wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We discuss the algorithmic design that allows a SIMD vectorization of the compute kernel, analyze the node-level performance  and report excellent weak and strong scaling of a hybrid thread/MPI parallelization.
Revised:  We discuss the algorithmic design that allows a SIMD vectorization of the compute kernel, identify the main ingredients for a good node-level performance and report excellent weak and strong scaling of a hybrid thread/MPI parallelization.
Edit intent: meaning-changed
Original:  We discuss the algorithmic design that allows a SIMD vectorization of the compute kernel, analyze the node-level performance  and report excellent weak and strong scaling of a hybrid thread/MPI parallelization.
Revised:  We discuss the algorithmic design that allows a SIMD vectorization of the compute kernel, analyze the node-level performance , and report excellent weak and strong scaling of a hybrid thread/MPI parallelization.
Edit intent: fluency
Original:  We find that word error rate can be reduced by a large margin by pre-training the acoustic  representation with AWEs, and additional (smaller) gains can be obtained by pre-training the word prediction layer with AGWEs.
Revised:  We find that word error rate can be reduced by a large margin by pre-training the acoustic segment representation with AWEs, and additional (smaller) gains can be obtained by pre-training the word prediction layer with AGWEs.
Edit intent: meaning-changed
Original: In the vision-and-language navigation (VLN) task, an agent follows natural language instructions and navigate in visual environments. Compared to the indoor navigation task that has been broadly studied, navigation in real-life outdoor environments remains a significant challenge with its complicated visual inputs and an insufficient amount of instructions that illustrate the intricate urban scenes .
Revised: In the vision-and-language navigation (VLN) task, an agent follows natural language instructions and navigates a real-life outdoor environments remains a significant challenge with its complicated visual inputs and an insufficient amount of instructions that illustrate the intricate urban scenes .
Edit intent: coherence
Original:  Compared to the indoor navigation task that has been broadly studied, navigation in real-life outdoor environments remains a significant challenge with its complicated visual inputs and an insufficient amount of instructions that illustrate the intricate urban scenes .
Revised:  Compared to the indoor navigation task that has been broadly studied, navigation in real-life outdoor environments remains a significant challenge with its complicated visual inputs and an insufficient amount of instructions that illustrate intricate urban scenes .
Edit intent: fluency
Original:  Compared to the indoor navigation task that has been broadly studied, navigation in real-life outdoor environments remains a significant challenge with its complicated visual inputs and an insufficient amount of instructions that illustrate the intricate urban scenes . In this paper , we introduce a Multimodal Text Style Transfer (MTST) learning approach to mitigate the problem of data scarcity in outdoor navigation tasks by effectively leveraging external multimodal resources .
Revised:  Compared to the indoor navigation task that has been broadly studied, navigation in real-life outdoor environments remains a significant challenge with its complicated visual inputs and an insufficient amount of instructions that illustrate the intricate urban scenes , outdoor VLN remains a challenging task to solve. This paper introduces a Multimodal Text Style Transfer (MTST) learning approach to mitigate the problem of data scarcity in outdoor navigation tasks by effectively leveraging external multimodal resources .
Edit intent: meaning-changed
Original:  In this paper , we introduce a Multimodal Text Style Transfer (MTST) learning approach to mitigate the problem of data scarcity in outdoor navigation tasks by effectively leveraging external multimodal resources .
Revised:  In this paper , we introduce a Multimodal Text Style Transfer (MTST) learning approach and leverages external multimodal resources to mitigate data scarcity in outdoor navigation tasks by effectively leveraging external multimodal resources .
Edit intent: coherence
Original:  Experimental results show that our MTST learning approach is model-agnostic, and our MTST approach significantly outperforms the baseline models on the outdoor VLN task, improving task completion rate by 22%DIFDELCMD < \\%%% %DIF < relatively on the test set and achieving new state-of-the-art performance.abstract 
Revised:  Experimental results show that our MTST learning approach is model-agnostic, and our MTST approach significantly outperforms the baseline models on the outdoor VLN task, improving task completion rate by %DIFDELCMD < \\%%% %DIF < relatively on the test set and achieving new state-of-the-art performance.abstract 
Edit intent: clarity
Original:  Experimental results show that our MTST learning approach is model-agnostic, and our MTST approach significantly outperforms the baseline models on the outdoor VLN task, improving task completion rate by 22%DIFDELCMD < \\%%% %DIF < relatively on the test set and achieving new state-of-the-art performance.abstract 
Revised:  Experimental results show that our MTST learning approach is model-agnostic, and our MTST approach significantly outperforms the baseline models on the outdoor VLN task, improving task completion rate by 22%DIFDELCMD < \\%%% %DIF < relatively on the test set and achieving new state-of-the-art performance.abstract 8.7\% relatively on the test set.
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Original: In this paper, we present SemEval-2020 Task 4, Commonsense Validation and Explanation (ComVE), which includes three subtasks, aiming to evaluate whether a system can distinguish a natural language statement that makes sense to human from one that does not, and provide the reasons.
Revised: In this paper, we present SemEval-2020 Task 4, Commonsense Validation and Explanation (ComVE), which includes three subtasks, aiming to evaluate whether a system can distinguish a natural language statement that makes sense to humans from one that does not, and provide the reasons.
Edit intent: fluency
Original:  In the third subtask, a participating system needs to generate the reason automatically .
Revised:  In the third subtask, a participating system needs to generate the reason . We finally attracted 39 teams participating at least one of the three subtasks. For Subtask A and Subtask B, the performances of top-ranked systems are close to that of humans. However, for Subtask C, there is still a relatively large gap between systems and human performance. The dataset used in our task can be found at URL Task4-Commonsense-Validation-and-Explanation; The leaderboard can be found at URL/competitions/21080#results .
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Original:  We show that this inductive bias towards tree structures dramatically improves systematic generalization to out-of-distribution examples  compared to strong baselines on an arithmetic expressions benchmark as well as on CLOSURE, a dataset that focuses on systematic generalization of models for grounded question answering.
Revised:  We show that this inductive bias towards tree structures dramatically improves systematic generalization to out-of-distribution examples , compared to strong baselines on an arithmetic expressions benchmark as well as on CLOSURE, a dataset that focuses on systematic generalization of models for grounded question answering.
Edit intent: fluency
Original:  We show that this inductive bias towards tree structures dramatically improves systematic generalization to out-of-distribution examples  compared to strong baselines on an arithmetic expressions benchmark as well as on CLOSURE, a dataset that focuses on systematic generalization of models for grounded question answering.
Revised:  We show that this inductive bias towards tree structures dramatically improves systematic generalization to out-of-distribution examples compared to strong baselines on an arithmetic expressions benchmark as well as on CLOSURE, a dataset that focuses on systematic generalization for grounded question answering.
Edit intent: clarity
Original: Zhang et al. (2020) reported that mandating face coverings in public is necessary to decrease the rate of new COVID-19 infections. We present a counterexample that disproves this finding.
Revised: Zhang et al. (2020) reported that mandating face coverings in public is necessary to decrease the rate of new COVID-19 . We show using differential questions from the SIR model and with a counterexample that disproves this finding.
Edit intent: meaning-changed
Original:  We agree with Zhang et al. that masks can be an important element in reducing virus transmission and that widespread use may be essential for returning to full activity. However, their analysis neglects the potential importance of physical distancing for limiting COVID-19 transmission by misattributing its effect to mask requirements. A full suite of epidemiological tools is necessary in these challenging times .
Revised:  We agree with Zhang et al. 's analysis that their method is flawed .
Edit intent: clarity
Original:  We show using differential equations from the SIR model and with an example from another location their analysis did not include that their analysis should not be considered sound evidence  .
Revised:  We show using differential equations from the SIR model and with an example from another location their analysis did not include that their analysis should not be considered sound evidence that mask mandates are sufficient to control or the primary factor controlling the spread of COVID-19 .
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Original: We analyse whether, and when, a large set of Google search data can be useful to increase euro area GDP nowcasting accuracy once we control for information contained in official variables. To deal with these data we propose an estimator that combines variable pre-selection and Ridge regularization and study its theoretical properties.
Revised: Alternative data sets are nowadays widely used for macroeconomic nowcasting together with new Machine Learning-based tools which often are applied without having a complete picture of their theoretical nowcasting properties. Against this background, this paper proposes a theoretically-funded nowcasting methodology allowing to incorporate alternative Google Search Data (GSD) among the predictors and combining targeted preselection, Ridge regularization and study its theoretical properties.
Edit intent: meaning-changed
Original:  To deal with these data we propose an estimator that combines variable pre-selection and Ridge regularization and study its theoretical properties. We show that in a period of cyclical stability Google data convey useful information for real-time nowcasting of GDP growth at the beginning of the quarter when macroeconomic information is lacking. On the other hand, in periods that exhibit a sudden downward shift in GDP growth rate , including Google search data in the information set improves nowcasting accuracyeven when official macroeconomic information is available .
Revised:  To deal with these data we propose an estimator that combines variable pre-selection and Ridge regularization and Generalized Cross Validation. Breaking with most of the existing literature that focuses on asymptotic in-sample theoretical properties, we establish the theoretical out-of-sample properties of our methodology, that are supported by Monte-Carlo simulations. We apply our methodology to GSD in order to nowcast GDP growth rate , including Google search data in the information set improves nowcasting accuracyeven when official macroeconomic information is available .
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Original:  On the other hand, in periods that exhibit a sudden downward shift in GDP growth rate , including Google search data in the information set improves nowcasting accuracyeven when official macroeconomic information is available .
Revised:  On the other hand, in periods that exhibit a sudden downward shift in GDP growth rate of different countries during various economic periods. Our empirical findings support the idea that GSD tend to increase nowcasting accuracy, even after controlling for official variables, but that the gain differs between periods of recessions and of macroeconomic stability .
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Original:  We test the robustness of the relaxation parameters on the second order multirate method in 2D. DNWR is shown to be very robust and consistently yielding fast convergence rates, whereas NNWR is slower or even diverges.
Revised:  We test the robustness of the relaxation parameters on the second order multirate method in 2D. DNWR is shown to be very robust and consistently yielding fast convergence rates, whereas the closely related Neumann-Neumann Waveform relaxtion (NNWR) method is slower or even diverges.
Edit intent: meaning-changed
Original: Electrical energy storage is considered essential for the future energy system to solve the intermittency problems caused by renewable energy sources such as wind and solar power . Among all the energy storage technologies, battery systems may provide flexibility  in a more distributed and decentralized way.
Revised: Electrical energy storage is considered essential for the future energy systems . Among all the energy storage technologies, battery systems may provide flexibility in a more distributed and decentralized way.
Edit intent: coherence
Original: Electrical energy storage is considered essential for the future energy system to solve the intermittency problems caused by renewable energy sources such as wind and solar power . Among all the energy storage technologies, battery systems may provide flexibility  in a more distributed and decentralized way.
Revised: Electrical energy storage is considered essential for the future energy system to solve the intermittency problems caused by renewable energy sources such as wind and solar power . Among all the energy storage technologies, battery systems may provide flexibility to the power grid in a more distributed and decentralized way.
Edit intent: clarity
Original:  In this study, the market designs of both wholesale markets and ancillary services in Spain are introduced, and the barriers to grid-connected battery storage are investigated under its specific market and regulatory framework.
Revised:  In this work, using the Spanish electricity market as an example, the market designs of both wholesale markets and ancillary services in Spain are introduced, and the barriers to grid-connected battery storage are investigated under its specific market and regulatory framework.
Edit intent: clarity
Original:  In this study, the market designs of both wholesale markets and ancillary services in Spain are introduced, and the barriers to grid-connected battery storage are investigated under its specific market and regulatory framework. Finally, the numerical and empirical analysis suggests that the high cycle cost for battery  is still the main barrier for grid-connected battery systems , and the flexibility offered by such systems would be currently the most promising comparative advantage for this novel technology.
Revised:  In this study, the market designs of both wholesale markets and ancillary services in Spain are introduced, and the barriers to grid-connected battery systems are investigated using utilization analysis. The concept of "potentially profitable utilization time" is proposed and introduced to identify and evaluate future potential grid applications for battery systems. The numerical and empirical analysis suggests that the high cycle cost for battery is still the main barrier for grid-connected battery systems , and the flexibility offered by such systems would be currently the most promising comparative advantage for this novel technology.
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Original:  Finally, the numerical and empirical analysis suggests that the high cycle cost for battery  is still the main barrier for grid-connected battery systems , and the flexibility offered by such systems would be currently the most promising comparative advantage for this novel technology.
Revised:  Finally, the numerical and empirical analysis suggests that the high cycle cost for battery systems is still the main barrier for grid-connected battery systems , and the flexibility offered by such systems would be currently the most promising comparative advantage for this novel technology.
Edit intent: fluency
Original:  Finally, the numerical and empirical analysis suggests that the high cycle cost for battery  is still the main barrier for grid-connected battery systems , and the flexibility offered by such systems would be currently the most promising comparative advantage for this novel technology. Additionally, a correct recognition of the barriers and advantages by all the stakeholders, including the system /  market operator, policy maker, investor, and project manager, is the key factor to promote battery storage technologies in grid-connected applications.
Revised:  Finally, the numerical and empirical analysis suggests that the high cycle cost for battery is still the main barrier for grid-connected battery systems . In Spain, for energy arbitrage within the day-ahead market, it is required that the battery wear cost decreases to 15 Euro / market operator, policy maker, investor, and project manager, is the key factor to promote battery storage technologies in grid-connected applications.
Edit intent: meaning-changed
Original:  Additionally, a correct recognition of the barriers and advantages by all the stakeholders, including the system /  market operator, policy maker, investor, and project manager, is the key factor to promote battery storage technologies in grid-connected applications.
Revised:  Additionally, a correct recognition of the barriers and advantages by all the stakeholders, including the system / MWh to make the potentially profitable utilization rate higher than 20\%. Nevertheless, the potentially profitable utilization of batteries is much higher in the applications when higher flexibility is demanded. The minimum required battery wear cost corresponding to 20\% potentially profitable utilization time increases to 35 Euro/MWh for energy arbitrage within the day-ahead market and ancillary services, and 50 Euro/MWh for upward secondary reserve. The results of this study contribute to the awareness of battery storage technology and its flexibility in grid applications. The findings also have significant implications for policy makers and market operator, policy maker, investor, and project manager, is the key factor to promote battery storage technologies in grid-connected applications.
Edit intent: meaning-changed
Original:  Additionally, a correct recognition of the barriers and advantages by all the stakeholders, including the system /  market operator, policy maker, investor, and project manager, is the key factor to promote battery storage technologies in grid-connected applications. For market and system regulators, more efforts are necessary to reduce the barriers from regulatory framework, promote pilot projects, and design appropriate market products or services that adequately address the flexibility provided by different technologies .
Revised:  Additionally, a correct recognition of the barriers and advantages by all the stakeholders, including the system / market operators interested in promoting grid-connected battery storage under a deregulated power market .
Edit intent: clarity
Original: The geodesic active contour model (GAC) is a commonly used segmentation model for medical image segmentation. The level set method (LSM) is the most popular approach for solving the model , via implicitly representing the contour by a level set function.
Revised: Active contour models have been widely used in image segmentation, and the level set method (LSM) is the most popular approach for solving the model , via implicitly representing the contour by a level set function.
Edit intent: clarity
Original:  In this paper, we use characteristic functions to implicitly approximate the contours, propose a new representation to the GAC and derive an efficient algorithm termed as the iterative convolution-thresholding method (ICTM).
Revised:  In this paper, we use characteristic functions to implicitly represent the contours, propose a new representation to the GAC and derive an efficient algorithm termed as the iterative convolution-thresholding method (ICTM).
Edit intent: clarity
Original:  In this paper, we use characteristic functions to implicitly approximate the contours, propose a new representation to the GAC and derive an efficient algorithm termed as the iterative convolution-thresholding method (ICTM).
Revised:  In this paper, we use characteristic functions to implicitly approximate the contours, propose a new representation to the geodesic active contours and derive an efficient algorithm termed as the iterative convolution-thresholding method (ICTM).
Edit intent: meaning-changed
Original:  Extensive experiments, on 2D synthetic, 2D ultrasound, 3D CT, and 3D MR images for URLan and lesion segmentation, demonstrate that the ICTM not only obtains comparable or even better segmentation results (compared to the LSM) but also achieves dozens or hundreds of times acceleration.
Revised:  Extensive experiments, on 2D synthetic, 2D ultrasound, 3D CT, and 3D MR images for URLan and lesion segmentation, demonstrate that the proposed method not only obtains comparable or even better segmentation results (compared to the LSM) but also achieves dozens or hundreds of times acceleration.
Edit intent: clarity
Original:  Extensive experiments, on 2D synthetic, 2D ultrasound, 3D CT, and 3D MR images for URLan and lesion segmentation, demonstrate that the ICTM not only obtains comparable or even better segmentation results (compared to the LSM) but also achieves dozens or hundreds of times acceleration.
Revised:  Extensive experiments, on 2D synthetic, 2D ultrasound, 3D CT, and 3D MR images for URLan and lesion segmentation, demonstrate that the ICTM not only obtains comparable or even better segmentation results (compared to the LSM) but also achieves significant acceleration.
Edit intent: clarity
Original:  Our focus here is on partial recovery , i.e., we look for a one-to-one mapping which is correct on a fraction of the nodes of the graph rather than on all of them, and we assume that the two input graphs to the problem are correlated Erd\"os-R\'enyi graphs of parameters (n,q,s).
Revised:  Our focus here is on partial recovery , i.e., we look for a one-to-one mapping which is correct on a fraction of the nodes of the graph rather than on all of them, and we assume that the two input graphs to the problem are correlated Erd\"os-R\'enyi graphs of parameters (n,q,s).
Edit intent: fluency
Original:  We have developed a novel and comprehensive knowledge discovery framework, COVID-KG, which leverages novel semantic representation and external ontologies to represent text and images in the input literature data, and then performs various extraction components to  extract fine-grained multimedia knowledge elements (entities, relations and events)  .
Revised:  We have developed a novel and comprehensive knowledge discovery framework, COVID-KG extract fine-grained multimedia knowledge elements (entities, relations and events) .
Edit intent: coherence