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
2410.03428	Research Landscape of the novel emerging field of Cryptoeconomics	A bibliometric literature analysis was conducted to illuminate the evolving and rapidly expanding literature in the field of cryptoeconomics. This analysis presented the emerging field's intellectual, social, and conceptual structure. The intellectual structure, characterized by schools of thought, emerged through a co...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	494,775
2303.00703	Nearest Neighbors Meet Deep Neural Networks for Point Cloud Analysis	Performances on standard 3D point cloud benchmarks have plateaued, resulting in oversized models and complex network design to make a fractional improvement. We present an alternative to enhance existing deep neural networks without any redesigning or extra parameters, termed as Spatial-Neighbor Adapter (SN-Adapter). B...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	348,684
2211.00894	Mixed Membership Estimation for Weighted Networks	Community detection in overlapping un-weighted networks in which nodes can belong to multiple communities is one of the most popular topics in modern network science during the last decade. However, community detection in overlapping weighted networks in which edge weights can be any real values remains a challenge. In...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	328,042
1810.01279	Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network	We present a new algorithm to train a robust neural network against adversarial attacks. Our algorithm is motivated by the following two ideas. First, although recent work has demonstrated that fusing randomness can improve the robustness of neural networks (Liu 2017), we noticed that adding noise blindly to all the la...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	109,367
2005.13312	AutoSweep: Recovering 3D Editable Objectsfrom a Single Photograph	This paper presents a fully automatic framework for extracting editable 3D objects directly from a single photograph. Unlike previous methods which recover either depth maps, point clouds, or mesh surfaces, we aim to recover 3D objects with semantic parts and can be directly edited. We base our work on the assumption t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	178,982
2406.11142	Graspness Discovery in Clutters for Fast and Accurate Grasp Detection	Efficient and robust grasp pose detection is vital for robotic manipulation. For general 6 DoF grasping, conventional methods treat all points in a scene equally and usually adopt uniform sampling to select grasp candidates. However, we discover that ignoring where to grasp greatly harms the speed and accuracy of curre...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	464,736
1112.1314	On Optimal Link Activation with Interference Cancellation in Wireless Networking	A fundamental aspect in performance engineering of wireless networks is optimizing the set of links that can be concurrently activated to meet given signal-to-interference-and-noise ratio (SINR) thresholds. The solution of this combinatorial problem is the key element in scheduling and cross-layer resource management. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	13,338
1901.11524	The Value Function Polytope in Reinforcement Learning	We establish geometric and topological properties of the space of value functions in finite state-action Markov decision processes. Our main contribution is the characterization of the nature of its shape: a general polytope (Aigner et al., 2010). To demonstrate this result, we exhibit several properties of the structu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	120,283
2410.01599	Towards Model Discovery Using Domain Decomposition and PINNs	We enhance machine learning algorithms for learning model parameters in complex systems represented by ordinary differential equations (ODEs) with domain decomposition methods. The study evaluates the performance of two approaches, namely (vanilla) Physics-Informed Neural Networks (PINNs) and Finite Basis Physics-Infor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	493,844
2007.12597	Decision-Making in Driver-Automation Shared Control: A Review and Perspectives	Shared control schemes allow a human driver to work with an automated driving agent in driver-vehicle systems while retaining the driver's abilities to control. The human driver, as an essential agent in the driver-vehicle shared control systems, should be precisely modeled regarding their cognitive processes, control ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	188,869
1409.4489	Distributed Rate Adaptation and Power Control in Fading Multiple Access Channels	Traditionally, the capacity region of a coherent fading multiple access channel (MAC) is analyzed in two popular contexts. In the first, a centralized system with full channel state information at the transmitters (CSIT) is assumed, and the communication parameters like transmit power and data-rate are jointly chosen f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	36,080
2112.06351	Neural Point Process for Learning Spatiotemporal Event Dynamics	Learning the dynamics of spatiotemporal events is a fundamental problem. Neural point processes enhance the expressivity of point process models with deep neural networks. However, most existing methods only consider temporal dynamics without spatial modeling. We propose Deep Spatiotemporal Point Process (\ours{}), a d...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	271,142
1212.5461	Interactive Ant Colony Optimisation (iACO) for Early Lifecycle Software Design	Software design is crucial to successful software development, yet is a demanding multi-objective problem for software engineers. In an attempt to assist the software designer, interactive (i.e. human in-the-loop) meta-heuristic search techniques such as evolutionary computing have been applied and show promising resul...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	20,557
1710.11344	A Sequential Matching Framework for Multi-turn Response Selection in Retrieval-based Chatbots	We study the problem of response selection for multi-turn conversation in retrieval-based chatbots. The task requires matching a response candidate with a conversation context, whose challenges include how to recognize important parts of the context, and how to model the relationships among utterances in the context. E...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	83,576
2206.05683	APT-36K: A Large-scale Benchmark for Animal Pose Estimation and Tracking	Animal pose estimation and tracking (APT) is a fundamental task for detecting and tracking animal keypoints from a sequence of video frames. Previous animal-related datasets focus either on animal tracking or single-frame animal pose estimation, and never on both aspects. The lack of APT datasets hinders the developmen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	302,094
2212.02081	YolOOD: Utilizing Object Detection Concepts for Multi-Label Out-of-Distribution Detection	Out-of-distribution (OOD) detection has attracted a large amount of attention from the machine learning research community in recent years due to its importance in deployed systems. Most of the previous studies focused on the detection of OOD samples in the multi-class classification task. However, OOD detection in the...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	334,678
2404.08069	Persistent Classification: A New Approach to Stability of Data and Adversarial Examples	There are a number of hypotheses underlying the existence of adversarial examples for classification problems. These include the high-dimensionality of the data, high codimension in the ambient space of the data manifolds of interest, and that the structure of machine learning models may encourage classifiers to develo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	446,098
2307.01540	Learning to Prompt in the Classroom to Understand AI Limits: A pilot study	Artificial intelligence's (AI) progress holds great promise in tackling pressing societal concerns such as health and climate. Large Language Models (LLM) and the derived chatbots, like ChatGPT, have highly improved the natural language processing capabilities of AI systems allowing them to process an unprecedented amo...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	377,389
1511.04670	Uncovering Temporal Context for Video Question and Answering	In this work, we introduce Video Question Answering in temporal domain to infer the past, describe the present and predict the future. We present an encoder-decoder approach using Recurrent Neural Networks to learn temporal structures of videos and introduce a dual-channel ranking loss to answer multiple-choice questio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,929
2002.03761	Music2Dance: DanceNet for Music-driven Dance Generation	Synthesize human motions from music, i.e., music to dance, is appealing and attracts lots of research interests in recent years. It is challenging due to not only the requirement of realistic and complex human motions for dance, but more importantly, the synthesized motions should be consistent with the style, rhythm a...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	163,394
2309.11011	OCC-VO: Dense Mapping via 3D Occupancy-Based Visual Odometry for Autonomous Driving	Visual Odometry (VO) plays a pivotal role in autonomous systems, with a principal challenge being the lack of depth information in camera images. This paper introduces OCC-VO, a novel framework that capitalizes on recent advances in deep learning to transform 2D camera images into 3D semantic occupancy, thereby circumv...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	393,238
2002.06885	What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions	In this work, we propose an automatic evaluation and comparison of the browsing behavior of Wikipedia readers that can be applied to any language editions of Wikipedia. As an example, we focus on English, French, and Russian languages during the last four months of 2018. The proposed method has three steps. Firstly, it...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	164,334
2304.10824	Rethinking Benchmarks for Cross-modal Image-text Retrieval	Image-text retrieval, as a fundamental and important branch of information retrieval, has attracted extensive research attentions. The main challenge of this task is cross-modal semantic understanding and matching. Some recent works focus more on fine-grained cross-modal semantic matching. With the prevalence of large ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	359,571
2404.03048	Decentralised Moderation for Interoperable Social Networks: A Conversation-based Approach for Pleroma and the Fediverse	The recent development of decentralised and interoperable social networks (such as the "fediverse") creates new challenges for content moderators. This is because millions of posts generated on one server can easily "spread" to another, even if the recipient server has very different moderation policies. An obvious sol...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	444,093
2407.03885	Perception-Guided Quality Metric of 3D Point Clouds Using Hybrid Strategy	Full-reference point cloud quality assessment (FR-PCQA) aims to infer the quality of distorted point clouds with available references. Most of the existing FR-PCQA metrics ignore the fact that the human visual system (HVS) dynamically tackles visual information according to different distortion levels (i.e., distortion...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,328
1911.00928	Novel Attacks against Contingency Analysis in Power Grids	Contingency Analysis (CA) is a core component of the Energy Management System (EMS) in the power grid. The goal of CA is to operate the power system in a secure manner by analyzing the system subject to a contingency (e.g., the outage of a transmission line or a power generator) to determine the setpoints that will all...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	true	151,958
1504.05740	When Do WOM Codes Improve the Erasure Factor in Flash Memories?	Flash memory is a write-once medium in which reprogramming cells requires first erasing the block that contains them. The lifetime of the flash is a function of the number of block erasures and can be as small as several thousands. To reduce the number of block erasures, pages, which are the smallest write unit, are re...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,311
1710.05426	Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect	A key question in causal inference analyses is how to find subgroups with elevated treatment effects. This paper takes a machine learning approach and introduces a generative model, Causal Rule Sets (CRS), for interpretable subgroup discovery. A CRS model uses a small set of short decision rules to capture a subgroup w...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	82,641
2403.09383	Pantypes: Diverse Representatives for Self-Explainable Models	Prototypical self-explainable classifiers have emerged to meet the growing demand for interpretable AI systems. These classifiers are designed to incorporate high transparency in their decisions by basing inference on similarity with learned prototypical objects. While these models are designed with diversity in mind, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	437,744
2409.03760	Rethinking Deep Learning: Propagating Information in Neural Networks without Backpropagation and Statistical Optimization	Developing strong AI signifies the arrival of technological singularity, contributing greatly to advancing human civilization and resolving social issues. Neural networks (NNs) and deep learning, which utilize NNs, are expected to lead to strong AI due to their biological neural system-mimicking structures. However, th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	486,160
2411.09730	SureMap: Simultaneous Mean Estimation for Single-Task and Multi-Task Disaggregated Evaluation	Disaggregated evaluation -- estimation of performance of a machine learning model on different subpopulations -- is a core task when assessing performance and group-fairness of AI systems. A key challenge is that evaluation data is scarce, and subpopulations arising from intersections of attributes (e.g., race, sex, ag...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	508,350
1403.6367	A Framework for Hybrid Systems with Denial-of-Service Security Attack	Hybrid systems are integrations of discrete computation and continuous physical evolution. The physical components of such systems introduce safety requirements, the achievement of which asks for the correct monitoring and control from the discrete controllers. However, due to denial-of-service security attack, the exp...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	true	31,817
1001.1597	The Berlekamp-Massey Algorithm via Minimal Polynomials	We present a recursive minimal polynomial theorem for finite sequences over a commutative integral domain $D$. This theorem is relative to any element of $D$. The ingredients are: the arithmetic of Laurent polynomials over $D$, a recursive 'index function' and simple mathematical induction. Taking reciprocals gives a '...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	5,310
1512.05990	Deformable Distributed Multiple Detector Fusion for Multi-Person Tracking	This paper addresses fully automated multi-person tracking in complex environments with challenging occlusion and extensive pose variations. Our solution combines multiple detectors for a set of different regions of interest (e.g., full-body and head) for multi-person tracking. The use of multiple detectors leads to fe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	50,272
2407.11047	An open source Multi-Agent Deep Reinforcement Learning Routing Simulator for satellite networks	This paper introduces an open source simulator for packet routing in Low Earth Orbit Satellite Constellations (LSatCs) considering the dynamic system uncertainties. The simulator, implemented in Python, supports traditional Dijkstra's based routing as well as more advanced learning solutions, specifically Q-Routing and...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	473,267
1906.02295	Progressive NAPSAC: sampling from gradually growing neighborhoods	We propose Progressive NAPSAC, P-NAPSAC in short, which merges the advantages of local and global sampling by drawing samples from gradually growing neighborhoods. Exploiting the fact that nearby points are more likely to originate from the same geometric model, P-NAPSAC finds local structures earlier than global sampl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	133,997
2112.01736	Gesture Recognition with a Skeleton-Based Keyframe Selection Module	We propose a bidirectional consecutively connected two-pathway network (BCCN) for efficient gesture recognition. The BCCN consists of two pathways: (i) a keyframe pathway and (ii) a temporal-attention pathway. The keyframe pathway is configured using the skeleton-based keyframe selection module. Keyframes pass through ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,594
2307.05663	Objaverse-XL: A Universe of 10M+ 3D Objects	Natural language processing and 2D vision models have attained remarkable proficiency on many tasks primarily by escalating the scale of training data. However, 3D vision tasks have not seen the same progress, in part due to the challenges of acquiring high-quality 3D data. In this work, we present Objaverse-XL, a data...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	378,824
2004.04674	Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks	Siamese neural network is a very powerful architecture for both feature extraction and metric learning. It usually consists of several networks that share weights. The Siamese concept is topology-agnostic and can use any neural network as its backbone. The two most popular loss functions for training these networks are...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	171,955
2305.12147	LogiCoT: Logical Chain-of-Thought Instruction-Tuning	Generative Pre-trained Transformer 4 (GPT-4) demonstrates impressive chain-of-thought reasoning ability. Recent work on self-instruction tuning, such as Alpaca, has focused on enhancing the general proficiency of models. These instructions enable the model to achieve performance comparable to GPT-3.5 on general tasks l...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	365,863
2404.11996	DST-GTN: Dynamic Spatio-Temporal Graph Transformer Network for Traffic Forecasting	Accurate traffic forecasting is essential for effective urban planning and congestion management. Deep learning (DL) approaches have gained colossal success in traffic forecasting but still face challenges in capturing the intricacies of traffic dynamics. In this paper, we identify and address this challenges by emphas...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	447,695
2405.15524	Polyp Segmentation Generalisability of Pretrained Backbones	It has recently been demonstrated that pretraining backbones in a self-supervised manner generally provides better fine-tuned polyp segmentation performance, and that models with ViT-B backbones typically perform better than models with ResNet50 backbones. In this paper, we extend this recent work to consider generalis...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	456,979
0908.4464	The eel-like robot	The aim of this project is to design, study and build an "eel-like robot" prototype able to swim in three dimensions. The study is based on the analysis of eel swimming and results in the realization of a prototype with 12 vertebrae, a skin and a head with two fins. To reach these objectives, a multidisciplinary group ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	4,369
2407.02963	Subspace Coding for Spatial Sensing	A subspace code is defined as a collection of subspaces of an ambient vector space, where each information-encoding codeword is a subspace. This paper studies a class of spatial sensing problems, notably direction of arrival (DoA) estimation using multisensor arrays, from a novel subspace coding perspective. Specifical...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	469,965
2201.05256	DapStep: Deep Assignee Prediction for Stack Trace Error rePresentation	The task of finding the best developer to fix a bug is called bug triage. Most of the existing approaches consider the bug triage task as a classification problem, however, classification is not appropriate when the sets of classes change over time (as developers often do in a project). Furthermore, to the best of our ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	275,333
cs/0504052	Learning Multi-Class Neural-Network Models from Electroencephalograms	We describe a new algorithm for learning multi-class neural-network models from large-scale clinical electroencephalograms (EEGs). This algorithm trains hidden neurons separately to classify all the pairs of classes. To find best pairwise classifiers, our algorithm searches for input variables which are relevant to the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	538,663
2403.18684	Scaling Laws For Dense Retrieval	Scaling up neural models has yielded significant advancements in a wide array of tasks, particularly in language generation. Previous studies have found that the performance of neural models frequently adheres to predictable scaling laws, correlated with factors such as training set size and model size. This insight is...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	442,037
2302.14442	City-scale Pollution Aware Traffic Routing by Sampling Max Flows using MCMC	A significant cause of air pollution in urban areas worldwide is the high volume of road traffic. Long-term exposure to severe pollution can cause serious health issues. One approach towards tackling this problem is to design a pollution-aware traffic routing policy that balances multiple objectives of i) avoiding extr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	348,301
2304.05060	SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI	Diffusion models have emerged as a leading methodology for image generation and have proven successful in the realm of magnetic resonance imaging (MRI) reconstruction. However, existing reconstruction methods based on diffusion models are primarily formulated in the image domain, making the reconstruction quality susce...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,470
1910.03162	A Physics-Based Attack Detection Technique in Cyber-Physical Systems: A Model Predictive Control Co-Design Approach	In this paper a novel approach to co-design controller and attack detector for nonlinear cyber-physical systems affected by false data injection (FDI) attack is proposed. We augment the model predictive controller with an additional constraint requiring the future---in some steps ahead---trajectory of the system to rem...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	148,430
2409.01022	SINET: Sparsity-driven Interpretable Neural Network for Underwater Image Enhancement	Improving the quality of underwater images is essential for advancing marine research and technology. This work introduces a sparsity-driven interpretable neural network (SINET) for the underwater image enhancement (UIE) task. Unlike pure deep learning methods, our network architecture is based on a novel channel-speci...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,179
2204.00193	Epipolar Focus Spectrum: A Novel Light Field Representation and Application in Dense-view Reconstruction	Existing light field representations, such as epipolar plane image (EPI) and sub-aperture images, do not consider the structural characteristics across the views, so they usually require additional disparity and spatial structure cues for follow-up tasks. Besides, they have difficulties dealing with occlusions or large...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	289,176
2105.05135	kdehumor at semeval-2020 task 7: a neural network model for detecting funniness in dataset humicroedit	This paper describes our contribution to SemEval-2020 Task 7: Assessing Humor in Edited News Headlines. Here we present a method based on a deep neural network. In recent years, quite some attention has been devoted to humor production and perception. Our team KdeHumor employs recurrent neural network models including ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	234,729
1701.00879	PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization	Over the last three decades, a large number of evolutionary algorithms have been developed for solving multiobjective optimization problems. However, there lacks an up-to-date and comprehensive software platform for researchers to properly benchmark existing algorithms and for practitioners to apply selected algorithms...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	66,330
1712.05644	graphTPP: A multivariate based method for interactive graph layout and analysis	Graph layout is the process of creating a visual representation of a graph through a node-link diagram. Node-attribute graphs have additional data stored on the nodes which describe certain properties of the nodes called attributes. Typical force-directed representations often produce hairball-like structures that neit...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	86,755
2401.04935	Learning Audio Concepts from Counterfactual Natural Language	Conventional audio classification relied on predefined classes, lacking the ability to learn from free-form text. Recent methods unlock learning joint audio-text embeddings from raw audio-text pairs describing audio in natural language. Despite recent advancements, there is little exploration of systematic methods to t...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	420,594
1910.06428	Restoration of marker occluded hematoxylin and eosin stained whole slide histology images using generative adversarial networks	It is common for pathologists to annotate specific regions of the tissue, such as tumor, directly on the glass slide with markers. Although this practice was helpful prior to the advent of histology whole slide digitization, it often occludes important details which are increasingly relevant to immuno-oncology due to r...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	149,333
2307.11867	Large-Scale Multi-Fleet Platoon Coordination: A Dynamic Programming Approach	Truck platooning is a promising technology that enables trucks to travel in formations with small inter-vehicle distances for improved aerodynamics and fuel economy. The real-world transportation system includes a vast number of trucks owned by different fleet owners, for example, carriers. To fully exploit the benefit...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	381,059
1505.02973	Comparing methods for Twitter Sentiment Analysis	This work extends the set of works which deal with the popular problem of sentiment analysis in Twitter. It investigates the most popular document ("tweet") representation methods which feed sentiment evaluation mechanisms. In particular, we study the bag-of-words, n-grams and n-gram graphs approaches and for each of t...	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	false	43,021
2212.01197	FedALA: Adaptive Local Aggregation for Personalized Federated Learning	A key challenge in federated learning (FL) is the statistical heterogeneity that impairs the generalization of the global model on each client. To address this, we propose a method Federated learning with Adaptive Local Aggregation (FedALA) by capturing the desired information in the global model for client models in p...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	334,341
2311.13878	Minimizing Factual Inconsistency and Hallucination in Large Language Models	Large Language Models (LLMs) are widely used in critical fields such as healthcare, education, and finance due to their remarkable proficiency in various language-related tasks. However, LLMs are prone to generating factually incorrect responses or "hallucinations," which can lead to a loss of credibility and trust amo...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	409,909
1909.09577	NeMo: a toolkit for building AI applications using Neural Modules	NeMo (Neural Modules) is a Python framework-agnostic toolkit for creating AI applications through re-usability, abstraction, and composition. NeMo is built around neural modules, conceptual blocks of neural networks that take typed inputs and produce typed outputs. Such modules typically represent data layers, encoders...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	146,297
2112.10775	HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images	Multiple medical institutions collaboratively training a model using federated learning (FL) has become a promising solution for maximizing the potential of data-driven models, yet the non-independent and identically distributed (non-iid) data in medical images is still an outstanding challenge in real-world practice. ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	272,530
2007.02758	Sentiment Polarity Detection on Bengali Book Reviews Using Multinomial Naive Bayes	Recently, sentiment polarity detection has increased attention to NLP researchers due to the massive availability of customer's opinions or reviews in the online platform. Due to the continued expansion of e-commerce sites, the rate of purchase of various products, including books, are growing enormously among the peop...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	185,846
1512.02752	A Novel Regularized Principal Graph Learning Framework on Explicit Graph Representation	Many scientific datasets are of high dimension, and the analysis usually requires visual manipulation by retaining the most important structures of data. Principal curve is a widely used approach for this purpose. However, many existing methods work only for data with structures that are not self-intersected, which is ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	49,966
2107.01303	Data-driven mapping between functional connectomes using optimal transport	Functional connectomes derived from functional magnetic resonance imaging have long been used to understand the functional organization of the brain. Nevertheless, a connectome is intrinsically linked to the atlas used to create it. In other words, a connectome generated from one atlas is different in scale and resolut...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	244,437
2406.18930	Reasoning About Action and Change	The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to kno...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	468,239
1803.00969	Energy Efficiency of Opportunistic Device-to-Device Relaying Under Lognormal Shadowing	Energy consumption is a major limitation of low power and mobile devices. Efficient transmission protocols are required to minimize an energy consumption of the mobile devices for ubiquitous connectivity in the next generation wireless networks. Opportunistic schemes select a single relay using the criteria of the best...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	91,788
2403.05557	Re-thinking Human Activity Recognition with Hierarchy-aware Label Relationship Modeling	Human Activity Recognition (HAR) has been studied for decades, from data collection, learning models, to post-processing and result interpretations. However, the inherent hierarchy in the activities remains relatively under-explored, despite its significant impact on model performance and interpretation. In this paper,...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	436,056
2108.02095	Human-In-The-Loop Document Layout Analysis	Document layout analysis (DLA) aims to divide a document image into different types of regions. DLA plays an important role in the document content understanding and information extraction systems. Exploring a method that can use less data for effective training contributes to the development of DLA. We consider a Huma...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	249,220
2203.10609	A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms	Image augmentation techniques have been widely investigated to improve the performance of deep learning (DL) algorithms on mammography classification tasks. Recent methods have proved the efficiency of image augmentation on data deficiency or data imbalance issues. In this paper, we propose a novel transparency strateg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,608
2008.01059	Improving One-stage Visual Grounding by Recursive Sub-query Construction	We improve one-stage visual grounding by addressing current limitations on grounding long and complex queries. Existing one-stage methods encode the entire language query as a single sentence embedding vector, e.g., taking the embedding from BERT or the hidden state from LSTM. This single vector representation is prone...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	190,191
2409.13672	Recent Advances in Non-convex Smoothness Conditions and Applicability to Deep Linear Neural Networks	The presence of non-convexity in smooth optimization problems arising from deep learning have sparked new smoothness conditions in the literature and corresponding convergence analyses. We discuss these smoothness conditions, order them, provide conditions for determining whether they hold, and evaluate their applicabi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	490,092
2301.01424	Scene Synthesis from Human Motion	Large-scale capture of human motion with diverse, complex scenes, while immensely useful, is often considered prohibitively costly. Meanwhile, human motion alone contains rich information about the scene they reside in and interact with. For example, a sitting human suggests the existence of a chair, and their leg posi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	339,233
1906.10048	SurReal: Fr\'echet Mean and Distance Transform for Complex-Valued Deep Learning	We develop a novel deep learning architecture for naturally complex-valued data, which is often subject to complex scaling ambiguity. We treat each sample as a field in the space of complex numbers. With the polar form of a complex-valued number, the general group that acts in this space is the product of planar rotati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	136,343
2205.03153	Bridging the Domain Gap for Stance Detection for the Zulu language	Misinformation has become a major concern in recent last years given its spread across our information sources. In the past years, many NLP tasks have been introduced in this area, with some systems reaching good results on English language datasets. Existing AI based approaches for fighting misinformation in literatur...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	295,187
2303.05208	Geometry of Language	In this article, we present a fresh perspective on language, combining ideas from various sources, but mixed in a new synthesis. As in the minimalist program, the question is whether we can formulate an elegant formalism, a universal grammar or a mechanism which explains significant aspects of the human faculty of lang...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	350,386
1005.5516	On the Fly Query Entity Decomposition Using Snippets	One of the most important issues in Information Retrieval is inferring the intents underlying users' queries. Thus, any tool to enrich or to better contextualized queries can proof extremely valuable. Entity extraction, provided it is done fast, can be one of such tools. Such techniques usually rely on a prior training...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	6,611
2406.13781	A Primal-Dual Framework for Transformers and Neural Networks	Self-attention is key to the remarkable success of transformers in sequence modeling tasks including many applications in natural language processing and computer vision. Like neural network layers, these attention mechanisms are often developed by heuristics and experience. To provide a principled framework for constr...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	465,996
2401.13537	Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models	We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a novel scheme to perform masked modeling based pre-training to learn permutation in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	423,759
2402.08320	The Paradox of Motion: Evidence for Spurious Correlations in Skeleton-based Gait Recognition Models	Gait, an unobtrusive biometric, is valued for its capability to identify individuals at a distance, across external outfits and environmental conditions. This study challenges the prevailing assumption that vision-based gait recognition, in particular skeleton-based gait recognition, relies primarily on motion patterns...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	429,059
2206.07632	Exploring Chemical Space with Score-based Out-of-distribution Generation	A well-known limitation of existing molecular generative models is that the generated molecules highly resemble those in the training set. To generate truly novel molecules that may have even better properties for de novo drug discovery, more powerful exploration in the chemical space is necessary. To this end, we prop...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,811
2106.12444	Prospects for Analog Circuits in Deep Networks	Operations typically used in machine learning al-gorithms (e.g. adds and soft max) can be implemented bycompact analog circuits. Analog Application-Specific Integrated Circuit (ASIC) designs that implement these algorithms using techniques such as charge sharing circuits and subthreshold transistors, achieve very high ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	242,726
2408.01035	Structure from Motion-based Motion Estimation and 3D Reconstruction of Unknown Shaped Space Debris	With the boost in the number of spacecraft launches in the current decades, the space debris problem is daily becoming significantly crucial. For sustainable space utilization, the continuous removal of space debris is the most severe problem for humanity. To maximize the reliability of the debris capture mission in or...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	478,076
2102.12463	Generating and Blending Game Levels via Quality-Diversity in the Latent Space of a Variational Autoencoder	Several works have demonstrated the use of variational autoencoders (VAEs) for generating levels in the style of existing games and blending levels across different games. Further, quality-diversity (QD) algorithms have also become popular for generating varied game content by using evolution to explore a search space ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	221,738
2410.00502	Multi-Target Cross-Lingual Summarization: a novel task and a language-neutral approach	Cross-lingual summarization aims to bridge language barriers by summarizing documents in different languages. However, ensuring semantic coherence across languages is an overlooked challenge and can be critical in several contexts. To fill this gap, we introduce multi-target cross-lingual summarization as the task of s...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	493,406
1903.01284	Relation Extraction Datasets in the Digital Humanities Domain and their Evaluation with Word Embeddings	In this research, we manually create high-quality datasets in the digital humanities domain for the evaluation of language models, specifically word embedding models. The first step comprises the creation of unigram and n-gram datasets for two fantasy novel book series for two task types each, analogy and doesn't-match...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	123,225
1907.03641	Smart Households Demand Response Management with Micro Grid	Nowadays the emerging smart grid technology opens up the possibility of two-way communication between customers and energy utilities. Demand Response Management (DRM) offers the promise of saving money for commercial customers and households while helps utilities operate more efficiently. In this paper, an Incentive-ba...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	137,901
2007.03032	Continual Learning in Human Activity Recognition: an Empirical Analysis of Regularization	Given the growing trend of continual learning techniques for deep neural networks focusing on the domain of computer vision, there is a need to identify which of these generalizes well to other tasks such as human activity recognition (HAR). As recent methods have mostly been composed of loss regularization terms and m...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	185,922
2401.00870	ConfusionPrompt: Practical Private Inference for Online Large Language Models	State-of-the-art large language models (LLMs) are typically deployed as online services, requiring users to transmit detailed prompts to cloud servers. This raises significant privacy concerns. In response, we introduce ConfusionPrompt, a novel framework for private LLM inference that protects user privacy by: (i) deco...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	419,136
2111.07256	Towards annotation of text worlds in a literary work	Literary texts are usually rich in meanings and their interpretation complicates corpus studies and automatic processing. There have been several attempts to create collections of literary texts with annotation of literary elements like the author's speech, characters, events, scenes etc. However, they resulted in smal...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	266,320
2302.09155	Med-EASi: Finely Annotated Dataset and Models for Controllable Simplification of Medical Texts	Automatic medical text simplification can assist providers with patient-friendly communication and make medical texts more accessible, thereby improving health literacy. But curating a quality corpus for this task requires the supervision of medical experts. In this work, we present $\textbf{Med-EASi}$ ($\underline{\te...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	346,300
2501.01874	DFF: Decision-Focused Fine-tuning for Smarter Predict-then-Optimize with Limited Data	Decision-focused learning (DFL) offers an end-to-end approach to the predict-then-optimize (PO) framework by training predictive models directly on decision loss (DL), enhancing decision-making performance within PO contexts. However, the implementation of DFL poses distinct challenges. Primarily, DL can result in devi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	522,247
2202.00772	PiP-X: Online feedback motion planning/replanning in dynamic environments using invariant funnels	Computing kinodynamically feasible motion plans and repairing them on-the-fly as the environment changes is a challenging, yet relevant problem in robot-navigation. We propose a novel online single-query sampling-based motion re-planning algorithm - PiP-X, using finite-time invariant sets - funnels. We combine concepts...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	278,252
1605.04672	A Critical Examination of RESCAL for Completion of Knowledge Bases with Transitive Relations	Link prediction in large knowledge graphs has received a lot of attention recently because of its importance for inferring missing relations and for completing and improving noisily extracted knowledge graphs. Over the years a number of machine learning researchers have presented various models for predicting the prese...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	55,904
2310.18479	Weighted Sampled Split Learning (WSSL): Balancing Privacy, Robustness, and Fairness in Distributed Learning Environments	This study presents Weighted Sampled Split Learning (WSSL), an innovative framework tailored to bolster privacy, robustness, and fairness in distributed machine learning systems. Unlike traditional approaches, WSSL disperses the learning process among multiple clients, thereby safeguarding data confidentiality. Central...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	403,562
2403.11795	Low-Cost Privacy-Aware Decentralized Learning	This paper introduces ZIP-DL, a novel privacy-aware decentralized learning (DL) algorithm that exploits correlated noise to provide strong privacy protection against a local adversary while yielding efficient convergence guarantees for a low communication cost. The progressive neutralization of the added noise during t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	438,866
2110.02896	Predicting the Popularity of Games on Steam	The video game industry has seen rapid growth over the last decade. Thousands of video games are released and played by millions of people every year, creating a large community of players. Steam is a leading gaming platform and social networking site, which allows its users to purchase and store games. A by-product of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	259,291
2202.01473	A multi-domain virtual network embedding algorithm with delay prediction	Virtual network embedding (VNE) is an crucial part of network virtualization (NV), which aims to map the virtual networks (VNs) to a shared substrate network (SN). With the emergence of various delay-sensitive applications, how to improve the delay performance of the system has become a hot topic in academic circles. B...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	278,496
2409.00890	Towards Investigating Biases in Spoken Conversational Search	Voice-based systems like Amazon Alexa, Google Assistant, and Apple Siri, along with the growing popularity of OpenAI's ChatGPT and Microsoft's Copilot, serve diverse populations, including visually impaired and low-literacy communities. This reflects a shift in user expectations from traditional search to more interact...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	485,119

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