wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Furthermore, we present an efficient post-computation which , when paired with an approximation algorithm for maximin support , returns a new solution that a) preserves the approximation guarantee, b) satisfies the PJRproperty , and c) can be efficiently verified to satisfy PJR by an untrusting third party. Besides being of independent theoretical interest, our results enable the network to run an efficient validator election protocol that simultaneously achieves the PJR property and a constant-factor approximation for maximin support, thus offering strong theoretical guarantees on decentralization and security .
Revised:  Furthermore, we present an efficient post-computation which , when paired with an approximation algorithm for maximin support , returns a new solution that a) preserves the approximation guarantee, b) satisfies the PJRproperty , and c) can be efficiently verified to satisfy PJR . Our work is motivated by an application on blockchains that implement Nominated Proof-of-Stake (NPoS), where the community must elect a committee of validators to participate in its consensus protocol, and where fighting overrepresentation protects the system against attacks by an adversarial minority. Our election rule enables a validator election protocol that simultaneously achieves the PJR property and a constant-factor approximation for maximin support, thus offering strong theoretical guarantees on decentralization and security .
Edit intent: meaning-changed
Original:  Besides being of independent theoretical interest, our results enable the network to run an efficient validator election protocol that simultaneously achieves the PJR property and a constant-factor approximation for maximin support, thus offering strong theoretical guarantees on decentralization and security .
Revised:  Besides being of independent theoretical interest, our results enable the network to run an efficient validator election protocol with formal and verifiable guarantees on security and proportionality. We propose a specific protocol that can be successfully implemented in spite of the stringent time constraints of a blockchain architecture, and that will be the basis for an implementation in the Polkadot network, launched in 2020.
Edit intent: meaning-changed
Original: The COVID-19 pandemic has emerged as one of the greatest public health challenges of modern times. Policy makers rely on measuring how quickly the disease is spreading to make decisions about mitigation strategies .
Revised: The COVID-19 pandemic has emerged as a global public health crisis. To make decisions about mitigation strategies and to understand the disease dynamics, policy makers and epidemiologists must know how the disease is spreading to make decisions about mitigation strategies .
Edit intent: coherence
Original:  We analyze US county-level data about confirmed COVID-19 infections and deaths  to show that its impact is heterogeneous. A small fraction of counties represent the majority of all infectionsand deaths. These hot spotsare correlated with populous areas where the disease arrives earlier and grows faster. When county-level data is aggregated to create state-level and national statistics, these hot spots systematically bias the growth rates.
Revised:  We analyze US county-level data about confirmed COVID-19 infections and deaths to show that COVID-19's impact is highly unequal: many subregions have nearly zero infections, and others are hot spots. We attribute the effect to a Reed-Hughes-like mechanism in which disease arrives at different times and grows exponentially. Hot spots, however, appear to grow faster than neighboring subregions and dominate spatially aggregated statistics, thereby amplifying growth rates.
Edit intent: meaning-changed
Original:  As a result, infections and deaths appear to grow faster at those larger scales than they do within typical counties that make up those larger regions . Public policy, economic analysis and epidemic modeling have to account for potential distortions introduced by spatial aggregation.
Revised:  The staggered spread of COVID-19 can also make aggregated growth rates appear higher even when subregions grow at the same rate . Public policy, economic analysis and epidemic modeling have to account for potential distortions introduced by spatial aggregation.
Edit intent: meaning-changed
Original:  As a result, infections and deaths appear to grow faster at those larger scales than they do within typical counties that make up those larger regions . Public policy, economic analysis and epidemic modeling have to account for potential distortions introduced by spatial aggregation.
Revised:  As a result, infections and deaths appear to grow faster at those larger scales than they do within typical counties that make up those larger regions . Public policy, economic analysis and epidemic modeling need to account for potential distortions introduced by spatial aggregation.
Edit intent: fluency
Original:  While this setup is a natural one and similar to humans conversing with each other, it introduces a key research challenge : understanding the context left implicit by the user in follow-up questions  .
Revised:  While this setup is a natural one and similar to humans conversing with each other, it introduces a key research challenge : understanding the context left implicit by the user in follow-up questions , and dealing with ad hoc question formulations .
Edit intent: meaning-changed
Original:  Experiments on Chinese- > English and German- > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in BLEU scores , but with much lower latency.
Revised:  Experiments on Chinese - > English and German- > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in BLEU scores , but with much lower latency.
Edit intent: fluency
Original:  Experiments on Chinese- > English and German- > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in BLEU scores , but with much lower latency.
Revised:  Experiments on Chinese- > English and German - > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in BLEU scores , but with much lower latency.
Edit intent: fluency
Original:  Experiments on Chinese- > English and German- > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in BLEU scores , but with much lower latency.
Revised:  Experiments on Chinese- > English and German- > English show that our adaptive policies can outperform fixed ones by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in BLEU scores , but with much lower latency.
Edit intent: clarity
Original:  Experiments on Chinese- > English and German- > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in BLEU scores , but with much lower latency.
Revised:  Experiments on Chinese- > English and German- > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses the BLEU score of full-sentence translation in BLEU scores , but with much lower latency.
Edit intent: clarity
Original:  Experiments on Chinese- > English and German- > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in BLEU scores , but with much lower latency.
Revised:  Experiments on Chinese- > English and German- > English show that our adaptive policies can outperform the fixed policies by up to 4 BLEU points for the same latency, and more surprisingly, it even surpasses greedy full-sentence translation in the greedy mode (and very close to beam mode) , but with much lower latency.
Edit intent: meaning-changed
Original: Daily case reports and daily fatalities for China, South Korea, France, Germany, Italy, Spain, Iran, Turkey, the United Kingdom and the United States over the period January 22, 2020 - April 20 , 2020 are analysed using the Susceptible-Infected-Removed (SIR) model.
Revised: The rapidly spreading Covid-19 that affected almost all countries, was first reported at the end of 2019. As a consequence of its highly infectious nature, countries all over the world have imposed extremely strict measures to control its spread. Since the earliest stages of this major pandemic, academics have done a huge amount of research in order to understand the disease, develop medication, vaccines and tests, and model its spread. Among these studies, a great deal of effort has been invested in the estimation of epidemic parameters in the early stage, for the countries affected by Covid-19, hence to predict the course of the epidemic but the variability of the controls over the course of the epidemic complicated the modeling processes. In this article, the determination of the basic reproduction number, the mean duration of the infectious period, the estimation of the timing of the peak of the epidemic wave is discussed using early phase data. Daily case reports and daily fatalities for ten countries over the period January 22, 2020 - April 20 , 2020 are analysed using the Susceptible-Infected-Removed (SIR) model.
Edit intent: meaning-changed
Original: Daily case reports and daily fatalities for China, South Korea, France, Germany, Italy, Spain, Iran, Turkey, the United Kingdom and the United States over the period January 22, 2020 - April 20 , 2020 are analysed using the Susceptible-Infected-Removed (SIR) model.
Revised: Daily case reports and daily fatalities for China, South Korea, France, Germany, Italy, Spain, Iran, Turkey, the United Kingdom and the United States over the period January 22, 2020 - April 18 , 2020 are analysed using the Susceptible-Infected-Removed (SIR) model.
Edit intent: meaning-changed
Original: Daily case reports and daily fatalities for China, South Korea, France, Germany, Italy, Spain, Iran, Turkey, the United Kingdom and the United States over the period January 22, 2020 - April 20 , 2020 are analysed using the Susceptible-Infected-Removed (SIR) model.
Revised: Daily case reports and daily fatalities for China, South Korea, France, Germany, Italy, Spain, Iran, Turkey, the United Kingdom and the United States over the period January 22, 2020 - April 20 , 2020 are evaluated using the Susceptible-Infected-Removed (SIR) model.
Edit intent: clarity
Original:  It is shown that the quantity that can be the most robustly estimated from the normalized data, is the timing of the maximum and timings of the inflection points of the proportion of infected individuals  .
Revised:  It is observed that the basic reproduction number and the mean duration of the infectious period can be estimated only in cases where the spread of the epidemic is over (for China and South Korea in the present case). Nevertheless, it is shown that the timing of the maximum and timings of the inflection points of the proportion of infected individuals .
Edit intent: meaning-changed
Original:  It is shown that the quantity that can be the most robustly estimated from the normalized data, is the timing of the maximum and timings of the inflection points of the proportion of infected individuals  .
Revised:  It is shown that the quantity that can be the most robustly estimated from the normalized data, is the timing of the maximum and timings of the inflection points of the proportion of infected individuals can be robustly estimated from the normalized data. The validation of the estimates by comparing the predictions with actual data has shown that the predictions were realised for all countries except USA, as long as lock-down measures were retained .
Edit intent: meaning-changed
Original:  Following a mean field approach that models individuals like particles in a well-mixed solution, I derive a modified SIR model in which the  contacts between susceptible and infected population are reduced based on the known infection levels  .
Revised:  Following a mean field approach that models individuals like molecules in a well-mixed solution, I derive a modified SIR model in which the contacts between susceptible and infected population are reduced based on the known infection levels .
Edit intent: clarity
Original:  Following a mean field approach that models individuals like particles in a well-mixed solution, I derive a modified SIR model in which the  contacts between susceptible and infected population are reduced based on the known infection levels  .
Revised:  Following a mean field approach that models individuals like particles in a well-mixed solution, I derive a modified SIR model in which the average daily contacts between susceptible and infected population are reduced based on the known infection levels .
Edit intent: meaning-changed
Original:  Following a mean field approach that models individuals like particles in a well-mixed solution, I derive a modified SIR model in which the  contacts between susceptible and infected population are reduced based on the known infection levels  .
Revised:  Following a mean field approach that models individuals like particles in a well-mixed solution, I derive a modified SIR model in which the contacts between susceptible and infected population are reduced based on the known infection levels , capturing the effects of social distancing policies .
Edit intent: meaning-changed
Original:  This approach yields a time-varying reproduction number that is continuously adjusted , based on infection information through a negative-feedback term that is similar to Michaelis-Menten and Hill functions in chemistry and molecular biology.
Revised:  This approach yields a time-varying reproduction number that is continuously adjusted based on infection information through a negative-feedback term that is similar to Michaelis-Menten and Hill functions in chemistry and molecular biology.
Edit intent: fluency
Original:  This approach yields a time-varying reproduction number that is continuously adjusted , based on infection information through a negative-feedback term that is similar to Michaelis-Menten and Hill functions in chemistry and molecular biology.
Revised:  This approach yields a time-varying reproduction number that is continuously adjusted , based on infection information through a negative-feedback term that is equivalent to Holling type II functions in ecology and Hill functions in chemistry and molecular biology.
Edit intent: meaning-changed
Original:  The main advantage of this model is that it adds a single parameter to the original SIR, making it useful to illustrate the effects of social distancing enforced based on awareness of infections.
Revised:  If the distancing rate is linearly proportional to infections, this model adds a single parameter to the original SIR, making it useful to illustrate the effects of social distancing enforced based on awareness of infections.
Edit intent: meaning-changed
Original: Contact tracing apps are one of the primary technology-facilitated Coronavirus (COVID) responses currently proposed. In the majority of Western nations there is the expectation that citizens will have the autonomy to decide whether or not to install a COVID-related app . Yet, the more users who install a COVID app, the greater the impact on public health.
Revised: The COVID19 pandemic spread across the world in late 2019 and early 2020. As the pandemic spread, technologists joined forces with public health officials to develop apps to support COVID19 response . Yet, the more users who install a COVID app, the greater the impact on public health.
Edit intent: meaning-changed
Original:  In the majority of Western nations there is the expectation that citizens will have the autonomy to decide whether or not to install a COVID-related app . Yet, the more users who install a COVID app, the greater the impact on public health. As explained by Chan et al. the value of users installing a contact-tracing app grows quadratically with the number of users who install. How can we get users to install COVID apps? By understanding and mitigating user concerns and tradeoffs.This document provides a framework for considering the user-relevant components of COVID apps and corresponding user tradeoffs related to these apps. Specifically, we enumerate usertradeoffs related to data collection, data quality, identifier/data encryption, privacy invasion, mobile costs, user agency, benefits from app use, and app transparency. We break down which tradeoffs are relevant for which contact tracing implementations (centralized vs. decentralized,location- vs. proximity-based). Additionally, we compare contact tracing to an alternative technology-facilitated COVID solution: narrowcasts. Narrowcasts are location-personalized broadcasts about COVID hotspots in your vicinity .
Revised:  In the majority of Western nations there is the expectation that citizens will have the autonomy to decide whether or not to install a COVID-related app . Yet, for these technological solutions to benefit public health, users must be willing to adopt these apps.This paper details the potential inputs to a user's decision to adopt a COVID19 contact-tracing app or other technology and empirically validates the relevance of these inputs via both the literature and a demographically-representative survey of 1,000 Americans .
Edit intent: meaning-changed
Original:  In this paper, we introduce the out-of-sample representation learning problem for non-attributed multi-relational graphs, create benchmark datasets for this task, develop several models and baselines, and provide empirical analyses and comparisons of the proposed models and baselines.
Revised:  In this paper, we study the out-of-sample representation learning problem for non-attributed multi-relational graphs, create benchmark datasets for this task, develop several models and baselines, and provide empirical analyses and comparisons of the proposed models and baselines.
Edit intent: clarity
Original:  In this paper, we introduce the out-of-sample representation learning problem for non-attributed multi-relational graphs, create benchmark datasets for this task, develop several models and baselines, and provide empirical analyses and comparisons of the proposed models and baselines.
Revised:  In this paper, we introduce the out-of-sample representation learning problem for non-attributed knowledge graphs, create benchmark datasets for this task, develop several models and baselines, and provide empirical analyses and comparisons of the proposed models and baselines.
Edit intent: clarity
Original:  Making use of Malliavin calculus, we recast the traditional Euler contributions from an expectation conditional to an event of zero probability to a ratio of conditional expectations , where both the numerator and the denominator's conditioning events have  positive probability.
Revised:  We recast the traditional Euler contributions from an expectation conditional to an event of zero probability to a ratio of conditional expectations , where both the numerator and the denominator's conditioning events have positive probability.
Edit intent: coherence
Original:  Making use of Malliavin calculus, we recast the traditional Euler contributions from an expectation conditional to an event of zero probability to a ratio of conditional expectations , where both the numerator and the denominator's conditioning events have  positive probability.
Revised:  Making use of Malliavin calculus, we recast the traditional Euler contributions from an expectation conditional on an event of zero probability to a ratio of conditional expectations , where both the numerator and the denominator's conditioning events have positive probability.
Edit intent: fluency
Original:  Making use of Malliavin calculus, we recast the traditional Euler contributions from an expectation conditional to an event of zero probability to a ratio of conditional expectations , where both the numerator and the denominator's conditioning events have  positive probability.
Revised:  Making use of Malliavin calculus, we recast the traditional Euler contributions from an expectation conditional to an event of zero probability to a ratio involving conditional expectations whose conditioning events have positive probability.
Edit intent: clarity
Original:  Making use of Malliavin calculus, we recast the traditional Euler contributions from an expectation conditional to an event of zero probability to a ratio of conditional expectations , where both the numerator and the denominator's conditioning events have  positive probability.
Revised:  Making use of Malliavin calculus, we recast the traditional Euler contributions from an expectation conditional to an event of zero probability to a ratio of conditional expectations , where both the numerator and the denominator's conditioning events have stricktly positive probability.
Edit intent: fluency
Original:  In particular, MultiMix targets to solve cross-lingual adaptation problems from a source (language ) distribution to an unknown target (language ) distributionassuming it has no training labels in the target language task.
Revised:  In particular, MultiMix targets to solve cross-lingual adaptation problems from a source language distribution to an unknown target (language ) distributionassuming it has no training labels in the target language task.
Edit intent: fluency
Original:  In particular, MultiMix targets to solve cross-lingual adaptation problems from a source (language ) distribution to an unknown target (language ) distributionassuming it has no training labels in the target language task.
Revised:  In particular, MultiMix targets to solve cross-lingual adaptation problems from a source (language ) distribution to an unknown target (language ) distributionassuming it has no training labels are available for the target language task.
Edit intent: clarity
Original:  To show its effectiveness, we have performed extensive experiments on zero-shot transfers for cross-lingual named entity recognition (XNER) and natural language inference (XNLI). Our experiments show sizeable improvements in both tasks  outperforming the baselines by a good margin  .
Revised:  To show its effectiveness, we have performed extensive experiments on zero-shot transfers for cross-lingual transfer tasks for Named Entity Recognition and Natural Language Inference. MultiMix achieves SoTA results in both tasks outperforming the baselines by a good margin .
Edit intent: meaning-changed
Original:  As discussed in S\"onmez and Yenmez (2019a), the lack of a well-defined procedure to implement horizontal reservations results in extensive confusion. Indirect mechanisms currently used in practice do not  allow reserve category applicants to fully express their preferences.
Revised:  As discussed in S\"onmez and Yenmez (2019a), the lack of a well-defined procedure to implement horizontal reservations jointly with vertical reservation and OBC de-reservations. Sequential processes currently in use for OBC de-reservations and meritorious reserve candidates lead to severe shortcomings. Most importantly, indirect mechanisms currently used in practice do not allow reserve category applicants to fully express their preferences.
Edit intent: meaning-changed