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
2407.18774	Optimal Control on Positive Cones	An optimal control problem on finite-dimensional positive cones is stated. Under a critical assumption on the cone, the corresponding Bellman equation is satisfied by a linear function, which can be computed by convex optimization. A separate theorem relates the assumption on the cone to the existence of minimal elemen...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	476,513
2212.03387	Generating Real-Time Strategy Game Units Using Search-Based Procedural Content Generation and Monte Carlo Tree Search	Real-Time Strategy (RTS) game unit generation is an unexplored area of Procedural Content Generation (PCG) research, which leaves the question of how to automatically generate interesting and balanced units unanswered. Creating unique and balanced units can be a difficult task when designing an RTS game, even for human...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	335,098
1908.04577	StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding	Recently, the pre-trained language model, BERT (and its robustly optimized version RoBERTa), has attracted a lot of attention in natural language understanding (NLU), and achieved state-of-the-art accuracy in various NLU tasks, such as sentiment classification, natural language inference, semantic textual similarity an...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	141,521
1601.03764	Linear Algebraic Structure of Word Senses, with Applications to Polysemy	Word embeddings are ubiquitous in NLP and information retrieval, but it is unclear what they represent when the word is polysemous. Here it is shown that multiple word senses reside in linear superposition within the word embedding and simple sparse coding can recover vectors that approximately capture the senses. The ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	50,939
2410.22489	Multimodality Helps Few-Shot 3D Point Cloud Semantic Segmentation	Few-shot 3D point cloud segmentation (FS-PCS) aims at generalizing models to segment novel categories with minimal annotated support samples. While existing FS-PCS methods have shown promise, they primarily focus on unimodal point cloud inputs, overlooking the potential benefits of leveraging multimodal information. In...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	503,650
1805.10505	Cookie Synchronization: Everything You Always Wanted to Know But Were Afraid to Ask	User data is the primary input of digital advertising, fueling the free Internet as we know it. As a result, web companies invest a lot in elaborate tracking mechanisms to acquire user data that can sell to data markets and advertisers. However, with same-origin policy, and cookies as a primary identification mechanism...	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	98,696
2312.12964	Far- and Near-Field Channel Measurements and Characterization in the Terahertz Band Using a Virtual Antenna Array	Extremely large-scale antenna array (ELAA) technologies consisting of ultra-massive multiple-input-multiple-output (UM-MIMO) or reconfigurable intelligent surfaces (RISs), are emerging to meet the demand of wireless systems in sixth-generation and beyond communications for enhanced coverage and extreme data rates up to...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	417,168
2407.16413	Low Complexity Regularized Phase Retrieval	In this paper, we study the phase retrieval problem in the situation where the vector to be recovered has an a priori structure that can encoded into a regularization term. This regularizer is intended to promote solutions conforming to some notion of simplicity or low complexity. We investigate both noiseless recovery...	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	475,595
2007.04410	A Bayesian decision support system for counteracting activities of terrorist groups	Activities of terrorist groups present a serious threat to the security and well-being of the general public. Counterterrorism authorities aim to identify and frustrate the plans of terrorist groups before they are put into action. Whilst the activities of terrorist groups are likely to be hidden and disguised, the mem...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	186,339
2208.00647	An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbers	We introduce a distance-based neural network model for regression, in which prediction uncertainty is quantified by a belief function on the real line. The model interprets the distances of the input vector to prototypes as pieces of evidence represented by Gaussian random fuzzy numbers (GRFN's) and combined by the gen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	310,925
2306.05014	Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges	There is growing interest in discovering interpretable, closed-form equations for subgrid-scale (SGS) closures/parameterizations of complex processes in Earth systems. Here, we apply a common equation-discovery technique with expansive libraries to learn closures from filtered direct numerical simulations of 2D turbule...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,013
2404.01218	Towards System Modelling to Support Diseases Data Extraction from the Electronic Health Records for Physicians Research Activities	The use of Electronic Health Records (EHRs) has increased dramatically in the past 15 years, as, it is considered an important source of managing data od patients. The EHRs are primary sources of disease diagnosis and demographic data of patients worldwide. Therefore, the data can be utilized for secondary tasks such a...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	443,316
1811.03217	RGB-D SLAM in Dynamic Environments Using Point Correlations	In this paper, a simultaneous localization and mapping (SLAM) method that eliminates the influence of moving objects in dynamic environments is proposed. This method utilizes the correlation between map points to separate points that are part of the static scene and points that are part of different moving objects into...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	112,782
2108.12176	Rethinking the Misalignment Problem in Dense Object Detection	Object detection aims to localize and classify the objects in a given image, and these two tasks are sensitive to different object regions. Therefore, some locations predict high-quality bounding boxes but low classification scores, and some locations are quite the opposite. A misalignment exists between the two tasks,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,419
2011.06982	Multi-layered tensor networks for image classification	The recently introduced locally orderless tensor network (LoTeNet) for supervised image classification uses matrix product state (MPS) operations on grids of transformed image patches. The resulting patch representations are combined back together into the image space and aggregated hierarchically using multiple MPS bl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	206,402
2109.09202	Automated and Explainable Ontology Extension Based on Deep Learning: A Case Study in the Chemical Domain	Reference ontologies provide a shared vocabulary and knowledge resource for their domain. Manual construction enables them to maintain a high quality, allowing them to be widely accepted across their community. However, the manual development process does not scale for large domains. We present a new methodology for au...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	256,190
2007.04490	Artificial Intelligence and Machine Learning in 5G Network Security: Opportunities, advantages, and future research trends	Recent technological and architectural advancements in 5G networks have proven their worth as the deployment has started over the world. Key performance elevating factor from access to core network are softwareization, cloudification and virtualization of key enabling network functions. Along with the rapid evolution c...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	186,368
1412.6012	CITlab ARGUS for historical data tables	We describe CITlab's recognition system for the ANWRESH-2014 competition attached to the 14. International Conference on Frontiers in Handwriting Recognition, ICFHR 2014. The task comprises word recognition from segmented historical documents. The core components of our system are based on multi-dimensional recurrent n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	38,547
1808.01785	Defense Against Adversarial Attacks with Saak Transform	Deep neural networks (DNNs) are known to be vulnerable to adversarial perturbations, which imposes a serious threat to DNN-based decision systems. In this paper, we propose to apply the lossy Saak transform to adversarially perturbed images as a preprocessing tool to defend against adversarial attacks. Saak transform i...	false	false	false	false	true	false	false	false	false	false	false	true	true	false	false	false	false	false	104,648
2211.05655	DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering	Question answering models commonly have access to two sources of "knowledge" during inference time: (1) parametric knowledge - the factual knowledge encoded in the model weights, and (2) contextual knowledge - external knowledge (e.g., a Wikipedia passage) given to the model to generate a grounded answer. Having these ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	329,638
1903.04298	An efficient iterative method for looped pipe network hydraulics	Original and improved version of the Hardy Cross iterative method with related modifications are today widely used for calculation of fluid flow through conduits in loops-like distribution networks of pipes with known node fluid consumptions. Fluid in these networks is usually natural gas for distribution in the munici...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	123,950
2110.10914	An Empirical Evaluation of Time-Series Feature Sets	Solving time-series problems with features has been rising in popularity due to the availability of software for feature extraction. Feature-based time-series analysis can now be performed using many different feature sets, including hctsa (7730 features: Matlab), feasts (42 features: R), tsfeatures (63 features: R), K...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,299
2011.04904	Feasible Region-based Identification Using Duality (Extended Version)	We consider the problem of estimating bounds on parameters representing tasks being performed by individual robots in a multirobot system. In our previous work, we derived necessary conditions based on persistency of excitation analysis for the exact identification of these parameters. We concluded that depending on th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	205,735
1912.11545	Barycenters of Natural Images -- Constrained Wasserstein Barycenters for Image Morphing	Image interpolation, or image morphing, refers to a visual transition between two (or more) input images. For such a transition to look visually appealing, its desirable properties are (i) to be smooth; (ii) to apply the minimal required change in the image; and (iii) to seem "real", avoiding unnatural artifacts in eac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	158,588
cs/0702144	Slope One Predictors for Online Rating-Based Collaborative Filtering	Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. We propose three related slope one schemes with predictors of the form f(x) = x + b, which precompute the average difference between the ratings of one item and another for users who rated both....	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	540,191
2407.06230	Predicting Word Similarity in Context with Referential Translation Machines	We identify the similarity between two words in English by casting the task as machine translation performance prediction (MTPP) between the words given the context and the distance between their similarities. We use referential translation machines (RTMs), which allows a common representation for training and test set...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	471,328
2406.18108	Token-Weighted RNN-T for Learning from Flawed Data	ASR models are commonly trained with the cross-entropy criterion to increase the probability of a target token sequence. While optimizing the probability of all tokens in the target sequence is sensible, one may want to de-emphasize tokens that reflect transcription errors. In this work, we propose a novel token-weight...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	467,874
2205.01875	Machine Learning based Framework for Robust Price-Sensitivity Estimation with Application to Airline Pricing	We consider the problem of dynamic pricing of a product in the presence of feature-dependent price sensitivity. Developing practical algorithms that can estimate price elasticities robustly, especially when information about no purchases (losses) is not available, to drive such automated pricing systems is a challenge ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	294,746
2403.00293	Efficient Adapter Tuning of Pre-trained Speech Models for Automatic Speaker Verification	With excellent generalization ability, self-supervised speech models have shown impressive performance on various downstream speech tasks in the pre-training and fine-tuning paradigm. However, as the growing size of pre-trained models, fine-tuning becomes practically unfeasible due to heavy computation and storage over...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	433,934
2311.17365	Symbol-LLM: Leverage Language Models for Symbolic System in Visual Human Activity Reasoning	Human reasoning can be understood as a cooperation between the intuitive, associative "System-1" and the deliberative, logical "System-2". For existing System-1-like methods in visual activity understanding, it is crucial to integrate System-2 processing to improve explainability, generalization, and data efficiency. O...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,274
2007.06343	AirCapRL: Autonomous Aerial Human Motion Capture using Deep Reinforcement Learning	In this letter, we introduce a deep reinforcement learning (RL) based multi-robot formation controller for the task of autonomous aerial human motion capture (MoCap). We focus on vision-based MoCap, where the objective is to estimate the trajectory of body pose and shape of a single moving person using multiple micro a...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	true	false	false	false	186,987
1907.01978	Using Bi-Directional Information Exchange to Improve Decentralized Schedule-Driven Traffic Control	Recent work in decentralized, schedule-driven traffic control has demonstrated the ability to improve the efficiency of traffic flow in complex urban road networks. In this approach, a scheduling agent is associated with each intersection. Each agent senses the traffic approaching its intersection and in real-time cons...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	137,488
2302.01676	Show me your NFT and I tell you how it will perform: Multimodal representation learning for NFT selling price prediction	Non-Fungible Tokens (NFTs) represent deeds of ownership, based on blockchain technologies and smart contracts, of unique crypto assets on digital art forms (e.g., artworks or collectibles). In the spotlight after skyrocketing in 2021, NFTs have attracted the attention of crypto enthusiasts and investors intent on placi...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	true	false	false	343,701
2403.03121	Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution	Large language models (LLMs) reflect societal norms and biases, especially about gender. While societal biases and stereotypes have been extensively researched in various NLP applications, there is a surprising gap for emotion analysis. However, emotion and gender are closely linked in societal discourse. E.g., women a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	435,071
2301.01057	BS3D: Building-scale 3D Reconstruction from RGB-D Images	Various datasets have been proposed for simultaneous localization and mapping (SLAM) and related problems. Existing datasets often include small environments, have incomplete ground truth, or lack important sensor data, such as depth and infrared images. We propose an easy-to-use framework for acquiring building-scale ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	339,119
1808.05727	Ensemble-based Adaptive Single-shot Multi-box Detector	We propose two improvements to the SSD---single shot multibox detector. First, we propose an adaptive approach for default box selection in SSD. This uses data to reduce the uncertainty in the selection of best aspect ratios for the default boxes and improves performance of SSD for datasets containing small and complex...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	105,400
1406.3726	Evaluation of Machine Learning Techniques for Green Energy Prediction	We evaluate the following Machine Learning techniques for Green Energy (Wind, Solar) Prediction: Bayesian Inference, Neural Networks, Support Vector Machines, Clustering techniques (PCA). Our objective is to predict green energy using weather forecasts, predict deviations from forecast green energy, find correlation am...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	33,866
2010.10885	Improved Runtime Results for Simple Randomised Search Heuristics on Linear Functions with a Uniform Constraint	In the last decade remarkable progress has been made in development of suitable proof techniques for analysing randomised search heuristics. The theoretical investigation of these algorithms on classes of functions is essential to the understanding of the underlying stochastic process. Linear functions have been tradit...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	202,041
2401.09336	To deform or not: treatment-aware longitudinal registration for breast DCE-MRI during neoadjuvant chemotherapy via unsupervised keypoints detection	Clinicians compare breast DCE-MRI after neoadjuvant chemotherapy (NAC) with pre-treatment scans to evaluate the response to NAC. Clinical evidence supports that accurate longitudinal deformable registration without deforming treated tumor regions is key to quantifying tumor changes. We propose a conditional pyramid reg...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	422,225
2005.03452	Lifted Regression/Reconstruction Networks	In this work we propose lifted regression/reconstruction networks (LRRNs), which combine lifted neural networks with a guaranteed Lipschitz continuity property for the output layer. Lifted neural networks explicitly optimize an energy model to infer the unit activations and therefore---in contrast to standard feed-forw...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	176,168
2306.03220	Risk-Aware Reward Shaping of Reinforcement Learning Agents for Autonomous Driving	Reinforcement learning (RL) is an effective approach to motion planning in autonomous driving, where an optimal driving policy can be automatically learned using the interaction data with the environment. Nevertheless, the reward function for an RL agent, which is significant to its performance, is challenging to be de...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	371,233
2304.05955	Unified Numerical Stability and Accuracy Analysis of the Partitioned-Solution Approach	This paper focuses on the Partitioned-Solution Approach (PSA) employed for the Time-Domain Simulation (TDS) of dynamic power system models. In PSA, differential equations are solved at each step of the TDS for state variables, whereas algebraic equations are solved separately. The goal of this paper is to propose a nov...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	357,792
2102.11274	Sustainable Federated Learning	Potential environmental impact of machine learning by large-scale wireless networks is a major challenge for the sustainability of future smart ecosystems. In this paper, we introduce sustainable machine learning in federated learning settings, using rechargeable devices that can collect energy from the ambient environ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	221,373
1802.09640	Modeling Others using Oneself in Multi-Agent Reinforcement Learning	We consider the multi-agent reinforcement learning setting with imperfect information in which each agent is trying to maximize its own utility. The reward function depends on the hidden state (or goal) of both agents, so the agents must infer the other players' hidden goals from their observed behavior in order to sol...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	91,353
2101.10113	ROS-NetSim: A Framework for the Integration of Robotic and Network Simulators	Multi-agent systems play an important role in modern robotics. Due to the nature of these systems, coordination among agents via communication is frequently necessary. Indeed, Perception-Action-Communication (PAC) loops, or Perception-Action loops closed over a communication channel, are a critical component of multi-r...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	216,823
2402.09009	A Practical and Online Trajectory Planner for Autonomous Ships' Berthing, Incorporating Speed Control	Autonomous ships are essentially designed and equipped to perceive their internal and external environment and subsequently perform appropriate actions depending on the predetermined objective(s) without human intervention. Consequently, trajectory planning algorithms for autonomous berthing must consider factors such ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	429,332
2008.01205	Concurrent Training Improves the Performance of Behavioral Cloning from Observation	Learning from demonstration is widely used as an efficient way for robots to acquire new skills. However, it typically requires that demonstrations provide full access to the state and action sequences. In contrast, learning from observation offers a way to utilize unlabeled demonstrations (e.g., video) to perform imit...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	190,237
1110.5396	Joint Channel-Network Coding Strategies for Networks with Low Complexity Relays	We investigate joint network and channel coding schemes for networks when relay nodes are not capable of performing channel coding operations. Rather, channel encoding is performed at the source node while channel decoding is done only at the destination nodes. We examine three different decoding strategies: independen...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,763
2502.09863	Solvable Dynamics of Self-Supervised Word Embeddings and the Emergence of Analogical Reasoning	The remarkable success of large language models relies on their ability to implicitly learn structured latent representations from the pretraining corpus. As a simpler surrogate for representation learning in language modeling, we study a class of solvable contrastive self-supervised algorithms which we term quadratic ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	533,634
2207.08080	Neural Color Operators for Sequential Image Retouching	We propose a novel image retouching method by modeling the retouching process as performing a sequence of newly introduced trainable neural color operators. The neural color operator mimics the behavior of traditional color operators and learns pixelwise color transformation while its strength is controlled by a scalar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	308,449
2312.00592	Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)	Reinforcement learning (RL) for robot control typically requires a detailed representation of the environment state, including information about task-relevant objects not directly measurable. Keypoint detectors, such as spatial autoencoders (SAEs), are a common approach to extracting a low-dimensional representation fr...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	412,104
1912.07209	Automated Thalamic Nuclei Segmentation Using Multi-Planar Cascaded Convolutional Neural Networks	A cascaded multi-planar scheme with a modified residual U-Net architecture was used to segment thalamic nuclei on conventional and white-matter-nulled (WMn) magnetization prepared rapid gradient echo (MPRAGE) data. A single network was optimized to work with images from healthy controls and patients with multiple scler...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	157,547
2106.13369	Distributed Nash Equilibrium Seeking Algorithm Design for Multi-Cluster Games with High-Order Players	In this paper, a multi-cluster game with high-order players is investigated. Different from the well-known multi-cluster games, the dynamics of players are taken into account in our problem. Due to the high-order dynamics of players, existing algorithms for multi-cluster games cannot solve the problem. For purpose of s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	243,051
2404.06178	Resilient Movement Planning for Continuum Robots	The paper presents an experimental study of resilient path planning for con-tinuum robots taking into account the multi-objective optimisation problem. To do this, we used two well-known algorithms, namely Genetic algorithm and A* algorithm, for path planning and the Analytical Hierarchy Process algorithm for paths eva...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	445,358
1902.08646	OpenKiwi: An Open Source Framework for Quality Estimation	We introduce OpenKiwi, a PyTorch-based open source framework for translation quality estimation. OpenKiwi supports training and testing of word-level and sentence-level quality estimation systems, implementing the winning systems of the WMT 2015-18 quality estimation campaigns. We benchmark OpenKiwi on two datasets fro...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	122,232
2110.09133	Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits	In the fixed budget thresholding bandit problem, an algorithm sequentially allocates a budgeted number of samples to different distributions. It then predicts whether the mean of each distribution is larger or lower than a given threshold. We introduce a large family of algorithms (containing most existing relevant one...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	261,691
2001.11177	A Hybrid Two-layer Feature Selection Method Using GeneticAlgorithm and Elastic Net	Feature selection, as a critical pre-processing step for machine learning, aims at determining representative predictors from a high-dimensional feature space dataset to improve the prediction accuracy. However, the increase in feature space dimensionality, comparing to the number of observations, poses a severe challe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,002
1804.08020	Synthesized Texture Quality Assessment via Multi-scale Spatial and Statistical Texture Attributes of Image and Gradient Magnitude Coefficients	Perceptual quality assessment for synthesized textures is a challenging task. In this paper, we propose a training-free reduced-reference (RR) objective quality assessment method that quantifies the perceived quality of synthesized textures. The proposed reduced-reference synthesized texture quality assessment metric i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	95,665
2403.20147	IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context	The pervasive influence of social biases in language data has sparked the need for benchmark datasets that capture and evaluate these biases in Large Language Models (LLMs). Existing efforts predominantly focus on English language and the Western context, leaving a void for a reliable dataset that encapsulates India's ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	442,632
1805.07171	On-board Range-based Relative Localization for Micro Aerial Vehicles in indoor Leader-Follower Flight	We present a range-based solution for indoor relative localization by Micro Air Vehicles (MAVs), achieving sufficient accuracy for leader-follower flight. Moving forward from previous work, we removed the dependency on a common heading measurement by the MAVs, making the relative localization accuracy independent of ma...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	97,756
2205.02987	Tell Me Something That Will Help Me Trust You: A Survey of Trust Calibration in Human-Agent Interaction	When a human receives a prediction or recommended course of action from an intelligent agent, what additional information, beyond the prediction or recommendation itself, does the human require from the agent to decide whether to trust or reject the prediction or recommendation? In this paper we survey literature in th...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	295,138
2102.06527	Mutually exciting point process graphs for modelling dynamic networks	A new class of models for dynamic networks is proposed, called mutually exciting point process graphs (MEG). MEG is a scalable network-wide statistical model for point processes with dyadic marks, which can be used for anomaly detection when assessing the significance of future events, including previously unobserved c...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,780
2412.15538	FedRLHF: A Convergence-Guaranteed Federated Framework for Privacy-Preserving and Personalized RLHF	In the era of increasing privacy concerns and demand for personalized experiences, traditional Reinforcement Learning with Human Feedback (RLHF) frameworks face significant challenges due to their reliance on centralized data. We introduce Federated Reinforcement Learning with Human Feedback (FedRLHF), a novel framewor...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	519,165
2110.08664	Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review	Scenario-based approaches have been receiving a huge amount of attention in research and engineering of automated driving systems. Due to the complexity and uncertainty of the driving environment, and the complexity of the driving task itself, the number of possible driving scenarios that an ADS or ADAS may encounter i...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	true	261,501
1911.12007	Weakly-Supervised Road Affordances Inference and Learning in Scenes without Traffic Signs	Road attributes understanding is extensively researched to support vehicle's action for autonomous driving, whereas current works mainly focus on urban road nets and rely much on traffic signs. This paper generalizes the same issue to the scenes with little or without traffic signs, such as campuses and residential are...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	155,289
2412.20172	On dataset transferability in medical image classification	Current transferability estimation methods designed for natural image datasets are often suboptimal in medical image classification. These methods primarily focus on estimating the suitability of pre-trained source model features for a target dataset, which can lead to unrealistic predictions, such as suggesting that t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	521,121
2410.04660	Knowledge Graph Based Agent for Complex, Knowledge-Intensive QA in Medicine	Biomedical knowledge is uniquely complex and structured, requiring distinct reasoning strategies compared to other scientific disciplines like physics or chemistry. Biomedical scientists do not rely on a single approach to reasoning; instead, they use various strategies, including rule-based, prototype-based, and case-...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	495,384
2203.16891	A survey of neural models for the automatic analysis of conversation: Towards a better integration of the social sciences	Some exciting new approaches to neural architectures for the analysis of conversation have been introduced over the past couple of years. These include neural architectures for detecting emotion, dialogue acts, and sentiment polarity. They take advantage of some of the key attributes of contemporary machine learning, s...	true	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	288,963
2106.05095	ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation	Self-training via pseudo labeling is a conventional, simple, and popular pipeline to leverage unlabeled data. In this work, we first construct a strong baseline of self-training (namely ST) for semi-supervised semantic segmentation via injecting strong data augmentations (SDA) on unlabeled images to alleviate overfitti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	239,968
1605.01091	The Resistance Perturbation Distance: A Metric for the Analysis of Dynamic Networks	To quantify the fundamental evolution of time-varying networks, and detect abnormal behavior, one needs a notion of temporal difference that captures significant organizational changes between two successive instants. In this work, we propose a family of distances that can be tuned to quantify structural changes occurr...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	55,426
2310.12964	PAC Prediction Sets Under Label Shift	Prediction sets capture uncertainty by predicting sets of labels rather than individual labels, enabling downstream decisions to conservatively account for all plausible outcomes. Conformal inference algorithms construct prediction sets guaranteed to contain the true label with high probability. These guarantees fail t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	401,220
2502.07730	DOGlove: Dexterous Manipulation with a Low-Cost Open-Source Haptic Force Feedback Glove	Dexterous hand teleoperation plays a pivotal role in enabling robots to achieve human-level manipulation dexterity. However, current teleoperation systems often rely on expensive equipment and lack multi-modal sensory feedback, restricting human operators' ability to perceive object properties and perform complex manip...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	532,726
2009.14780	Bridging Information-Seeking Human Gaze and Machine Reading Comprehension	In this work, we analyze how human gaze during reading comprehension is conditioned on the given reading comprehension question, and whether this signal can be beneficial for machine reading comprehension. To this end, we collect a new eye-tracking dataset with a large number of participants engaging in a multiple choi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	198,137
2309.13753	Policy Stitching: Learning Transferable Robot Policies	Training robots with reinforcement learning (RL) typically involves heavy interactions with the environment, and the acquired skills are often sensitive to changes in task environments and robot kinematics. Transfer RL aims to leverage previous knowledge to accelerate learning of new tasks or new body configurations. H...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	394,341
1406.1906	Refinement-Cut: User-Guided Segmentation Algorithm for Translational Science	In this contribution, a semi-automatic segmentation algorithm for (medical) image analysis is presented. More precise, the approach belongs to the category of interactive contouring algorithms, which provide real-time feedback of the segmentation result. However, even with interactive real-time contouring approaches th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	33,691
1605.08833	Muffled Semi-Supervised Learning	We explore a novel approach to semi-supervised learning. This approach is contrary to the common approach in that the unlabeled examples serve to "muffle," rather than enhance, the guidance provided by the labeled examples. We provide several variants of the basic algorithm and show experimentally that they can achieve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	56,481
2307.01881	ProPILE: Probing Privacy Leakage in Large Language Models	The rapid advancement and widespread use of large language models (LLMs) have raised significant concerns regarding the potential leakage of personally identifiable information (PII). These models are often trained on vast quantities of web-collected data, which may inadvertently include sensitive personal data. This p...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	377,501
2412.01221	Assessing GPT Model Uncertainty in Mathematical OCR Tasks via Entropy Analysis	This paper investigates the uncertainty of Generative Pre-trained Transformer (GPT) models in extracting mathematical equations from images of varying resolutions and converting them into LaTeX code. We employ concepts of entropy and mutual information to examine the recognition process and assess the model's uncertain...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	513,012
1403.6946	The NUbots Team Description Paper 2014	The NUbots team, from The University of Newcastle, Australia, has had a strong record of success in the RoboCup Standard Platform League since first entering in 2002. The team has also competed within the RoboCup Humanoid Kid-Size League since 2012. The 2014 team brings a renewed focus on software architecture, modular...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	31,852
1912.01966	Epoch-wise label attacks for robustness against label noise	The current accessibility to large medical datasets for training convolutional neural networks is tremendously high. The associated dataset labels are always considered to be the real "ground truth". However, the labeling procedures often seem to be inaccurate and many wrong labels are integrated. This may have fatal c...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	156,222
2305.15483	Weakly Supervised Vision-and-Language Pre-training with Relative Representations	Weakly supervised vision-and-language pre-training (WVLP), which learns cross-modal representations with limited cross-modal supervision, has been shown to effectively reduce the data cost of pre-training while maintaining decent performance on downstream tasks. However, current WVLP methods use only local descriptions...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	367,631
2306.06409	Functional Causal Bayesian Optimization	We propose functional causal Bayesian optimization (fCBO), a method for finding interventions that optimize a target variable in a known causal graph. fCBO extends the CBO family of methods to enable functional interventions, which set a variable to be a deterministic function of other variables in the graph. fCBO mode...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,598
2301.13267	ArchiSound: Audio Generation with Diffusion	The recent surge in popularity of diffusion models for image generation has brought new attention to the potential of these models in other areas of media generation. One area that has yet to be fully explored is the application of diffusion models to audio generation. Audio generation requires an understanding of mult...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	342,829
2310.00074	SocREval: Large Language Models with the Socratic Method for Reference-Free Reasoning Evaluation	To comprehensively gauge the capacity of current models for complex reasoning, it is crucial to assess their step-by-step reasoning in a scalable manner. Established reference-based evaluation metrics rely on human-annotated reasoning chains as references to assess the model-derived chains. However, such "gold-standard...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	395,807
2112.13756	Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment	Clinical information systems have become large repositories for semi-structured and partly annotated electronic health record data, which have reached a critical mass that makes them interesting for supervised data-driven neural network approaches. We explored automated coding of 50 character long clinical problem list...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	273,349
1502.01075	Classificatory Sorites, Probabilistic Supervenience, and Rule-Making	We view sorites in terms of stimuli acting upon a system and evoking this system's responses. Supervenience of responses on stimuli implies that they either lack tolerance (i.e., they change in every vicinity of some of the stimuli), or stimuli are not always connectable by finite chains of stimuli in which successive ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	39,901
1212.0207	Modelling Multi-Trait Scale-free Networks by Optimization	Recently, one paper in Nature(Papadopoulos, 2012) raised an old debate on the origin of the scale-free property of complex networks, which focuses on whether the scale-free property origins from the optimization or not. Because the real-world complex networks often have multiple traits, any explanation on the scale-fre...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	20,074
2202.03480	Universal Spam Detection using Transfer Learning of BERT Model	Deep learning transformer models become important by training on text data based on self-attention mechanisms. This manuscript demonstrated a novel universal spam detection model using pre-trained Google's Bidirectional Encoder Representations from Transformers (BERT) base uncased models with four datasets by efficient...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	279,215
2408.01692	A Comparative Analysis of CNN-based Deep Learning Models for Landslide Detection	Landslides inflict substantial societal and economic damage, underscoring their global significance as recurrent and destructive natural disasters. Recent landslides in northern parts of India and Nepal have caused significant disruption, damaging infrastructure and posing threats to local communities. Convolutional Ne...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	478,336
2306.04130	Collision-free Motion Generation Based on Stochastic Optimization and Composite Signed Distance Field Networks of Articulated Robot	Safe robot motion generation is critical for practical applications from manufacturing to homes. In this work, we proposed a stochastic optimization-based motion generation method to generate collision-free and time-optimal motion for the articulated robot represented by composite signed distance field (SDF) networks. ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	371,616
2501.17701	Decision-Theoretic Approaches in Learning-Augmented Algorithms	In this work, we initiate the systemic study of decision-theoretic metrics in the design and analysis of algorithms with machine-learned predictions. We introduce approaches based on both deterministic measures such as distance-based evaluation, that help us quantify how close the algorithm is to an ideal solution, as ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	528,423
2012.04728	Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics	Understanding the dynamics of neural network parameters during training is one of the key challenges in building a theoretical foundation for deep learning. A central obstacle is that the motion of a network in high-dimensional parameter space undergoes discrete finite steps along complex stochastic gradients derived f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	210,545
2112.13507	Block Modeling-Guided Graph Convolutional Neural Networks	Graph Convolutional Network (GCN) has shown remarkable potential of exploring graph representation. However, the GCN aggregating mechanism fails to generalize to networks with heterophily where most nodes have neighbors from different classes, which commonly exists in real-world networks. In order to make the propagati...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,260
1005.3873	Improved OMP Approach to Sparse Multi-path Channel Estimation via Adaptive Inter-atom Interference Mitigation	Since most components of sparse multi-path channel (SMPC) are zero, impulse response of SMPC can be recovered from a short training sequence. Though the ordinary orthogonal matching pursuit (OMP) algorithm provides a very fast implementation of SMPC estimation, it suffers from inter-atom interference (IAI), especially ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	6,530
2408.00753	A deep learning-enabled smart garment for accurate and versatile sleep conditions monitoring in daily life	In wearable smart systems, continuous monitoring and accurate classification of different sleep-related conditions are critical for enhancing sleep quality and preventing sleep-related chronic conditions. However, the requirements for device-skin coupling quality in electrophysiological sleep monitoring systems hinder ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	477,958
1709.02426	Intelligent Disaster Response via Social Media Analysis - A Survey	The success of a disaster relief and response process is largely dependent on timely and accurate information regarding the status of the disaster, the surrounding environment, and the affected people. This information is primarily provided by first responders on-site and can be enhanced by the firsthand reports posted...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	80,257
2011.12392	Geom-SPIDER-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization	The Expectation Maximization (EM) algorithm is a key reference for inference in latent variable models; unfortunately, its computational cost is prohibitive in the large scale learning setting. In this paper, we propose an extension of the Stochastic Path-Integrated Differential EstimatoR EM (SPIDER-EM) and derive comp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	208,139
2401.09716	HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization	Domain Generalization (DG) endeavors to create machine learning models that excel in unseen scenarios by learning invariant features. In DG, the prevalent practice of constraining models to a fixed structure or uniform parameterization to encapsulate invariant features can inadvertently blend specific aspects. Such an ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	422,355
2310.10355	Topology optimization of fluidic pressure-driven multi-material compliant mechanisms	Compliant mechanisms actuated by pneumatic loads are receiving increasing attention due to their direct applicability as soft robots that perform tasks using their flexible bodies. Using multiple materials to build them can further improve their performance and efficiency. Due to developments in additive manufacturing,...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	400,187
2206.00473	ILMART: Interpretable Ranking with Constrained LambdaMART	Interpretable Learning to Rank (LtR) is an emerging field within the research area of explainable AI, aiming at developing intelligible and accurate predictive models. While most of the previous research efforts focus on creating post-hoc explanations, in this paper we investigate how to train effective and intrinsical...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	300,135

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