wanyu/IteraTeR_full_sent huggingface dataset:
Original:  By this we mean that, instead of listing all solutions , we list, in an efficient way, directly only the equivalence classes or  one representative per class . Besides the need to then provide ana priori relation of equivalence between solutions, we place ourselves in the special context where the problem to be addressed , either after some preliminary polynomial time dynamic programming computation or directly from the start, leads to a decomposable tropical circuit .
Revised:  By this we mean that, instead of listing all solutions , we list, in an efficient way, directly only the equivalence classes or of one representative per class . Besides the need to then provide ana priori relation of equivalence between solutions, we place ourselves in the special context where the problem to be addressed , either after some preliminary polynomial time dynamic programming computation or directly from the start, leads to a decomposable tropical circuit .
Edit intent: fluency
Original:  By this we mean that, instead of listing all solutions , we list, in an efficient way, directly only the equivalence classes or  one representative per class . Besides the need to then provide ana priori relation of equivalence between solutions, we place ourselves in the special context where the problem to be addressed , either after some preliminary polynomial time dynamic programming computation or directly from the start, leads to a decomposable tropical circuit .
Revised:  By this we mean that, instead of listing all solutions , we list, in an efficient way, directly only the equivalence classes or one representative per class a priori relation of equivalence between solutions, we place ourselves in the special context where the problem to be addressed , either after some preliminary polynomial time dynamic programming computation or directly from the start, leads to a decomposable tropical circuit .
Edit intent: clarity
Original:  By this we mean that, instead of listing all solutions , we list, in an efficient way, directly only the equivalence classes or  one representative per class . Besides the need to then provide ana priori relation of equivalence between solutions, we place ourselves in the special context where the problem to be addressed , either after some preliminary polynomial time dynamic programming computation or directly from the start, leads to a decomposable tropical circuit .
Revised:  By this we mean that, instead of listing all solutions , we list, in an efficient way, directly only the equivalence classes or one representative per class . Besides the need to then provide an relation of equivalence between solutions, we place ourselves in the special context where the problem to be addressed , either after some preliminary polynomial time dynamic programming computation or directly from the start, leads to a decomposable tropical circuit .
Edit intent: clarity
Original:  By this we mean that, instead of listing all solutions , we list, in an efficient way, directly only the equivalence classes or  one representative per class . Besides the need to then provide ana priori relation of equivalence between solutions, we place ourselves in the special context where the problem to be addressed , either after some preliminary polynomial time dynamic programming computation or directly from the start, leads to a decomposable tropical circuit .
Revised:  By this we mean that, instead of listing all solutions , we list, in an efficient way, directly only the equivalence classes or one representative per class . Besides the need to then provide ana priori (without generating all the solutions), although identified as a need in many areas, has been addressed only for very few specific cases. In this paper, we provide a general framework that solves this problem in polynomial delay for a wide variety of contexts, including optimization ones that can be addressed by dynamic programming algorithms, and for certain types of equivalence relations between solutions .
Edit intent: coherence
Original:  2) Next we consider few semi-adversarial inputs: random order of arrival with adversarially generated and sparse graphs. 3) Lastly we introduce a new model, which we call the friendly sequence model. We look at several online optimization problems : mincut, maxcut and submodular maximization and show that there are input ordering where a greedy strategy can produce an optimalanswer\mc .
Revised:  2) Next we consider few semi-adversarial inputs: random order of arrival with adversarially generated and sparse graphs. 3) Lastly we derive some structural properties of\mc .
Edit intent: coherence
Original:  We look at several online optimization problems : mincut, maxcut and submodular maximization and show that there are input ordering where a greedy strategy can produce an optimalanswer\mc .
Revised:  We look at several online optimization problems : mincut, maxcut and submodular maximization and show that there are input ordering where a greedy strategy can produce an optimalanswer\mc-type problems with respect to greedy strategies. Finally we consider a non-stationary regret setting with a variational budget V_T and give tights bounds on the regret function. Specifically, we show that if V_T is sublinear in T (number of rounds) then there is a deterministic algorithm achieving a sublinear regret bound (O(V_T)). Further, this is optimal, even if randomization is allowed .
Edit intent: meaning-changed
Original:  Our main result is an almost optimal polynomial time (1-e^{-1}- %DIFDELCMD < \eps%%%  )-approximation algorithm for the problem, for any %DIFDELCMD < \eps%%%  >0.
Revised:  Our main result is an almost optimal polynomial time (1-e^{-1}- %DIFDELCMD < \eps%%% \varepsilon )-approximation algorithm for the problem, for any %DIFDELCMD < \eps%%% >0.
Edit intent: meaning-changed
Original:  Our main result is an almost optimal polynomial time (1-e^{-1}- %DIFDELCMD < \eps%%%  )-approximation algorithm for the problem, for any %DIFDELCMD < \eps%%%  >0.
Revised:  Our main result is an almost optimal polynomial time (1-e^{-1}- %DIFDELCMD < \eps%%% )-approximation algorithm for the problem, for any %DIFDELCMD < \eps%%% \varepsilon >0.
Edit intent: meaning-changed
Original:  Notably, our results show that persona improves empathetic responding more when CoBERT is trained on empathetic conversations than non-empathetic ones, establishing an empirical link between persona and empathy in human conversations .
Revised:  Notably, our results show that persona improves empathetic responding more when CoBERT is trained on empathetic dialogues than non-empathetic ones, establishing an empirical link between persona and empathy in human conversations .
Edit intent: clarity
Original:  Notably, our results show that persona improves empathetic responding more when CoBERT is trained on empathetic conversations than non-empathetic ones, establishing an empirical link between persona and empathy in human conversations .
Revised:  Notably, our results show that persona improves empathetic responding more when CoBERT is trained on empathetic conversations than non-empathetic ones, establishing an empirical link between persona and empathy in human dialogues .
Edit intent: clarity
Original:  Notably, our results show that persona improves empathetic responding more when CoBERT is trained on empathetic dialogues than non-empathetic ones, establishing an empirical link between persona and empathy in human dialogues .
Revised:  Notably, our results show that persona improves empathetic responding more when CoBERT is trained on empathetic conversations than non-empathetic ones, establishing an empirical link between persona and empathy in human dialogues .
Edit intent: clarity
Original:  Notably, our results show that persona improves empathetic responding more when CoBERT is trained on empathetic dialogues than non-empathetic ones, establishing an empirical link between persona and empathy in human dialogues .
Revised:  Notably, our results show that persona improves empathetic responding more when CoBERT is trained on empathetic dialogues than non-empathetic ones, establishing an empirical link between persona and empathy in human conversations .
Edit intent: clarity
Original: During the epidemics of COVID-19, not only China but the whole world is experiencing a serious crisis on public health and economy , and the epidemics have become pandemic. As estimating the overall loss and the effectiveness of preventive measures in China is a complex task, we try to reveal the behavior change of people over time & space in order to infer the impact on daily life of and overall economy.
Revised: During the epidemics of COVID-19, not only China but the whole world is experiencing a serious crisis on public health and economy . Detailed information in the behavior of residents during epidemic benefits emergency management when one tries to design intervention strategies and resilience measures. From the perspective of movements, the widely used Bike Sharing System (BSS) in China is a complex task, we try to reveal the behavior change of people over time & space in order to infer the impact on daily life of and overall economy.
Edit intent: meaning-changed
Original:  As estimating the overall loss and the effectiveness of preventive measures in China is a complex task, we try to reveal the behavior change of people over time & space in order to infer the impact on daily life of and overall economy.
Revised:  As estimating the overall loss and the effectiveness of preventive measures in China is capable of characterizing the behavior patterns over time & space in order to infer the impact on daily life of and overall economy.
Edit intent: clarity
Original:  As estimating the overall loss and the effectiveness of preventive measures in China is a complex task, we try to reveal the behavior change of people over time & space in order to infer the impact on daily life of and overall economy. Spatiotemporal behavior patterns can be reflected by share bike usage because great majority of Chinese urban residents use share bikes to connect public transports and both ends of travel. Taking records of Bike Sharing Systems (BSSs) in Beijing, this paper characterizes not only temporal behavior patterns of share bike users: during ordinary days, holidays and the pandemic, but also spatial behavior patterns: around malls, metros, normal communities and infected communities, etc.
Revised:  As estimating the overall loss and the effectiveness of preventive measures in China is a complex task, we try to reveal the behavior change of people over time & space within big cities. Although share bikes are playing an important role as data sources in data mining, they could be of help but are rarely reported in pandemic-related researches. Based on the share bike records in Beijing, this paper characterizes not only temporal behavior patterns of share bike users: during ordinary days, holidays and the pandemic, but also spatial behavior patterns: around malls, metros, normal communities and infected communities, etc.
Edit intent: coherence
Original:  Taking records of Bike Sharing Systems (BSSs) in Beijing, this paper characterizes not only temporal behavior patterns of share bike users: during ordinary days, holidays and the pandemic, but also spatial behavior patterns: around malls, metros, normal communities and infected communities, etc. This paper illustrates the evolution of share bikes usage during the pandemic and discover the critical time places showing the significant impact on the productive and social activities.
Revised:  Taking records of Bike Sharing Systems (BSSs) in Beijing, we constructed a behavior pattern analysis framework, then analyzed the spatiotemporal behavior patterns of residents, figured out the key time nodes of different pandemic periods, and discover the critical time places showing the significant impact on the productive and social activities.
Edit intent: clarity
Original:  This paper illustrates the evolution of share bikes usage during the pandemic and discover the critical time places showing the significant impact on the productive and social activities.
Revised:  This paper illustrates the evolution of share bikes usage during the pandemic and discover the critical time demonstrated the variations in mobility due to the onset of the COVID-19 threat and administrative restrictions. The impact of the pandemic was assessed by performing co-location analysis between share bike usage and POIs (Point Of Interest). Classification of POIs is helpful to distinguish the behavior patterns generated by various the productive and social activities.
Edit intent: meaning-changed
Original:  From the perspective of movements, the widely used Bike Sharing System (BSS) in China is capable of characterizing the behavior patterns over time & space within big cities . Although share bikes are playing an important role as data sources in data mining, they could be of help but are rarely reported in pandemic-related researches.
Revised:  From the perspective of movements, the widely used Bike Sharing System (BSS) in China is capable of characterizing the behavior patterns over time & space in big cities but is rarely reported in pandemic-related researches.
Edit intent: coherence
Original:  Although share bikes are playing an important role as data sources in data mining, they could be of help but are rarely reported in pandemic-related researches. Based on the share bike records in Beijing, we constructed a behavior pattern analysis framework, then analyzed the spatiotemporal behavior patterns of residents, figured out  the key time nodes of different pandemic periods, and demonstrated the variations in mobility due to the onset of the COVID-19 threat and administrative restrictions.
Revised:  Although share bikes are playing an important role as data sources in data mining, they could be of help but are rarely reported in epidemiological research. In this paper, we present a human mobility analyzing framework the key time nodes of different pandemic periods, and demonstrated the variations in mobility due to the onset of the COVID-19 threat and administrative restrictions.
Edit intent: clarity
Original:  Based on the share bike records in Beijing, we constructed a behavior pattern analysis framework, then analyzed the spatiotemporal behavior patterns of residents, figured out  the key time nodes of different pandemic periods, and demonstrated the variations in mobility due to the onset of the COVID-19 threat and administrative restrictions.
Revised:  Based on the share bike records in Beijing, we constructed a behavior pattern analysis framework, then analyzed the spatiotemporal behavior patterns of residents, figured out based on BSS data, which examines the spatiotemporal characteristics of share bike users, detects the key time nodes of different pandemic periods, and demonstrated the variations in mobility due to the onset of the COVID-19 threat and administrative restrictions.
Edit intent: meaning-changed
Original:  Based on the share bike records in Beijing, we constructed a behavior pattern analysis framework, then analyzed the spatiotemporal behavior patterns of residents, figured out  the key time nodes of different pandemic periods, and demonstrated the variations in mobility due to the onset of the COVID-19 threat and administrative restrictions.
Revised:  Based on the share bike records in Beijing, we constructed a behavior pattern analysis framework, then analyzed the spatiotemporal behavior patterns of residents, figured out the key time nodes of different pandemic stages, and demonstrats the evolution of human mobility due to the onset of the COVID-19 threat and administrative restrictions.
Edit intent: clarity
Original:  Classification of POIs is helpful to distinguish the behavior patterns generated by various the productive and social activities . Discussions with evolving confirmed COVID-19 cases suggest the effectiveness and necessity of the public interventions in the COVID-19 containment during the resilience period .
Revised:  Our results show the pandemic reduced the overall bike usage by 64.8\%, then an average increase (15.9\%) in share bike usage appeared afterwards, suggesting that productive and residential activities have partially recovered but far from the ordinary days .
Edit intent: meaning-changed
Original:  Under appropriate restrictions, we show that the conditional distribution of the stochastic inefficiency term  is a folded normal distribution . The latter reduces to the half-normal distribution when both inputs and environmental variables are independent of the stochastic inefficiency term.
Revised:  Under appropriate restrictions, we show that the conditional distribution of the stochastic inefficiency term is a folded normal distribution , which reduces to the half-normal distribution when both inputs and environmental variables are independent of the stochastic inefficiency term.
Edit intent: coherence
Original:  We achieve identification using a control function assumption. We show that the conditional distribution of the stochastic inefficiency term given the control functions is a folded normal distribution, which reduces to the half-normal distribution when both inputs and environmental variables are independent of the stochastic inefficiency term .
Revised:  Our framework is a generalization of the normal half-normal stochastic frontier model with endogeneity. We derive the likelihood function in closed form using three fundamental assumptions: the existence of control functions that fully capture the dependence between regressors and unobservables; the conditional independence of the two error components given the control functions is a folded normal distribution, which reduces to the half-normal distribution when both inputs and environmental variables are independent of the stochastic inefficiency term .
Edit intent: meaning-changed
Original:  We show that the conditional distribution of the stochastic inefficiency term given the control functions is a folded normal distribution, which reduces to the half-normal distribution when both inputs and environmental variables are independent of the stochastic inefficiency term . Hence, our framework is a natural generalization of the normal half-normal stochastic frontier model with endogeneity. We further provide a Battese-Coelli estimator of technical efficiency in this context .
Revised:  We show that the conditional distribution of the stochastic inefficiency term given the control functions is a folded normal distribution, which reduces to the half-normal distribution when both inputs and environmental variables are independent of the stochastic inefficiency term given the control functions being a folded normal distribution. We also provide a Battese-Coelli estimator of technical efficiency in this context .
Edit intent: clarity
Original:  However, many prior works in this area mostly focus on the application of the traditional SIR model and disregard the transmission characteristics of 2019-nCoV, exceptionally the infectious of undiagnosed cases. Here , we propose a SUIR model based on the classical SIR model object to supervise the effective prediction, prevention, and control of infectious diseases.
Revised:  Given its successful application in the evaluation of infectious diseases scale , we propose a SUIR model based on the classical SIR model object to supervise the effective prediction, prevention, and control of infectious diseases.
Edit intent: meaning-changed
Original:  SUIR model adds a unique U (Undiagnosed) state of the epidemic and divides the population into four states: S (Susceptible), U (Undiagnosed), I (Infectious and Uninfectious), and R (Recovered).
Revised:  Our model is a modified susceptible-infected-recovered (SIR) model that injects undiagnosed state and offers pre-training effective reproduction number. Our SUIR model is more precise than the traditional SIR model. Moreover, we combine domain knowledge of the epidemic and divides the population into four states: S (Susceptible), U (Undiagnosed), I (Infectious and Uninfectious), and R (Recovered).
Edit intent: meaning-changed
Original:  SUIR model adds a unique U (Undiagnosed) state of the epidemic and divides the population into four states: S (Susceptible), U (Undiagnosed), I (Infectious and Uninfectious), and R (Recovered). This approach enables us to predict the incidence of 2019-nCoV effectively and the clear advantage of the model accuracy more reliable than the traditional SIR model .
Revised:  SUIR model adds a unique U (Undiagnosed) state of the epidemic to estimate effective reproduction number, which addresses the initial susceptible population of the infectious disease model approach to the model accuracy more reliable than the traditional SIR model .
Edit intent: meaning-changed
Original:  This approach enables us to predict the incidence of 2019-nCoV effectively and the clear advantage of the model accuracy more reliable than the traditional SIR model .
Revised:  This approach enables us to predict the incidence of 2019-nCoV effectively and the clear advantage of the ground truth. These findings have implications for the forecasting of epidemic trends in COVID-19 as these could help the growth of estimating epidemic situation .
Edit intent: meaning-changed
Original: In the face of a pandemic , individuals may decide whether they take actions to mitigate the spread of the disease(cooperate) , or not (defect) , resulting in a 'disease dilemma' similar to the  prisoner's dilemma.
Revised: In numerous contexts , individuals may decide whether they take actions to mitigate the spread of the disease(cooperate) , or not (defect) , resulting in a 'disease dilemma' similar to the prisoner's dilemma.
Edit intent: clarity
Original: In the face of a pandemic , individuals may decide whether they take actions to mitigate the spread of the disease(cooperate) , or not (defect) , resulting in a 'disease dilemma' similar to the  prisoner's dilemma.
Revised: In the face of a pandemic , individuals may decide whether they take actions to mitigate the spread of disease , or not (defect) , resulting in a 'disease dilemma' similar to the prisoner's dilemma.
Edit intent: fluency
Original: In the face of a pandemic , individuals may decide whether they take actions to mitigate the spread of the disease(cooperate) , or not (defect) , resulting in a 'disease dilemma' similar to the  prisoner's dilemma.
Revised: In the face of a pandemic , individuals may decide whether they take actions to mitigate the spread of the disease(cooperate) , or not . Mitigating the spread of disease requires an individual to change their routine behaviours to benefit others , resulting in a 'disease dilemma' similar to the prisoner's dilemma.
Edit intent: meaning-changed
Original: In the face of a pandemic , individuals may decide whether they take actions to mitigate the spread of the disease(cooperate) , or not (defect) , resulting in a 'disease dilemma' similar to the  prisoner's dilemma.
Revised: In the face of a pandemic , individuals may decide whether they take actions to mitigate the spread of the disease(cooperate) , or not (defect) , resulting in a 'disease dilemma' similar to the seminal prisoner's dilemma.
Edit intent: fluency
Original:  The rate of cooperation within a population is directly linked to the rate of spread of the disease . Unfortunately, evolutionary game dynamics predict that all individuals evolve to 'defect. ' Here, we combine the disease dilemma with the compartmental model used for diseases which do not confer immunity .
Revised:  The rate of cooperation within a population is directly linked to the rate of spread of the disease , cooperation evolves under certain conditions. For diseases which do not confer immunity .
Edit intent: clarity