wanyu/IteraTeR_v2 huggingface dataset:
Original:  We demonstrate the effectiveness of our algorithms with real data set, especially when the source and target data have a strong similarity .
Revised:  We demonstrate the effectiveness of our algorithms with real data sets, focusing primarily on when the source and target data have a strong similarity .
Edit intent: clarity
Original:  We demonstrate the effectiveness of our algorithms with real data set, especially when the source and target data have a strong similarity .
Revised:  We demonstrate the effectiveness of our algorithms with real data set, especially when the source and target data have strong similarities .
Edit intent: fluency
Original: This paper presents the development of mixed reality multi-sensor  platform to improve the teaching and learning experience of arc welding tasks.
Revised: This paper presents the development of a multi-sensor platform to improve the teaching and learning experience of arc welding tasks.
Edit intent: clarity
Original:  Some new teaching methods have introduced the use of virtual reality as a way to safely simulate the process and visualize the geometry of the workpieces.
Revised:  To tackle these problems, some recent training approaches have leveraged on virtual reality (VR) as a way to safely simulate the process and visualize the geometry of the workpieces.
Edit intent: clarity
Original:  However, the synthetic nature of these simulators reduces the effectiveness of the platforms.
Revised:  However, the synthetic nature of the virtual simulation reduces the effectiveness of the platforms.
Edit intent: clarity
Original:  In contrast with traditional systems, our new platform provides trainees with  virtual cues of the seam geometry, automatic spot tracking, and a performance score (useful for instructors to assess the task) .
Revised:  In contrast with traditional systems, our new platform provides trainees with virtual cues of the seam geometry, automatic spot tracking, and a performance score .
Edit intent: coherence
Original:  To validate the method 's feasibility, we conducted a detailed experimental study with several teaching and learning welding tasks, and compared its advantages with the current practice and virtual welding solutions .
Revised:  To validate the platform 's feasibility, we conducted a detailed experimental study with several teaching and learning welding tasks, and compared its advantages with the current practice and virtual welding solutions .
Edit intent: clarity
Original:  To validate the method 's feasibility, we conducted a detailed experimental study with several teaching and learning welding tasks, and compared its advantages with the current practice and virtual welding solutions .
Revised:  To validate the method 's feasibility, we conduct extensive experiments with several welding training tasks. We show that compared with the traditional training practice and recent virtual reality approaches, our automated method achieves better performances in terms of accuracy, learning curve, and effectiveness .
Edit intent: clarity
Original:  The code will be publicly available.
Revised:  The code is publicly available.
Edit intent: clarity
Original: In order to meet mobile cellular users' ever-increasing network usage , today's 4G and 5G networks are designed mainly with the goal of maximizing spectral efficiency.
Revised: In order to meet mobile cellular users' ever-increasing data demands , today's 4G and 5G networks are designed mainly with the goal of maximizing spectral efficiency.
Edit intent: clarity
Original:  This Challenge paper takes a long view on this problem, envisioning a NextG scenario where the network leverages quantum annealing computation for cellular baseband processing.
Revised:  This Challenge paper takes a long view on this problem, envisioning a NextG scenario where the network leverages quantum annealing for cellular baseband processing.
Edit intent: clarity
Original:  We gather and synthesize insights on power consumption, computational throughput and latency, spectral efficiency, and operational cost, and deployment timelines surrounding quantum technology.
Revised:  We gather and synthesize insights on power consumption, computational throughput and latency, spectral efficiency, operational cost, and deployment timelines surrounding quantum technology.
Edit intent: fluency
Original:  Our quantitative analysis predicts that with quantum  hardware operating at a 140 \mus problem latency and 4.3M qubits, quantum computation will achieve a spectral efficiency equal to silicon while reducing power consumption by 40.8 kW (45\% lower) in a representative 5G base station scenario with 400 MHz bandwidth and 64 antennas, and an 8 kW power reduction (16\% lower) using 2.2M qubits in a 200 MHz-bandwidth 5G scenario.
Revised:  Our quantitative analysis predicts that with quantum hardware operating at a 140 \mus problem latency and 4.3M qubits, quantum annealing will achieve a spectral efficiency equal to silicon while reducing power consumption by 40.8 kW (45\% lower) in a representative 5G base station scenario with 400 MHz bandwidth and 64 antennas, and an 8 kW power reduction (16\% lower) using 2.2M qubits in a 200 MHz-bandwidth 5G scenario.
Edit intent: clarity
Original:  Researchers have been using this foundation for the past 35 years to elevate logic programming from its roots in first-order classical logic into higher-order versions of both intuitionistic and linear logic.
Revised:  Researchers have been using this foundation for the past 35 years to elevate logic programming from its roots in first-order classical logic into higher-order versions of intuitionistic and linear logic.
Edit intent: coherence
Original:  Logic programming has also inspired new results in proof theory, such as  polarity and focused proofs.
Revised:  Logic programming has also inspired new results in proof theory, such as those involving polarity and focused proofs.
Edit intent: clarity
Original:  These recent results have also provided a high-level means for presenting the differences between forward-chaining and backward-chaining style inferences.
Revised:  These recent results provide a high-level means for presenting the differences between forward-chaining and backward-chaining style inferences.
Edit intent: clarity
Original: Scientists have long aimed to discover meaningful equations which accurately describe data.
Revised: Scientists have long aimed to discover meaningful formulae which accurately describe data.
Edit intent: clarity
Original:  We developed a methodology combining automated theorem proving with symbolic regression, enabling principled derivations of laws of nature .
Revised:  We developed a methodology combining automated theorem proving with symbolic regression, enabling principled derivations of models of natural phenomena .
Edit intent: clarity
Original:  We demonstrate this for Kepler's third law  , Einstein's relativistic time dilation , and Langmuir's theory of adsorption, in each case, automatically connecting experimental data with background theory .
Revised:  We demonstrate these concepts for Kepler's third law , Einstein's relativistic time dilation , and Langmuir's theory of adsorption, in each case, automatically connecting experimental data with background theory .
Edit intent: clarity
Original:  We demonstrate this for Kepler's third law  , Einstein's relativistic time dilation , and Langmuir's theory of adsorption, in each case, automatically connecting experimental data with background theory .
Revised:  We demonstrate this for Kepler's third law , Einstein's relativistic time-dilation law , and Langmuir's theory of adsorption, in each case, automatically connecting experimental data with background theory .
Edit intent: clarity
Original:  We demonstrate this for Kepler's third law  , Einstein's relativistic time dilation , and Langmuir's theory of adsorption, in each case, automatically connecting experimental data with background theory .
Revised:  We demonstrate this for Kepler's third law , Einstein's relativistic time dilation , and Langmuir's theory of adsorption, automatically connecting experimental data with background theory .
Edit intent: clarity
Original:  The combination of logical reasoning with machine learning provides generalizable insights into key aspects of the natural phenomena .
Revised:  The combination of reasoning with machine learning provides generalizable insights into key aspects of the natural phenomena .
Edit intent: clarity
Original:  However, such method fundamentally endangers user privacy.
Revised:  However, this method fundamentally endangers user privacy.
Edit intent: clarity
Original:  To analyze the privacy risk of the revealed information, we introduce a reasoning framework that measures an adversary's ability to infer a predicate about the client input with good confidence.
Revised:  To analyze the privacy risk of the revealed information, we introduce a framework for measuring an adversary's ability to infer a predicate about the client input with good confidence.
Edit intent: clarity
Original:  We then combine the protocol with various similarity protocols, showing that SBB provides a speedup of at least 29x on large-scale databases, while retaining correctness of over 95\%.
Revised:  We then combine SBB with various similarity protocols, showing that SBB provides a speedup of at least 29x on large-scale databases, while retaining correctness of over 95\%.
Edit intent: clarity
Original:  To contend with this challenge, we propose and formalize the concept of similarity-based bucketization  (SBB).
Revised:  To contend with this challenge, we propose and formalize the concept of similarity-based bucketization ~ (SBB).
Edit intent: fluency
Original:  To analyze the privacy risk of the revealed information, we introduce a framework for measuring an adversary's ability to infer a predicate about the client input with good confidence .
Revised:  To analyze the privacy risk of the revealed information, we introduce a framework for measuring an adversary's confidence in inferring a predicate about the client input with good confidence .
Edit intent: clarity
Original:  To analyze the privacy risk of the revealed information, we introduce a framework for measuring an adversary's ability to infer a predicate about the client input with good confidence .
Revised:  To analyze the privacy risk of the revealed information, we introduce a framework for measuring an adversary's ability to infer a predicate about the client input correctly .
Edit intent: clarity
Original: Let X = (X_i)_{1\leq i \leq n} be an i.i.d. sample of square-integrable variables in R^d, with common expectation \mu and covariance matrix \Sigma, both unknown.
Revised: Let X = (X_i)_{1\leq i \leq n} be an i.i.d. sample of square-integrable variables in R^d, 
Edit intent: coherence
Original:  we also tackle the more general two-sample mean closeness {\em   testing problem.
Revised:  we also tackle the more general two-sample mean closeness {\em ) testing problem.
Edit intent: fluency
Original:  Our method relies on Spark AR Studio, a developer program made by Facebook that is used to create Instagram face filters.
Revised:  Our method relies on SparkAR Studio, a developer program made by Facebook that is used to create Instagram face filters.
Edit intent: fluency
Original:  We also demonstrate the usefulness of our method by evaluating state-of-the-art face recognition systems (FaceNet, VGG-face, ArcFace) trained on the enhanced data sets and showing that they outperform equivalent systems trained on the original data sets (containing faces without masks)  , when the test benchmark contains masked faces.
Revised:  We also demonstrate the usefulness of our method by evaluating state-of-the-art face recognition systems (FaceNet, VGG-face, ArcFace) trained on our enhanced data sets and showing that they outperform equivalent systems trained on the original data sets (containing faces without masks) , when the test benchmark contains masked faces.
Edit intent: fluency
Original:  We also demonstrate the usefulness of our method by evaluating state-of-the-art face recognition systems (FaceNet, VGG-face, ArcFace) trained on the enhanced data sets and showing that they outperform equivalent systems trained on the original data sets (containing faces without masks)  , when the test benchmark contains masked faces.
Revised:  We also demonstrate the usefulness of our method by evaluating state-of-the-art face recognition systems (FaceNet, VGG-face, ArcFace) trained on the enhanced data sets and showing that they outperform equivalent systems trained on original data sets (containing faces without masks) , when the test benchmark contains masked faces.
Edit intent: fluency
Original:  We also demonstrate the usefulness of our method by evaluating state-of-the-art face recognition systems (FaceNet, VGG-face, ArcFace) trained on the enhanced data sets and showing that they outperform equivalent systems trained on the original data sets (containing faces without masks)  , when the test benchmark contains masked faces.
Revised:  We also demonstrate the usefulness of our method by evaluating state-of-the-art face recognition systems (FaceNet, VGG-face, ArcFace) trained on the enhanced data sets and showing that they outperform equivalent systems trained on the original data sets (containing faces without masks) , when the test benchmarks contain masked faces.
Edit intent: fluency
Original: Glioma is a common malignant brain tumor that shows distinct survival among patients.
Revised: Glioma is a common malignant brain tumor with distinct survival among patients.
Edit intent: clarity
Original:  The isocitrate dehydrogenase (IDH) gene mutation status provides critical diagnostic and prognostic value for glioma and is now accepted as the standard of care.
Revised:  The isocitrate dehydrogenase (IDH) gene mutation provides critical diagnostic and prognostic value for glioma and is now accepted as the standard of care.
Edit intent: clarity
Original:  A non-invasive prediction of IDH mutation based on the pre-treatment MRI has crucial clinical significance .
Revised:  A non-invasive prediction of IDH mutation based on pre-treatment MRI has crucial clinical significance .
Edit intent: fluency
Original:  A non-invasive prediction of IDH mutation based on the pre-treatment MRI has crucial clinical significance .
Revised:  A non-invasive prediction of IDH mutation based on the pre-treatment MRI .
Edit intent: clarity
Original:  Machine learning and deep learning models show reasonable performance in predicting IDH mutation status .
Revised:  Machine learning / deep learning models show reasonable performance in predicting IDH mutation status .
Edit intent: fluency
Original:  However, most models neglect the systematic brain alterations caused by tumor invasion, where the infiltration along white matter tracts throughout the brain is identified as a hallmark of glioma.
Revised:  However, most models neglect the systematic brain alterations caused by tumor invasion, where widespread infiltration along white matter tracts throughout the brain is identified as a hallmark of glioma.
Edit intent: clarity
Original:  However, most models neglect the systematic brain alterations caused by tumor invasion, where the infiltration along white matter tracts throughout the brain is identified as a hallmark of glioma.
Revised:  However, most models neglect the systematic brain alterations caused by tumor invasion, where the infiltration along white matter tracts is a hallmark of glioma.
Edit intent: clarity
Original:  Structural brain network provides an effective tool to characterise brain organisation, which could be captured by the graph neural networks (GNN) for a more accurate prediction of IDH mutationstatus .
Revised:  Structural brain network provides an effective tool to characterize brain organisation, which could be captured by the graph neural networks (GNN) for a more accurate prediction of IDH mutationstatus .
Edit intent: fluency
Original:  Structural brain network provides an effective tool to characterise brain organisation, which could be captured by the graph neural networks (GNN) for a more accurate prediction of IDH mutationstatus .
Revised:  Structural brain network provides an effective tool to characterise brain organisation, which could be captured by the graph neural networks (GNN) to more accurately predict IDH mutation .
Edit intent: clarity
Original:  Here we propose a method to predict the IDH mutation using GNN, based on the structural brain network of patients.
Revised:  Here we propose a method to predict IDH mutation using GNN, based on the structural brain network of patients.
Edit intent: fluency
Original:  Specifically, we firstly construct a network template of healthy subjects, which consists of atlases of edges (white matter tracts) and nodes (cortical and subcortical brain regions) to provide regions of interest ( ROI ).
Revised:  Specifically, we firstly construct a network template of healthy subjects, consisting of atlases of edges (white matter tracts) and nodes (cortical and subcortical brain regions) to provide regions of interest ( ROI ).
Edit intent: coherence
Original:  Specifically, we firstly construct a network template of healthy subjects, which consists of atlases of edges (white matter tracts) and nodes (cortical and subcortical brain regions) to provide regions of interest ( ROI ).
Revised:  Specifically, we firstly construct a network template of healthy subjects, which consists of atlases of edges (white matter tracts) and nodes (cortical / subcortical brain regions) to provide regions of interest ( ROI ).
Edit intent: fluency
Original:  Specifically, we firstly construct a network template of healthy subjects, which consists of atlases of edges (white matter tracts) and nodes (cortical and subcortical brain regions) to provide regions of interest ( ROI ).
Revised:  Specifically, we firstly construct a network template of healthy subjects, which consists of atlases of edges (white matter tracts) and nodes (cortical and subcortical brain regions) to provide regions of interest ( ROIs ).
Edit intent: fluency
Original:  These features of edge and node of brain networks are used to train a GNN architecture in predicting IDH mutation status .
Revised:  These features of edge and node of brain networks are used to train a GNN architecture for predicting IDH mutation status .
Edit intent: fluency
Original:  These features of edge and node of brain networks are used to train a GNN architecture in predicting IDH mutation status .
Revised:  These features of edge and node of brain networks are used to train a GNN architecture in predicting IDH mutation .
Edit intent: clarity
Original:  The results show that the proposed method outperforms the baseline models using  3D-CNN and 3D-DenseNet.
Revised:  The results show that the proposed method outperforms the baseline models using the 3D-CNN and 3D-DenseNet.
Edit intent: clarity
Original:  In addition, the model interpretation suggests its ability to identify the tracts infiltrated by tumor and corresponds to clinical prior knowledge.
Revised:  In addition, model interpretation suggests its ability to identify the tracts infiltrated by tumor and corresponds to clinical prior knowledge.
Edit intent: fluency
Original:  In addition, the model interpretation suggests its ability to identify the tracts infiltrated by tumor and corresponds to clinical prior knowledge.
Revised:  In addition, the model interpretation suggests its ability to identify the tracts infiltrated by tumor , corresponding to clinical prior knowledge.
Edit intent: coherence
Original: Moving object detection is a crucial task in computer vision.
Revised: Moving object detection is important in computer vision.
Edit intent: clarity
Original:  However, these advantagescome at a high cost, as event-based cameras are noise sensitive and have low resolution.
Revised:  In spite of these advantages, event-based cameras are noise sensitive and have low resolution.
Edit intent: clarity
Original:  However, these advantagescome at a high cost, as event-based cameras are noise sensitive and have low resolution.
Revised:  However, these advantagescome at a high cost, as event-based cameras are noise-sensitive and have low resolution.
Edit intent: fluency
Original:  Moreover, the task of moving object detection in these cameras is difficult, as event-based sensors capture only the binary changes in brightness of a scene, lacking useful visual features like texture and color.
Revised:  Moreover, the task of moving object detection in these cameras is difficult, as event-based sensors lack useful visual features like texture and color.
Edit intent: clarity
Original:  In this paper, we investigate the application of the k-means clustering technique in detecting moving objects in event-based data . Experimental results in publicly available datasets using k-means show significant improvement in performance over the state-of-the-art methods .
Revised:  In this paper, we investigate the application of the k-means clustering technique in detecting moving objects in event-based data .
Edit intent: coherence
Original:  Our algorithm uses game theory to develop a new auction, called %DIFDELCMD < \model%%%  , that directly determines the optimal action for each agent based on their driving style (which is observable via commonly available sensors like lidars and cameras ).
Revised:  Our algorithm uses game theory to develop a new auction, called %DIFDELCMD < \model%%% , that directly determines the optimal action for each agent based on their driving style (which is observable via commonly available sensors ).
Edit intent: clarity
Original:  we theoretically prove that such an approach , although counter-intuitive, is game-theoretically optimal .
Revised:  we theoretically prove that such an approach is game-theoretically optimal .
Edit intent: coherence
Original:  The resulting code is open source and available for general use .
Revised:  The resulting code is available on GitHub under a permissive open source license .
Edit intent: clarity
Original: Performance is serious business for a scientific programming language .
Revised: As a scientific programming language .
Edit intent: clarity
Original:  To avoid performance pathologies, Julia programmers strive to write code that is type stable  .
Revised:  To avoid performance pathologies, Julia users are expected to adhere to a coding discipline that enables so-called type stability. Informally, a function is type stable .
Edit intent: clarity
Original: Mixture of Experts (MoE) with sparse conditional computation has been proved an effective architecture for scaling attention-based models to more parameters with comparable computation cost.
Revised: Mixture-of-Experts (MoE) with sparse conditional computation has been proved an effective architecture for scaling attention-based models to more parameters with comparable computation cost.
Edit intent: fluency
Original:  Besides, to reduce computational cost in routing and improve experts capacity, we design Re-represent layers in each Sparse block.
Revised:  Besides, to reduce computational cost in routing and improve expert capacity, we design Re-represent layers in each Sparse block.
Edit intent: fluency
Original:  By pre-training on ImageNet-1k with MoCo v3 algorithm, our models can outperform dense MLP models with comparable parameters and less computational coston several\\%DIF > on  downstream image classification tasks  .
Revised:  When pre-training on ImageNet-1k with MoCo v3 algorithm, our models can outperform dense MLP models with comparable parameters and less computational coston several\\%DIF > on downstream image classification tasks .
Edit intent: fluency
Original: Underwater 3D reconstruction is challenging due to the refraction of light at the water-air interface (most electronic devices cannot be directly submerged in water).
Revised: Recovering 3D reconstruction is challenging due to the refraction of light at the water-air interface (most electronic devices cannot be directly submerged in water).
Edit intent: clarity