wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We derive the limit distribution of the QTE estimator under MPDs, highlighting the difficulties that arise in analytical inference due to parameter tuning. It is shown that both the naive multiplier bootstrap and the naive multiplier bootstrap of the pairs fail to approximate the limit distribution of the QTE estimator under MPDs because they do not preserve the dependence structure within the matched pairs. To address this difficulty we propose two bootstrap methods that can consistently approximate the limit distribution : the gradient bootstrap and the multiplier bootstrap of the inverse propensity score weighted (IPW) estimator.
Revised:  Standard multiplier bootstrap inference fails to capture the negative dependence of observations within each pair and is therefore conservative. Analytical inference involves estimating multiple functional quantities that require several tuning parameters. Instead, this paper proposes two bootstrap methods that can consistently approximate the limit distribution : the gradient bootstrap and the multiplier bootstrap of the inverse propensity score weighted (IPW) estimator.
Edit intent: meaning-changed
Original:  To address this difficulty we propose two bootstrap methods that can consistently approximate the limit distribution : the gradient bootstrap and the multiplier bootstrap of the inverse propensity score weighted (IPW) estimator.
Revised:  To address this difficulty we propose two bootstrap methods that can consistently approximate the limit distribution of the original QTE estimator and lessen the burden of tuning parameter choice. Most especially, the multiplier bootstrap of the inverse propensity score weighted (IPW) estimator.
Edit intent: meaning-changed
Original:  To address this difficulty we propose two bootstrap methods that can consistently approximate the limit distribution : the gradient bootstrap and the multiplier bootstrap of the inverse propensity score weighted (IPW) estimator. The gradient bootstrap is free of tuning parameters but requires knowledge of the pair identities. The multiplier bootstrap of the IPW estimator does not require such knowledge but involves one tuning parameter. Both methods are straightforward to implement and able to provide pointwise confidence intervals and uniform confidence bands that achieve exact limiting coverage rates. We demonstrate their finite sample performance using simulations and provide an empirical application to a well-known dataset in macroinsurance .
Revised:  To address this difficulty we propose two bootstrap methods that can consistently approximate the limit distribution : the gradient bootstrap and the multiplier bootstrap of the inverse propensity score weighted multiplier bootstrap can be implemented without knowledge of pair identities .
Edit intent: coherence
Original:  The redundant CPU cycles are not burned ``for nothing'' . Our work employs a weakly consistent data model where replicas run independently yet inform each other through heartbeat messages whether they are still up and running.
Revised:  The redundant CPU cycles are not burned "for nothing" . Our work employs a weakly consistent data model where replicas run independently yet inform each other through heartbeat messages whether they are still up and running.
Edit intent: fluency
Original: In this paper we model and predict the spread of COVID-19 infection at a provincial (i.e. EU NUTS-3) level in Italy by using official data from the Italian Ministry of Health integrated with data extracted from daily official press conferences of regional authorities and from local newspaper websites.
Revised: In this paper we develop a predictive model for the spread of COVID-19 infection at a provincial (i.e. EU NUTS-3) level in Italy by using official data from the Italian Ministry of Health integrated with data extracted from daily official press conferences of regional authorities and from local newspaper websites.
Edit intent: clarity
Original:  Therefore, we require systems that can accurately rate AMR quality in the absence of costly gold data . To achieve this , we transfer the AMR graph to the domain of images.
Revised:  Therefore, we require systems that can accurately rate AMR quality in the absence of costly gold data , allowing us to inform downstream systems about an incorporated parse's trustworthiness or select among different candidate parses. In this work, we propose to transfer the AMR graph to the domain of images.
Edit intent: meaning-changed
Original:  This allows us to create a simple convolutional neural network (CNN) that imitates a human rater. In our experiments , we show that the method can rate the quality of AMR graphs more accurately than a strong baseline, with respect to several dimensions of interest.
Revised:  This allows us to create a simple convolutional neural network (CNN) that imitates a human judge tasked with rating graph quality. Our experiments show that the method can rate the quality of AMR graphs more accurately than a strong baseline, with respect to several dimensions of interest.
Edit intent: clarity
Original:  In our experiments , we show that the method can rate the quality of AMR graphs more accurately than a strong baseline, with respect to several dimensions of interest. Furthermore , the method proves to be more efficient as it reduces the incurred energy consumption.
Revised:  In our experiments , we show that the method can rate the quality of AMR graphs more accurately than strong baselines, in several quality dimensions. Moreover , the method proves to be more efficient as it reduces the incurred energy consumption.
Edit intent: clarity
Original: In this paper, we develop the notion of controllability for uniform hypergraphs via tensor algebra and the theory of polynomial control . We propose a tensor-based multilinear system representation to characterize the multidimensional state dynamics of uniform hypergraphs , and derive a Kalman-rank-like condition to identify the minimum number of driver vertices in order to achieve full control of the whole hypergraph.
Revised: In this paper, we develop the notion of controllability for uniform hypergraphs via tensor algebra and polynomial control theory. Inspired by uniform hypergraphs, we propose a new tensor-based multilinear system representation to characterize the multidimensional state dynamics of uniform hypergraphs , and derive a Kalman-rank-like condition to identify the minimum number of driver vertices in order to achieve full control of the whole hypergraph.
Edit intent: meaning-changed
Original:  We propose a tensor-based multilinear system representation to characterize the multidimensional state dynamics of uniform hypergraphs , and derive a Kalman-rank-like condition to identify the minimum number of driver vertices in order to achieve full control of the whole hypergraph.
Revised:  We propose a tensor-based multilinear dynamical system representation , and derive a Kalman-rank-like condition to identify the minimum number of driver vertices in order to achieve full control of the whole hypergraph.
Edit intent: clarity
Original:  We propose a tensor-based multilinear system representation to characterize the multidimensional state dynamics of uniform hypergraphs , and derive a Kalman-rank-like condition to identify the minimum number of driver vertices in order to achieve full control of the whole hypergraph.
Revised:  We propose a tensor-based multilinear system representation to characterize the multidimensional state dynamics of uniform hypergraphs , and derive a Kalman-rank-like condition to determine the minimum number of driver vertices in order to achieve full control of the whole hypergraph.
Edit intent: clarity
Original:  We propose a tensor-based multilinear system representation to characterize the multidimensional state dynamics of uniform hypergraphs , and derive a Kalman-rank-like condition to identify the minimum number of driver vertices in order to achieve full control of the whole hypergraph. We discover that the minimum number of driver vertices can be determined by the hypergraph degree distributions, and high degree vertices are preferred to be the drivers in the chain, ring and star hypergraph configurations .
Revised:  We propose a tensor-based multilinear system representation to characterize the multidimensional state dynamics of uniform hypergraphs , and derive a Kalman-rank-like condition to identify the minimum number of control nodes (MCN) needed to achieve controllability of even uniform hypergraphs. We present an efficient heuristic to obtain the MCN. MCN can be used as a measure of robustness, and we show that it is related to the hypergraph degree distribution in simulated examples .
Edit intent: meaning-changed
Original:  Since the main energetic costs of ventilation are related to the convective transport, we prove that, for all mammals, the localization of the shift from an convective transport into a diffusive transport plays a critical role on keeping that cost low while fulfilling the lung 's function.
Revised:  Since the main energetic costs of ventilation are related to the convective transport, we prove that, for all mammals, the localization of the shift from a convective transport into a diffusive transport plays a critical role on keeping that cost low while fulfilling the lung 's function.
Edit intent: fluency
Original:  Since the main energetic costs of ventilation are related to the convective transport, we prove that, for all mammals, the localization of the shift from an convective transport into a diffusive transport plays a critical role on keeping that cost low while fulfilling the lung 's function.
Revised:  Since the main energetic costs of ventilation are related to the convective transport, we prove that, for all mammals, the localization of the shift from an convective transport into a diffusive transport plays a critical role on keeping that cost low while fulfilling the lung function.
Edit intent: fluency
Original:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates  are driven by a few core geometrical characteristics shared by the mammals' lungs , the physical processes of  respiratory gas transport and the metabolic needs .
Revised:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates at a given metabolic rate are driven by a few core geometrical characteristics shared by the mammals' lungs , the physical processes of respiratory gas transport and the metabolic needs .
Edit intent: meaning-changed
Original:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates  are driven by a few core geometrical characteristics shared by the mammals' lungs , the physical processes of  respiratory gas transport and the metabolic needs .
Revised:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates are driven by a few core geometrical characteristics shared by the mammals' lungs and the physical processes of respiratory gas transport and the metabolic needs .
Edit intent: fluency
Original:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates  are driven by a few core geometrical characteristics shared by the mammals' lungs , the physical processes of  respiratory gas transport and the metabolic needs .
Revised:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates are driven by a few core geometrical characteristics shared by the mammals' lungs , the physical processes of the respiratory gas transport and the metabolic needs .
Edit intent: fluency
Original:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates  are driven by a few core geometrical characteristics shared by the mammals' lungs , the physical processes of  respiratory gas transport and the metabolic needs .
Revised:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates are driven by a few core geometrical characteristics shared by the mammals' lungs , the physical processes of respiratory gas transport .
Edit intent: clarity
Original: A model of optimal control of ventilation recently developed for humans has suggested that the localization of the transition between a convective and a diffusive transport of the respiratory gas determines how ventilation should be controlled to minimize its energetic cost at any metabolic regime.
Revised: A model of optimal control of ventilation has recently been developed for humans has suggested that the localization of the transition between a convective and a diffusive transport of the respiratory gas determines how ventilation should be controlled to minimize its energetic cost at any metabolic regime.
Edit intent: fluency
Original: A model of optimal control of ventilation recently developed for humans has suggested that the localization of the transition between a convective and a diffusive transport of the respiratory gas determines how ventilation should be controlled to minimize its energetic cost at any metabolic regime.
Revised: A model of optimal control of ventilation recently developed for humans . This model suggests that the localization of the transition between a convective and a diffusive transport of the respiratory gas determines how ventilation should be controlled to minimize its energetic cost at any metabolic regime.
Edit intent: coherence
Original:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates at a given metabolic rate are driven by a few core geometrical characteristics shared by the mammals' lungs and  the physical processes of the respiratory gas transport.
Revised:  Our analysis supports the hypothesis that the mammals' allometric scaling laws of tidal volumes and breathing rates at a given metabolic rate are driven by a few core geometrical characteristics shared by the mammals' lungs and by the physical processes of the respiratory gas transport.
Edit intent: fluency
Original:  Particularities of SARS-CoV-2,  as its persistence in surfaces and the lack of a cure for COVID-19, have pushed authorities to apply restrictive policies to control its spreading.
Revised:  Particularities of SARS-CoV-2, such as its persistence in surfaces and the lack of a cure for COVID-19, have pushed authorities to apply restrictive policies to control its spreading.
Edit intent: fluency
Original:  Particularities of SARS-CoV-2,  as its persistence in surfaces and the lack of a cure for COVID-19, have pushed authorities to apply restrictive policies to control its spreading.
Revised:  Particularities of SARS-CoV-2, as its persistence in surfaces and the lack of a curative treatment or vaccine against COVID-19, have pushed authorities to apply restrictive policies to control its spreading.
Edit intent: meaning-changed
Original:  By a statistically-based algorithm, we perform a temporal reclassification of cases to avoid delay-induced errors, building up new epidemiologic curves centered in the day where the contagion effectively occurred.
Revised:  Using a statistically-based algorithm, we perform a temporal reclassification of cases to avoid delay-induced errors, building up new epidemiologic curves centered in the day where the contagion effectively occurred.
Edit intent: fluency
Original:  We also statistically enhance the robustness behind the discharge/recovery clinical criteria in the lack of a direct test, which is typically the case of non-first world countries, where the limited testing capabilities are fully dedicated to the evaluation of new cases.
Revised:  We also statistically enhance the robustness behind the discharge/recovery clinical criteria in the absence of a direct test, which is typically the case of non-first world countries, where the limited testing capabilities are fully dedicated to the evaluation of new cases.
Edit intent: clarity
Original:  We adapt and optimize a dynamic programming algorithm for sequential hypergraph partitioning to produce a linear time algorithm which can determine the optimal partition of rows under an expressive cost model, assuming the column partition remains fixed. Furthermore, we show that the problem of determining an optimal partition for the rows and columns simultaneously is NP-Hard under a simple linear cost model.
Revised:  We show that finding the optimal grouping of rows and columns simultaneously is NP-Hard under a simple linear cost model.
Edit intent: clarity
Original:  Furthermore, we show that the problem of determining an optimal partition for the rows and columns simultaneously is NP-Hard under a simple linear cost model. To evaluate our algorithm empirically against existing heuristics, we introduce the 1D-VBR format, a specialization of VBRformat where columns are left ungrouped.
Revised:  Furthermore, we show that the problem of determining an optimal partition for the rows and columns for VBR is NP-hard under several reasonable cost models. In light of this finding, we propose a 1-dimensional variant of VBR, called 1D-VBR format, a specialization of VBRformat where columns are left ungrouped.
Edit intent: clarity
Original:  To evaluate our algorithm empirically against existing heuristics, we introduce the 1D-VBR format, a specialization of VBRformat where columns are left ungrouped. We evaluate our algorithms on all 1626 real-valued matrices in the SuiteSparse Matrix Collection. When asked to minimize an empirically derived cost model for a sparse matrix-vector multiplication kernel, our algorithm produced partitions whose 1D-VBR realizations achieve a speedup of at least 1.18 over an unblocked kernel on 25\% of the matrices, and a speedup of at least 1.59 on 12.5\% of the matrices.
Revised:  To evaluate our algorithm empirically against existing heuristics, we introduce the 1D-VBR , which achieves better performance than VBR by only grouping rows. We describe detailed cost models for runtime and memory consumption. Then, we describe a linear time dynamic programming solution for optimally grouping the rows for 1D-VBR realizations achieve a speedup of at least 1.18 over an unblocked kernel on 25\% of the matrices, and a speedup of at least 1.59 on 12.5\% of the matrices.
Edit intent: meaning-changed
Original:  When asked to minimize an empirically derived cost model for a sparse matrix-vector multiplication kernel, our algorithm produced partitions whose 1D-VBR realizations achieve a speedup of at least 1.18 over an unblocked kernel on 25\% of the matrices, and a speedup of at least 1.59 on 12.5\% of the matrices. The 1D-VBR representation produced by our algorithm had faster SpMVs than the 1D-VBR representations produced by any existing heuristics on 87.8\% of the test matrices .
Revised:  When asked to minimize an empirically derived cost model for a sparse matrix-vector multiplication kernel, our algorithm produced partitions whose 1D-VBR format. We extend our algorithm to produce a heuristic VBR partitioner which alternates between optimally partitioning rows and columns, assuming the columns or rows to be fixed, respectively. Our alternating heuristic produces VBR matrices with the smallest memory footprint of any partitioner we tested .
Edit intent: meaning-changed
Original:  These state estimates require a measurement of the recovered population, and are tolerant to low errors in that measurement. Further, excellent estimates of all quantities are obtained using a temporal baseline of 112 days, with the exception of the time-varying transmission rate at times prior to the implementation of social distancing.
Revised:  These state estimates require a measurement of the recovered population, excellent estimates of all quantities are obtained using a temporal baseline of 112 days, with the exception of the time-varying transmission rate at times prior to the implementation of social distancing.
Edit intent: coherence
Original:  The aim of this paper is not to assign extreme significance to the results of these specific experimentsper se . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Revised:  The aim of this paper is per se . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Edit intent: clarity
Original:  The aim of this paper is not to assign extreme significance to the results of these specific experimentsper se . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Revised:  The aim of this paper is not to assign extreme significance to the results of these specific experiments . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Edit intent: clarity
Original:  The aim of this paper is not to assign extreme significance to the results of these specific experimentsper se . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Revised:  The aim of this paper is not to assign extreme significance to the results of these specific experimentsper se to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Edit intent: coherence
Original:  The aim of this paper is not to assign extreme significance to the results of these specific experimentsper se . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Revised:  The aim of this paper is not to assign extreme significance to the results of these specific experimentsper se . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Edit intent: clarity
Original:  The aim of this paper is not to assign extreme significance to the results of these specific experimentsper se . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision - all set within the complex context of the COVID-19 pandemic.
Revised:  The aim of this paper is not to assign extreme significance to the results of these specific experimentsper se . Rather, we intend to exemplify the power of SDA to determine what properties of measurements will yield estimates of unknown model parameters to a desired precision , in a model with the complexity required to capture important features of the COVID-19 pandemic.
Edit intent: clarity
Original:  Here we consider a social distancing problem for how a population, when in a world with a network of social sites, such as schools, restaurants, shopping centers, residential areas, etc., decides to visit or stay at some sites while avoiding or closing down  others so that the social contacts across the network can be minimized.
Revised:  Here we consider a social distancing problem for how a population, when in a world with a network of social sites, decides to visit or stay at some sites while avoiding or closing down others so that the social contacts across the network can be minimized.
Edit intent: clarity