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
2108.02267	A Method to use Nonlinear Dynamics in a Whisker Sensor for Terrain Identification by Mobile Robots	This paper shows analytical and experimental evidence of using the vibration dynamics of a compliant whisker for accurate terrain classification during steady state motion of a mobile robot. A Hall effect sensor was used to measure whisker vibrations due to perturbations from the ground. Analytical results predict that...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	249,264
2402.08348	Visually Dehallucinative Instruction Generation	In recent years, synthetic visual instructions by generative language model have demonstrated plausible text generation performance on the visual question-answering tasks. However, challenges persist in the hallucination of generative language models, i.e., the generated image-text data contains unintended contents. Th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	429,069
1601.06376	Throughput Maximization for Mobile Relaying Systems	This paper studies a novel mobile relaying technique, where relays of high mobility are employed to assist the communications from source to destination. By exploiting the predictable channel variations introduced by relay mobility, we study the throughput maximization problem in a mobile relaying system via dynamic ra...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,272
2309.14868	Cross-Dataset-Robust Method for Blind Real-World Image Quality Assessment	Although many effective models and real-world datasets have been presented for blind image quality assessment (BIQA), recent BIQA models usually tend to fit specific training set. Hence, it is still difficult to accurately and robustly measure the visual quality of an arbitrary real-world image. In this paper, a robust...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,768
1405.5978	Blockmodeling of multilevel networks	The article presents several approaches to the blockmodeling of multilevel network data. Multilevel network data consist of networks that are measured on at least two levels (e.g. between organizations and people) and information on ties between those levels (e.g. information on which people are members of which organi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	33,324
2407.09524	Geometric Understanding of Discriminability and Transferability for Visual Domain Adaptation	To overcome the restriction of identical distribution assumption, invariant representation learning for unsupervised domain adaptation (UDA) has made significant advances in computer vision and pattern recognition communities. In UDA scenario, the training and test data belong to different domains while the task model ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	472,617
2002.05721	A New Exocentric Metaphor for Complex Path Following to Control a UAV Using Mixed Reality	Teleoperation of Unmanned Aerial Vehicles (UAVs) has recently become an noteworthly research topic in the field of human robot interaction. Each year, a variety of devices is being studied to design adapted interface for diverse purpose such as view taking, search and rescue operation or suveillance. New interfaces hav...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	163,991
2010.03189	Theedhum Nandrum@Dravidian-CodeMix-FIRE2020: A Sentiment Polarity Classifier for YouTube Comments with Code-switching between Tamil, Malayalam and English	Theedhum Nandrum is a sentiment polarity detection system using two approaches--a Stochastic Gradient Descent (SGD) based classifier and a Long Short-term Memory (LSTM) based Classifier. Our approach utilises language features like use of emoji, choice of scripts and code mixing which appeared quite marked in the datas...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	199,316
2407.19667	Smart Language Agents in Real-World Planning	Comprehensive planning agents have been a long term goal in the field of artificial intelligence. Recent innovations in Natural Language Processing have yielded success through the advent of Large Language Models (LLMs). We seek to improve the travel-planning capability of such LLMs by extending upon the work of the pr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	476,874
2312.01816	Class Symbolic Regression: Gotta Fit 'Em All	We introduce 'Class Symbolic Regression' (Class SR) a first framework for automatically finding a single analytical functional form that accurately fits multiple datasets - each realization being governed by its own (possibly) unique set of fitting parameters. This hierarchical framework leverages the common constraint...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	412,601
1802.08949	OhioState at SemEval-2018 Task 7: Exploiting Data Augmentation for Relation Classification in Scientific Papers using Piecewise Convolutional Neural Networks	We describe our system for SemEval-2018 Shared Task on Semantic Relation Extraction and Classification in Scientific Papers where we focus on the Classification task. Our simple piecewise convolution neural encoder performs decently in an end to end manner. A simple inter-task data augmentation signifi- cantly boosts t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	91,229
1602.00363	INSQ: An Influential Neighbor Set Based Moving kNN Query Processing System	We revisit the moving k nearest neighbor (MkNN) query, which computes one's k nearest neighbor set and maintains it while at move. Existing MkNN algorithms are mostly safe region based, which lack efficiency due to either computing small safe regions with a high recomputation frequency or computing larger safe regions ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	51,567
2312.11420	Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning	This paper introduces an efficient strategy to transform Large Language Models (LLMs) into Multi-Modal Large Language Models (MLLMs). By conceptualizing this transformation as a domain adaptation process, i.e., transitioning from text understanding to embracing multiple modalities, we intriguingly note that, within eac...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	416,561
2209.00190	A Transferable Multi-stage Model with Cycling Discrepancy Learning for Lithium-ion Battery State of Health Estimation	As a significant ingredient regarding health status, data-driven state-of-health (SOH) estimation has become dominant for lithium-ion batteries (LiBs). To handle data discrepancy across batteries, current SOH estimation models engage in transfer learning (TL), which reserves apriori knowledge gained through reusing par...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	315,508
1909.11286	Stochastic Conditional Generative Networks with Basis Decomposition	While generative adversarial networks (GANs) have revolutionized machine learning, a number of open questions remain to fully understand them and exploit their power. One of these questions is how to efficiently achieve proper diversity and sampling of the multi-mode data space. To address this, we introduce BasisGAN, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	146,768
2202.10066	Multi-task Representation Learning with Stochastic Linear Bandits	We study the problem of transfer-learning in the setting of stochastic linear bandit tasks. We consider that a low dimensional linear representation is shared across the tasks, and study the benefit of learning this representation in the multi-task learning setting. Following recent results to design stochastic bandit ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	281,411
2111.05710	Object Servoing of Differential-Drive Robots	Due to possibly changing pose of a movable object and nonholonomic constraint of a differential-drive robot, it is challenging to design an object servoing scheme for the differential-drive robot to asymptotically park at a predefined relative pose to the movable object. In this paper, a novel object servoing scheme is...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	265,864
2206.05530	Memorization-Dilation: Modeling Neural Collapse Under Label Noise	The notion of neural collapse refers to several emergent phenomena that have been empirically observed across various canonical classification problems. During the terminal phase of training a deep neural network, the feature embedding of all examples of the same class tend to collapse to a single representation, and t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,039
2105.05542	!Qu\'e maravilla! Multimodal Sarcasm Detection in Spanish: a Dataset and a Baseline	We construct the first ever multimodal sarcasm dataset for Spanish. The audiovisual dataset consists of sarcasm annotated text that is aligned with video and audio. The dataset represents two varieties of Spanish, a Latin American variety and a Peninsular Spanish variety, which ensures a wider dialectal coverage for th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	234,847
2010.09413	Image Captioning with Visual Object Representations Grounded in the Textual Modality	We present our work in progress exploring the possibilities of a shared embedding space between textual and visual modality. Leveraging the textual nature of object detection labels and the hypothetical expressiveness of extracted visual object representations, we propose an approach opposite to the current trend, grou...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	201,528
1901.08152	Veridical Data Science	Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, comprised of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and tr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	119,392
1810.09000	Safe Adaptive Cruise Control with Road Grade Preview and V2V Communication	We present the design of a safe Adaptive Cruise Control (ACC) which uses road grade and lead vehicle motion preview. The ACC controller is designed by using a Model Predictive Control (MPC) framework to optimize comfort, safety, energy-efficiency and speed tracking accuracy. Safety is achieved by computing a robust inv...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	110,957
2302.03608	Online Reinforcement Learning with Uncertain Episode Lengths	Existing episodic reinforcement algorithms assume that the length of an episode is fixed across time and known a priori. In this paper, we consider a general framework of episodic reinforcement learning when the length of each episode is drawn from a distribution. We first establish that this problem is equivalent to o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	344,407
1610.00700	Footstep and Motion Planning in Semi-unstructured Environments Using Randomized Possibility Graphs	Traversing environments with arbitrary obstacles poses significant challenges for bipedal robots. In some cases, whole body motions may be necessary to maneuver around an obstacle, but most existing footstep planners can only select from a discrete set of predetermined footstep actions; they are unable to utilize the c...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	61,868
0907.3445	Investigating the Change of Web Pages' Titles Over Time	Inaccessible web pages are part of the browsing experience. The content of these pages however is often not completely lost but rather missing. Lexical signatures (LS) generated from the web pages' textual content have been shown to be suitable as search engine queries when trying to discover a (missing) web page. Sinc...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	4,136
2307.09146	PRO-Face S: Privacy-preserving Reversible Obfuscation of Face Images via Secure Flow	This paper proposes a novel paradigm for facial privacy protection that unifies multiple characteristics including anonymity, diversity, reversibility and security within a single lightweight framework. We name it PRO-Face S, short for Privacy-preserving Reversible Obfuscation of Face images via Secure flow-based model...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	380,069
2303.00408	A Persian Benchmark for Joint Intent Detection and Slot Filling	Natural Language Understanding (NLU) is important in today's technology as it enables machines to comprehend and process human language, leading to improved human-computer interactions and advancements in fields such as virtual assistants, chatbots, and language-based AI systems. This paper highlights the significance ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	348,586
2006.09158	G1020: A Benchmark Retinal Fundus Image Dataset for Computer-Aided Glaucoma Detection	Scarcity of large publicly available retinal fundus image datasets for automated glaucoma detection has been the bottleneck for successful application of artificial intelligence towards practical Computer-Aided Diagnosis (CAD). A few small datasets that are available for research community usually suffer from impractic...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	182,447
2211.06154	REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study	Explainable artificial intelligence is proposed to provide explanations for reasoning performed by an Artificial Intelligence. There is no consensus on how to evaluate the quality of these explanations, since even the definition of explanation itself is not clear in the literature. In particular, for the widely known L...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	329,801
2403.12580	Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection	Industrial anomaly detection (IAD) has garnered significant attention and experienced rapid development. However, the recent development of IAD approach has encountered certain difficulties due to dataset limitations. On the one hand, most of the state-of-the-art methods have achieved saturation (over 99% in AUROC) on ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	439,257
2405.05780	Neural Network Learning of Black-Scholes Equation for Option Pricing	One of the most discussed problems in the financial world is stock option pricing. The Black-Scholes Equation is a Parabolic Partial Differential Equation which provides an option pricing model. The present work proposes an approach based on Neural Networks to solve the Black-Scholes Equations. Real-world data from the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	453,054
1511.02459	SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception	In this paper, a novel face dataset with attractiveness ratings, namely, the SCUT-FBP dataset, is developed for automatic facial beauty perception. This dataset provides a benchmark to evaluate the performance of different methods for facial attractiveness prediction, including the state-of-the-art deep learning method...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,639
1605.03356	Dual of Codes over Finite Quotients of Polynomial Rings	Let $A=\frac{\mathbb{F}[x]}{\langle f(x)\rangle }$, where $f(x)$ is a monic polynomial over a finite field $\mathbb{F}$. In this paper, we study the relation between $A$-codes and their duals. In particular, we state a counterexample and a correction to a theorem of Berger and El Amrani (Codes over finite quotients of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,739
1907.05789	Generating Sentences from Disentangled Syntactic and Semantic Spaces	Variational auto-encoders (VAEs) are widely used in natural language generation due to the regularization of the latent space. However, generating sentences from the continuous latent space does not explicitly model the syntactic information. In this paper, we propose to generate sentences from disentangled syntactic a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	138,454
1803.02991	Disentangled Sequential Autoencoder	We present a VAE architecture for encoding and generating high dimensional sequential data, such as video or audio. Our deep generative model learns a latent representation of the data which is split into a static and dynamic part, allowing us to approximately disentangle latent time-dependent features (dynamics) from ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	92,172
2102.00277	Estimating galaxy masses from kinematics of globular cluster systems: a new method based on deep learning	We present a new method by which the total masses of galaxies including dark matter can be estimated from the kinematics of their globular cluster systems (GCSs). In the proposed method, we apply the convolutional neural networks (CNNs) to the two-dimensional (2D) maps of line-of-sight-velocities ($V$) and velocity dis...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	217,726
2404.02388	CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation	Deep Neural Networks (DNNs) are widely used for visual classification tasks, but their complex computation process and black-box nature hinder decision transparency and interpretability. Class activation maps (CAMs) and recent variants provide ways to visually explain the DNN decision-making process by displaying 'atte...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	443,833
cs/0610111	Local approximate inference algorithms	We present a new local approximation algorithm for computing Maximum a Posteriori (MAP) and log-partition function for arbitrary exponential family distribution represented by a finite-valued pair-wise Markov random field (MRF), say $G$. Our algorithm is based on decomposition of $G$ into {\em appropriately} chosen sma...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	539,802
2010.05529	PolyFrame: A Retargetable Query-based Approach to Scaling DataFrames (Extended Version)	In the last few years, the field of data science has been growing rapidly as various businesses have adopted statistical and machine learning techniques to empower their decision making and applications. Scaling data analysis, possibly including the application of custom machine learning models, to large volumes of dat...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	200,173
2008.08114	Commonsense Knowledge in Wikidata	Wikidata and Wikipedia have been proven useful for reason-ing in natural language applications, like question answering or entitylinking. Yet, no existing work has studied the potential of Wikidata for commonsense reasoning. This paper investigates whether Wikidata con-tains commonsense knowledge which is complementary...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	192,319
1710.02653	Increasing Availability in Distributed Storage Systems via Clustering	We introduce the Fixed Cluster Repair System (FCRS) as a novel architecture for Distributed Storage Systems (DSS), achieving a small repair bandwidth while guaranteeing a high availability. Specifically we partition the set of servers in a DSS into $s$ clusters and allow a failed server to choose any cluster other than...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	82,203
1805.11651	Splitting source code identifiers using Bidirectional LSTM Recurrent Neural Network	Programmers make rich use of natural language in the source code they write through identifiers and comments. Source code identifiers are selected from a pool of tokens which are strongly related to the meaning, naming conventions, and context. These tokens are often combined to produce more precise and obvious designa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	98,970
1909.01541	Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution	This paper studies the problem of cross-network node classification to overcome the insufficiency of labeled data in a single network. It aims to leverage the label information in a partially labeled source network to assist node classification in a completely unlabeled or partially labeled target network. Existing met...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	143,933
1910.09056	Amortized Rejection Sampling in Universal Probabilistic Programming	Naive approaches to amortized inference in probabilistic programs with unbounded loops can produce estimators with infinite variance. This is particularly true of importance sampling inference in programs that explicitly include rejection sampling as part of the user-programmed generative procedure. In this paper we de...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	150,056
2305.19065	Template-free Articulated Neural Point Clouds for Reposable View Synthesis	Dynamic Neural Radiance Fields (NeRFs) achieve remarkable visual quality when synthesizing novel views of time-evolving 3D scenes. However, the common reliance on backward deformation fields makes reanimation of the captured object poses challenging. Moreover, the state of the art dynamic models are often limited by lo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	369,359
2410.05317	Accelerating Diffusion Transformers with Token-wise Feature Caching	Diffusion transformers have shown significant effectiveness in both image and video synthesis at the expense of huge computation costs. To address this problem, feature caching methods have been introduced to accelerate diffusion transformers by caching the features in previous timesteps and reusing them in the followi...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	495,671
2311.12323	Modeling Political Orientation of Social Media Posts: An Extended Analysis	Developing machine learning models to characterize political polarization on online social media presents significant challenges. These challenges mainly stem from various factors such as the lack of annotated data, presence of noise in social media datasets, and the sheer volume of data. The common research practice t...	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	409,291
2310.07554	Retrieve Anything To Augment Large Language Models	Large language models (LLMs) face significant challenges stemming from their inherent limitations in knowledge, memory, alignment, and action. These challenges cannot be addressed by LLMs alone, but should rely on assistance from the external world, such as knowledge base, memory store, demonstration examples, and tool...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	399,017
2101.10838	Visible light communication-based monitoring for indoor environments using unsupervised learning	Visible Light Communication~(VLC) systems provide not only illumination and data communication, but also indoor monitoring services if the effect that different events create on the received optical signal is properly tracked. For this purpose, the Channel State Information that a VLC receiver computes to equalize the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	217,070
2007.04853	Identifying efficient controls of complex interaction networks using genetic algorithms	Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	186,493
2308.07921	Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification	Recent progress in large language models (LLMs) like GPT-4 and PaLM-2 has brought significant advancements in addressing math reasoning problems. In particular, OpenAI's latest version of GPT-4, known as GPT-4 Code Interpreter, shows remarkable performance on challenging math datasets. In this paper, we explore the eff...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	385,693
1906.06719	Dispersed Exponential Family Mixture VAEs for Interpretable Text Generation	Deep generative models are commonly used for generating images and text. Interpretability of these models is one important pursuit, other than the generation quality. Variational auto-encoder (VAE) with Gaussian distribution as prior has been successfully applied in text generation, but it is hard to interpret the mean...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	135,393
2402.08576	Regret Minimization in Stackelberg Games with Side Information	Algorithms for playing in Stackelberg games have been deployed in real-world domains including airport security, anti-poaching efforts, and cyber-crime prevention. However, these algorithms often fail to take into consideration the additional information available to each player (e.g. traffic patterns, weather conditio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	429,145
2205.10065	Approximate Dynamic Programming for Constrained Linear Systems: A Piecewise Quadratic Approximation Approach	Approximate dynamic programming (ADP) faces challenges in dealing with constraints in control problems. Model predictive control (MPC) is, in comparison, well-known for its accommodation of constraints and stability guarantees, although its computation is sometimes prohibitive. This paper introduces an approach combini...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	297,542
1901.00413	Lipi Gnani - A Versatile OCR for Documents in any Language Printed in Kannada Script	A Kannada OCR, named Lipi Gnani, has been designed and developed from scratch, with the motivation of it being able to convert printed text or poetry in Kannada script, without any restriction on vocabulary. The training and test sets have been collected from over 35 books published between the period 1970 to 2002, and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,769
0902.2788	Using SLP Neural Network to Persian Handwritten Digits Recognition	This paper has been withdrawn by the author ali pourmohammad.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	3,174
2003.00754	Plug-and-Play SLAM: A Unified SLAM Architecture for Modularity and Ease of Use	Nowadays, SLAM (Simultaneous Localization and Mapping) is considered by the Robotics community to be a mature field. Currently, there are many open-source systems that are able to deliver fast and accurate estimation in typical real-world scenarios. Still, all these systems often provide an ad-hoc implementation that e...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	166,405
1710.08756	EagleMine: Vision-Guided Mining in Large Graphs	Given a graph with millions of nodes, what patterns exist in the distributions of node characteristics, and how can we detect them and separate anomalous nodes in a way similar to human vision? In this paper, we propose a vision-guided algorithm, EagleMine, to summarize micro-cluster patterns in two-dimensional histogr...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	83,123
2312.03407	Extremal Fitting CQs do not Generalize	A fitting algorithm for conjunctive queries (CQs) produces, given a set of positively and negatively labeled data examples, a CQ that fits these examples. In general, there may be many non-equivalent fitting CQs and thus the algorithm has some freedom in producing its output. Additional desirable properties of the prod...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	413,244
2207.13332	RealTime QA: What's the Answer Right Now?	We introduce REALTIME QA, a dynamic question answering (QA) platform that announces questions and evaluates systems on a regular basis (weekly in this version). REALTIME QA inquires about the current world, and QA systems need to answer questions about novel events or information. It therefore challenges static, conven...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	310,272
1512.01027	Discrete Equilibrium Sampling with Arbitrary Nonequilibrium Processes	We present a novel framework for performing statistical sampling, expectation estimation, and partition function approximation using \emph{arbitrary} heuristic stochastic processes defined over discrete state spaces. Using a highly parallel construction we call the \emph{sequential constraining process}, we are able to...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	49,768
0902.0947	On the Gaussian MAC with Imperfect Feedback	New achievable rate regions are derived for the two-user additive white Gaussian multiple-access channel with noisy feedback. The regions exhibit the following two properties. Irrespective of the (finite) Gaussian feedback-noise variances, the regions include rate points that lie outside the no-feedback capacity region...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,114
1902.03487	A Quasi-static Model and Simulation Approach for Pushing, Grasping, and Jamming	Quasi-static models of robotic motion with frictional contact provide a computationally efficient framework for analysis and have been widely used for planning and control of non-prehensile manipulation. In this work, we present a novel quasi-static model of planar manipulation that directly maps commanded manipulator ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	121,118
1606.00128	Self-Paced Learning: an Implicit Regularization Perspective	Self-paced learning (SPL) mimics the cognitive mechanism of humans and animals that gradually learns from easy to hard samples. One key issue in SPL is to obtain better weighting strategy that is determined by minimizer function. Existing methods usually pursue this by artificially designing the explicit form of SPL re...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	56,633
1707.00081	Synthesizing Deep Neural Network Architectures using Biological Synaptic Strength Distributions	In this work, we perform an exploratory study on synthesizing deep neural networks using biological synaptic strength distributions, and the potential influence of different distributions on modelling performance particularly for the scenario associated with small data sets. Surprisingly, a CNN with convolutional layer...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	false	76,290
2408.10469	LSVOS Challenge 3rd Place Report: SAM2 and Cutie based VOS	Video Object Segmentation (VOS) presents several challenges, including object occlusion and fragmentation, the dis-appearance and re-appearance of objects, and tracking specific objects within crowded scenes. In this work, we combine the strengths of the state-of-the-art (SOTA) models SAM2 and Cutie to address these ch...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	481,862
2404.05468	Mind-to-Image: Projecting Visual Mental Imagination of the Brain from fMRI	The reconstruction of images observed by subjects from fMRI data collected during visual stimuli has made strong progress in the past decade, thanks to the availability of extensive fMRI datasets and advancements in generative models for image generation. However, the application of visual reconstruction has remained l...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	445,096
2210.12571	A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence	Explainable Artificial Intelligence (XAI) is a paradigm that delivers transparent models and decisions, which are easy to understand, analyze, and augment by a non-technical audience. Fuzzy Logic Systems (FLS) based XAI can provide an explainable framework, while also modeling uncertainties present in real-world enviro...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	325,800
2306.10790	Preserving Commonsense Knowledge from Pre-trained Language Models via Causal Inference	Fine-tuning has been proven to be a simple and effective technique to transfer the learned knowledge of Pre-trained Language Models (PLMs) to downstream tasks. However, vanilla fine-tuning easily overfits the target data and degrades the generalization ability. Most existing studies attribute it to catastrophic forgett...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	374,368
1809.02387	Improving On-policy Learning with Statistical Reward Accumulation	Deep reinforcement learning has obtained significant breakthroughs in recent years. Most methods in deep-RL achieve good results via the maximization of the reward signal provided by the environment, typically in the form of discounted cumulative returns. Such reward signals represent the immediate feedback of a partic...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	107,041
2501.01438	Toi uu hieu suat toc do dong co Servo DC su dung bo dieu khien PID ket hop mang no-ron	DC motors have been widely used in many industrial applications, from small jointed robots with multiple degrees of freedom to household appliances and transportation vehicles such as electric cars and trains. The main function of these motors is to ensure stable positioning performance and speed for mechanical systems...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	522,070
2111.04070	Em-K Indexing for Approximate Query Matching in Large-scale ER	Accurate and efficient entity resolution (ER) is a significant challenge in many data mining and analysis projects requiring integrating and processing massive data collections. It is becoming increasingly important in real-world applications to develop ER solutions that produce prompt responses for entity queries on l...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	265,369
2307.03884	Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization	Variational Quantum algorithms, especially Quantum Approximate Optimization and Variational Quantum Eigensolver (VQE) have established their potential to provide computational advantage in the realm of combinatorial optimization. However, these algorithms suffer from classically intractable gradients limiting the scala...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	378,189
1808.09060	An Investigation of the Interactions Between Pre-Trained Word Embeddings, Character Models and POS Tags in Dependency Parsing	We provide a comprehensive analysis of the interactions between pre-trained word embeddings, character models and POS tags in a transition-based dependency parser. While previous studies have shown POS information to be less important in the presence of character models, we show that in fact there are complex interacti...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	106,102
2502.09053	Game Theory Meets Large Language Models: A Systematic Survey	Game theory establishes a fundamental framework for analyzing strategic interactions among rational decision-makers. The rapid advancement of large language models (LLMs) has sparked extensive research exploring the intersection of these two fields. Specifically, game-theoretic methods are being applied to evaluate and...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	533,285
2106.11057	QuaPy: A Python-Based Framework for Quantification	QuaPy is an open-source framework for performing quantification (a.k.a. supervised prevalence estimation), written in Python. Quantification is the task of training quantifiers via supervised learning, where a quantifier is a predictor that estimates the relative frequencies (a.k.a. prevalence values) of the classes of...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	242,262
2305.11111	PPDONet: Deep Operator Networks for Fast Prediction of Steady-State Solutions in Disk-Planet Systems	We develop a tool, which we name Protoplanetary Disk Operator Network (PPDONet), that can predict the solution of disk-planet interactions in protoplanetary disks in real-time. We base our tool on Deep Operator Networks (DeepONets), a class of neural networks capable of learning non-linear operators to represent determ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	365,391
2004.03590	Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation	Many tasks in computer vision and graphics fall within the framework of conditional image synthesis. In recent years, generative adversarial nets (GANs) have delivered impressive advances in quality of synthesized images. However, it remains a challenge to generate both diverse and plausible images for the same input, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	true	171,616
2012.05510	SE-ECGNet: A Multi-scale Deep Residual Network with Squeeze-and-Excitation Module for ECG Signal Classification	The classification of electrocardiogram (ECG) signals, which takes much time and suffers from a high rate of misjudgment, is recognized as an extremely challenging task for cardiologists. The major difficulty of the ECG signals classification is caused by the long-term sequence dependencies. Most existing approaches fo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	210,809
2307.04494	Enabling Faster Locomotion of Planetary Rovers with a Mechanically-Hybrid Suspension	The exploration of the lunar poles and the collection of samples from the martian surface are characterized by shorter time windows demanding increased autonomy and speeds. Autonomous mobile robots must intrinsically cope with a wider range of disturbances. Faster off-road navigation has been explored for terrestrial a...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	378,422
1811.07502	Fast Efficient Object Detection Using Selective Attention	Retraction due to significant oversight	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,793
2305.17178	Rate-Splitting Multiple Access: Finite Constellations, Receiver Design, and SIC-free Implementation	Rate-Splitting Multiple Access (RSMA) has emerged as a novel multiple access technique that enlarges the achievable rate region of Multiple-Input Multiple-Output (MIMO) broadcast channels with linear precoding. In this work, we jointly address three practical but fundamental questions: (1) How to exploit the benefit of...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	368,444
1810.08179	Thermodynamics and Feature Extraction by Machine Learning	Machine learning methods are powerful in distinguishing different phases of matter in an automated way and provide a new perspective on the study of physical phenomena. We train a Restricted Boltzmann Machine (RBM) on data constructed with spin configurations sampled from the Ising Hamiltonian at different values of te...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,776
2402.13584	WinoViz: Probing Visual Properties of Objects Under Different States	Humans perceive and comprehend different visual properties of an object based on specific contexts. For instance, we know that a banana turns brown ``when it becomes rotten,'' whereas it appears green ``when it is unripe.'' Previous studies on probing visual commonsense knowledge have primarily focused on examining lan...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	431,322
2308.03594	FeatEnHancer: Enhancing Hierarchical Features for Object Detection and Beyond Under Low-Light Vision	Extracting useful visual cues for the downstream tasks is especially challenging under low-light vision. Prior works create enhanced representations by either correlating visual quality with machine perception or designing illumination-degrading transformation methods that require pre-training on synthetic datasets. We...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	384,096
1907.04060	Event-based attention and tracking on neuromorphic hardware	We present a fully event-driven vision and processing system for selective attention and tracking, realized on a neuromorphic processor Loihi interfaced to an event-based Dynamic Vision Sensor DAVIS. The attention mechanism is realized as a recurrent spiking neural network that implements attractor-dynamics of dynamic ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	138,009
1710.07782	Image Disguise based on Generative Model	To protect image contents, most existing encryption algorithms are designed to transform an original image into a texture-like or noise-like image, which is, however, an obvious visual sign indicating the presence of an encrypted image, results in a significantly large number of attacks. To solve this problem, in this ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	82,987
2304.03285	$\text{DC}^2$: Dual-Camera Defocus Control by Learning to Refocus	Smartphone cameras today are increasingly approaching the versatility and quality of professional cameras through a combination of hardware and software advancements. However, fixed aperture remains a key limitation, preventing users from controlling the depth of field (DoF) of captured images. At the same time, many s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,742
2111.11442	Scalar Gaussian Wiretap Channel with Peak Amplitude Constraint: Numerical Computation of the Optimal Input Distribution	This paper studies a scalar Gaussian wiretap channel where instead of an average input power constraint, we consider a peak amplitude constraint on the input. The goal is to obtain insights into the secrecy-capacity and the structure of the secrecy-capacity-achieving distribution. Capitalizing on the recent theoretical...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	267,673
1703.10570	The Impact of Crowds on News Engagement: A Reddit Case Study	Today, users are reading the news through social platforms. These platforms are built to facilitate crowd engagement, but not necessarily disseminate useful news to inform the masses. Hence, the news that is highly engaged with may not be the news that best informs. While predicting news popularity has been well studie...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	70,934
2012.15754	Limitations of Deep Neural Networks: a discussion of G. Marcus' critical appraisal of deep learning	Deep neural networks have triggered a revolution in artificial intelligence, having been applied with great results in medical imaging, semi-autonomous vehicles, ecommerce, genetics research, speech recognition, particle physics, experimental art, economic forecasting, environmental science, industrial manufacturing, a...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	213,893
2007.15293	A Heterogeneous Information Network based Cross Domain Insurance Recommendation System for Cold Start Users	Internet is changing the world, adapting to the trend of internet sales will bring revenue to traditional insurance companies. Online insurance is still in its early stages of development, where cold start problem (prospective customer) is one of the greatest challenges. In traditional e-commerce field, several cross-d...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	189,637
2108.06468	Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation	Aiming to alleviate data sparsity and cold-start problems of traditional recommender systems, incorporating knowledge graphs (KGs) to supplement auxiliary information has recently gained considerable attention. Via unifying the KG with user-item interactions into a tripartite graph, recent works explore the graph topol...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	250,606
1511.08887	On the Degrees of Freedom of the Symmetric Multi-Relay MIMO Y Channel	In this paper, we study the degrees of freedom (DoF) of the symmetric multi-relay multiple-input multiple-output (MIMO) Y channel, where three user nodes, each with M antennas, communicate via K geographically separated relay nodes, each with N antennas. For this model, we establish a general DoF achievability framewor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	49,589
1907.09554	Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning	Learning representations that can disentangle explanatory attributes underlying the data improves interpretabilty as well as provides control on data generation. Various learning frameworks such as VAEs, GANs and auto-encoders have been used in the literature to learn such representations. Most often, the latent space ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	139,392
1811.08286	Accelerating the Evolution of Convolutional Neural Networks with Node-Level Mutations and Epigenetic Weight Initialization	This paper examines three generic strategies for improving the performance of neuro-evolution techniques aimed at evolving convolutional neural networks (CNNs). These were implemented as part of the Evolutionary eXploration of Augmenting Convolutional Topologies (EXACT) algorithm. EXACT evolves arbitrary convolutional ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	114,003
2207.01072	Dynamic Sub-Cluster-Aware Network for Few-Shot Skin Disease Classification	This paper addresses the problem of few-shot skin disease classification by introducing a novel approach called the Sub-Cluster-Aware Network (SCAN) that enhances accuracy in diagnosing rare skin diseases. The key insight motivating the design of SCAN is the observation that skin disease images within a class often exh...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	306,024
2104.09428	AI supported Topic Modeling using KNIME-Workflows	Topic modeling algorithms traditionally model topics as list of weighted terms. These topic models can be used effectively to classify texts or to support text mining tasks such as text summarization or fact extraction. The general procedure relies on statistical analysis of term frequencies. The focus of this work is ...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	231,237
1305.4548	Distributed Learning of Distributions via Social Sampling	A protocol for distributed estimation of discrete distributions is proposed. Each agent begins with a single sample from the distribution, and the goal is to learn the empirical distribution of the samples. The protocol is based on a simple message-passing model motivated by communication in social networks. Agents sam...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	24,700
2305.19754	Sentence Simplification Using Paraphrase Corpus for Initialization	Neural sentence simplification method based on sequence-to-sequence framework has become the mainstream method for sentence simplification (SS) task. Unfortunately, these methods are currently limited by the scarcity of parallel SS corpus. In this paper, we focus on how to reduce the dependence on parallel corpus by le...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	369,673

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