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
2202.12065	Activation Functions: Dive into an optimal activation function	Activation functions have come up as one of the essential components of neural networks. The choice of adequate activation function can impact the accuracy of these methods. In this study, we experiment for finding an optimal activation function by defining it as a weighted sum of existing activation functions and then...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	282,098
2404.13984	RHanDS: Refining Malformed Hands for Generated Images with Decoupled Structure and Style Guidance	Although diffusion models can generate high-quality human images, their applications are limited by the instability in generating hands with correct structures. Some previous works mitigate the problem by considering hand structure yet struggle to maintain style consistency between refined malformed hands and other ima...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	448,524
2007.03065	A Boolean Control Network Approach to the Formal Verification of Feedback Context-Aware Pervasive Systems	The emergence of Context-aware systems in the domains of autonomic, monitoring, and safety-critical applications asks for the definition of methods to formally assess their correctness and dependability properties. Many of these properties are common to Automatic Control systems, a field that developed well established...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	185,935
2301.10057	Planar Object Tracking via Weighted Optical Flow	We propose WOFT -- a novel method for planar object tracking that estimates a full 8 degrees-of-freedom pose, i.e. the homography w.r.t. a reference view. The method uses a novel module that leverages dense optical flow and assigns a weight to each optical flow correspondence, estimating a homography by weighted least ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	341,688
2502.02063	CASIM: Composite Aware Semantic Injection for Text to Motion Generation	Recent advances in generative modeling and tokenization have driven significant progress in text-to-motion generation, leading to enhanced quality and realism in generated motions. However, effectively leveraging textual information for conditional motion generation remains an open challenge. We observe that current ap...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	530,165
1811.07032	Mining Entity Synonyms with Efficient Neural Set Generation	Mining entity synonym sets (i.e., sets of terms referring to the same entity) is an important task for many entity-leveraging applications. Previous work either rank terms based on their similarity to a given query term, or treats the problem as a two-phase task (i.e., detecting synonymy pairs, followed by organizing t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	113,646
2211.00537	On the Semi-supervised Expectation Maximization	The Expectation Maximization (EM) algorithm is widely used as an iterative modification to maximum likelihood estimation when the data is incomplete. We focus on a semi-supervised case to learn the model from labeled and unlabeled samples. Existing work in the semi-supervised case has focused mainly on performance rath...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	327,907
2310.02435	Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Control	Traffic signal control (TSC) is a challenging problem within intelligent transportation systems and has been tackled using multi-agent reinforcement learning (MARL). While centralized approaches are often infeasible for large-scale TSC problems, decentralized approaches provide scalability but introduce new challenges,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	396,846
2502.09188	Matina: A Large-Scale 73B Token Persian Text Corpus	Text corpora are essential for training models used in tasks like summarization, translation, and large language models (LLMs). While various efforts have been made to collect monolingual and multilingual datasets in many languages, Persian has often been underrepresented due to limited resources for data collection an...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	533,341
2105.08431	Predictor-Based Output Feedback Stabilization of an Input Delayed Parabolic PDE with Boundary Measurement	This paper is concerned with the output feedback boundary stabilization of general 1-D reaction diffusion PDEs in the presence of an arbitrarily large input delay. We consider the cases of Dirichlet/Neumann/Robin boundary conditions for the both boundary control and boundary condition. The boundary measurement takes th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	235,752
1802.10203	Behavioral Learning of Aircraft Landing Sequencing Using a Society of Probabilistic Finite State Machines	Air Traffic Control (ATC) is a complex safety critical environment. A tower controller would be making many decisions in real-time to sequence aircraft. While some optimization tools exist to help the controller in some airports, even in these situations, the real sequence of the aircraft adopted by the controller is s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	91,477
1910.02270	Parallelizing Training of Deep Generative Models on Massive Scientific Datasets	Training deep neural networks on large scientific data is a challenging task that requires enormous compute power, especially if no pre-trained models exist to initialize the process. We present a novel tournament method to train traditional as well as generative adversarial networks built on LBANN, a scalable deep lea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	148,192
1905.10674	Compositional Fairness Constraints for Graph Embeddings	Learning high-quality node embeddings is a key building block for machine learning models that operate on graph data, such as social networks and recommender systems. However, existing graph embedding techniques are unable to cope with fairness constraints, e.g., ensuring that the learned representations do not correla...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	132,143
2212.08700	Rarely a problem? Language models exhibit inverse scaling in their predictions following few-type quantifiers	How well do language models deal with quantification? In this study, we focus on 'few'-type quantifiers, as in 'few children like toys', which might pose a particular challenge for language models because the sentence components with out the quantifier are likely to co-occur, and 'few'-type quantifiers are rare. We pre...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	336,841
2312.15157	CodeScholar: Growing Idiomatic Code Examples	Programmers often search for usage examples for API methods. A tool that could generate realistic, idiomatic, and contextual usage examples for one or more APIs would be immensely beneficial to developers. Such a tool would relieve the need for a deep understanding of the API landscape, augment existing documentation, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	417,894
2209.11827	One-Shot Reachability Analysis of Neural Network Dynamical Systems	The arising application of neural networks (NN) in robotic systems has driven the development of safety verification methods for neural network dynamical systems (NNDS). Recursive techniques for reachability analysis of dynamical systems in closed-loop with a NN controller, planner, or perception can over-approximate t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	319,311
2210.15882	Can Current Explainability Help Provide References in Clinical Notes to Support Humans Annotate Medical Codes?	The medical codes prediction problem from clinical notes has received substantial interest in the NLP community, and several recent studies have shown the state-of-the-art (SOTA) code prediction results of full-fledged deep learning-based methods. However, most previous SOTA works based on deep learning are still in ea...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	327,124
1907.01070	A Semi-Supervised Self-Organizing Map for Clustering and Classification	There has been an increasing interest in semi-supervised learning in the recent years because of the great number of datasets with a large number of unlabeled data but only a few labeled samples. Semi-supervised learning algorithms can work with both types of data, combining them to obtain better performance for both c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,213
2111.00977	Fast Convolution based on Winograd Minimum Filtering: Introduction and Development	Convolutional Neural Network (CNN) has been widely used in various fields and played an important role. Convolution operators are the fundamental component of convolutional neural networks, and it is also the most time-consuming part of network training and inference. In recent years, researchers have proposed several ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	264,416
2105.07202	FOGA: Flag Optimization with Genetic Algorithm	Recently, program autotuning has become very popular especially in embedded systems, when we have limited resources such as computing power and memory where these systems run generally time-critical applications. Compiler optimization space gradually expands with the renewed compiler options and inclusion of new archit...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	235,358
2410.07297	Autonomous Navigation and Collision Avoidance for Mobile Robots: Classification and Review	This paper introduces a novel classification for Autonomous Mobile Robots (AMRs), into three phases and five steps, focusing on autonomous collision-free navigation. Additionally, it presents the main methods and widely accepted technologies for each phase of the proposed classification. The purpose of this classificat...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	496,576
2011.07981	Resilient Identification of Distribution Network Topology	Network topology identification (TI) is an essential function for distributed energy resources management systems (DERMS) to organize and operate widespread distributed energy resources (DERs). In this paper, discriminant analysis (DA) is deployed to develop a network TI function that relies only on the measurements av...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	206,732
2410.18007	Effective Finite Time Stability Control for Human-Machine Shared Vehicle Following System	With the development of intelligent connected vehicle technology, human-machine shared control has gained popularity in vehicle following due to its effectiveness in driver assistance. However, traditional vehicle following systems struggle to maintain stability when driver reaction time fluctuates, as these variations...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	501,706
2108.07151	Learning Friction Model for Tethered Capsule Robot	With the potential applications of capsule robots in medical endoscopy, accurate dynamic control of the capsule robot is becoming more and more important. In the scale of a capsule robot, the friction between capsule and the environment plays an essential role in the dynamic model, which is usually difficult to model b...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	250,848
2501.11041	Enhancing Semantic Consistency of Large Language Models through Model Editing: An Interpretability-Oriented Approach	A Large Language Model (LLM) tends to generate inconsistent and sometimes contradictory outputs when presented with a prompt that has equivalent semantics but is expressed differently from the original prompt. To achieve semantic consistency of an LLM, one of the key approaches is to finetune the model with prompt-outp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	525,765
1803.05880	GossipGraD: Scalable Deep Learning using Gossip Communication based Asynchronous Gradient Descent	In this paper, we present GossipGraD - a gossip communication protocol based Stochastic Gradient Descent (SGD) algorithm for scaling Deep Learning (DL) algorithms on large-scale systems. The salient features of GossipGraD are: 1) reduction in overall communication complexity from {\Theta}(log(p)) for p compute nodes in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	92,732
2502.00928	Mathematical Cell Deployment Optimization for Capacity and Coverage of Ground and UAV Users	We present a general mathematical framework for optimizing cell deployment and antenna configuration in wireless networks, inspired by quantization theory. Unlike traditional methods, our framework supports networks with deterministically located nodes, enabling modeling and optimization under controlled deployment sce...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	529,609
1807.05284	Survey on Deep Learning Techniques for Person Re-Identification Task	Intelligent video-surveillance is currently an active research field in computer vision and machine learning techniques. It provides useful tools for surveillance operators and forensic video investigators. Person re-identification (PReID) is one among these tools. It consists of recognizing whether an individual has a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	102,891
2103.16427	Investigation of Multiple Resource Theory Design Principles on Robot Teleoperation and Workload Management	Robot interfaces often only use the visual channel. Inspired by Wickens' Multiple Resource Theory, we investigated if the addition of audio elements would reduce cognitive workload and improve performance. Specifically, we designed a search and threat-defusal task (primary) with a memory test task (secondary). Eleven p...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	227,581
2412.04177	Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning	Recently, there has been an increasing interest in performing post-hoc uncertainty estimation about the predictions of pre-trained deep neural networks (DNNs). Given a pre-trained DNN via back-propagation, these methods enhance the original network by adding output confidence measures, such as error bars, without compr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	514,293
2202.03867	Offline Reinforcement Learning for Mobile Notifications	Mobile notification systems have taken a major role in driving and maintaining user engagement for online platforms. They are interesting recommender systems to machine learning practitioners with more sequential and long-term feedback considerations. Most machine learning applications in notification systems are built...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,369
2409.09844	A Benchmark Dataset with Larger Context for Non-Factoid Question Answering over Islamic Text	Accessing and comprehending religious texts, particularly the Quran (the sacred scripture of Islam) and Ahadith (the corpus of the sayings or traditions of the Prophet Muhammad), in today's digital era necessitates efficient and accurate Question-Answering (QA) systems. Yet, the scarcity of QA systems tailored specific...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	488,498
2411.04098	Interpretable and Efficient Data-driven Discovery and Control of Distributed Systems	Effectively controlling systems governed by Partial Differential Equations (PDEs) is crucial in several fields of Applied Sciences and Engineering. These systems usually yield significant challenges to conventional control schemes due to their nonlinear dynamics, partial observability, high-dimensionality once discreti...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	506,147
2403.19629	Metric Learning from Limited Pairwise Preference Comparisons	We study metric learning from preference comparisons under the ideal point model, in which a user prefers an item over another if it is closer to their latent ideal item. These items are embedded into $\mathbb{R}^d$ equipped with an unknown Mahalanobis distance shared across users. While recent work shows that it is po...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	442,422
2204.08090	Learning Compositional Representations for Effective Low-Shot Generalization	We propose Recognition as Part Composition (RPC), an image encoding approach inspired by human cognition. It is based on the cognitive theory that humans recognize complex objects by components, and that they build a small compact vocabulary of concepts to represent each instance with. RPC encodes images by first decom...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	291,955
2304.01509	Sensing Performance of Cooperative Joint Sensing-Communication UAV Network	We propose a novel cooperative joint sensing-communication (JSC) unmanned aerial vehicle (UAV) network that can achieve downward-looking detection and transmit detection data simultaneously using the same time and frequency resources by exploiting the beam sharing scheme. The UAV network consists of a UAV that works as...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	356,105
1005.2898	Saturation Throughput - Delay Analysis of IEEE 802.11 DCF in Fading Channel	In this paper, we analytically analyzed the impact of an error-prone channel over all performance measures in a trafficsaturated IEEE 802.11 WLAN. We calculated station's transmission probability by using the modified Markov chain model of the backoff window size that considers the frame-error rates and maximal allowab...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	6,504
2302.09560	Deep Selector-JPEG: Adaptive JPEG Image Compression for Computer Vision in Image classification with Human Vision Criteria	With limited storage/bandwidth resources, input images to Computer Vision (CV) applications that use Deep Neural Networks (DNNs) are often encoded with JPEG that is tailored to Human Vision (HV). This paper presents Deep Selector-JPEG, an adaptive JPEG compression method that targets image classification while satisfyi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	346,473
1407.0698	Continuous On-line Evolution of Agent Behaviours with Cartesian Genetic Programming	Evolutionary Computation has been successfully used to synthesise controllers for embodied agents and multi-agent systems in general. Notwithstanding this, continuous on-line adaptation by the means of evolutionary algorithms is still under-explored, especially outside the evolutionary robotics domain. In this paper, w...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	34,354
2408.03533	Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation	We primarily focus on the field of large language models (LLMs) for recommendation, which has been actively explored recently and poses a significant challenge in effectively enhancing recommender systems with logical reasoning abilities and open-world knowledge. Current mainstream efforts mainly center around injectin...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	479,054
2008.10818	Transmitting Extra Bits by Rotating Signal Constellations	In this letter, we propose a novel LDPC coding scheme to transmit extra bits aided by rotated signal constellations without any additional cost in transmission power or bandwidth. In the proposed scheme, the LDPC coded data are modulated by a rotated two-dimensional signal constellation, in which the rotation angle is ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	193,101
2301.07806	Federated Automatic Differentiation	Federated learning (FL) is a general framework for learning across an axis of group partitioned data (heterogeneous clients) while preserving data privacy, under the orchestration of a central server. FL methods often compute gradients of loss functions purely locally (ie. entirely at each client, or entirely at the se...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	341,012
2205.04153	Linear Runlength-Limited Subcodes of Reed-Muller Codes and Coding Schemes for Input-Constrained BMS Channels	In this work, we address the question of the largest rate of linear subcodes of Reed-Muller (RM) codes, all of whose codewords respect a runlength-limited (RLL) constraint. Our interest is in the $(d,\infty)$-RLL constraint, which mandates that every pair of successive $1$s be separated by at least $d$ $0$s. Consider a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	295,554
2210.04106	The effect of variable labels on deep learning models trained to predict breast density	Purpose: High breast density is associated with reduced efficacy of mammographic screening and increased risk of developing breast cancer. Accurate and reliable automated density estimates can be used for direct risk prediction and passing density related information to further predictive models. Expert reader assessme...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	322,303
1909.00193	Functional advantages of an adaptive Theory of Mind for robotics: a review of current architectures	Great advancements have been achieved in the field of robotics, however, main challenges remain, including building robots with an adaptive Theory of Mind (ToM). In the present paper, seven current robotic architectures for human-robot interactions were described as well as four main functional advantages of equipping ...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	143,563
2205.13901	Bias Reduction via Cooperative Bargaining in Synthetic Graph Dataset Generation	In general, to draw robust conclusions from a dataset, all the analyzed population must be represented on said dataset. Having a dataset that does not fulfill this condition normally leads to selection bias. Additionally, graphs have been used to model a wide variety of problems. Although synthetic graphs can be used t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	299,132
2402.07011	FedImpro: Measuring and Improving Client Update in Federated Learning	Federated Learning (FL) models often experience client drift caused by heterogeneous data, where the distribution of data differs across clients. To address this issue, advanced research primarily focuses on manipulating the existing gradients to achieve more consistent client models. In this paper, we present an alter...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	428,529
2305.02139	A Curriculum View of Robust Loss Functions	Robust loss functions are designed to combat the adverse impacts of label noise, whose robustness is typically supported by theoretical bounds agnostic to the training dynamics. However, these bounds may fail to characterize the empirical performance as it remains unclear why robust loss functions can underfit. We show...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	361,930
2101.10184	Optimal Placement of Detectors to Minimize Casualties on a Manmade Attack	This study proposes a mathematical model to optimally locate a set of detectors in such a way that the expected number of casualties in a given threat area can be minimized. Detectors may not be perfectly reliable, which is often a function of how long an attacker would stay within the detectors effective detection rad...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	216,848
cs/0510067	On the Spread of Random Interleaver	For a given blocklength we determine the number of interleavers which have spread equal to two. Using this, we find out the probability that a randomly chosen interleaver has spread two. We show that as blocklength increases, this probability increases but very quickly converges to the value $1-e^{-2} \approx 0.8647$. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,032
2104.09809	Inference of Common Multidimensional Equally-Distributed Attributes	Given two relations containing multiple measurements - possibly with uncertainties - our objective is to find which sets of attributes from the first have a corresponding set on the second, using exclusively a sample of the data. This approach could be used even when the associated metadata is damaged, missing or incom...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	231,366
2003.03531	Friend Recommendation based on Hashtags Analysis	Social networks include millions of users constantly looking for new relationships for personal or professional purposes. Social network sites recommend friends based on relationship features and content information. A significant part of information shared every day is spread in Hashtags. None of the existing content-...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	167,261
1009.4973	Performance Analysis of Pulse Shaping Technique for OFDM PAPR Reduction	Orthogonal Frequency Division Multiplexing (OFDM) is an attractive modulation and multiple access techniques for channels with a nonflat frequency response, as it saves the need for complex equalizers. It can offer high quality performance in terms of bandwidth efficiency, robustness against multipath fading and cost-e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,661
2412.15652	Error-driven Data-efficient Large Multimodal Model Tuning	Large Multimodal Models (LMMs) have demonstrated impressive performance across numerous academic benchmarks. However, fine-tuning still remains essential to achieve satisfactory performance on downstream tasks, while the task-specific tuning samples are usually not readily available or expensive and time-consuming to o...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	519,220
2309.00855	DoRA: Domain-Based Self-Supervised Learning Framework for Low-Resource Real Estate Appraisal	The marketplace system connecting demands and supplies has been explored to develop unbiased decision-making in valuing properties. Real estate appraisal serves as one of the high-cost property valuation tasks for financial institutions since it requires domain experts to appraise the estimation based on the correspond...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	389,448
1506.09084	Implementation of Nonlinear Model Predictive Path-Following Control for an Industrial Robot	Many robotic applications, such as milling, gluing, or high precision measurements, require the exact following of a pre-defined geometric path. In this paper, we investigate the real-time feasible implementation of model predictive path-following control for an industrial robot. We consider constrained output path fol...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	44,690
2301.10684	Consistency is Key: Disentangling Label Variation in Natural Language Processing with Intra-Annotator Agreement	We commonly use agreement measures to assess the utility of judgements made by human annotators in Natural Language Processing (NLP) tasks. While inter-annotator agreement is frequently used as an indication of label reliability by measuring consistency between annotators, we argue for the additional use of intra-annot...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	341,885
1907.00749	Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data	Corner cases are the main bottlenecks when applying Artificial Intelligence (AI) systems to safety-critical applications. An AI system should be intelligent enough to detect such situations so that system developers can prepare for subsequent planning. In this paper, we propose semi-supervised anomaly detection conside...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	137,135
1802.00066	Dynamics of Driver's Gaze: Explorations in Behavior Modeling & Maneuver Prediction	The study and modeling of driver's gaze dynamics is important because, if and how the driver is monitoring the driving environment is vital for driver assistance in manual mode, for take-over requests in highly automated mode and for semantic perception of the surround in fully autonomous mode. We developed a machine v...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,338
2207.10551	Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?	There have been a lot of interest in the scaling properties of Transformer models. However, not much has been done on the front of investigating the effect of scaling properties of different inductive biases and model architectures. Do model architectures scale differently? If so, how does inductive bias affect scaling...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	309,299
2006.16318	Learning and Planning in Average-Reward Markov Decision Processes	We introduce learning and planning algorithms for average-reward MDPs, including 1) the first general proven-convergent off-policy model-free control algorithm without reference states, 2) the first proven-convergent off-policy model-free prediction algorithm, and 3) the first off-policy learning algorithm that converg...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	184,764
1702.05858	Multi-Sensor Control for Multi-Object Bayes Filters	Sensor management in multi-object stochastic systems is a theoretically and computationally challenging problem. This paper presents a novel approach to the multi-target multi-sensor control problem within the partially observed Markov decision process (POMDP) framework. We model the multi-object state as a labeled mul...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	68,486
2206.06584	Probabilistic Conformal Prediction Using Conditional Random Samples	This paper proposes probabilistic conformal prediction (PCP), a predictive inference algorithm that estimates a target variable by a discontinuous predictive set. Given inputs, PCP construct the predictive set based on random samples from an estimated generative model. It is efficient and compatible with either explici...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,422
2209.08375	Six-DOF Spacecraft Dynamics Simulator For Testing Translation and Attitude Control	This paper presents a method to control a manipulator system grasping a rigid-body payload so that the motion of the combined system in consequence of externally applied forces to be the same as another free-floating rigid-body (with different inertial properties). This allows zero-g emulation of a scaled spacecraft pr...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	318,100
2404.18279	Out-of-distribution Detection in Medical Image Analysis: A survey	Computer-aided diagnostics has benefited from the development of deep learning-based computer vision techniques in these years. Traditional supervised deep learning methods assume that the test sample is drawn from the identical distribution as the training data. However, it is possible to encounter out-of-distribution...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,202
2207.13211	A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog	Interest in dialog systems has grown substantially in the past decade. By extension, so too has interest in developing and improving intent classification and slot-filling models, which are two components that are commonly used in task-oriented dialog systems. Moreover, good evaluation benchmarks are important in helpi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	310,225
2403.13560	eRST: A Signaled Graph Theory of Discourse Relations and Organization	In this article we present Enhanced Rhetorical Structure Theory (eRST), a new theoretical framework for computational discourse analysis, based on an expansion of Rhetorical Structure Theory (RST). The framework encompasses discourse relation graphs with tree-breaking, non-projective and concurrent relations, as well a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	439,681
2406.04724	Probabilistic Perspectives on Error Minimization in Adversarial Reinforcement Learning	Deep Reinforcement Learning (DRL) policies are highly susceptible to adversarial noise in observations, which poses significant risks in safety-critical scenarios. For instance, a self-driving car could experience catastrophic consequences if its sensory inputs about traffic signs are manipulated by an adversary. The c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	461,812
1909.12837	SegMap: Segment-based mapping and localization using data-driven descriptors	Precisely estimating a robot's pose in a prior, global map is a fundamental capability for mobile robotics, e.g. autonomous driving or exploration in disaster zones. This task, however, remains challenging in unstructured, dynamic environments, where local features are not discriminative enough and global scene descrip...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	147,227
2404.06162	Characterizing Multimodal Long-form Summarization: A Case Study on Financial Reports	As large language models (LLMs) expand the power of natural language processing to handle long inputs, rigorous and systematic analyses are necessary to understand their abilities and behavior. A salient application is summarization, due to its ubiquity and controversy (e.g., researchers have declared the death of summ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	445,351
1603.08582	Provably Safe and Deadlock-Free Execution of Multi-Robot Plans under Delaying Disturbances	One of the standing challenges in multi-robot systems is the ability to reliably coordinate motions of multiple robots in environments where the robots are subject to disturbances. We consider disturbances that force the robot to temporarily stop and delay its advancement along its planned trajectory which can be used ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	53,798
2207.07764	Yet another stability condition for switched nonlinear systems	This paper deals with input/output-to-state stability (IOSS) of continuous-time switched nonlinear systems. Given a family of systems, possibly containing unstable dynamics, and a set of restrictions on admissible switches between the subsystems and admissible dwell times on the subsystems, we identify a class of switc...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	308,302
1712.03280	Nintendo Super Smash Bros. Melee: An "Untouchable" Agent	Nintendo's Super Smash Bros. Melee fighting game can be emulated on modern hardware allowing us to inspect internal memory states, such as character positions. We created an AI that avoids being hit by training using these internal memory states and outputting controller button presses. After training on a month's wort...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	86,416
1802.05737	JU_KS@SAIL_CodeMixed-2017: Sentiment Analysis for Indian Code Mixed Social Media Texts	This paper reports about our work in the NLP Tool Contest @ICON-2017, shared task on Sentiment Analysis for Indian Languages (SAIL) (code mixed). To implement our system, we have used a machine learning algo-rithm called Multinomial Na\"ive Bayes trained using n-gram and SentiWordnet features. We have also used a small...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	90,491
2310.11966	Flexible Payload Configuration for Satellites using Machine Learning	Satellite communications, essential for modern connectivity, extend access to maritime, aeronautical, and remote areas where terrestrial networks are unfeasible. Current GEO systems distribute power and bandwidth uniformly across beams using multi-beam footprints with fractional frequency reuse. However, recent researc...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	400,853
2303.16150	Multimodal video and IMU kinematic dataset on daily life activities using affordable devices (VIDIMU)	Human activity recognition and clinical biomechanics are challenging problems in physical telerehabilitation medicine. However, most publicly available datasets on human body movements cannot be used to study both problems in an out-of-the-lab movement acquisition setting. The objective of the VIDIMU dataset is to pave...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	354,757
2501.06262	Towards smart and adaptive agents for active sensing on edge devices	TinyML has made deploying deep learning models on low-power edge devices feasible, creating new opportunities for real-time perception in constrained environments. However, the adaptability of such deep learning methods remains limited to data drift adaptation, lacking broader capabilities that account for the environm...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	523,918
1912.10784	An improper estimator with optimal excess risk in misspecified density estimation and logistic regression	We introduce a procedure for conditional density estimation under logarithmic loss, which we call SMP (Sample Minmax Predictor). This estimator minimizes a new general excess risk bound for statistical learning. On standard examples, this bound scales as $d/n$ with $d$ the model dimension and $n$ the sample size, and c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	158,404
1711.09783	Data Dependent Kernel Approximation using Pseudo Random Fourier Features	Kernel methods are powerful and flexible approach to solve many problems in machine learning. Due to the pairwise evaluations in kernel methods, the complexity of kernel computation grows as the data size increases; thus the applicability of kernel methods is limited for large scale datasets. Random Fourier Features (R...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,472
2206.09420	Agricultural Plantation Classification using Transfer Learning Approach based on CNN	Hyper-spectral images are images captured from a satellite that gives spatial and spectral information of specific region.A Hyper-spectral image contains much more number of channels as compared to a RGB image, hence containing more information about entities within the image. It makes them well suited for the classifi...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	303,565
1912.03582	PIDForest: Anomaly Detection via Partial Identification	We consider the problem of detecting anomalies in a large dataset. We propose a framework called Partial Identification which captures the intuition that anomalies are easy to distinguish from the overwhelming majority of points by relatively few attribute values. Formalizing this intuition, we propose a geometric anom...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,627
1608.02728	OnionNet: Sharing Features in Cascaded Deep Classifiers	The focus of our work is speeding up evaluation of deep neural networks in retrieval scenarios, where conventional architectures may spend too much time on negative examples. We propose to replace a monolithic network with our novel cascade of feature-sharing deep classifiers, called OnionNet, where subsequent stages m...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	59,593
2412.12571	ChatDiT: A Training-Free Baseline for Task-Agnostic Free-Form Chatting with Diffusion Transformers	Recent research arXiv:2410.15027 arXiv:2410.23775 has highlighted the inherent in-context generation capabilities of pretrained diffusion transformers (DiTs), enabling them to seamlessly adapt to diverse visual tasks with minimal or no architectural modifications. These capabilities are unlocked by concatenating self-a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	517,930
2405.10577	DuoSpaceNet: Leveraging Both Bird's-Eye-View and Perspective View Representations for 3D Object Detection	Recent advances in multi-view camera-only 3D object detection either rely on an accurate reconstruction of bird's-eye-view (BEV) 3D features or on traditional 2D perspective view (PV) image features. While both have their own pros and cons, few have found a way to stitch them together in order to benefit from "the best...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	454,812
1910.05036	Impact of independence on polarization of opinions	Polarization of societies is getting more and more attention from researchers working at the intersection of many fields, because it seems to be a defining feature of many public domains. In this paper, we are going to investigate how the unwillingness to yield to the group pressure, also known as independence, influen...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	148,953
1908.05868	See Clearer at Night: Towards Robust Nighttime Semantic Segmentation through Day-Night Image Conversion	Currently, semantic segmentation shows remarkable efficiency and reliability in standard scenarios such as daytime scenes with favorable illumination conditions. However, in face of adverse conditions such as the nighttime, semantic segmentation loses its accuracy significantly. One of the main causes of the problem is...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	141,845
2211.08603	Asynchronous Bayesian Learning over a Network	We present a practical asynchronous data fusion model for networked agents to perform distributed Bayesian learning without sharing raw data. Our algorithm uses a gossip-based approach where pairs of randomly selected agents employ unadjusted Langevin dynamics for parameter sampling. We also introduce an event-triggere...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	330,694
2112.05237	Transfer learning using deep neural networks for Ear Presentation Attack Detection: New Database for PAD	Ear recognition system has been widely studied whereas there are just a few ear presentation attack detection methods for ear recognition systems, consequently, there is no publicly available ear presentation attack detection (PAD) database. In this paper, we propose a PAD method using a pre-trained deep neural network...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	270,778
2410.08230	Finetuning YOLOv9 for Vehicle Detection: Deep Learning for Intelligent Transportation Systems in Dhaka, Bangladesh	Rapid urbanization in megacities around the world, like Dhaka, has caused numerous transportation challenges that need to be addressed. Emerging technologies of deep learning and artificial intelligence can help us solve these problems to move towards Intelligent Transportation Systems (ITS) in the city. The government...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	497,019
cs/0202007	Steady State Resource Allocation Analysis of the Stochastic Diffusion Search	This article presents the long-term behaviour analysis of Stochastic Diffusion Search (SDS), a distributed agent-based system for best-fit pattern matching. SDS operates by allocating simple agents into different regions of the search space. Agents independently pose hypotheses about the presence of the pattern in the ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	537,495
2107.07763	Topology optimization using the unsmooth variational topology optimization (UNVARTOP) method. An educational implementation in Matlab	This paper presents an efficient and comprehensive MATLAB code to solve two-dimensional structural topology optimization problems, including minimum mean compliance, compliant mechanism synthesis and multi-load compliance problems. The Unsmooth Variational Topology Optimization (UNVARTOP) method, developed by the autho...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	246,522
2101.08837	Time-Correlated Sparsification for Communication-Efficient Federated Learning	Federated learning (FL) enables multiple clients to collaboratively train a shared model without disclosing their local datasets. This is achieved by exchanging local model updates with the help of a parameter server (PS). However, due to the increasing size of the trained models, the communication load due to the iter...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	216,424
1909.05827	Proximal Recursion for the Wonham Filter	This paper contributes to the emerging viewpoint that governing equations for dynamic state estimation, conditioned on the history of noisy measurements, can be viewed as gradient flow on the manifold of joint probability density functions with respect to suitable metrics. Herein, we focus on the Wonham filter where th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	145,219
2410.17579	Bonsai: Gradient-free Graph Distillation for Node Classification	Graph distillation has emerged as a promising avenue to enable scalable training of GNNs by compressing the training dataset while preserving essential graph characteristics. Our study uncovers significant shortcomings in current graph distillation techniques. First, the majority of the algorithms paradoxically require...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	501,531
2407.08061	Geospecific View Generation -- Geometry-Context Aware High-resolution Ground View Inference from Satellite Views	Predicting realistic ground views from satellite imagery in urban scenes is a challenging task due to the significant view gaps between satellite and ground-view images. We propose a novel pipeline to tackle this challenge, by generating geospecifc views that maximally respect the weak geometry and texture from multi-v...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	471,993
2405.15007	RE-Adapt: Reverse Engineered Adaptation of Large Language Models	We introduce RE-Adapt, an approach to fine-tuning large language models on new domains without degrading any pre-existing instruction-tuning. We reverse engineer an adapter which isolates what an instruction-tuned model has learned beyond its corresponding pretrained base model. Importantly, this requires no additional...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	456,696
0802.1738	Characterising through Erasing: A Theoretical Framework for Representing Documents Inspired by Quantum Theory	The problem of representing text documents within an Information Retrieval system is formulated as an analogy to the problem of representing the quantum states of a physical system. Lexical measurements of text are proposed as a way of representing documents which are akin to physical measurements on quantum states. Co...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	1,280
2411.04533	Neural Fingerprints for Adversarial Attack Detection	Deep learning models for image classification have become standard tools in recent years. A well known vulnerability of these models is their susceptibility to adversarial examples. These are generated by slightly altering an image of a certain class in a way that is imperceptible to humans but causes the model to clas...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	506,305
1810.09103	Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement	Many policy gradient methods are variants of Actor-Critic (AC), where a value function (critic) is learned to facilitate updating the parameterized policy (actor). The update to the actor involves a log-likelihood update weighted by the action-values, with the addition of entropy regularization for soft variants. In th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	110,986
2408.12674	One-shot Video Imitation via Parameterized Symbolic Abstraction Graphs	Learning to manipulate dynamic and deformable objects from a single demonstration video holds great promise in terms of scalability. Previous approaches have predominantly focused on either replaying object relationships or actor trajectories. The former often struggles to generalize across diverse tasks, while the lat...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	482,839

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