wanyu/IteraTeR_full_sent huggingface dataset:
Original:  These works have the potential to deepen our understanding of the inner mechanisms of human perception and to improve machine learning. Drawing robust conclusions from comparison studies, however, turns out to be difficult. Here, we highlight common shortcomings that can easily lead to fragile conclusions. First, if a model does achieve high performance on a task similar to humans, its decision-making process is not necessarily human-like. Moreover, further analyses can reveal differences. Second, the performance of neural networks is sensitive to training procedures and architectural details. Thus, generalizing conclusions from specific architectures is difficult. Finally, when comparing humans and machines, equivalent experimental settings are crucial in order to identify innate differences. Addressing these shortcomings alters or refines the conclusions of studies. We show that , despite their ability to solve closed-contour tasks, our neural networks use different decision-making strategies than humans. We further show that there is no fundamental difference between same-different and spatial tasks for common feed-forward neural networks and finally, that neural networks do experience a "recognition gap" on minimal recognizable images. All in all, care has to be taken to not impose our human systematic bias when comparing human and machine perception .
Revised:  These studies are an exciting chance to learn about one system by studying the other. Here, we propose ideas on how to design, conduct and interpret experiments such that they adequately support the investigation of mechanisms when comparing human and machine perception. We demonstrate and apply these ideas through three case studies. The first case study shows how human bias can affect how we interpret results, and that several analytic tools can help to overcome this human reference point. In the second case study, we highlight the difference between necessary and sufficient mechanisms in visual reasoning tasks. Thereby, we show that contrary to previous suggestions, feedback mechanisms might not be necessary for the tasks in question. The third case study highlights the importance of aligning experimental conditions. We find that a previously-observed difference in object recognition does not hold when adapting the experiment to make conditions more equitable between humans and machines. In presenting a checklist for comparative studies of visual reasoning in humans and machines, we hope to highlight how to overcome potential pitfalls in design or inference .
Edit intent: coherence
Original:  While the resulting sampling design is sometimes described as akin to  locally randomized experiment in a neighborhood of the threshold, standard formal analyses do not make reference to probabilistic treatment assignment and instead identify treatment effects via continuity arguments.
Revised:  While the resulting sampling design is sometimes described as akin to a locally randomized experiment in a neighborhood of the threshold, standard formal analyses do not make reference to probabilistic treatment assignment and instead identify treatment effects via continuity arguments.
Edit intent: fluency
Original:  Under an assumption that the measurement error is exogenous, we show how to consistently estimate causal effects using a class  linear estimators that weight treated and control units so as to balance a latent variable of which the running variable is a noisy measure.
Revised:  Under an assumption that the measurement error is exogenous, we show how to consistently estimate causal effects using a class of linear estimators that weight treated and control units so as to balance a latent variable of which the running variable is a noisy measure.
Edit intent: fluency
Original: When effective medical treatment and vaccination are not available, non-pharmaceutical interventions such as social distancing, home quarantine and far-reaching shutdown of public life are the only available strategies to prevent the spreading of epidemics.
Revised: When effective medical treatment and vaccination are not available, non-pharmaceutical interventions such as social distancing, home quarantine and far-reaching shutdown of public life are the only available strategies to prevent the spread of epidemics.
Edit intent: fluency
Original:  Based on an extended SEIR model and continuous-time optimal control theory, in this paper the optimal non-pharmaceutical intervention strategy is presented for the case that a vaccine is never found  .
Revised:  Based on an extended SEIR model and continuous-time optimal control theory, in this paper the optimal non-pharmaceutical intervention strategy is presented for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible .
Edit intent: meaning-changed
Original:  In this case, the optimal control must meet two competing requirements: First, the minimization of disease-related deaths, and, second, the establishment of a sufficient degree of herd immunity at the end of the measures, in order to exclude a second wave.
Revised:  In this case, the optimal control must meet competing requirements: First, the minimization of disease-related deaths, and, second, the establishment of a sufficient degree of herd immunity at the end of the measures, in order to exclude a second wave.
Edit intent: clarity
Original:  In this case, the optimal control must meet two competing requirements: First, the minimization of disease-related deaths, and, second, the establishment of a sufficient degree of herd immunity at the end of the measures, in order to exclude a second wave.
Revised:  In this case, the optimal control must meet two competing requirements: First, the minimization of disease-related deaths, and, second, the establishment of a sufficient degree of natural immunity at the end of the measures, in order to exclude a second wave.
Edit intent: clarity
Original:  The characteristic time course of the computed optimal control is the following: After an intense but short initial lockdown, a dynamical equilibrium is enforced during which the number of actively infected is held on a constant level for a longer period of time. At the same time, the measures can be gradually relaxed with an ever increasing speed. Two simple rules for the optimal control of the effective reproduction number are presented, see Eqs. (13)-(14), which ensure a stable route out of the initial lockdown.
Revised:  Careful analysis of the resulting evolution of the time-dependent effective reproduction number are presented, see Eqs. (13)-(14), which ensure a stable route out of the initial lockdown.
Edit intent: clarity
Original:  Two simple rules for the optimal control of the effective reproduction number are presented, see Eqs. (13)-(14), which ensure a stable route out of the initial lockdown. The rules are directly applicable in practice, as they only depend on a precise knowledge of the cumulative number of cases and a reliable estimate of the effective reproduction number. The obtained results could serve as a guideline for the implementation and gradual relaxation of non-pharmaceutical intervention measures also in other scenarios, e.g., when the development of a vaccine is expected soon .
Revised:  Two simple rules for the optimal control of the effective reproduction number reveals, however, that the obtained solution is in fact a tightrope walk close to the stability boundary of the system, where socio-economic costs and the risk of a new outbreak must be constantly balanced against one another .
Edit intent: coherence
Original:  Based on an extended SEIR  model and continuous-time optimal control theory, in this paper the optimal non-pharmaceutical intervention strategy is presented for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible.
Revised:  Based on an extended SEIR (susceptible-exposed-infectious-recovered) model and continuous-time optimal control theory, in this paper the optimal non-pharmaceutical intervention strategy is presented for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible.
Edit intent: meaning-changed
Original:  Based on an extended SEIR  model and continuous-time optimal control theory, in this paper the optimal non-pharmaceutical intervention strategy is presented for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible.
Revised:  Based on an extended SEIR model and continuous-time optimal control theory, we compute the optimal non-pharmaceutical intervention strategy is presented for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible.
Edit intent: clarity
Original:  Based on an extended SEIR  model and continuous-time optimal control theory, in this paper the optimal non-pharmaceutical intervention strategy is presented for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible.
Revised:  Based on an extended SEIR model and continuous-time optimal control theory, in this paper the optimal non-pharmaceutical intervention strategy for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible.
Edit intent: clarity
Original:  Careful analysis of the resulting evolution of the time-dependent effective reproduction number reveals, however, that the obtained solution is in fact a tightrope walk close to the stability boundary of the system, where socio-economic costs and the risk of a new outbreak must be constantly balanced against one another.
Revised:  Careful analysis of the computed control strategy reveals, however, that the obtained solution is in fact a tightrope walk close to the stability boundary of the system, where socio-economic costs and the risk of a new outbreak must be constantly balanced against one another.
Edit intent: clarity
Original: 3M English tweets about COVID-19 and provide early evidence of the use of bots to promote political conspiracies in the US, but also as a tool to enable participatory activism to surface information that could otherwise be censored in China .
Revised: 3M English tweets about COVID-19 and provide early evidence of the use of bots to promote political conspiracies in the United States, in stark contrast with humans who focus on public health concerns .
Edit intent: meaning-changed
Original:  Considering the mode of spread and the level of severityof this disease , it is extremely important to make people aware of various safety precautions such as using sanitizers and masks and maintaining social distancing , that are to be followed to prevent the disease and break the chain of spread .
Revised:  Considering the mode of spread and severity , it is extremely important to make people aware of various safety precautions such as using sanitizers and masks and maintaining social distancing , that are to be followed to prevent the disease and break the chain of spread .
Edit intent: clarity
Original:  Considering the mode of spread and the level of severityof this disease , it is extremely important to make people aware of various safety precautions such as using sanitizers and masks and maintaining social distancing , that are to be followed to prevent the disease and break the chain of spread .
Revised:  Considering the mode of spread and the level of severityof this disease , it is essential to make it a habit to follow various safety precautions such as using sanitizers and masks and maintaining social distancing , that are to be followed to prevent the disease and break the chain of spread .
Edit intent: clarity
Original:  Considering the mode of spread and the level of severityof this disease , it is extremely important to make people aware of various safety precautions such as using sanitizers and masks and maintaining social distancing , that are to be followed to prevent the disease and break the chain of spread . This mode of educating individuals about the disease is being widely carried out as announcements through online or physical awareness campaigns, advertisements in the media and so on.
Revised:  Considering the mode of spread and the level of severityof this disease , it is extremely important to make people aware of various safety precautions such as using sanitizers and masks and maintaining social distancing to prevent the spread of Covid-19. Individuals are widely educated about the safety measures against the disease through various modes such as announcements through online or physical awareness campaigns, advertisements in the media and so on.
Edit intent: clarity
Original:  Hence, we propose a 2D survival based game, SurviveCovid-19, aimed to educate people about safety precautions to be taken for Covid-19 outside their homes , by incorporating social distancing and usage of masks and sanitizers in the game.
Revised:  Hence, we propose a 2D survival-based game, SurviveCovid-19, aimed to educate people about safety precautions to be taken for Covid-19 outside their homes , by incorporating social distancing and usage of masks and sanitizers in the game.
Edit intent: fluency
Original:  Hence, we propose a 2D survival based game, SurviveCovid-19, aimed to educate people about safety precautions to be taken for Covid-19 outside their homes , by incorporating social distancing and usage of masks and sanitizers in the game.
Revised:  Hence, we propose a 2D survival based game, SurviveCovid-19, aimed to educate people about safety precautions to be taken for Covid-19 outside their homes by incorporating social distancing and usage of masks and sanitizers in the game.
Edit intent: fluency
Original:  SurviveCovid-19 has been designed as an Android based mobile game and has been evaluated through a remote qualitative user survey, with 20 volunteers . The results of the survey are promising with all the questions of survey having mean value greater than 3.6 .
Revised:  SurviveCovid-19 has been designed as an Android based mobile game and has been evaluated through a remote qualitative user survey, with 30 volunteers using the questionnaire based on the MEEGA+ model. The survey results are promising, with all the questions of survey having mean value greater than 3.6 .
Edit intent: meaning-changed
Original: This paper proposes a new nonparametric mixed data sampling (MIDAS) model and develops a framework to infer clusters in a panel dataset of mixed sampling frequencies. The nonparametric MIDAS estimation method is more flexible but substantially less costly to estimate than existing approaches.
Revised: This paper proposes a new nonparametric mixed data sampling (MIDAS) model and develops a framework to infer clusters in a panel regression with mixed frequency data. The linearized MIDAS estimation method is more flexible but substantially less costly to estimate than existing approaches.
Edit intent: meaning-changed
Original:  The nonparametric MIDAS estimation method is more flexible but substantially less costly to estimate than existing approaches. The proposed clustering algorithm successfully recovers true membership in the cross-section  both in theory and in simulations  without requiring prior knowledge such as the number of clusters.
Revised:  The nonparametric MIDAS estimation method is more flexible and substantially simpler to implement than competing approaches. We show that the proposed clustering algorithm successfully recovers true membership in the cross-section both in theory and in simulations without requiring prior knowledge such as the number of clusters.
Edit intent: clarity
Original:  This methodology is applied to estimate a mixed-frequency Okun's law model for the state-level data in the U.S. and uncovers four  clusters based on the dynamic features of  labor markets.
Revised:  This methodology is applied to estimate a mixed-frequency Okun's law model for state-level data in the U.S. and uncovers four clusters based on the dynamic features of labor markets.
Edit intent: fluency
Original:  This methodology is applied to estimate a mixed-frequency Okun's law model for the state-level data in the U.S. and uncovers four  clusters based on the dynamic features of  labor markets.
Revised:  This methodology is applied to estimate a mixed-frequency Okun's law model for the state-level data in the U.S. and uncovers four meaningful clusters based on the dynamic features of labor markets.
Edit intent: meaning-changed
Original:  This methodology is applied to estimate a mixed-frequency Okun's law model for the state-level data in the U.S. and uncovers four  clusters based on the dynamic features of  labor markets.
Revised:  This methodology is applied to estimate a mixed-frequency Okun's law model for the state-level data in the U.S. and uncovers four clusters based on the dynamic features of state-level labor markets.
Edit intent: fluency
Original:  Unlike most existing strategies that rely on performance maximization in downstream tasks , here we propose a principled method for the identification of an optimal dimension such that all structural information of a network is parsimoniously encoded.
Revised:  Existing strategies for the selection of the embedding dimension rely on performance maximization in downstream tasks , here we propose a principled method for the identification of an optimal dimension such that all structural information of a network is parsimoniously encoded.
Edit intent: meaning-changed
Original:  Unlike most existing strategies that rely on performance maximization in downstream tasks , here we propose a principled method for the identification of an optimal dimension such that all structural information of a network is parsimoniously encoded.
Revised:  Unlike most existing strategies that rely on performance maximization in downstream tasks . Here, we propose a principled method for the identification of an optimal dimension such that all structural information of a network is parsimoniously encoded.
Edit intent: fluency
Original: Successfully combating climate change will require substantial technological improvements in Low-Carbon Energy Technologies (LCETs) . An efficient allocation of R D budgets to accelerate technological advancement necessitates a better understanding of how LCETs rely on scientific knowledge.
Revised: Successfully combating climate change will require substantial technological improvements in Low-Carbon Energy Technologies (LCETs) , but designing efficient allocation of R D budgets to accelerate technological advancement necessitates a better understanding of how LCETs rely on scientific knowledge.
Edit intent: coherence
Original:  In this paper, we sketch for the first time the evolution of knowledge bases for key LCETs and show how technological interdependencies change in time. We use data covering almost all US patents as well as scientific articles published in the past two centuries to quantify the history of LCETs and their dependence on science.
Revised:  Using data covering almost all US patents as well as scientific articles published in the past two centuries to quantify the history of LCETs and their dependence on science.
Edit intent: coherence
Original:  We use data covering almost all US patents as well as scientific articles published in the past two centuries to quantify the history of LCETs and their dependence on science. We show how the drivers of low-carbon innovations shifted from Hydro and Wind energy  to Nuclear fission  , and more recently to Solar PV and back to Wind.
Revised:  We use data covering almost all US patents as well as scientific articles published in the past two centuries , we describe the evolution of knowledge bases of ten key LCETs and show how technological interdependencies have changed over time. The composition of low-carbon innovations shifted from Hydro and Wind energy to Nuclear fission , and more recently to Solar PV and back to Wind.
Edit intent: meaning-changed
Original:  Our analysis demonstrates that 1) LCETs rely increasingly on science, 2) Solar PVand Nuclear fusion depend heavily on science, while Hydro energy does not, 3) renewable and nuclear energy technologies rely on a strikingly different kind of science, and 4) there is a remarkable convergence of scientific knowledge bases of renewables over recent decades. These findings suggest a need for technology-specific research policies, although targeted research in renewables is likely to cross-fertilize a wider range of LCETs.
Revised:  In recent years, Solar PV, Nuclear fusion and Biofuels (including energy from waste) have 35-65
Edit intent: coherence
Original:  We use change point detection to partition a time series into locally stationary segments , then estimate the distributionsof each piece. The distributions are clustered into a learned number of discrete volatility regimes via an optimisation routine.
Revised:  We use change point detection to partition a time series into locally stationary segments and then compute a distance matrix between segment distributions. The segments are clustered into a learned number of discrete volatility regimes via an optimisation routine.
Edit intent: meaning-changed
Original:  Using this method, we investigate and determine a clustering structure for indices , large cap equitiesand exchange-traded funds .
Revised:  Using this method, we investigate and determine a clustering structure for indices , large cap equitiesand exchange-traded funds and currency pairs. Our method overcomes the rigid assumptions necessary to implement many parametric regime-switching models, while effectively distilling a time series into several characteristic behaviours. Our results provide significant simplification of these time series and a strong descriptive analysis of prior behaviours of volatility. This empirical analysis could be used with other regime-switching implementations, justifying the parametric structure encoded in any candidate model.
Edit intent: meaning-changed
Original:  our result is the first sub-linear time algorithm having the sample size {\em   independent of both the input number of points n and dimensionality d  . Furthermore, we observe that these two techniques can be generalized to deal with a broader range of geometric optimization problems with outliers in high dimensions, including flat fitting, k-center clustering, and SVM with outliers, and therefore achieve  sub-linear time bi-criteria approximation algorithms for these problems respectively.
Revised:  our result is the first sub-linear time algorithm , which has the sample size {\em independent of both the input number of points n and dimensionality d . Furthermore, we observe that these two techniques can be generalized to deal with a broader range of geometric optimization problems with outliers in high dimensions, including flat fitting, k-center clustering, and SVM with outliers, and therefore achieve sub-linear time bi-criteria approximation algorithms for these problems respectively.
Edit intent: coherence
Original:  our result is the first sub-linear time algorithm having the sample size {\em   independent of both the input number of points n and dimensionality d  . Furthermore, we observe that these two techniques can be generalized to deal with a broader range of geometric optimization problems with outliers in high dimensions, including flat fitting, k-center clustering, and SVM with outliers, and therefore achieve  sub-linear time bi-criteria approximation algorithms for these problems respectively.
Revised:  our result is the first sub-linear time algorithm having the sample size ({\em independent of both the input number of points n and dimensionality d . Furthermore, we observe that these two techniques can be generalized to deal with a broader range of geometric optimization problems with outliers in high dimensions, including flat fitting, k-center clustering, and SVM with outliers, and therefore achieve sub-linear time bi-criteria approximation algorithms for these problems respectively.
Edit intent: fluency