wanyu/IteraTeR_v2 huggingface dataset:
Original:  To illustrate the advantage and potential of this method, it is applied separately to both simulated citation counts and also seven Scopusfields with collaboration, title length, and journal internationality as independent variables .
Revised:  To illustrate the advantage and potential of this method, it is applied separately to both simulated citation counts and data from Scopus .
Edit intent: clarity
Original: We present a procedure for efficiently sampling colors in the CONGEST {\congest} model.
Revised: We present a procedure for efficiently sampling colors in the {\congest} model.
Edit intent: fluency
Original: Optimising the approximation of Average Precision (AP) has been widely studied for  retrieval.
Revised: Optimising the approximation of Average Precision (AP) has been widely studied for image retrieval.
Edit intent: clarity
Original:  Such methods consider both negative and positive instances before each target positive one according to the definition of AP . However, we argue that only penalizing negative instances before positive ones is enough, because the loss only comes from them.
Revised:  Such methods consider both negative and positive instances ranking before each positive instance . However, we argue that only penalizing negative instances before positive ones is enough, because the loss only comes from them.
Edit intent: clarity
Original:  Such methods consider both negative and positive instances before each target positive one according to the definition of AP . However, we argue that only penalizing negative instances before positive ones is enough, because the loss only comes from them.
Revised:  Such methods consider both negative and positive instances before each target positive one according to the definition of AP . However, we claim that only penalizing negative instances before positive ones is enough, because the loss only comes from them.
Edit intent: clarity
Original:  To this end, instead of following the AP-based loss, we propose a new loss, namely Penalizing Negative instances before Positive ones (PNP), which directly minimizes the number of negative instances before each positive one.
Revised:  To this end, we propose a new loss, namely Penalizing Negative instances before Positive ones (PNP), which directly minimizes the number of negative instances before each positive one.
Edit intent: coherence
Original:  To this end, instead of following the AP-based loss, we propose a new loss, namely Penalizing Negative instances before Positive ones (PNP), which directly minimizes the number of negative instances before each positive one.
Revised:  To this end, instead of following the AP-based loss, we propose a novel loss, namely Penalizing Negative instances before Positive ones (PNP), which directly minimizes the number of negative instances before each positive one.
Edit intent: clarity
Original:  Meanwhile, limited by the definition of AP, AP-based methods only adopt a specific gradient assignment strategy.
Revised:  Meanwhile, AP-based methods only adopt a specific gradient assignment strategy.
Edit intent: clarity
Original:  Meanwhile, limited by the definition of AP, AP-based methods only adopt a specific gradient assignment strategy.
Revised:  Meanwhile, limited by the definition of AP, AP-based methods adopt a sub-optimal gradient assignment strategy.
Edit intent: clarity
Original:  Because of their gradient assignment strategies, PNP-I  tries to make all the relevant instances together, while PNP-D only quickly corrects positive one with fewer negative instances before.
Revised:  PNP-I tries to make all the relevant instances together, while PNP-D only quickly corrects positive one with fewer negative instances before.
Edit intent: clarity
Original:  Thus , PNP-D may be more suitable for real-world data, which usually contains several local clusters for one class.
Revised:  Thus , PNP-D pays less attention to such instances and keeps them as they were. For most real-world data, which usually contains several local clusters for one class.
Edit intent: clarity
Original:  Thus , PNP-D may be more suitable for real-world data, which usually contains several local clusters for one class.
Revised:  Thus , PNP-D may be more suitable for real-world data, one class usually contains several local clusters for one class.
Edit intent: coherence
Original:  Considerable efforts have been devoted to exploring the  spectral radius of the preconditioned matrix and this leads to many case-by-case studies depending on the used time-integrator.
Revised:  Considerable efforts have been devoted to exploring the spectral radius of the iteration matrix, and this leads to many case-by-case studies depending on the used time-integrator.
Edit intent: clarity
Original:  The main conclusion is that the global error satisfies \|{err^{k+1}\|_{{\mathbf W}, 2}\leq \alpha{1-\alpha}\|{err}^{k}\|_{{\mathbf W}, 2} provided that the time-integrator }  is stable, where k is the iteration index and for any vector v the norm \|v\|_{{\mathbf W, 2} is defined by \|v\|_{{\mathbf W}, 2}=\|{\mathbf W}v\|_2 with }%DIFDELCMD < {%%% \mathbf W being a matrix depending on the space discretization matrix only.
Revised:  The main conclusion is that the global error satisfies \|{err^{k+1}\|_{{\mathbf W}, 2}\leq \alpha{1-\alpha}\|{err}^{k}\|_{{\mathbf W}, 2} provided that the time-integrator } is stable, where k is the iteration index and for any vector v the norm \|v\|_{{\mathbf W, 2} is defined by \|v\|_{{\mathbf W}, 2}=\|{\mathbf W}v\|_2 with }%DIFDELCMD < {%%% being a matrix depending on the space discretization matrix only.
Edit intent: fluency
Original:  Any language with products and functions can be modelled as a higher-order algebraic theory with rewrites , and the internal language of its presheaf topos provides total specification of the structure and behavior of terms.
Revised:  Any language with products and functions can be modelled as a higher-order algebraic theory with rewrites , and the internal language of their presheaf toposes provides total specification of the structure and behavior of terms.
Edit intent: fluency
Original:  Any language with products and functions can be modelled as a higher-order algebraic theory with rewrites , and the internal language of its presheaf topos provides total specification of the structure and behavior of terms.
Revised:  Any language with products and functions can be modelled as a higher-order algebraic theory with rewrites , and the internal language of its presheaf topos provides total specification the structure and behavior of terms.
Edit intent: fluency
Original:  An experiment of speech signal separation shows that, compared to a conventional method that integrates WPE and independent vector analysis, our proposed algorithm has significantly faster convergence speeds while maintaining its separation performance.
Revised:  An experiment of speech signal separation shows that, compared to a conventional method that integrates WPE and independent vector analysis, our proposed method achieves much faster convergence while maintaining its separation performance.
Edit intent: clarity
Original:  In particular, given conditions for which one or more speciation events within an ecosystem occur, our aim is to develop the  modeling and simulation tools necessary to handle such events.
Revised:  In particular, given conditions for which one or more speciation events within an ecosystem occur, our aim is to develop the necessary modeling and simulation tools necessary to handle such events.
Edit intent: clarity
Original: Search-based test generation is guided by feedback from one or more fitness functions - scoring functions that judge solution optimality.
Revised: Search-based test generation is guided by feedback from one or more fitness functions -- scoring functions that judge solution optimality.
Edit intent: fluency
Original:  We have evaluated our framework, EvoSuiteFIT, on a set of real Java case examples.
Revised:  We have evaluated our framework, EvoSuiteFIT, on a set of Java case examples.
Edit intent: clarity
Original:  EvoSuiteFIT techniques attain significant improvements for two of the three goals, and show small improvements on the third when the number of generations of evolution is fixed.
Revised:  EvoSuiteFIT techniques attain significant improvements for two of the three goals, and show limited improvements on the third when the number of generations of evolution is fixed.
Edit intent: clarity
Original:  The ability to adjust fitness functions allows EvoSuiteFIT to make strategic choices that efficiently produce more effective test suites, and examining its choices offers insight into how to attain our testing goals.
Revised:  The ability to adjust fitness functions allows strategic choices that efficiently produce more effective test suites, and examining its choices offers insight into how to attain our testing goals.
Edit intent: clarity
Original:  The ability to adjust fitness functions allows EvoSuiteFIT to make strategic choices that efficiently produce more effective test suites, and examining its choices offers insight into how to attain our testing goals.
Revised:  The ability to adjust fitness functions allows EvoSuiteFIT to make strategic choices that efficiently produce more effective test suites, and examining these choices offers insight into how to attain our testing goals.
Edit intent: clarity
Original:  We find that AFFS is a powerful technique to apply when an effective fitness function does not already exist for generating tests to achieve a testing goal.
Revised:  We find that adaptive fitness function selection is a powerful technique to apply when an effective fitness function does not already exist for generating tests to achieve a testing goal.
Edit intent: clarity
Original:  We find that AFFS is a powerful technique to apply when an effective fitness function does not already exist for generating tests to achieve a testing goal.
Revised:  We find that AFFS is a powerful technique to apply when an effective fitness function does not already exist for achieving a testing goal.
Edit intent: clarity
Original: Search-based test generation is guided by feedback from one or more fitness functions -- scoring functions that judge solution optimality.
Revised: Search-based test generation is guided by feedback from one or more fitness functions - scoring functions that judge solution optimality.
Edit intent: fluency
Original: Assessing that a sparse polynomial G divides another sparse polynomial F is not yet known to admit a polynomial time algorithm .
Revised: No polynomial-time algorithm is known to test whether a sparse polynomial G divides another sparse polynomial F is not yet known to admit a polynomial time algorithm .
Edit intent: clarity
Original: Assessing that a sparse polynomial G divides another sparse polynomial F is not yet known to admit a polynomial time algorithm .
Revised: Assessing that a sparse polynomial G divides another sparse polynomial F .
Edit intent: clarity
Original:  While computing the quotient Q=F quo G can be done in polynomial time with respect to the sparsities of F, G and Q, it is not yet sufficient to get a polynomial time divisibility test in general.
Revised:  While computing the quotient Q=F quo G can be done in polynomial time with respect to the sparsities of F, G and Q, this is not yet sufficient to get a polynomial time divisibility test in general.
Edit intent: clarity
Original:  While computing the quotient Q=F quo G can be done in polynomial time with respect to the sparsities of F, G and Q, it is not yet sufficient to get a polynomial time divisibility test in general.
Revised:  While computing the quotient Q=F quo G can be done in polynomial time with respect to the sparsities of F, G and Q, it is not yet sufficient to get a polynomial-time divisibility test in general.
Edit intent: fluency
Original:  Its complexity is quasi-linear in the sparsities of F, G and Q. Our approach relies on sparse interpolation and it works over any finite fields or the ring of integers.
Revised:  Its complexity is quasi-linear in the sparsities of F, G and Q. Our approach relies on sparse interpolation and it works over any finite field or the ring of integers.
Edit intent: fluency
Original:  Then, as a step toward faster divisibility testing, we provide a new polynomial time algorithm when the divisor has some specific shapes . More precisely, we reduce the problem to finding a polynomial S such that QS is sparse and testing divisibility by S can be done in polynomial time.
Revised:  Then, as a step toward faster divisibility testing, we provide a new polynomial-time algorithm when the divisor has some specific shapes . More precisely, we reduce the problem to finding a polynomial S such that QS is sparse and testing divisibility by S can be done in polynomial time.
Edit intent: fluency
Original:  Then, as a step toward faster divisibility testing, we provide a new polynomial time algorithm when the divisor has some specific shapes . More precisely, we reduce the problem to finding a polynomial S such that QS is sparse and testing divisibility by S can be done in polynomial time.
Revised:  Then, as a step toward faster divisibility testing, we provide a new polynomial time algorithm when the divisor has a specific shape . More precisely, we reduce the problem to finding a polynomial S such that QS is sparse and testing divisibility by S can be done in polynomial time.
Edit intent: clarity
Original:  We illustrate the utility and specifics of applications of the new method in practice by using synthetic and natural speech signals.
Revised:  We illustrate the utility and specifics of applications of the new method in practice by using natural speech and synthetic signals.
Edit intent: fluency
Original:  However, pre-pandemic experimental studies have produced mixed results regarding their effectiveness against respiratory viruses  , leading to confusion over whether masks protect the wearer, or only those with whom the wearer interacts .
Revised:  However, pre-pandemic empirical studies have produced mixed results regarding their effectiveness against respiratory viruses , leading to confusion over whether masks protect the wearer, or only those with whom the wearer interacts .
Edit intent: clarity
Original:  However, pre-pandemic experimental studies have produced mixed results regarding their effectiveness against respiratory viruses  , leading to confusion over whether masks protect the wearer, or only those with whom the wearer interacts .
Revised:  However, pre-pandemic experimental studies have produced mixed results regarding their effectiveness against respiratory viruses , leading to confusion regarding the effectiveness of masks .
Edit intent: clarity
Original:  Thus, such studies should not be interpreted as providing evidence against masks.
Edit intent: coherence
Original:  The framework demonstrates that the impact of wearing a mask more frequently compounds super-linearly , as can the impact of both the susceptible and infected individual wearing a mask.
Revised:  The framework demonstrates that more frequently wearing a mask more frequently compounds super-linearly , as can the impact of both the susceptible and infected individual wearing a mask.
Edit intent: clarity
Original:  The framework demonstrates that the impact of wearing a mask more frequently compounds super-linearly , as can the impact of both the susceptible and infected individual wearing a mask.
Revised:  The framework demonstrates that the impact of wearing a mask provides super-linearly , as can the impact of both the susceptible and infected individual wearing a mask.
Edit intent: clarity
Original:  The framework demonstrates that the impact of wearing a mask more frequently compounds super-linearly , as can the impact of both the susceptible and infected individual wearing a mask.
Revised:  The framework demonstrates that the impact of wearing a mask more frequently compounds super-linearly compounding protection, as does both the susceptible and infected individual wearing a mask.
Edit intent: clarity
Original: We investigate how activation functions can be used to describe neural firing in an abstract way, and in turn, why they work well in artificial neural networks.
Revised: We investigate how the activation function can be used to describe neural firing in an abstract way, and in turn, why they work well in artificial neural networks.
Edit intent: style
Original: We investigate how activation functions can be used to describe neural firing in an abstract way, and in turn, why they work well in artificial neural networks.
Revised: We investigate how activation functions can be used to describe neural firing in an abstract way, and in turn, why it works well in artificial neural networks.
Edit intent: coherence
Original:  Together, it is show that there is not only a biological meaning, but a physical justification, for the emergence and performance of canonical activation functions;
Revised:  Together, it is shown that there is not only a biological meaning, but a physical justification, for the emergence and performance of canonical activation functions;
Edit intent: fluency
Original:  Together, it is show that there is not only a biological meaning, but a physical justification, for the emergence and performance of canonical activation functions;
Revised:  Together, it is show that there is not only a biological meaning, but a physical justification, for the emergence and performance of typical activation functions;
Edit intent: clarity
Original:  The key component of this approach is an artificial light field superimposed on a grid environment, which is determined by the positions of all agents and at the same time drives all agents to further change their positions, forming a dynamic mutual feedback process.
Revised:  The key component of this approach is an artificial light field superimposed on a grid environment, which is determined by the positions of all agents and at the same time drives all agents to change their positions, forming a dynamic mutual feedback process.
Edit intent: clarity
Original: Data augmentation is an inexpensive way to increase training data diversity , and is commonly achieved via transformations of existing data.
Revised: Data augmentation is an inexpensive way to increase training data diversity and is commonly achieved via transformations of existing data.
Edit intent: fluency
Original:  This paper investigates the use of training objectives that explicitly impose this consistency constraint , and how it can impact downstream audio classification tasks.
Revised:  This paper investigates the use of training objectives that explicitly impose this consistency constraint and how it can impact downstream audio classification tasks.
Edit intent: fluency
Original:  In the context of deep convolutional neural networks in the supervised setting, we show empirically that certain measures of consistency are not implicitly captured by the cross-entropy loss , and that incorporating such measures into the loss function can improve the performance of tasks such as audio tagging .
Revised:  In the context of deep convolutional neural networks in the supervised setting, we show empirically that certain measures of consistency are not implicitly captured by the cross-entropy loss and that incorporating such measures into the loss function can improve the performance of tasks such as audio tagging .
Edit intent: fluency
Original:  In the context of deep convolutional neural networks in the supervised setting, we show empirically that certain measures of consistency are not implicitly captured by the cross-entropy loss , and that incorporating such measures into the loss function can improve the performance of tasks such as audio tagging .
Revised:  In the context of deep convolutional neural networks in the supervised setting, we show empirically that certain measures of consistency are not implicitly captured by the cross-entropy loss , and that incorporating such measures into the loss function can improve the performance of audio classification systems .
Edit intent: clarity
Original:  The introduction of side constraints prevents this problem from being solved using the well-known network simplex algorithm, however by characterizing its basis structure we develop a generalization of network simplex algorithm that can be used for its  efficient solution.
Revised:  The introduction of side constraints prevents this problem from being solved using the well-known network simplex algorithm, however by characterizing its basis structure we develop a generalization of network simplex algorithm that can be used for its computationally efficient solution.
Edit intent: clarity
Original:  We also show that BOExplain is effective at deriving explanations for inference queries from source and training data on three real-world datasets. 
Revised:  We also show that BOExplain is effective at deriving explanations for inference queries from source and training data on a variety of real-world datasets. 
Edit intent: clarity
Original:  We implement our idea in a tool named Dompteur and demonstrate that our augmented system, in contrast to an unmodified baseline, successfully focuses on perceptible ranges of the input signal.
Revised:  We implement our idea in a tool named DOMPTEUR and demonstrate that our augmented system, in contrast to an unmodified baseline, successfully focuses on perceptible ranges of the input signal.
Edit intent: fluency
Original:  To evaluate our approach, we construct an adaptive attacker , which actively tries to avoid our augmentations and demonstrate that adversarial examples from this attacker remain clearly perceivable.
Revised:  To evaluate our approach, we construct an adaptive attacker that actively tries to avoid our augmentations and demonstrate that adversarial examples from this attacker remain clearly perceivable.
Edit intent: fluency
Original:  There is clear evidence that previous shortages of COVID-19 related goods (e.g., masks and COVID-19 tests) and services pushed customers, and vendors, towards illicit online trade occurring on dark web marketplaces.
Revised:  There is clear evidence that previous shortages of COVID-19 related products (e.g., masks and COVID-19 tests) and services pushed customers, and vendors, towards illicit online trade occurring on dark web marketplaces.
Edit intent: clarity
Original:  To do so, we partnered with a major mHealth firm that provides one of the largest mobile health app platforms in Asia specializing in diabetes care.
Revised:  We partnered with a major mHealth firm that provides one of the largest mobile health app platforms in Asia specializing in diabetes care.
Edit intent: coherence
Original:  To do so, we partnered with a major mHealth firm that provides one of the largest mobile health app platforms in Asia specializing in diabetes care.
Revised:  To do so, we partnered with a major mHealth firm that provides one of the largest mHealth apps in Asia specializing in diabetes care.
Edit intent: clarity
Original:  Patients who adopted the mHealth app undertook higher levels of exercise, consumed healthier food with lower calories , walked more steps and slept for longer times on a daily basis.
Revised:  Patients who adopted the mHealth app undertook more exercise, consumed healthier food with lower calories , walked more steps and slept for longer times on a daily basis.
Edit intent: clarity
Original:  Patients who adopted the mHealth app undertook higher levels of exercise, consumed healthier food with lower calories , walked more steps and slept for longer times on a daily basis.
Revised:  Patients who adopted the mHealth app undertook higher levels of exercise, consumed healthier food , walked more steps and slept for longer times on a daily basis.
Edit intent: clarity
Original:  We found that personalized mobile message with patient-specific guidance can have an inadvertent  effect on patient app engagement , life style changes, and health improvement.
Revised:  Surprisingly, we find personalized mobile messages with patient-specific guidance can have an inadvertent effect on patient app engagement , life style changes, and health improvement.
Edit intent: coherence