utilization of either theory-driven process-based crop growth models, which have proven to be difficult to calibrate for local conditions, or data-driven machine learning methods, which are known to require large datasets. In this work we investigate potato yield prediction ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	381,595
2303.14453	Federated Learning without Full Labels: A Survey	Data privacy has become an increasingly important concern in real-world big data applications such as machine learning. To address the problem, federated learning (FL) has been a promising solution to building effective machine learning models from decentralized and private data. Existing federated learning algorithms ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	354,100
1608.03374	Automatic text extraction and character segmentation using maximally stable extremal regions	Text detection and segmentation is an important prerequisite for many content based image analysis tasks. The paper proposes a novel text extraction and character segmentation algorithm using Maximally Stable Extremal Regions as basic letter candidates. These regions are then subjected to thresholding and thereafter va...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,668
2112.01360	Probabilistic Approach for Road-Users Detection	Object detection in autonomous driving applications implies that the detection and tracking of semantic objects are commonly native to urban driving environments, as pedestrians and vehicles. One of the major challenges in state-of-the-art deep-learning based object detection are false positives which occur with overco...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	269,457
2401.15910	Correction to "Private Information Retrieval Over Gaussian MAC"	In the above article \cite{shmuel2021private}, the authors introduced a PIR scheme for the Additive White Gaussian Noise (AWGN) Multiple Access Channel (MAC), both with and without fading. The authors utilized the additive nature of the channel and leveraged the linear properties and structure of lattice codes to retri...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	424,642
2410.23962	Image Synthesis with Class-Aware Semantic Diffusion Models for Surgical Scene Segmentation	Surgical scene segmentation is essential for enhancing surgical precision, yet it is frequently compromised by the scarcity and imbalance of available data. To address these challenges, semantic image synthesis methods based on generative adversarial networks and diffusion models have been developed. However, these mod...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	504,268
2202.06498	Task-Adaptive Feature Transformer with Semantic Enrichment for Few-Shot Segmentation	Few-shot learning allows machines to classify novel classes using only a few labeled samples. Recently, few-shot segmentation aiming at semantic segmentation on low sample data has also seen great interest. In this paper, we propose a learnable module that can be placed on top of existing segmentation networks for perf...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	280,245
2407.01471	Tracking the 2024 US Presidential Election Chatter on Tiktok: A Public Multimodal Dataset	This paper documents our release of a large-scale data collection of TikTok posts related to the upcoming 2024 U.S. Presidential Election. Our current data comprises 1.8 million videos published between November 1, 2023, and May 26, 2024. Its exploratory analysis identifies the most common keywords, hashtags, and bigra...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	469,313
2008.07338	Predicting United States policy outcomes with Random Forests	Two decades of U.S. government legislative outcomes, as well as the policy preferences of rich people, the general population, and diverse interest groups, were captured in a detailed dataset curated and analyzed by Gilens, Page et al. (2014). They found that the preferences of the rich correlated strongly with policy ...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	192,077
2111.13185	Learning Conditional Invariance through Cycle Consistency	Identifying meaningful and independent factors of variation in a dataset is a challenging learning task frequently addressed by means of deep latent variable models. This task can be viewed as learning symmetry transformations preserving the value of a chosen property along latent dimensions. However, existing approach...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	268,217
2308.12964	Dense Text-to-Image Generation with Attention Modulation	Existing text-to-image diffusion models struggle to synthesize realistic images given dense captions, where each text prompt provides a detailed description for a specific image region. To address this, we propose DenseDiffusion, a training-free method that adapts a pre-trained text-to-image model to handle such dense ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	387,736
2502.09970	Universal Machine Learning Interatomic Potentials are Ready for Solid Ion Conductors	With the rapid development of energy storage technology, high-performance solid-state electrolytes (SSEs) have become critical for next-generation lithium-ion batteries. These materials require high ionic conductivity, excellent electrochemical stability, and good mechanical properties to meet the demands of electric v...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	533,684
2306.17690	Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering	Dictionary learning is an effective tool for pattern recognition and classification of time series data. Among various dictionary learning techniques, the dynamic time warping (DTW) is commonly used for dealing with temporal delays, scaling, transformation, and many other kinds of temporal misalignments issues. However...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	376,783
2402.11819	Head-wise Shareable Attention for Large Language Models	Large Language Models (LLMs) suffer from huge number of parameters, which restricts their deployment on edge devices. Weight sharing is one promising solution that encourages weight reuse, effectively reducing memory usage with less performance drop. However, current weight sharing techniques primarily focus on small-s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	430,587
2502.02067	AdaptBot: Combining LLM with Knowledge Graphs and Human Input for Generic-to-Specific Task Decomposition and Knowledge Refinement	Embodied agents assisting humans are often asked to complete a new task in a new scenario. An agent preparing a particular dish in the kitchen based on a known recipe may be asked to prepare a new dish or to perform cleaning tasks in the storeroom. There may not be sufficient resources, e.g., time or labeled examples, ...	false	false	false	false	true	false	true	true	true	false	false	false	false	false	false	false	false	false	530,167
1311.5998	A brief network analysis of Artificial Intelligence publication	In this paper, we present an illustration to the history of Artificial Intelligence(AI) with a statistical analysis of publish since 1940. We collected and mined through the IEEE publish data base to analysis the geological and chronological variance of the activeness of research in AI. The connections between differen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	28,604
2104.05239	Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation	Tremendous efforts have been made on instance segmentation but the mask quality is still not satisfactory. The boundaries of predicted instance masks are usually imprecise due to the low spatial resolution of feature maps and the imbalance problem caused by the extremely low proportion of boundary pixels. To address th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	229,652
2111.06364	Open Data Fabric: A Decentralized Data Exchange and Transformation Protocol With Complete Reproducibility and Provenance	Data is the most powerful decision-making tool at our disposal. However, despite the exponentially growing volumes of data generated in the world, putting it to effective use still presents many challenges. Relevant data seems to be never there when it is needed - it remains siloed, hard to find, hard to access, outdat...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	266,051
1909.05024	Learning to Propagate for Graph Meta-Learning	Meta-learning extracts common knowledge from learning different tasks and uses it for unseen tasks. It can significantly improve tasks that suffer from insufficient training data, e.g., few shot learning. In most meta-learning methods, tasks are implicitly related by sharing parameters or optimizer. In this paper, we s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	144,973
2104.04238	Legged Robot State Estimation in Slippery Environments Using Invariant Extended Kalman Filter with Velocity Update	This paper proposes a state estimator for legged robots operating in slippery environments. An Invariant Extended Kalman Filter (InEKF) is implemented to fuse inertial and velocity measurements from a tracking camera and leg kinematic constraints. {\color{black}The misalignment between the camera and the robot-frame is...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	229,334
1401.4589	miRNA and Gene Expression based Cancer Classification using Self- Learning and Co-Training Approaches	miRNA and gene expression profiles have been proved useful for classifying cancer samples. Efficient classifiers have been recently sought and developed. A number of attempts to classify cancer samples using miRNA/gene expression profiles are known in literature. However, the use of semi-supervised learning models have...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	30,086
2406.15958	Bone Fracture Classification using Transfer Learning	The manual examination of X-ray images for fractures is a time-consuming process that is prone to human error. In this work, we introduce a robust yet simple training loop for the classification of fractures, which significantly outperforms existing methods. Our method achieves superior performance in less than ten epo...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	466,935
2112.04591	Variational Regularization in Inverse Problems and Machine Learning	This paper discusses basic results and recent developments on variational regularization methods, as developed for inverse problems. In a typical setup we review basic properties needed to obtain a convergent regularization scheme and further discuss the derivation of quantitative estimates respectively needed ingredie...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	270,574
1612.06138	Boosting Neural Machine Translation	Training efficiency is one of the main problems for Neural Machine Translation (NMT). Deep networks need for very large data as well as many training iterations to achieve state-of-the-art performance. This results in very high computation cost, slowing down research and industrialisation. In this paper, we propose to ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	65,781
2003.09855	TanhExp: A Smooth Activation Function with High Convergence Speed for Lightweight Neural Networks	Lightweight or mobile neural networks used for real-time computer vision tasks contain fewer parameters than normal networks, which lead to a constrained performance. In this work, we proposed a novel activation function named Tanh Exponential Activation Function (TanhExp) which can improve the performance for these ne...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	169,164
1703.10772	Joining Hands: Exploiting Monolingual Treebanks for Parsing of Code-mixing Data	In this paper, we propose efficient and less resource-intensive strategies for parsing of code-mixed data. These strategies are not constrained by in-domain annotations, rather they leverage pre-existing monolingual annotated resources for training. We show that these methods can produce significantly better results as...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	70,975
2309.06844	Gpachov at CheckThat! 2023: A Diverse Multi-Approach Ensemble for Subjectivity Detection in News Articles	The wide-spread use of social networks has given rise to subjective, misleading, and even false information on the Internet. Thus, subjectivity detection can play an important role in ensuring the objectiveness and the quality of a piece of information. This paper presents the solution built by the Gpachov team for the...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	391,568
1511.07677	A robust extension to the triple plane pressure mode matching method by filtering convective perturbations	Time-periodic CFD simulations are widely used to investigate turbomachinery components. The triple-plane pressure mode matching method (TPP) developed by Ovenden and Rienstra extracts the acoustic part in such simulations. Experience shows that this method is subject to significant errors when the amplitude of pseudo-s...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	49,460
2310.14777	Geographical Erasure in Language Generation	Large language models (LLMs) encode vast amounts of world knowledge. However, since these models are trained on large swaths of internet data, they are at risk of inordinately capturing information about dominant groups. This imbalance can propagate into generated language. In this work, we study and operationalise a f...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	402,016
2403.09305	Pushing in the Dark: A Reactive Pushing Strategy for Mobile Robots Using Tactile Feedback	For mobile robots, navigating cluttered or dynamic environments often necessitates non-prehensile manipulation, particularly when faced with objects that are too large, irregular, or fragile to grasp. The unpredictable behavior and varying physical properties of these objects significantly complicate manipulation tasks...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	437,715
2002.03329	Better Theory for SGD in the Nonconvex World	Large-scale nonconvex optimization problems are ubiquitous in modern machine learning, and among practitioners interested in solving them, Stochastic Gradient Descent (SGD) reigns supreme. We revisit the analysis of SGD in the nonconvex setting and propose a new variant of the recently introduced expected smoothness as...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	163,233
1805.03435	Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks	Experimental evidence indicates that simple models outperform complex deep networks on many unsupervised similarity tasks. We provide a simple yet rigorous explanation for this behaviour by introducing the concept of an optimal representation space, in which semantically close symbols are mapped to representations that...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	97,052
2012.06919	Offline Policy Selection under Uncertainty	The presence of uncertainty in policy evaluation significantly complicates the process of policy ranking and selection in real-world settings. We formally consider offline policy selection as learning preferences over a set of policy prospects given a fixed experience dataset. While one can select or rank policies base...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	211,270
1404.1972	Regularization for Design	When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given. The task of designing this architecture is now as important as the design of the control laws themselves....	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	32,160
2308.03417	PURL: Safe and Effective Sanitization of Link Decoration	While privacy-focused browsers have taken steps to block third-party cookies and mitigate browser fingerprinting, novel tracking techniques that can bypass existing countermeasures continue to emerge. Since trackers need to share information from the client-side to the server-side through link decoration regardless of ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	384,033
1701.06331	Higher-order models capture changes in controllability of temporal networks	In many complex systems, elements interact via time-varying network topologies. Recent research shows that temporal correlations in the chronological ordering of interactions crucially influence network properties and dynamical processes. How these correlations affect our ability to control systems with time-varying in...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	67,114
1309.6301	Solving OSCAR regularization problems by proximal splitting algorithms	The OSCAR (octagonal selection and clustering algorithm for regression) regularizer consists of a L_1 norm plus a pair-wise L_inf norm (responsible for its grouping behavior) and was proposed to encourage group sparsity in scenarios where the groups are a priori unknown. The OSCAR regularizer has a non-trivial proximit...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	27,235
2101.10002	Securing Full-Duplex Amplify-and-Forward Relay-Aided Transmissions Through Processing-Time Optimization	We investigate physical-layer security of the full-duplex (FD) amplify-and-forward (AF) relay channel. We provide a new perspective on the problem and show that the processing time (delay) at the relay can be exploited to improve the system's security. We show that the FD AF relay channel can be seen as an intersymbol-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	216,789
2410.01984	A Preventive-Corrective Scheme for Ensuring Power System Security During Active Wildfire Risks	The focus of this paper is on operating the electric power grid in a secure manner when wildfire risks are high. This is a challenging problem because of the uncertain ways in which the fires can impact the operation of the power system. To address this challenge, we propose a novel preventive-corrective coordinated de...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	494,044
2110.10575	SocialVisTUM: An Interactive Visualization Toolkit for Correlated Neural Topic Models on Social Media Opinion Mining	Recent research in opinion mining proposed word embedding-based topic modeling methods that provide superior coherence compared to traditional topic modeling. In this paper, we demonstrate how these methods can be used to display correlated topic models on social media texts using SocialVisTUM, our proposed interactive...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	262,203
1506.01911	Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video	Recent studies have demonstrated the power of recurrent neural networks for machine translation, image captioning and speech recognition. For the task of capturing temporal structure in video, however, there still remain numerous open research questions. Current research suggests using a simple temporal feature pooling...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	43,835
1406.7128	On a new formulation of nonlocal image filters involving the relative rearrangement	Nonlocal filters are simple and powerful techniques for image denoising. In this paper we study the reformulation of a broad class of nonlocal filters in terms of two functional rearrangements: the decreasing and the relative rearrangements. Independently of the dimension of the image, we reformulate these filters as...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	34,187
1706.09395	Recovery of Missing Samples Using Sparse Approximation via a Convex Similarity Measure	In this paper, we study the missing sample recovery problem using methods based on sparse approximation. In this regard, we investigate the algorithms used for solving the inverse problem associated with the restoration of missed samples of image signal. This problem is also known as inpainting in the context of image ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	76,133
2202.00882	MPVNN: Mutated Pathway Visible Neural Network Architecture for Interpretable Prediction of Cancer-specific Survival Risk	Survival risk prediction using gene expression data is important in making treatment decisions in cancer. Standard neural network (NN) survival analysis models are black boxes with lack of interpretability. More interpretable visible neural network (VNN) architectures are designed using biological pathway knowledge. Bu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,295
2003.05259	Capturing document context inside sentence-level neural machine translation models with self-training	Neural machine translation (NMT) has arguably achieved human level parity when trained and evaluated at the sentence-level. Document-level neural machine translation has received less attention and lags behind its sentence-level counterpart. The majority of the proposed document-level approaches investigate ways of con...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	167,820
1905.03670	S4L: Self-Supervised Semi-Supervised Learning	This work tackles the problem of semi-supervised learning of image classifiers. Our main insight is that the field of semi-supervised learning can benefit from the quickly advancing field of self-supervised visual representation learning. Unifying these two approaches, we propose the framework of self-supervised semi-s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	130,249
2002.09843	An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning	Although federated learning improves privacy of training data by exchanging local gradients or parameters rather than raw data, the adversary still can leverage local gradients and parameters to obtain local training data by launching reconstruction and membership inference attacks. To defend such privacy attacks, many...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	165,202
2204.01721	Meta-Learning Approaches for a One-Shot Collective-Decision Aggregation: Correctly Choosing how to Choose Correctly	Aggregating successfully the choices regarding a given decision problem made by the multiple collective members into a single solution is essential for exploiting the collective's intelligence and for effective crowdsourcing. There are various aggregation techniques, some of which come down to a simple and sometimes ef...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	289,707
2305.19455	Implementation of a framework for deploying AI inference engines in FPGAs	The LCLS2 Free Electron Laser FEL will generate xray pulses to beamline experiments at up to 1Mhz These experimentals will require new ultrahigh rate UHR detectors that can operate at rates above 100 kHz and generate data throughputs upwards of 1 TBs a data velocity which requires prohibitively large investments in sto...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	369,531
2303.08513	On the number of subproblem iterations per coupling step in partitioned fluid-structure interaction simulations	In literature, the cost of a partitioned fluid-structure interaction scheme is typically assessed by the number of coupling iterations required per time step, while ignoring the internal iterations within the nonlinear subproblems. In this work, we demonstrate that these internal iterations have a significant influence...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	351,671
2411.17559	Degrees of Freedom of Cache-Aided Interference Channels Assisted by Active Intelligent Reflecting Surfaces	This paper studies cache-aided wireless networks in the presence of active intelligent reflecting surfaces (IRS) from an information-theoretic perspective. Specifically, we explore interference management in a cache-aided wireless network assisted by an active IRS, to enhance the achievable degrees of freedom (DoF). To...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	511,500

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