wanyu/IteraTeR_v2 huggingface dataset:
Original:  We implement the summarization algorithm and show experimentally that it is precise and performant  .
Revised:  We implement the summarization algorithm and show experimentally that it is precise and performant in practice .
Edit intent: clarity
Original:  Here, we investigate how the degree sequence of directed networks constrains the number of driver nodes.
Revised:  Here, we investigate how the degree sequence of a directed network constrains the number of driver nodes.
Edit intent: fluency
Original:  We develop a pair of algorithms that take a directed degree sequence as input and  output a network with the maximum or minimum number of driver nodes such that the network does not have multi-links .
Revised:  We develop a pair of algorithms that take a directed degree sequence as input and aim to output a network with the maximum or minimum number of driver nodes such that the network does not have multi-links .
Edit intent: clarity
Original:  We develop a pair of algorithms that take a directed degree sequence as input and  output a network with the maximum or minimum number of driver nodes such that the network does not have multi-links .
Revised:  We develop a pair of algorithms that take a directed degree sequence as input and output a network with the maximum or minimum number of driver nodes .
Edit intent: coherence
Original:  We find an upper bound for the maximum and a lower bound for the minimum number of driver nodes, and we show that the algorithms always find realizations such that we reach these bounds for all real and model networks, with a few exceptions characterized by very small system size and heterogeneous degree distributions.
Revised:  We find an upper bound for the maximum and a lower bound for the minimum , and show that the algorithms always find realizations such that we reach these bounds for all real and model networks, with a few exceptions characterized by very small system size and heterogeneous degree distributions.
Edit intent: clarity
Original:  We find an upper bound for the maximum and a lower bound for the minimum number of driver nodes, and we show that the algorithms always find realizations such that we reach these bounds for all real and model networks, with a few exceptions characterized by very small system size and heterogeneous degree distributions.
Revised:  We find an upper bound for the maximum and a lower bound for the minimum number of driver nodes, and we show that the algorithms achieve these bounds for all real and model networks, with a few exceptions characterized by very small system size and heterogeneous degree distributions.
Edit intent: clarity
Original:  We find an upper bound for the maximum and a lower bound for the minimum number of driver nodes, and we show that the algorithms always find realizations such that we reach these bounds for all real and model networks, with a few exceptions characterized by very small system size and heterogeneous degree distributions.
Revised:  We find an upper bound for the maximum and a lower bound for the minimum number of driver nodes, and we show that the algorithms always find realizations such that we reach these bounds for all real and model networks, with few exceptions characterized by very small system size and heterogeneous degree distributions.
Edit intent: fluency
Original:  We find an upper bound for the maximum and a lower bound for the minimum number of driver nodes, and we show that the algorithms always find realizations such that we reach these bounds for all real and model networks, with a few exceptions characterized by very small system size and heterogeneous degree distributions.
Revised:  We find an upper bound for the maximum and a lower bound for the minimum number of driver nodes, and we show that the algorithms always find realizations such that we reach these bounds for all real and model networks, with a few exceptions characterized by tiny system size and heterogeneous degree distributions.
Edit intent: clarity
Original:  Exploiting these algorithms , we introduce the notion of control complexity to quantify how hard it is to control a network given its degree sequence, capturing the richness of its structure beyond its degree distribution.
Revised:  Exploiting these algorithms , we introduce the notion of complexity to capture how much more difficult it is to control a network given its degree sequence, capturing the richness of its structure beyond its degree distribution.
Edit intent: clarity
Original:  Using a collection of real and model networks, we numerically and analytically investigate how typical features of the degree distribution affect the range of possible number of driver nodesand control complexity .
Revised:  Using a collection of real and model networks, we numerically and analytically investigate how typical features of the degree distribution affect the range of required driver nodes .
Edit intent: clarity
Original:  We find that the minimum number of drivers is determined by  number of sources or sinks in the network , while the maximum number of drivers is strongly affected by the presence of hubs .
Revised:  We find that the minimum is determined by number of sources or sinks in the network , while the maximum number of drivers is strongly affected by the presence of hubs .
Edit intent: fluency
Original:  We find that the minimum number of drivers is determined by  number of sources or sinks in the network , while the maximum number of drivers is strongly affected by the presence of hubs .
Revised:  We find that the minimum number of drivers is determined by the number of sources or sinks in the network , while the maximum number of drivers is strongly affected by the presence of hubs .
Edit intent: fluency
Original:  We find that the minimum number of drivers is determined by  number of sources or sinks in the network , while the maximum number of drivers is strongly affected by the presence of hubs .
Revised:  We find that the minimum number of drivers is determined by number of sources or sinks , while the maximum number of drivers is strongly affected by the presence of hubs .
Edit intent: clarity
Original:  We find that the minimum number of drivers is determined by  number of sources or sinks in the network , while the maximum number of drivers is strongly affected by the presence of hubs .
Revised:  We find that the minimum number of drivers is determined by number of sources or sinks in the network , while the maximum is strongly affected by the presence of hubs .
Edit intent: fluency
Original: Data-driven modelling and synthesis of motion data is an active research area with applications that include animation and games .
Revised: Data-driven modelling and synthesis of motion is an active research area with applications that include animation and games .
Edit intent: clarity
Original:  This paper introduces a new class of probabilistic, generative  motion-data models based on normalising flows , specifically Glow .
Revised:  This paper introduces a new class of probabilistic, generative motion-data models based on normalising flows .
Edit intent: clarity
Original:  Models of this kind can describe highly complex distributions (unlike many classical approaches like GMMs) yet can be trained stably and efficiently using standard maximum likelihood(unlike GANs ).
Revised:  Models of this kind can describe highly complex distributions , yet can be trained stably and efficiently using standard maximum likelihood(unlike GANs ).
Edit intent: clarity
Original:  The last type uses LSTMs to enable arbitrarily long time-dependencies and is, importantly, causal, meaning it only depends on control and pose information from current and previous timesteps.
Revised:  The last type uses LSTMs to enable arbitrarily long time-dependencies . Importantly, is is also causal, meaning it only depends on control and pose information from current and previous timesteps.
Edit intent: clarity
Original:  Every model type can in principle be applied to any motion since they do not make restrictive assumptions such as the motion being cyclic in nature.
Revised:  Every model type can in principle be applied to any type of motion since it does not make restrictive assumptions such as the motion being cyclic in nature.
Edit intent: clarity
Original:  Objective and subjective results show that randomly-sampled motion from the proposed method  attains a motion quality close to recorded motion capture for both humans and animals .
Revised:  Objective and subjective results show that randomly-sampled motion from the proposed method attains a motion quality close to recorded motion capture .
Edit intent: clarity
Original:  Additionally we conduct an empirical evaluation to compare various measures over many different types of "fair" stable matchings, including rank-maximal, generous, egalitarian, sex-equal and median stable matchings.
Revised:  Additionally we conduct an empirical evaluation to compare various measures over many different types of "fair" stable matchings.
Edit intent: coherence
Original:  However these approaches involve the use of weights that are in general exponential in n , potentially leading to inaccuracies or memory issues upon implementation .
Revised:  However these approaches involve the use of weights that are in general exponential in n .
Edit intent: clarity
Original: In this paper, we propose a compositional approach for verifying autonomous track-based traffic control systems at runtime.
Revised: Autonomous traffic control systems at runtime.
Edit intent: clarity
Original:  The results of our experiments indicate that the proposed approach improves the model checking time and the memory consumption  .
Revised:  The results of our experiments indicate that the proposed approach improves the verification time and the memory consumption .
Edit intent: clarity
Original: Employment gratuity is the money companies typically give to their employees at the end of their contracts as a legal requirement.
Revised: Employment gratuity is the money companies typically pay their employees at the end of their contracts as a legal requirement.
Edit intent: clarity
Original:  In Botswana, for instance, some companies give their employees an option to receive their gratuity on a monthly basis rather than having them wait for a year or more.
Revised:  In particular, some companies give their employees an option to receive their gratuity on a monthly basis rather than having them wait for a year or more.
Edit intent: clarity
Original:  It quantifies the economic benefits of the tax relief provided by government relative to investing the monthly-received funds in a risk-free savings account or in helping repay a loan.
Revised:  It quantifies the economic benefits of the tax relief provided by government relative to investing the monthly-received funds in a risk-free savings account or helping repay a loan.
Edit intent: fluency
Original:  The principles and methods used herein can be adapted and applied to different circumstances .
Revised:  The principles and methods used herein can be adapted and applied to different taxation systems .
Edit intent: clarity
Original:  Under mild assumptions we derive ]  convergence rates in expected value for sub-sampled low rank Newton methods, and sub-sampled inexact Newton Krylov methods.
Revised:  Under mild assumptions we derive ] we derive bounds for convergence rates in expected value for sub-sampled low rank Newton methods, and sub-sampled inexact Newton Krylov methods.
Edit intent: clarity
Original:  These convergence rates quantify the errors incurred in sub-sampling the Hessian and gradient, as well as in approximating the Newton linear solve, and in choosing regularization and step length parameters.
Revised:  These bounds quantify the errors incurred in sub-sampling the Hessian and gradient, as well as in approximating the Newton linear solve, and in choosing regularization and step length parameters.
Edit intent: clarity
Original:  These convergence rates quantify the errors incurred in sub-sampling the Hessian and gradient, as well as in approximating the Newton linear solve, and in choosing regularization and step length parameters.
Revised:  These convergence rates quantify the errors incurred in subsampling the Hessian and gradient, as well as in approximating the Newton linear solve, and in choosing regularization and step length parameters.
Edit intent: fluency
Original:  We deploy these methods in training convolutional autoencoders for the MNIST , CIFAR10 and LFW data sets.
Revised:  We deploy these methods in training convolutional autoencoders for the MNIST and CIFAR10 data sets.
Edit intent: clarity
Original:  These numerical results demonstrate that these sub-sampled inexact Newton methods are competitive with first order methods in computational cost, and can outperform first order methods with respect to generalization errors .
Revised:  Numerical results demonstrate that these sub-sampled inexact Newton methods are competitive with first order methods in computational cost, and can outperform first order methods with respect to generalization errors .
Edit intent: clarity
Original:  These numerical results demonstrate that these sub-sampled inexact Newton methods are competitive with first order methods in computational cost, and can outperform first order methods with respect to generalization errors .
Revised:  These numerical results demonstrate that these sub-sampled inexact Newton methods often converge faster, are more cost-effective, and generalize better .
Edit intent: clarity
Original: Root is an important organ of a plant since it is responsible for water and nutrient uptake.
Revised: The root is an important organ of a plant since it is responsible for water and nutrient uptake.
Edit intent: fluency
Original:  We then use these building blocks to compute geodesics, %DIFDELCMD < \ie %%%  optimal deformations under the metric , between root structures, and to perform statistical analysis of a population of roots .
Revised:  We then use these building blocks to compute geodesics, %DIFDELCMD < \ie %%% optimal deformations under the metric between root structures, and to perform statistical analysis of a population of roots .
Edit intent: fluency
Original:  We then use these building blocks to compute geodesics, %DIFDELCMD < \ie %%%  optimal deformations under the metric , between root structures, and to perform statistical analysis of a population of roots .
Revised:  We then use these building blocks to compute geodesics, %DIFDELCMD < \ie %%% optimal deformations under the metric , between root structures, and to perform statistical analysis on root populations .
Edit intent: clarity
Original:  We demonstrate the utility of the proposed framework on a dataset of wheat roots grown in different environmental conditions.
Revised:  We demonstrate the utility of the proposed framework through an application to a dataset of wheat roots grown in different environmental conditions.
Edit intent: clarity
Original:  We will also show that the framework can be used in various applications including classification and symmetry analysis .
Revised:  We also show that the framework can be used in various applications including classification and symmetry analysis .
Edit intent: coherence
Original:  We will also show that the framework can be used in various applications including classification and symmetry analysis .
Revised:  We will also show that the framework can be used in various applications including classification and regression .
Edit intent: clarity
Original: Nowadays, Bitcoin and Proof-of-Work blockchain systems are becoming prominent and incorporated in many applications and multi-agent systems.
Revised:  Proof-of-Work blockchain systems are becoming prominent and incorporated in many applications and multi-agent systems.
Edit intent: coherence
Original:  Our empirical investigation extends the original study by accounting for multiple Selfish miners (who always use Selfish mining strategy) and multiple strategic miners (who choose a mining strategy to maximise their individual mining reward .)We show that the number of miners in the system is as important as the distribution of hash rate among minersand Selfish mining can be prevented in the presence of multiple miners .
Revised:  Our empirical investigation extends the original study by accounting for multiple Selfish miners (who always perform SM) and strategic miners (who choose a mining strategy to maximise their individual mining reward .)We show that the number of miners in the system is as important as the distribution of hash rate among minersand Selfish mining can be prevented in the presence of multiple miners .
Edit intent: clarity
Original: Body size or mass is generally seen as one of the main factors which structure food webs .
Revised: Body size or mass is one of the main factors which structure food webs .
Edit intent: clarity
Original: Body size or mass is generally seen as one of the main factors which structure food webs .
Revised: Body size or mass is generally seen as one of the main factors underlying food webs structure .
Edit intent: clarity
Original:  A large number of evolutionary models have shown that indeed, the  evolution of body size (or mass) can give rise to hierarchically organized trophic levels with complex between and within trophic interactions.
Revised:  A large number of evolutionary models have shown that indeed, the adaptive evolution of body size (or mass) can give rise to hierarchically organized trophic levels with complex between and within trophic interactions.
Edit intent: clarity
Original:  A large number of evolutionary models have shown that indeed, the  evolution of body size (or mass) can give rise to hierarchically organized trophic levels with complex between and within trophic interactions.
Revised:  A large number of evolutionary models have shown that indeed, the evolution of body size (or mass) can give rise to hierarchically organised trophic levels with complex between and within trophic interactions.
Edit intent: fluency
Original:  Third, we show that the assumptions made regarding the form of biomass conversion efficiency are key for food webs evolution, a parameter which was neglected in previous models.
Revised:  We then show that considering biomass conversion efficiency are key for food webs evolution, a parameter which was neglected in previous models.
Edit intent: clarity
Original:  On the other hand, all these properties are a challenge when the densities need to be approximated with spline functions, including construction of the respective B-spline basis.
Revised:  On the other hand, all these properties are a challenge when the densities need to be approximated with spline functions, including construction of the respective spline basis.
Edit intent: clarity
Original:  The resulting functions possess the zero integral constraint.
Revised:  The resulting functions satisfy the zero integral constraint.
Edit intent: clarity
Original:  The paper provides also construction of smoothing simplicial splines and possible orthonormalization of the B-spline basis which might be useful in some applications.
Revised:  The paper provides also construction of smoothing simplicial splines and possible orthonormalization of the spline basis which might be useful in some applications.
Edit intent: clarity
Original: We propose a new algorithm for Adaptive Finite Element Methods based on Smoothing iterations (S-AFEM)  . The algorithm is inspired by the ascending phase of the V-cycle multigrid method: we replace accurate algebraic solutions in intermediate cycles of the classical AFEM with the application of a prolongation step, followed by a fixed number of  smoothing steps.
Revised: We propose a new algorithm for Adaptive Finite Element Methods (AFEMs) based on smoothing iterations (S-AFEM) . The algorithm is inspired by the ascending phase of the V-cycle multigrid method: we replace accurate algebraic solutions in intermediate cycles of the classical AFEM with the application of a prolongation step, followed by a fixed number of smoothing steps.
Edit intent: clarity
Original: We propose a new algorithm for Adaptive Finite Element Methods based on Smoothing iterations (S-AFEM)  . The algorithm is inspired by the ascending phase of the V-cycle multigrid method: we replace accurate algebraic solutions in intermediate cycles of the classical AFEM with the application of a prolongation step, followed by a fixed number of  smoothing steps.
Revised: We propose a new algorithm for Adaptive Finite Element Methods based on Smoothing iterations (S-AFEM) . The algorithm is inspired by the ascending phase of the V-cycle multigrid method: we replace accurate algebraic solutions in intermediate cycles of the classical AFEM with the application of a prolongation step, followed by a fixed number of few smoothing steps.
Edit intent: coherence
Original:  The algorithm is inspired by the ascending phase of the V-cycle multigrid method: we replace accurate algebraic solutions in intermediate cycles of the classical AFEM with the application of a prolongation step, followed by a fixed number of few smoothing steps .
Revised:  The algorithm is inspired by the ascending phase of the V-cycle multigrid method: we replace accurate algebraic solutions in intermediate cycles of the classical AFEM with the application of a prolongation step, followed by the application of a smoother .
Edit intent: clarity
Original:  We quantify rigorously how the error propagates throughout the algorithm, and we provide a connection with classical a posteriori error analysis.
Revised:  We provide a qualitative analysis of how the error propagates throughout the algorithm, and we provide a connection with classical a posteriori error analysis.
Edit intent: clarity
Original:  A series of numerical experiments highlights the efficiency and the computational speedup of S-AFEM.
Revised:  A series of numerical experiments that highlight the efficiency and the computational speedup of S-AFEM.
Edit intent: fluency
Original: Routine operational use of sensitive data is commonly governed by laws and regulations .
Revised: Routine operational use of sensitive data is often governed by law and regulation .
Edit intent: clarity
Original:  For instance, in the medical domain, there are various laws at the state and federal level that dictate who is permitted to work with patients' records and under what conditions.
Revised:  For instance, in the medical domain, there are various statues at the state and federal level that dictate who is permitted to work with patients' records and under what conditions.
Edit intent: clarity
Original:  To screen for potential privacy breaches, logging systems typically trigger alerts whenever a suspicious access is detected.
Revised:  To screen for potential privacy breaches, logging systems are usually deployed to trigger alerts whenever a suspicious access is detected.
Edit intent: clarity
Original:  To screen for potential privacy breaches, logging systems typically trigger alerts whenever a suspicious access is detected.
Revised:  To screen for potential privacy breaches, logging systems typically trigger alerts whenever suspicious access is detected.
Edit intent: fluency
Original:  However, the efficiency of such mechanism is low because 1) the vast majority of  alerts are false positive and 2) limited budget leads to a small chance of detecting the true attack .
Revised:  However, such mechanisms are often inefficient because 1) the vast majority of alerts are false positive and 2) limited budget leads to a small chance of detecting the true attack .
Edit intent: clarity
Original:  However, the efficiency of such mechanism is low because 1) the vast majority of  alerts are false positive and 2) limited budget leads to a small chance of detecting the true attack .
Revised:  However, the efficiency of such mechanism is low because 1) the vast majority of alerts are false positives, 2) limited budget leads to a small chance of detecting the true attack .
Edit intent: coherence