wanyu/IteraTeR_full_sent huggingface dataset:
Original:  It takes the form of a Kullback-Leibler divergence and enables data-driven inference of model parameters and Bayesian prediction of time series  .
Revised:  It takes the form of a Kullback-Leibler divergence and enables data-driven inference of model parameters and Bayesian prediction of time series , and calculation of fluctuations beyond mean--field theory. Lastly, we expose a regime with fluctuation--induced transitions between mean--field solutions .
Edit intent: meaning-changed
Original: We propose a novel method---based on local moment matching---to approximate the value function of a Markov Decision Process . The method is grounded in recent work by Braverman et al (2020 ) that relates the solution of the Bellman equation to that of a PDE where, in the spirit of the central limit theorem, the transition matrix is reduced to its local first and second moments.
Revised: We propose a novel method---based on local moment matching---to approximate the value function of a Markov Decision Process that stands on two pillars: state aggregation -- as the algorithmic infrastructure; and central-limit-theorem-type approximations -- as the mathematical underpinning of optimality guarantees. The theory is grounded in recent work by Braverman et al (2020 ) that relates the solution of the Bellman equation to that of a PDE where, in the spirit of the central limit theorem, the transition matrix is reduced to its local first and second moments.
Edit intent: meaning-changed
Original:  The method is grounded in recent work by Braverman et al (2020 ) that relates the solution of the Bellman equation to that of a PDE where, in the spirit of the central limit theorem, the transition matrix is reduced to its local first and second moments.
Revised:  The method is grounded in recent work Braverman et al (2020 ) that relates the solution of the Bellman equation to that of a PDE where, in the spirit of the central limit theorem, the transition matrix is reduced to its local first and second moments.
Edit intent: fluency
Original:  The method is grounded in recent work by Braverman et al (2020 ) that relates the solution of the Bellman equation to that of a PDE where, in the spirit of the central limit theorem, the transition matrix is reduced to its local first and second moments.
Revised:  The method is grounded in recent work by Braverman et al (2020 that relates the solution of the Bellman equation to that of a PDE where, in the spirit of the central limit theorem, the transition matrix is reduced to its local first and second moments.
Edit intent: fluency
Original:  We show how this view can be embedded into the existing aggregation framework of ADP, providing a disciplined mechanism to tune the aggregation and disaggregation probabilities . This embedding into aggregation also reveals how the approximation's accuracy depends on a certain local linearity of the value function .
Revised:  We show how this view can be embedded into the existing aggregation framework of ADP, providing a disciplined mechanism to tune the aggregation and disaggregation probabilities .
Edit intent: coherence
Original:  Another dominant component especially in continuous domains is the policy gradient method which models and optimizes the policy directly. However, when Q functions are approximated with neural networks, their landscapes can be complex and therefore mislead the local gradient. In this work , we propose a self-regularized and self-guided actor-critic method .
Revised:  Our main contribution in this work is a self-regularized and self-guided actor-critic method .
Edit intent: coherence
Original:  In addition , we propose a self-guided policy improvement method by combining policy-gradient with zero-order optimization such as the Cross Entropy Method. It helps to search for actions associated with higher Q-values in a broad neighborhood and is robust to local noise in the Q function approximation .
Revised:  In addition , we propose a self-guided policy improvement method by combining policy-gradient with zero-order optimization to search for actions associated with higher Q-values in a broad neighborhood and is robust to local noise in the Q function approximation .
Edit intent: coherence
Original:  Our first construction is top-down and considers the maximal domain of a worst-case Luxemburg norm. From an applied persepective, this approach can be justified by a uniform-boundedness-type result. In typical situations, the worst-case Orlicz space agrees with the intersection of the corresponding individual Orlicz spaces. Our second construction produces the closure of a space of test random variables with respect to the worst-case Luxemburg norm.
Revised:  Our first construction is top-down and considers the maximal domain of a top-down approach and a bottom-up approach.
Edit intent: coherence
Original:  We show that separability of such spaces or their subspaces has very strong implications in terms of  dominatedness of the set of priors and thus for applications in the field of robust finance.
Revised:  We show that separability of such spaces or their subspaces has very strong implications in terms of dominatedness of the set of priors and the lack of order completeness. Our results have subtle implications for the field of robust finance.
Edit intent: meaning-changed
Original:  For instance, norm closures of bounded continuous functions  as considered in the G-framework  lead to spaces which are lattice-isomorphic to sublattices of a classical L^1-space lacking, however, Dedekind \sigma-completeness .
Revised:  For instance, norm closures of bounded continuous functions with respect to the worst-case L^p-norm, as considered in the G-framework lead to spaces which are lattice-isomorphic to sublattices of a classical L^1-space lacking, however, Dedekind \sigma-completeness .
Edit intent: meaning-changed
Original:  For instance, norm closures of bounded continuous functions  as considered in the G-framework  lead to spaces which are lattice-isomorphic to sublattices of a classical L^1-space lacking, however, Dedekind \sigma-completeness .
Revised:  For instance, norm closures of bounded continuous functions as considered in the G-framework , lead to spaces which are lattice-isomorphic to sublattices of a classical L^1-space lacking, however, Dedekind \sigma-completeness .
Edit intent: fluency
Original:  For instance, norm closures of bounded continuous functions  as considered in the G-framework  lead to spaces which are lattice-isomorphic to sublattices of a classical L^1-space lacking, however, Dedekind \sigma-completeness .
Revised:  For instance, norm closures of bounded continuous functions as considered in the G-framework lead to spaces which are lattice isomorphic to a sublattice of a classical L^1-space lacking, however, Dedekind \sigma-completeness .
Edit intent: fluency
Original:  For instance, norm closures of bounded continuous functions  as considered in the G-framework  lead to spaces which are lattice-isomorphic to sublattices of a classical L^1-space lacking, however, Dedekind \sigma-completeness .
Revised:  For instance, norm closures of bounded continuous functions as considered in the G-framework lead to spaces which are lattice-isomorphic to sublattices of a classical L^1-space lacking, however, any form of order completeness .
Edit intent: clarity
Original:  These basis dictionaries can be seen as generalizations of the classical Shannon wavelet packet dictionary and of classical time-frequency adapted wavelet packets to arbitrary graphs, and does not rely on the frequency interpretation of Laplacian eigenvalues.
Revised:  These basis dictionaries can be seen as generalizations of the classical Shannon wavelet packet dictionary to arbitrary graphs, and does not rely on the frequency interpretation of Laplacian eigenvalues.
Edit intent: clarity
Original:  These basis dictionaries can be seen as generalizations of the classical Shannon wavelet packet dictionary and of classical time-frequency adapted wavelet packets to arbitrary graphs, and does not rely on the frequency interpretation of Laplacian eigenvalues.
Revised:  These basis dictionaries can be seen as generalizations of the classical Shannon wavelet packet dictionary and of classical time-frequency adapted wavelet packets to arbitrary graphs, and do not rely on the frequency interpretation of Laplacian eigenvalues.
Edit intent: fluency
Original:  We describe the algorithms (involving either vector rotations or orthogonalizations) to efficiently approximate and compress signals through the best-basis algorithm , and demonstrate the strengths of these basis dictionaries for graph signals  on sunflower graphs and road traffic networks.
Revised:  We describe the algorithms (involving either vector rotations or orthogonalizations) to construct these basis dictionaries, use them to efficiently approximate graph signals through the best-basis algorithm , and demonstrate the strengths of these basis dictionaries for graph signals on sunflower graphs and road traffic networks.
Edit intent: meaning-changed
Original:  We describe the algorithms (involving either vector rotations or orthogonalizations) to efficiently approximate and compress signals through the best-basis algorithm , and demonstrate the strengths of these basis dictionaries for graph signals  on sunflower graphs and road traffic networks.
Revised:  We describe the algorithms (involving either vector rotations or orthogonalizations) to efficiently approximate and compress signals through the best basis search , and demonstrate the strengths of these basis dictionaries for graph signals on sunflower graphs and road traffic networks.
Edit intent: clarity
Original:  We describe the algorithms (involving either vector rotations or orthogonalizations) to efficiently approximate and compress signals through the best-basis algorithm , and demonstrate the strengths of these basis dictionaries for graph signals  on sunflower graphs and road traffic networks.
Revised:  We describe the algorithms (involving either vector rotations or orthogonalizations) to efficiently approximate and compress signals through the best-basis algorithm , and demonstrate the strengths of these basis dictionaries for graph signals measured on sunflower graphs and road traffic networks.
Edit intent: clarity
Original:  We describe the algorithms (involving either vector rotations or orthogonalizations) to efficiently approximate and compress signals through the best-basis algorithm , and demonstrate the strengths of these basis dictionaries for graph signals  on sunflower graphs and road traffic networks.
Revised:  We describe the algorithms (involving either vector rotations or orthogonalizations) to efficiently approximate and compress signals through the best-basis algorithm , and demonstrate the strengths of these basis dictionaries for graph signals on sunflower graphs and street networks.
Edit intent: clarity
Original: Complex 3D curves can be created by directly drawing mid-air in immersive environments ( AR/VR ). Drawing mid-air strokes precisely on the surface of a 3D virtual object  however, is difficult;
Revised: Complex 3D curves can be created by directly drawing mid-air in immersive environments ( Augmented and Virtual Realities ). Drawing mid-air strokes precisely on the surface of a 3D virtual object however, is difficult;
Edit intent: clarity
Original: Complex 3D curves can be created by directly drawing mid-air in immersive environments ( AR/VR ). Drawing mid-air strokes precisely on the surface of a 3D virtual object  however, is difficult;
Revised: Complex 3D curves can be created by directly drawing mid-air in immersive environments ( AR/VR ). Drawing mid-air strokes precisely on the surface of a 3D virtual object , however, is difficult;
Edit intent: fluency
Original:  We present the first detailed investigation of the fundamental problem of 3D stroke projection in AR/ VR. An assessment of the design requirements of real-time drawing of curves on 3D objects in AR/ VR is followed by the definition and classification of multiple techniques for 3D stroke projection.
Revised:  We present the first detailed investigation of the fundamental problem of 3D stroke projection in VR. An assessment of the design requirements of real-time drawing of curves on 3D objects in AR/ VR is followed by the definition and classification of multiple techniques for 3D stroke projection.
Edit intent: fluency
Original:  We present the first detailed investigation of the fundamental problem of 3D stroke projection in AR/ VR. An assessment of the design requirements of real-time drawing of curves on 3D objects in AR/ VR is followed by the definition and classification of multiple techniques for 3D stroke projection.
Revised:  We present the first detailed investigation of the fundamental problem of 3D stroke projection in AR/ VR. An assessment of the design requirements of real-time drawing of curves on 3D objects in VR is followed by the definition and classification of multiple techniques for 3D stroke projection.
Edit intent: fluency
Original:  We are able to accurately predict IPV victims and injury labels, and our best model predicts IPV a median of 1.34 years before violence prevention program entry with a sensitivity of  95 %DIFDELCMD < \\%%% %DIF < and a specificity of 71\\%.
Revised:  Our best model predicts IPV a median of 1.34 years before violence prevention program entry with a sensitivity of 95 %DIFDELCMD < \\%%% %DIF < and a specificity of 71\\%.
Edit intent: coherence
Original:  We are able to accurately predict IPV victims and injury labels, and our best model predicts IPV a median of 1.34 years before violence prevention program entry with a sensitivity of  95 %DIFDELCMD < \\%%% %DIF < and a specificity of 71\\%.
Revised:  We are able to accurately predict IPV victims and injury labels, and our best model predicts IPV a median of 3.08 years before violence prevention program entry with a sensitivity of 95 %DIFDELCMD < \\%%% %DIF < and a specificity of 71\\%.
Edit intent: meaning-changed
Original:  We are able to accurately predict IPV victims and injury labels, and our best model predicts IPV a median of 1.34 years before violence prevention program entry with a sensitivity of  95 %DIFDELCMD < \\%%% %DIF < and a specificity of 71\\%.
Revised:  We are able to accurately predict IPV victims and injury labels, and our best model predicts IPV a median of 1.34 years before violence prevention program entry with a sensitivity of 64\% and a specificity of 95 %DIFDELCMD < \\%%% %DIF < and a specificity of 71\\%.
Edit intent: meaning-changed
Original:  We conduct error analysis to determine for which patients our model has especially high or low performance and discuss next steps for a deployed clinical risk model.abstract 
Revised:  We conduct error analysis to determine for which patients our model has especially high or low performance and discuss next steps for a deployed clinical risk model.abstract \%. We conduct error analysis to determine for which patients our model has especially high or low performance and discuss next steps for a deployed clinical risk model.
Edit intent: meaning-changed
Original:  The author of this paper instead advocated for the continuation of existing means-tested welfare systems and further investment in education scheme for unskilled and low-skilled labour. This paper was submitted to the "Young Economist of the Year 2019" essay competition hosted by the Financial Times and the Royal Economic Society, where it won a high commendation and was one of the 36 best papers shortlisted among 1,300 qualified submissions to be honoured on the website of the Royal Economic Society (2.7\% acceptance rate). Due to the rules and policies of the Royal Economic Society, the author could only make this paper available to the public at least one year after the original date of submission .
Revised:  The author of this paper instead advocated for the continuation of existing means-tested welfare systems and further investment in education scheme for unskilled and low-skilled labor as a more sustainable and effective solution to the automation-induced large-scale displacement of workers .
Edit intent: meaning-changed
Original:  The efficiency of the method is examined in the case of the prediction of the number of hospitalized  infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Revised:  The efficiency of the method is shown in the case of the prediction of the number of hospitalized infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Edit intent: clarity
Original:  The efficiency of the method is examined in the case of the prediction of the number of hospitalized  infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Revised:  The efficiency of the method is examined in the case of the prediction of the number of hospitalized and infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Edit intent: fluency
Original:  The efficiency of the method is shown in the case of the prediction of the number of hospitalized and infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Revised:  The efficiency of the method is shown in the case of the prediction of the number of infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Edit intent: clarity
Original:  The efficiency of the method is shown in the case of the prediction of the number of hospitalized and infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Revised:  The efficiency of the method is shown in the case of the prediction of the number of hospitalized and infected and removed people during the two pandemic waves of COVID-19 in France, which has taken place approximately between February and May 2020.
Edit intent: meaning-changed
Original:  The efficiency of the method is shown in the case of the prediction of the number of hospitalized and infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Revised:  The efficiency of the method is shown in the case of the prediction of the number of hospitalized and infected and removed people during the first pandemic wave of COVID-19 in France, which have taken place approximately between February and May 2020.
Edit intent: fluency
Original:  The efficiency of the method is shown in the case of the prediction of the number of hospitalized and infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and May 2020.
Revised:  The efficiency of the method is shown in the case of the prediction of the number of hospitalized and infected and removed people during the first pandemic wave of COVID-19 in France, which has taken place approximately between February and November 2020.
Edit intent: meaning-changed
Original:  The approach is validated by several robustness tests and by contrasting our estimates with the official statistics on the recession caused by COVID-19 in different European countries during the first  two quarters of 2020.
Revised:  The approach is validated by several robustness tests and by contrasting our estimates with the official statistics on the recession caused by COVID-19 in twelve European countries during the first two quarters of 2020.
Edit intent: meaning-changed
Original:  The approach is validated by several robustness tests and by contrasting our estimates with the official statistics on the recession caused by COVID-19 in different European countries during the first  two quarters of 2020.
Revised:  The approach is validated by several robustness tests and by contrasting our estimates with the official statistics on the recession caused by COVID-19 in different European countries during the first wave of the pandemic. Our results are almost indistinguishable from the official statistics of the recession during the first two quarters of 2020.
Edit intent: meaning-changed
Original:  The approach is validated by several robustness tests and by contrasting our estimates with the official statistics on the recession caused by COVID-19 in different European countries during the first  two quarters of 2020. Compared with the standard indicators, our results are much more chronologically disaggregated and up-to-date  and, therefore, can inform the current debate on the appropriate policy response to the pandemic.
Revised:  The approach is validated by several robustness tests and by contrasting our estimates with the official statistics on the recession caused by COVID-19 in different European countries during the first two quarters of 2020 (correlation coefficient of 0.98) and are validated by several robustness tests. However, they are also more chronologically disaggregated and up-to-date and, therefore, can inform the current debate on the appropriate policy response to the pandemic.
Edit intent: meaning-changed
Original:  Compared with the standard indicators, our results are much more chronologically disaggregated and up-to-date  and, therefore, can inform the current debate on the appropriate policy response to the pandemic.
Revised:  Compared with the standard indicators, our results are much more chronologically disaggregated and up-to-date than standard macroeconomic indicators and, therefore, can inform the current debate on the appropriate policy response to the pandemic.
Edit intent: meaning-changed
Original:  Compared with the standard indicators, our results are much more chronologically disaggregated and up-to-date  and, therefore, can inform the current debate on the appropriate policy response to the pandemic. Unsurprisingly, we find that nations that experienced the most severe initial outbreaks also grappled with the hardest economic recessions. However, we detect diffused signs of recovery, with economic activity in most European countries returning to its pre-pandemic level by August 2020. Furthermore, we show how delaying intervention or pursuing 'herd immunity' are not successful strategies , since they increase both economic disruption and mortality.
Revised:  Compared with the standard indicators, our results are much more chronologically disaggregated and up-to-date and, therefore, can provide crucial and timely information for policy evaluation. Our results show that delaying intervention and pursuing 'herd immunity' are not successful strategies , since they increase both economic disruption and mortality.
Edit intent: clarity
Original:  Considering the expansion of robot applications in more complex and dynamic environments,it is evident that it is impossible to pre-program all possible object categories . Robots will have to be able to learn new object categories in the field.
Revised:  Considering the expansion of robot applications in more complex and dynamic environments,it is evident that it is not possible to pre-program all possible object categories . Robots will have to be able to learn new object categories in the field.
Edit intent: fluency
Original:  Considering the expansion of robot applications in more complex and dynamic environments,it is evident that it is impossible to pre-program all possible object categories . Robots will have to be able to learn new object categories in the field.
Revised:  Considering the expansion of robot applications in more complex and dynamic environments,it is evident that it is impossible to pre-program all object categories and anticipate all exceptions in advance. Therefore, robots should have the functionality to learn about new object categories in the field.
Edit intent: meaning-changed