wanyu/IteraTeR_full_sent huggingface dataset:
Original:  By varying p_c from p_c^*, we find that a plot of saturated learning gain degree {\cal L}_g^* versus p_c forms a bell-shaped curve with a peak at p_c^* (where the diversity degree in firing of GR cells is also maximum).
Revised:  By varying p_c from p_c^*, we find that a plot of saturated learning gain degree {\cal L}_g^* versus p_c forms a bell-shaped curve with a peak at p_c^* (where the diversity degree in spiking patterns of GR cells is also maximum).
Edit intent: clarity
Original: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 294,000 cases as of March 22nd 2020.
Revised: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 2.5 million confirmed cases as of March 22nd 2020.
Edit intent: meaning-changed
Original: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 294,000 cases as of March 22nd 2020.
Revised: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 294,000 cases as of April 23, 2020.
Edit intent: meaning-changed
Original:  In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis at different scales including molecular, medical and epidemiological applications.
Revised:  In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis at different scales including molecular, clinical, and societal applications.
Edit intent: meaning-changed
Original:  We finish with a discussion of promising future directions of research and the tools and resources needed to facilitate AI research  .
Revised:  We finish with a discussion of promising future directions of research and the tools and resources needed to facilitate AI research . Finally, we discuss strategic considerations related to the operational implementation of projects, multidisciplinary partnerships, and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics .
Edit intent: meaning-changed
Original: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 2.5 million confirmed cases as of April 23 , 2020.
Revised: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of April 23 , 2020.
Edit intent: meaning-changed
Original: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 2.5 million confirmed cases as of April 23 , 2020.
Revised: COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, with over 2.5 million confirmed cases as of August 5 , 2020.
Edit intent: meaning-changed
Original:  In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis  at different scales including molecular, clinical, and societal applications .
Revised:  In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis . We have identified applications that address challenges posed by COVID-19 at different scales including molecular, clinical, and societal applications .
Edit intent: meaning-changed
Original:  In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis  at different scales including molecular, clinical, and societal applications .
Revised:  In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis at different scales , including: molecular, by identifying new or existing drugs for treatment; clinical, by supporting diagnosis and evaluating prognosis based on medical imaging and non-invasive measures; and societal, by tracking both the epidemic and the accompanying infodemic using multiple data sources .
Edit intent: meaning-changed
Original: Since the inception of cryptocurrencies, an increasing number of financial institutions are getting involved in cryptocurrency trading.
Revised: Since the inception of cryptocurrencies, an increasing number of financial institutions including cryptocurrencies in their portfolios has accelerated. Cryptocurrencies are the first pure digital assets to be included by asset managers. Even though they share some commonalities with more traditional assets, they have a separate nature of its own and their behaviour as an asset is still under the process of being understood.
Edit intent: clarity
Original:  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 118 research papers on various aspects of cryptocurrency trading ( e.g. , cryptocurrency trading systems, bubble and extreme condition, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).
Revised:  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 126 research papers on various aspects of cryptocurrency trading ( e.g. , cryptocurrency trading systems, bubble and extreme condition, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).
Edit intent: meaning-changed
Original:  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 118 research papers on various aspects of cryptocurrency trading ( e.g. , cryptocurrency trading systems, bubble and extreme condition, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).
Revised:  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 118 research papers on various aspects of cryptocurrency trading ( eg. , cryptocurrency trading systems, bubble and extreme condition, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).
Edit intent: fluency
Original:  It is shown how social measures such as distancing, regional lock-downs , quarantine and global public health vigilance, influence the model parameters, which can eventually change the mortality rates and active contaminated cases over time, in the real world.
Revised:  It is shown how social measures such as distancing, regional lockdowns , quarantine and global public health vigilance, influence the model parameters, which can eventually change the mortality rates and active contaminated cases over time, in the real world.
Edit intent: fluency
Original:  Despite lots of known results in the field of submodular maximization, surprisingly, it remains unknown whether or not this problem enjoys the well-known tight (1 - 1 / e )-approximation .
Revised:  Despite lots of known results in the field of submodular maximization, surprisingly, it remains unknown whether or not this problem enjoys the well-known tight (1 - 1 / e-\epsilon )-approximation .
Edit intent: meaning-changed
Original:  Despite lots of known results in the field of submodular maximization, surprisingly, it remains unknown whether or not this problem enjoys the well-known tight (1 - 1 / e )-approximation .
Revised:  Despite lots of known results in the field of submodular maximization, surprisingly, it remains unknown whether or not this problem enjoys the well-known tight (1 - 1 / e )-approximation randomized algorithm for SMKP. Their algorithm is based on the continuous greedy technique which inherently involves randomness. However, the deterministic algorithm of this problem has not been understood very well previously.
Edit intent: meaning-changed
Original:  We can further boost the approximation ratio to (1 - 1 / e - \epsilon ) with the help of continuous greedy technique, which gives a tight randomized approximation algorithm for this case .
Revised:  We can further boost the approximation ratio to (1 - 1 / e-\epsilon randomized algorithm for the general case, thus achieving the same result as Fairstein et al. (ESA20) .
Edit intent: meaning-changed
Original:  We first considered the case when the number of bins is a constant . Previously a randomized approximation algorithm can obtain approximation ratio (1 - 1/e-\epsilon)  based on the involved continuous greedy technique.
Revised:  We first consider the case when the number of bins is a constant . Previously a randomized approximation algorithm can obtain approximation ratio (1 - 1/e-\epsilon) based on the involved continuous greedy technique.
Edit intent: fluency
Original:  We first considered the case when the number of bins is a constant . Previously a randomized approximation algorithm can obtain approximation ratio (1 - 1/e-\epsilon)  based on the involved continuous greedy technique.
Revised:  We first considered the case when the number of bins is a constant and provide a simple combinatorial deterministic algorithm with an optimal (1-1/e) ratio. Previously, a randomized approximation algorithm can obtain approximation ratio (1 - 1/e-\epsilon) based on the involved continuous greedy technique.
Edit intent: meaning-changed
Original:  We first considered the case when the number of bins is a constant . Previously a randomized approximation algorithm can obtain approximation ratio (1 - 1/e-\epsilon)  based on the involved continuous greedy technique.
Revised:  We first considered the case when the number of bins is a constant . Previously a randomized approximation algorithm obtained a (1 - 1/e-\epsilon) based on the involved continuous greedy technique.
Edit intent: clarity
Original:  We first considered the case when the number of bins is a constant . Previously a randomized approximation algorithm can obtain approximation ratio (1 - 1/e-\epsilon)  based on the involved continuous greedy technique.
Revised:  We first considered the case when the number of bins is a constant . Previously a randomized approximation algorithm can obtain approximation ratio (1 - 1/e-\epsilon) approximation ratio based on the involved continuous greedy technique.
Edit intent: meaning-changed
Original:  We first consider the case when the number of bins is a constant and provide a simple combinatorial deterministic algorithm with an optimal (1-1/ e) ratio. Previously, a randomized approximation algorithm obtained a (1 - 1/ e-\epsilon) approximation ratio based on the involved continuous greedy technique.
Revised:  We first consider the case when the number of bins is a constant and provide a simple combinatorial deterministic algorithm with an optimal (1-1/ e-\epsilon) approximation ratio based on the involved continuous greedy technique.
Edit intent: coherence
Original:  Previously, a randomized approximation algorithm obtained a (1 - 1/ e-\epsilon) approximation ratio based on the involved continuous greedy technique. We then generalize the result to arbitrary number of bins. When the capacity of bins are identical, we design a combinatorial and deterministic algorithm which achieves an almost tight approximation ratio (1 - 1 / e-\epsilon). In the general case, we provide a (1/2-\epsilon)-approximation algorithm which is also combinatorial and deterministic . We finally boost this algorithmto a (1-1/e-\epsilon) randomized algorithm for the general case, thus matching the result of Fairstein et al. 13 .
Revised:  Previously, a randomized approximation algorithm obtained a (1 - 1/ e-\epsilon) 13 .
Edit intent: coherence
Original:  We finally boost this algorithmto a (1-1/e-\epsilon) randomized algorithm for the general case, thus matching the result of Fairstein et al. 13 .
Revised:  We finally boost this algorithmto a (1-1/e-\epsilon) randomized algorithm for the general case, thus matching the result of Fairstein et al. deterministic algorithm for SMKP. Our algorithm is based on reducing SMKP to an exponential-size submodular maximizaion problem over a special partition matroid which enjoys a tight deterministic algorithm. We develop several techniques to mimic the algorithm, leading to a tight deterministic approximation for SMKP .
Edit intent: meaning-changed
Original:  We  hope this dataset can help researchers around the world better understand the spread dynamics of COVID-19 at a regional level, to inform intervention and mitigation strategies for policymakers.
Revised:  We cross validate the dataset and the estimate error rate is about 0.04\%. We then give several examples to show how to trace the spreading in particular cities or provinces, and also contrast the development of COVID-19 in all cities in China at the early, middle and late stages. We hope this dataset can help researchers around the world better understand the spread dynamics of COVID-19 at a regional level, to inform intervention and mitigation strategies for policymakers.
Edit intent: meaning-changed
Original: We  employ a spin S = 1/2 Ising-like model and a  Fermi-Dirac-like function to describe the spread of Covid-19.
Revised: We revisit well-established concepts of epidemiology, the Ising-model, and percolation theory. Also, we employ a spin S = 1/2 Ising-like model and a Fermi-Dirac-like function to describe the spread of Covid-19.
Edit intent: meaning-changed
Original:  Our analysis , using the available official infections rate data reveals: i ) that the epidemic curves , i.e., the number of reported cases versus time, is well-described by a Gaussian function; ii ) that the temporal evolution of the cumulative number of infected people follows a distorted Fermi-Dirac-like distribution function;
Revised:  Our analysis , using the available official infections rate data reveals: i ) that the epidemic curves can be described by a Gaussian-type function; ) that the temporal evolution of the cumulative number of infected people follows a distorted Fermi-Dirac-like distribution function;
Edit intent: clarity
Original:  ii ) that the temporal evolution of the cumulative number of infected people follows a distorted Fermi-Dirac-like distribution function; iii ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an interacting \emph{ parameter, which emulates the contact between infected and non-infected people.
Revised:  ii ) that the temporal evolution of the cumulative number of infected people follows a distorted Fermi-Dirac-like function; ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an interacting \emph{ parameter, which emulates the contact between infected and non-infected people.
Edit intent: clarity
Original:  iii ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an interacting \emph{ parameter, which emulates the contact between infected and non-infected people.
Revised:  iiiiii ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an interacting \emph{ parameter, which emulates the contact between infected and non-infected people.
Edit intent: fluency
Original:  iii ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an interacting \emph{ parameter, which emulates the contact between infected and non-infected people.
Revised:  iii ) the key role played by the quarantine to block the spread of Covid-19 in terms of an interacting \emph{ parameter, which emulates the contact between infected and non-infected people.
Edit intent: clarity
Original:  iii ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an interacting \emph{ parameter, which emulates the contact between infected and non-infected people.
Revised:  iii ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an \emph{ parameter, which emulates the contact between infected and non-infected people.
Edit intent: clarity
Original:  iii ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an interacting \emph{ parameter, which emulates the contact between infected and non-infected people.
Revised:  iii ) the key role played by the quarantine in the prevention of the spread of Covid-19 in terms of an interacting \emph{interacting parameter, which emulates the contact between infected and non-infected people.
Edit intent: meaning-changed
Original:  An analysis of the epidemic curves for Ebola, SARS, and Influenza A/H1N1 is also presented and described by a Gaussian function as well. Our findings demonstrate the universal character of\emph{ \emph{  well-established concepts in condensed matter Physics and their applications in different areas .
Revised:  Furthermore, in the frame of elementary percolation theory, we show that:\emph{ \emph{ well-established concepts in condensed matter Physics and their applications in different areas .
Edit intent: meaning-changed
Original:  Our findings demonstrate the universal character of\emph{ \emph{  well-established concepts in condensed matter Physics and their applications in different areas .
Revised:  Our findings demonstrate the universal character of\emph{ \emph{ ) the concepts of blocked and non-blocked connections can be associated, respectively, with a person respecting or not the social distancing, impacting thus in the probability of an infected person to infect other people. Increasing the number of infected people leads to an increase in the number of net connections, giving rise thus to a higher probability of new infections (percolation). We demonstrate the importance of social distancing in preventing the spread of Covid-19 in a pedagogical way. Given the impossibility of making a precise forecast of the disease spread, we highlight the importance of taking into account additional factors, such as climate changes and urbanization, in the mathematical description of epidemics. Yet, we make a connection between the standard mathematical models employed in epidemics and well-established concepts in condensed matter Physics and their applications in different areas .
Edit intent: meaning-changed
Original: Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on  high-streets.
Revised: Autonomous vehicles (AVs) must share space with pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on high-streets.
Edit intent: clarity
Original: Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on  high-streets.
Revised: Autonomous vehicles (AVs) must share space with human pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on high-streets.
Edit intent: meaning-changed
Original: Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on  high-streets.
Revised: Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on high-streets.
Edit intent: clarity
Original: Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on  high-streets.
Revised: Autonomous vehicles (AVs) must share space with human pedestrians, both in on-road cases such as cars at pedestrian crossings and off-road cases such as delivery vehicles navigating through crowds on pedestrianized high-streets.
Edit intent: clarity
Original:  This narrative review article is Part II of a pair which together survey the current technology stack involved in this URLanising recent research into a hierarchical taxonomy ranging from low level image detection to high-level psychological models, from the perspective of an AV designer.
Revised:  This narrative review article is Part II of a pair , together surveying the current technology stack involved in this URLanising recent research into a hierarchical taxonomy ranging from low level image detection to high-level psychological models, from the perspective of an AV designer.
Edit intent: clarity
Original:  This narrative review article is Part II of a pair which together survey the current technology stack involved in this URLanising recent research into a hierarchical taxonomy ranging from low level image detection to high-level psychological models, from the perspective of an AV designer.
Revised:  This narrative review article is Part II of a pair which together survey the current technology stack involved in this URLanising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychological models, from the perspective of an AV designer.
Edit intent: fluency
Original:  This self-contained Part II covers the higher levels of this stack, consisting of models of pedestrian behaviour, from prediction of individual pedestrians' likely destinations and paths, to game theoretic models of interactions between pedestrians and autonomous vehicles.
Revised:  This self-contained Part II covers the higher levels of this stack, consisting of models of pedestrian behaviour, from prediction of individual pedestrians' likely destinations and paths, to game-theoretic models of interactions between pedestrians and autonomous vehicles.
Edit intent: fluency
Original:  This survey clearly shows that, although there are good models for optimal walking behaviour, high-level psychological and social modelling of pedestrian behaviour still remains an open research question that requires many conceptual issues to be clarified by the community. At these levels, early work has been done on descriptive and qualitative models of behaviour, but much work is still needed to translate them into quantitative algorithms for practical AV control.
Revised:  This survey clearly shows that, although there are good models for optimal walking behaviour, high-level psychological and social modelling of pedestrian behaviour still remains an open research question that requires many conceptual issues to be clarified . Early work has been done on descriptive and qualitative models of behaviour, but much work is still needed to translate them into quantitative algorithms for practical AV control.
Edit intent: clarity
Original:  On the contrary, such problems have been pivotal in obtaining completeness results for PPAD and PPA, for several important problems, such as finding a Nash equilibrium [Daskalakis et al., 2009, Chen et al., 2009b] and  Necklace Splitting with 2 thieves [Filos-Ratsikas and Goldberg, 2019].
Revised:  On the contrary, topological problems have been pivotal in obtaining completeness results for PPAD and PPA, for several important problems, such as finding a Nash equilibrium [Daskalakis et al., 2009, Chen et al., 2009b] and Necklace Splitting with 2 thieves [Filos-Ratsikas and Goldberg, 2019].
Edit intent: meaning-changed