wanyu/IteraTeR_v2 huggingface dataset:
Original: Compared to traditional online maps, crowdsourced maps such as Waze are unique in providing real-time updates on traffic, congestion, accidents and points of interest.
Revised: Compared to traditional online maps, crowdsourced maps such as Waze provide timely updates on traffic, congestion, accidents and points of interest.
Edit intent: clarity
Original:  We describe techniques to emulate Waze-enabled vehicles using lightweight scripts, and how to use these "ghost riders" to compromise user privacy by remotely tracking precise user movements while avoiding detection.
Revised:  More importantly, we describe techniques to emulate Waze-enabled vehicles using lightweight scripts, and how to use these "ghost riders" to compromise user privacy by remotely tracking precise user movements while avoiding detection.
Edit intent: coherence
Original:  Over time, co-location edges combine to form large {\em proximity graphs} , network that attest to physical interactions between devices . "Ghost-riders" cannot physically interact with real devices and can be detected using graph algorithms.
Revised:  Over time, co-location edges combine to form large {\em proximity graphs} that attest to physical interactions between devices . "Ghost-riders" cannot physically interact with real devices and can be detected using graph algorithms.
Edit intent: clarity
Original:  Over time, co-location edges combine to form large {\em proximity graphs} , network that attest to physical interactions between devices . "Ghost-riders" cannot physically interact with real devices and can be detected using graph algorithms.
Revised:  Over time, co-location edges combine to form large {\em proximity graphs} , network that attest to physical interactions between devices , allowing scalable detection of virtual vehicles.
Edit intent: clarity
Original:  We demonstrate the efficacy of this approach using large simulations, and discuss how they can be used to dramatically reduce the impact of attacks against crowdsourced mapping services.
Revised:  We demonstrate the efficacy of this approach using large-scale simulations, and discuss how they can be used to dramatically reduce the impact of attacks against crowdsourced mapping services.
Edit intent: clarity
Original: In particular,two forms of interactions in bacterial systems will be examined:electron transfer (ET) and quorum sensing (QS) .While the diffusion of chemical signals has been heavily studied, ET occurring in living cells and its role in cell-cell interaction is less understood.
Revised: In particular,two forms of interactions in bacterial systems will be examined:electron transfer and quorum sensing (QS) .While the diffusion of chemical signals has been heavily studied, ET occurring in living cells and its role in cell-cell interaction is less understood.
Edit intent: fluency
Original: In particular,two forms of interactions in bacterial systems will be examined:electron transfer (ET) and quorum sensing (QS) .While the diffusion of chemical signals has been heavily studied, ET occurring in living cells and its role in cell-cell interaction is less understood.
Revised: In particular,two forms of interactions in bacterial systems will be examined:electron transfer (ET) and quorum sensing .While the diffusion of chemical signals has been heavily studied, ET occurring in living cells and its role in cell-cell interaction is less understood.
Edit intent: clarity
Original: In particular,two forms of interactions in bacterial systems will be examined:electron transfer (ET) and quorum sensing (QS) .While the diffusion of chemical signals has been heavily studied, ET occurring in living cells and its role in cell-cell interaction is less understood.
Revised: In particular,two forms of interactions in bacterial systems will be examined:electron transfer (ET) and quorum sensing (QS) .While the diffusion of chemical signals has been heavily studied, electron transfer occurring in living cells and its role in cell-cell interaction is less understood.
Edit intent: fluency
Original: Recent experimental observations open up new frontiers in the design of ET-based communication in microbial communities ,which may coexist with the more well-known interaction strategies based on molecular diffusion.
Revised: Recent experimental observations open up new frontiers in the design of microbial systems based on electron transfer ,which may coexist with the more well-known interaction strategies based on molecular diffusion.
Edit intent: clarity
Original: In QS ,the concentration of certain signature chemical compounds emitted by the bacteria is used to estimate the bacterial population size,so as to activate collective behaviors.
Revised: In quorum sensing ,the concentration of certain signature chemical compounds emitted by the bacteria is used to estimate the bacterial population size,so as to activate collective behaviors.
Edit intent: clarity
Original: In this paper, new queueing models for ET and QS are proposed .
Revised: In this position paper,queuing models for electron transfer are summarized and adapted to provide new models for quorum sensing .
Edit intent: clarity
Original: It is shown that queuing models allow the characterization of the state of a single cell as a function of interactions with other cells and the environment, thus enabling the construction of an information theoretic framework, while being amenable to complexity reduction using methods based on statistical physics and wireless network design .
Revised: It is shown that queuing models allow the characterization of the state of a single cell as a function of interactions with other cells and the environment, while being amenable to complexity reduction using methods based on statistical physics and wireless network design .
Edit intent: coherence
Original: It is shown that queuing models allow the characterization of the state of a single cell as a function of interactions with other cells and the environment, thus enabling the construction of an information theoretic framework, while being amenable to complexity reduction using methods based on statistical physics and wireless network design .
Revised: It is shown that queuing models allow the characterization of the state of a single cell as a function of interactions with other cells and the environment, thus enabling the construction of an information theoretic framework, while being amenable to complexity reduction .
Edit intent: clarity
Original:  For example, convolutional neural networks (CNN) have delivered state-of-the-art performance without much effort on feature engineering as the conventional pattern-based methods.
Revised:  For example, convolutional neural networks (CNN) have delivered competitive performance without much effort on feature engineering as the conventional pattern-based methods.
Edit intent: clarity
Original:  A key issue that has not been well addressed by the existing research is the lack of capability to learn \%in modeling temporal features, especially long-distance dependency between nominal pairs.
Revised:  A key issue that has not been well addressed by the existing research is the lack of capability to learn temporal features, especially long-distance dependency between nominal pairs.
Edit intent: clarity
Original:  In this paper, we propose a novel framework based on recurrent neural networks (RNN) to tackle the problem, and present several modifications to enhance the model, including a max-pooling approach and a bi-directional architecture.
Revised:  In this paper, we propose a simple framework based on recurrent neural networks (RNN) to tackle the problem, and present several modifications to enhance the model, including a max-pooling approach and a bi-directional architecture.
Edit intent: clarity
Original:  Our experiment on the SemEval-2010 Task-8 datasetshows that the RNN model can deliver state-of-the-art performance on relation classification, and it is particularly capable of learning long-distance relation patterns.
Revised:  Our experiment on the SemEval-2010 Task-8 datasetshows that the RNN model can deliver better performance on relation classification, and it is particularly capable of learning long-distance relation patterns.
Edit intent: clarity
Original:  Arguably, the most fundamental problem in this domain is the influence maximizationproblem , where the goal is to identify a small seed set of individuals that can trigger a large cascade of influence in the network.
Revised:  Arguably, the most fundamental problem in this domain is influence maximization , where the goal is to identify a small seed set of individuals that can trigger a large cascade of influence in the network.
Edit intent: fluency
Original:  Arguably, the most fundamental problem in this domain is the influence maximizationproblem , where the goal is to identify a small seed set of individuals that can trigger a large cascade of influence in the network.
Revised:  Arguably, the most fundamental problem in this domain is the influence maximizationproblem , where the goal is to identify a seed set of individuals that can trigger a large cascade of influence in the network.
Edit intent: clarity
Original:  While there has been significant progress regarding this problem and its variants, one basic shortcoming of the underlying models is that they lack the flexibility in the way the overall budget is allocated to different individuals.
Revised:  While there has been significant progress regarding this problem and its variants, one basic shortcoming of the models is that they lack the flexibility in the way the overall budget is allocated to different individuals.
Edit intent: clarity
Original:  While there has been significant progress regarding this problem and its variants, one basic shortcoming of the underlying models is that they lack the flexibility in the way the overall budget is allocated to different individuals.
Revised:  While there has been significant progress regarding this problem and its variants, one basic shortcoming of the underlying models is that they lack the flexibility in the way the budget is allocated to different individuals.
Edit intent: clarity
Original:  While there has been significant progress regarding this problem and its variants, one basic shortcoming of the underlying models is that they lack the flexibility in the way the overall budget is allocated to different individuals.
Revised:  While there has been significant progress regarding this problem and its variants, one basic shortcoming of the underlying models is that they lack the flexibility in the way the overall budget is allocated to individuals.
Edit intent: clarity
Original:  Taking the other point of view, known models allowing flexible budget allocation do not take into account the influence spread in social networks .
Revised:  Taking the other point of view, known models allowing flexible budget allocation do not take into account the influence spread in the network .
Edit intent: clarity
Original:  For the offline setting, we identify a large family of natural budget-based propagation functions that admits a tight approximation guarantee.
Revised:  For the offline setting, we identify a large family of budget-based propagation functions that admits a tight approximation guarantee.
Edit intent: clarity
Original:  For the offline setting, we identify a large family of natural budget-based propagation functions that admits a tight approximation guarantee.
Revised:  For the offline setting, we identify a large family of natural budget-based propagation functions that admit tight approximation guarantee.
Edit intent: fluency
Original:  This problem is known to admit an optimal  1-1/e \approx 0.632 -approximation.
Revised:  This problem is known to admit an optimal ( 1-1/e \approx 0.632 -approximation.
Edit intent: fluency
Original:  This setting extends the celebrated secretary problem, and its variant, the submodular knapsack secretary problem.
Revised:  This setting extends the secretary problem, and its variant, the submodular knapsack secretary problem.
Edit intent: clarity
Original:  We propose an algorithmic technique for MapReduce algorithms, called Meta-MapReduce, that decreases the communication cost by allowing us to process and move metadata to clouds and from the map to reduce phases .
Revised:  In this work, we propose an algorithmic technique for MapReduce algorithms, called Meta-MapReduce, that decreases the communication cost by allowing us to process and move metadata to clouds and from the map to reduce phases .
Edit intent: clarity
Original:  In comparison, the state-of-the-art CLDNN-HMM model achieves a WER of 10.9 \%.
Revised:  By comparison, the state-of-the-art CLDNN-HMM model achieves a WER of 10.9 \%.
Edit intent: fluency
Original: Nonlinear kernels are used extensively in regression models in statistics and machine learning since they often improve predictive accuracy . Variable selection  is a challenge in the context of kernel based regression models.
Revised: Nonlinear kernel regression models are often used in statistics and machine learning since they often improve predictive accuracy . Variable selection is a challenge in the context of kernel based regression models.
Edit intent: clarity
Original: Nonlinear kernels are used extensively in regression models in statistics and machine learning since they often improve predictive accuracy . Variable selection  is a challenge in the context of kernel based regression models.
Revised: Nonlinear kernels are used extensively in regression models in statistics and machine learning due to greater accuracy than linear models . Variable selection is a challenge in the context of kernel based regression models.
Edit intent: clarity
Original: Nonlinear kernels are used extensively in regression models in statistics and machine learning since they often improve predictive accuracy . Variable selection  is a challenge in the context of kernel based regression models.
Revised: Nonlinear kernels are used extensively in regression models in statistics and machine learning since they often improve predictive accuracy . Variable selection for kernel regression models is a challenge in the context of kernel based regression models.
Edit intent: clarity
Original:  In linear regression the concept of an effect size for the regression coefficientsis very useful for variable selection .
Revised:  In linear regression the concept of an effect size for regression coefficients .
Edit intent: clarity
Original:  In this paper we provide an analog for the effect size of each explanatory variable for Bayesian kernel regression models when the kernel is shift-invariant---for example the Gaussian kernel.
Revised:  In this paper , we propose a novel framework that provides an analog of the effect size of each explanatory variable for Bayesian kernel regression models when the kernel is shift-invariant---for example the Gaussian kernel.
Edit intent: clarity
Original:  The key idea that allows for the extraction of effect sizes is a random Fourier expansion for shift-invariant kernel functions.
Revised:  We use function analytic properties of shift-invariant kernel functions.
Edit intent: clarity
Original:  This projection serves as the analog for effect sizes.
Revised:  This projection serves as the analog of effect sizes.
Edit intent: fluency
Original:  We apply this idea to specify a class of scalable Bayesian kernel regression models (SBKMs) for both nonparametric regression and binary classification  .
Revised:  We apply this idea to specify a class of scalable Bayesian kernel regression and binary classification .
Edit intent: clarity
Original:  We also demonstrate how this framework encompasses both fixed and mixed effects modeling characteristics.
Edit intent: coherence
Original:  We illustrate the utility of our approach on simulated and real data .
Revised:  We illustrate the utility of BAKR by examining, in some detail, two important problems in statistical genetics: genomic selection (predicting phenotype from genotype) and association mapping (inference of significant variables or loci). State-of-the-art methods for genomic selection and association mapping are based on kernel regression and linear models, respectively. BAKR is the first method that is competitive in both settings .
Edit intent: coherence
Original: Nonlinear kernel regression models are often used in statistics and machine learning due to greater accuracy than linear models.
Revised: Nonlinear kernel regression models are often used in statistics and machine learning because they are more accurate than linear models.
Edit intent: clarity
Original:  In this paper, we propose a novel framework that provides an analog of the effect size of each explanatory variable for Bayesian kernel regression models when the kernel is shift-invariant---for example the Gaussian kernel.
Revised:  In this paper, we propose a novel framework that provides an effect size analog of each explanatory variable for Bayesian kernel regression models when the kernel is shift-invariant---for example the Gaussian kernel.
Edit intent: fluency
Original:  In this paper, we propose a novel framework that provides an analog of the effect size of each explanatory variable for Bayesian kernel regression models when the kernel is shift-invariant---for example the Gaussian kernel.
Revised:  In this paper, we propose a novel framework that provides an analog of the effect size of each explanatory variable for Bayesian kernel regression models when the kernel is shift-invariant --- for example, the Gaussian kernel.
Edit intent: fluency
Original:  We use function analytic properties of shift-invariant reproducing kernel Hilbert spaces (RKHS) to define a linear vector space that (1 ) captures nonlinear structure and (2 ) can be projected onto the original explanatory variables.
Revised:  We use function analytic properties of shift-invariant reproducing kernel Hilbert spaces (RKHS) to define a linear vector space that (1 ) captures nonlinear structure , and (ii ) can be projected onto the original explanatory variables.
Edit intent: coherence
Original:  The projection onto the original explanatory variables serves as the analog of effect sizes.
Revised:  The projection onto the original explanatory variables serves as an analog of effect sizes.
Edit intent: fluency
Original:  By adapting some classical results in compressive sensing we state conditions under which BAKR can recover a sparse set of effect sizes, simultaneous variable selection and regression.
Edit intent: coherence
Original:  We illustrate the utility of BAKR by examining , in some detail, two important problems in statistical genetics: genomic selection ( predicting phenotype from genotype ) and association mapping (  inference of significant variables or loci).
Revised:  We illustrate the utility of BAKR by examining two important problems in statistical genetics: genomic selection ( predicting phenotype from genotype ) and association mapping ( inference of significant variables or loci).
Edit intent: clarity
Original:  We illustrate the utility of BAKR by examining , in some detail, two important problems in statistical genetics: genomic selection ( predicting phenotype from genotype ) and association mapping (  inference of significant variables or loci).
Revised:  We illustrate the utility of BAKR by examining , in some detail, two important problems in statistical genetics: genomic selection ( i.e. phenotypic prediction ) and association mapping ( inference of significant variables or loci).
Edit intent: clarity
Original:  We illustrate the utility of BAKR by examining , in some detail, two important problems in statistical genetics: genomic selection ( predicting phenotype from genotype ) and association mapping (  inference of significant variables or loci).
Revised:  We illustrate the utility of BAKR by examining , in some detail, two important problems in statistical genetics: genomic selection ( predicting phenotype from genotype ) and association mapping ( i.e. inference of significant variables or loci).
Edit intent: coherence
Original:  We illustrate the utility of BAKR by examining , in some detail, two important problems in statistical genetics: genomic selection ( predicting phenotype from genotype ) and association mapping (  inference of significant variables or loci).
Revised:  We illustrate the utility of BAKR by examining , in some detail, two important problems in statistical genetics: genomic selection ( predicting phenotype from genotype ) and association mapping ( inference of significant variants or loci).
Edit intent: fluency
Original: Loss tomography has received considerable attention in recent years and a large number of estimators based on maximum likelihood (ML) or Bayesian principles have been proposed for the tree topology.
Revised: Three types of explicit estimators are proposed here to estimate the loss rates of the links in a network of the tree topology.
Edit intent: clarity
Original: It is known that subtree overlap graphs are equivalent to subtree filament graphs .
Revised: The overlap graphs of subtrees of a tree are equivalent to subtree filament graphs .
Edit intent: clarity
Original:  Models with coarse-grained states, for example those in Markov models of molecular kinetics, or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics.
Revised:  Models with coarse-grained states, for example those employed in studies of molecular kinetics, or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics.
Edit intent: clarity
Original:  Models with coarse-grained states, for example those in Markov models of molecular kinetics, or spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics.
Revised:  Models with coarse-grained states, for example those in Markov models of molecular kinetics, and models with spatial disorder can give rise to memory and non-exponential distributions of waiting times and first-passage statistics.
Edit intent: coherence
Original:  Our approach is valuable for calculating higher moments (beyond the mean) of path statistics such as path length, time, and action, as well as  any conservative or nonconservative force along a path.
Revised:  Our approach is valuable for calculating higher moments (beyond the mean) of path length, time, and action, as well as any conservative or nonconservative force along a path.
Edit intent: clarity
Original:  Our approach is valuable for calculating higher moments (beyond the mean) of path statistics such as path length, time, and action, as well as  any conservative or nonconservative force along a path.
Revised:  Our approach is valuable for calculating higher moments (beyond the mean) of path statistics such as path length, time, and action, as well as statistics of any conservative or nonconservative force along a path.
Edit intent: clarity
Original:  Our approach is valuable for calculating higher moments (beyond the mean) of path statistics such as path length, time, and action, as well as  any conservative or nonconservative force along a path.
Revised:  Our approach is valuable for calculating higher moments (beyond the mean) of path statistics such as path length, time, and action, as well as any conservative or non-conservative force along a path.
Edit intent: fluency
Original:  For homogeneous networks we derive exact relations between these moments, quantifying the validity of approximating a continuous-time process (path times) with its discrete-time projection (path lengths) .
Revised:  For homogeneous networks we derive exact relations between length and time moments, quantifying the validity of approximating a continuous-time process (path times) with its discrete-time projection (path lengths) .
Edit intent: clarity