wanyu/IteraTeR_v2 huggingface dataset:
Original:  In the first part of the study , we conducted systematic evaluations and found that while the present method achieved high transcription accuracies at the note level, global characteristics such as tempo scale, metre (time signature), and bar line positions  were often incorrectly estimated.
Revised:  In the first part , we conducted systematic evaluations and found that while the present method achieved high transcription accuracies at the note level, global characteristics such as tempo scale, metre (time signature), and bar line positions were often incorrectly estimated.
Edit intent: clarity
Original:  In the first part of the study , we conducted systematic evaluations and found that while the present method achieved high transcription accuracies at the note level, global characteristics such as tempo scale, metre (time signature), and bar line positions  were often incorrectly estimated.
Revised:  In the first part of the study , we conducted systematic evaluations and found that while the present method achieved high transcription accuracies at the note level, some global characteristics of music, such as tempo scale, metre (time signature), and bar line positions were often incorrectly estimated.
Edit intent: clarity
Original:  In the first part of the study , we conducted systematic evaluations and found that while the present method achieved high transcription accuracies at the note level, global characteristics such as tempo scale, metre (time signature), and bar line positions  were often incorrectly estimated.
Revised:  In the first part of the study , we conducted systematic evaluations and found that while the present method achieved high transcription accuracies at the note level, global characteristics such as tempo scale, metre (time signature), and bar line positions , were often incorrectly estimated.
Edit intent: fluency
Original:  In the second part, we formulated non-local statistics of pitch and rhythmic content that are derived from musical knowledge and studied their effects in inferring those global characteristics.
Revised:  In the second part, we formulated non-local statistics of pitch and rhythmic contents that are derived from musical knowledge and studied their effects in inferring those global characteristics.
Edit intent: fluency
Original:  We found an optimal combination of these statistics for significantly improving the transcription results , which suggests using statistics obtained from separated hand parts.
Revised:  We found that these statistics are markedly effective for improving the transcription results , which suggests using statistics obtained from separated hand parts.
Edit intent: clarity
Original:  The integrated method can generate transcriptions that can be partially used for music performance and assisting human transcribers, which demonstrates the potential for a practical audio-to-score piano transcription system .
Revised:  The integrated method can generate transcriptions that can be partially used for music performance and assisting human transcribers, thus demonstrating the potential for a practical audio-to-score piano transcription system .
Edit intent: coherence
Original:  The integrated method can generate transcriptions that can be partially used for music performance and assisting human transcribers, which demonstrates the potential for a practical audio-to-score piano transcription system .
Revised:  The integrated method can generate transcriptions that can be partially used for music performance and assisting human transcribers, which demonstrates the potential for practical applications .
Edit intent: clarity
Original: Coronaviruses attach to host cell surface receptors via their spike (S) proteins to mediate the entry into the host cell.
Revised: Spike (S) proteins to mediate the entry into the host cell.
Edit intent: clarity
Original:  A still open gap in that literature is that statistical and ensemble learning approaches systematically present lower predictive performance than deep learning methods as they generally disregard the data sequence aspect entangled with multivariate data represented in more than one time series.
Revised:  A still open gap in that literature is that statistical and ensemble learning approaches systematically present lower predictive performance than deep learning methods . They generally disregard the data sequence aspect entangled with multivariate data represented in more than one time series.
Edit intent: coherence
Original:  In this paper, we proposed a semismooth Newton method based augmented Lagrangian method to solve this problem.
Revised:  In this paper, we proposed a semismooth Newton based augmented Lagrangian method to solve this problem.
Edit intent: fluency
Original:  Augmented Lagrangian method (also called as method of multipliers) is widely used for lots of smooth or nonsmooth variational problems.
Revised:  The augmented Lagrangian method (also called as method of multipliers) is widely used for lots of smooth or nonsmooth variational problems.
Edit intent: clarity
Original:  With efficient primal-dual semismooth Newton method for the complicated linear subproblems involving total generalized variation, we investigated a highly efficient and competitive algorithm compared to some popular first-order method.
Revised:  With efficient primal-dual semismooth Newton methods for the complicated linear subproblems involving total generalized variation, we investigated a highly efficient and competitive algorithm compared to some popular first-order method.
Edit intent: fluency
Original:  With efficient primal-dual semismooth Newton method for the complicated linear subproblems involving total generalized variation, we investigated a highly efficient and competitive algorithm compared to some popular first-order method.
Revised:  With efficient primal-dual semismooth Newton method for the complicated linear subproblems involving total generalized variation, we investigated a highly efficient and competitive algorithm compared to some efficient first-order method.
Edit intent: clarity
Original:  With the analysis of the metric subregularities of the corresponding functions, we give both the global convergence and local linear convergence rate for the proposed augmented Lagrangian methods with semismooth Newton solvers .
Revised:  With the analysis of the metric subregularities of the corresponding functions, we give both the global convergence and local linear convergence rate for the proposed augmented Lagrangian methods .
Edit intent: clarity
Original:  secondly, her psychometric properties (Cronbach's \alpha of 0.81, sensitivity of 96\% and specificity of 90\%) are excellent and comparable to the traditional well-established depression screening questionnaires.
Revised:  secondly, her psychometric properties (Cronbach's alpha of 0.81, sensitivity of 96\% and specificity of 90\%) are excellent and comparable to the traditional well-established depression screening questionnaires.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, \ell \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq u , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ r + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + ns } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times r + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + ns } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ t \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times r } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ t } on the diagonal line aside.
Edit intent: fluency
Original:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t  } on the diagonal line aside.
Revised:  A 2-stage stochastic ILP is an integer program of the form \min \{ w ^T x \mid A x = b, L \leq x \leq U , x \in Z^{ s + nt } \} where the constraint matrix A \in Z^{ r n \times s + nt } consists of n repetitions of a block matrix A\in \mathbb{Z ^{ r \times s } on the vertical line and n repetitions of a matrix B\in \mathbb{Z ^{ r \times t \times s } on the diagonal line aside.
Edit intent: fluency
Original:  In this paper we show an advanced hardness result for a number theoretic problem called Quadratic Congruences where the objective is to compute a number z \leq \gamma satisfying z^2 \equiv \alpha \bmod \beta for given \alpha, \beta, \gamma \in \mathbb{Z}.
Revised:  First, we show a stronger hardness result for a number theoretic problem called Quadratic Congruences where the objective is to compute a number z \leq \gamma satisfying z^2 \equiv \alpha \bmod \beta for given \alpha, \beta, \gamma \in \mathbb{Z}.
Edit intent: clarity
Original:  As an implication of our hardness result for the Quadratic Congruences problem  we prove a lower bound of 2^{2 ^{\delta(r+t) } |I|^{O(1)} for some \delta > 0 for the running time of any algorithm solving 2-stage stochastic ILPs where |I| is the encoding length of the instance.
Revised:  As an implication of our hardness result for the Quadratic Congruences problem , we prove a lower bound of 2^{2 ^{\delta(r+t) } |I|^{O(1)} for some \delta > 0 for the running time of any algorithm solving 2-stage stochastic ILPs where |I| is the encoding length of the instance.
Edit intent: fluency
Original:  We propose a general and robust approach for solving inverse problems for the steady state Navier-Stokes equations by combining deep neural networks and numerical PDE schemes.
Revised:  We propose a general and robust approach for solving inverse problems in the steady-state Navier-Stokes equations by combining deep neural networks and numerical PDE schemes.
Edit intent: fluency
Original:  We propose a general and robust approach for solving inverse problems for the steady state Navier-Stokes equations by combining deep neural networks and numerical PDE schemes.
Revised:  We propose a general and robust approach for solving inverse problems for the steady state Navier-Stokes equations by combining deep neural networks and numerical partial differential equation (PDE) schemes.
Edit intent: clarity
Original:  Specifically, we express the Newton's iteration to solve the highly nonlinear Navier-Stokes equations as a computational graph.
Edit intent: coherence
Original:  We demonstrate the effectiveness of our method by computing spatially-varying viscosity and conductivity fields with deep neural networks (DNNs) and training  DNNs using partial observations of velocity fields.
Revised:  We demonstrate the effectiveness of our method by computing spatially-varying viscosity and conductivity fields with deep neural networks (DNNs) and training the DNNs using partial observations of velocity fields.
Edit intent: clarity
Original:  We show that  DNNs are capable of modeling complex spatially-varying physical field with sparse and noisy data.
Revised:  We show that the DNNs are capable of modeling complex spatially-varying physical field with sparse and noisy data.
Edit intent: clarity
Original:  We show that  DNNs are capable of modeling complex spatially-varying physical field with sparse and noisy data.
Revised:  We show that DNNs are capable of modeling complex spatially-varying physical fields with sparse and noisy data.
Edit intent: fluency
Original:  We implement our method using ADCME, a library for solving inverse modeling problems in scientific computing using automatic differentiation.
Revised:  Our implementation leverages the open access ADCME, a library for solving inverse modeling problems in scientific computing using automatic differentiation.
Edit intent: clarity
Original:  It has been greatly witnessed by DNN researchers owing to the promising performance of automatically designing the satisfied DNN architectures.
Edit intent: coherence
Original:  However, most ENAS algorithms require intensive computational resource  which is not necessarily available to each of the users interested.
Revised:  However, most ENAS algorithms require intensive computational resource , which is not necessarily available to each of the users interested.
Edit intent: fluency
Original:  However, most ENAS algorithms require intensive computational resource  which is not necessarily available to each of the users interested.
Revised:  However, most ENAS algorithms require intensive computational resource which is not necessarily available to the users interested.
Edit intent: clarity
Original:  Performance predictors are a type of regression models , can assist to accomplish the search without much computational resource.
Revised:  Performance predictors are a type of regression models which can assist to accomplish the search without much computational resource.
Edit intent: fluency
Original:  Performance predictors are a type of regression models , can assist to accomplish the search without much computational resource.
Revised:  Performance predictors are a type of regression models , can assist to accomplish the search , while without exerting much computational resource.
Edit intent: clarity
Original:  In this paper, we point out that the three steps constituting the training protocol are not reasonable through intuitive and illustrative examples.
Revised:  In this paper, we point out that the three steps constituting the training protocol are not well though-out through intuitive and illustrative examples.
Edit intent: clarity
Original:  Further , we propose a new training protocol to address the issues, consisting of designing a pair-wise ranking indicator to construct the training target, proposing to use the logistic regression to fit the training samples, and developing a differential method to building the training instances.
Revised:  Furthermore , we propose a new training protocol to address the issues, consisting of designing a pair-wise ranking indicator to construct the training target, proposing to use the logistic regression to fit the training samples, and developing a differential method to building the training instances.
Edit intent: coherence
Original:  Further , we propose a new training protocol to address the issues, consisting of designing a pair-wise ranking indicator to construct the training target, proposing to use the logistic regression to fit the training samples, and developing a differential method to building the training instances.
Revised:  Further , we propose a new training protocol to address these issues, consisting of designing a pair-wise ranking indicator to construct the training target, proposing to use the logistic regression to fit the training samples, and developing a differential method to building the training instances.
Edit intent: fluency
Original:  Further , we propose a new training protocol to address the issues, consisting of designing a pair-wise ranking indicator to construct the training target, proposing to use the logistic regression to fit the training samples, and developing a differential method to building the training instances.
Revised:  Further , we propose a new training protocol to address the issues, consisting of designing a pairwise ranking indicator to construct the training target, proposing to use the logistic regression to fit the training samples, and developing a differential method to building the training instances.
Edit intent: fluency
Original:  The experimental results of all the comparisons demonstrate that the proposed  protocol can significantly improve the performance prediction accuracy against the traditional training protocol .
Revised:  The experimental results of all the comparisons demonstrate that the proposed training protocol can significantly improve the performance prediction accuracy against the traditional training protocol .
Edit intent: fluency
Original:  The experimental results of all the comparisons demonstrate that the proposed  protocol can significantly improve the performance prediction accuracy against the traditional training protocol .
Revised:  The experimental results of all the comparisons demonstrate that the proposed protocol can significantly improve the performance prediction accuracy against the traditional training protocols .
Edit intent: fluency
Original: COVID-19 presents a great threat to public health worldwide and the infectious agent SARS-CoV- 2 is currently the target of much research aiming at inhibition.
Revised: COVID-19 presents a great threat to public health worldwide and the infectious agent SARS-CoV-2 is currently the target of much research aiming at inhibition.
Edit intent: fluency
Original:  The virus' main protease is a dimeric enzyme that has only recently begun to be thoroughly described, opening the door for docking assays and virtual screening more broadly.
Revised:  The virus' main protease is a dimeric enzyme that has only recently begun to be thoroughly described, opening the door for virtual screening more broadly.
Edit intent: clarity
Original:  Here, three putative binding sites were described through computational means, while 5 organic compounds for each location were reached through virtual screening from a massive, PAIN-filtered flavonoid database . Virtual screening integrated several confirmation methods, including validation docking based on 2Dscore, cross-docking assays and positive and negative controls.
Revised:  Here, a PAIN-filtered flavonoid database . Virtual screening integrated several confirmation methods, including validation docking based on 2Dscore, cross-docking assays and positive and negative controls.
Edit intent: clarity