wanyu/IteraTeR_full_sent huggingface dataset:
Original:  While similar, these two concepts are equivalent only when the topology satisfies the following universal property: for each continuous mapping from preferences to outcomes there is a unique mapping from utilities to outcomes that is faithful to the preference map and is continuous.
Revised:  While similar, these two concepts are equivalent only when the topology satisfies the following universal property: for each continuous mapping from preferences to outcomes there is a unique mapping from utilities to model's outputs that is faithful to the preference map and is continuous.
Edit intent: clarity
Original: The task of building automatic agents that can negotiate with humans in free-form natural language has gained recent interest in the literature. Although there have been initial attempts, combining linguistic understanding with strategy effectively still remains a challenge. Towards this end, we aim to understand the role of natural language in negotiations from a data-driven perspective by attempting to predict a negotiation's outcome, well before the negotiation is complete. Building on the recent advancements in pre-trained language encoders, our model is able to predict correctly within 10\% for more than 70\% of the cases, by looking at just 60\% of the negotiation. These results suggest that rather than just being a way to realize a negotiation, natural language should be incorporated in the negotiation planning as well. Such a framework can be directly used to get feedback for training an automatically negotiating agent .
Revised: The task of building automatic agents that can negotiate with humans find broad applications in pedagogy and conversational AI. Most efforts in human-agent negotiations rely on restrictive menu-driven interfaces for communication. To advance the research in language-based negotiation systems, we explore a novel task of early prediction of buyer-seller negotiation outcomes, by varying the fraction of utterances that the model can access. We explore the feasibility of early prediction by using traditional feature-based methods, as well as by incorporating the non-linguistic task context into a pretrained language model using sentence templates. We further quantify the extent to which linguistic features help in making better predictions apart from the task-specific price information. Finally, probing the pretrained model helps us to identify specific features, such as trust and agreement, that contribute to the prediction performance .
Edit intent: meaning-changed
Original: We fit a Bayesian model to data on the number of deaths attributable to COVID-19 with the goal of estimating the number of infected individuals. Our model links an underlying Susceptible Infectious Removed (SIR) model of disease dynamics to observed deaths via a time-to-death distribution informed by previous studies. This allows us to actually fit a statistical model to the data, unlike many epidemiological studies in which the SIR model parameters are simply "calibrated" to obtain outputs that look similar to the real data. The main outputs of our model are estimates of the number of infections currently, as well as forecasts of the number of infections and deaths under various scenarios for the effectiveness of social distancing measures .
Revised: We fit a Bayesian model to data on the number of individuals who have been infected with the novel coronavirus SARS-CoV-2, and the extent to which social distancing policies have been effective at limiting its spread, are critical for effective policy going forward. Here we present estimates of the number of infections currently, as well as forecasts of the number of infections and deaths under various scenarios for the effectiveness of social distancing measures .
Edit intent: meaning-changed
Original:  The main outputs of our model are estimates of the number of infections currently, as well as forecasts of the number of infections and deaths under various scenarios for the effectiveness of social distancing measures . All of our outputs have attached Bayesian credible intervals. An important conclusion is that the confirmed case counts greatly underestimate the total number of infected individuals .
Revised:  The main outputs of our model are estimates of the number of infections currently, as well as forecasts of the number of infections and deaths under various scenarios for the effectiveness of social distancing measures have been at mitigating or suppressing the virus. Our analysis uses a Bayesian model of COVID-19 fatalities with a likelihood based on an underlying differential equation model of the epidemic. We provide analysis for four states with significant epidemics: California, Florida, New York, and Washington. Our short-term forecasts suggest that these states may be following somewhat different trajectories for growth of the number of cases and fatalities .
Edit intent: meaning-changed
Original:  an Inconic is tangent to the sides. We introduce the Circumbilliard: the circumellipse of a generic triangle which is an Elliptic Billiard (EB) to the latter. Given a fixed EB, we study varying Circumbilliards obtained from triangles derived from the 3-periodic family .
Revised:  an Inconic is tangent to the sidelines. We study the variable geometry of certain conics derived from the 3-periodic family .
Edit intent: clarity
Original:  Given a fixed EB, we study varying Circumbilliards obtained from triangles derived from the 3-periodic family . Finally we describe invariants displayed by certain Circumconics and Inconics associated with the family including: axis alignment, aspect ratio , and pairwise focal length ratio .
Revised:  Given a fixed EB, we study varying Circumbilliards obtained from triangles derived from the 1d family of 3-periodics in the Elliptic Billiard. Some display intriguing invariances such as aspect ratio and pairwise ratio of focal lengths. We also define the Circumbilliard, a circumellipse to a generic triangle for which the latter is a 3-periodic .
Edit intent: meaning-changed
Original:  Our epidemic risk index shows strong correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country.
Revised:  The corresponding risk index shows strong correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country.
Edit intent: clarity
Original:  Our epidemic risk index shows strong correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country.
Revised:  Our epidemic risk index shows correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country.
Edit intent: clarity
Original:  Our epidemic risk index shows strong correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country.
Revised:  Our epidemic risk index shows strong correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can help explaining why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country.
Edit intent: clarity
Original:  Our epidemic risk index shows strong correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country.
Revised:  Our epidemic risk index shows strong correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto have suffered much more than the rest of the country.
Edit intent: clarity
Original:  Although the COVID-19 outbreak started in both North (Lombardia and Veneto) and Central Italy (Lazio) almost at the same time, when the first infected were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk.
Revised:  Although the COVID-19 outbreak started in both North (Lombardia and Veneto) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk.
Edit intent: clarity
Original:  Although the COVID-19 outbreak started in both North (Lombardia and Veneto ) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk.
Revised:  Although the COVID-19 outbreak started in both North (Lombardia ) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk.
Edit intent: clarity
Original:  This study analyses the most retweeted posts on Twitterduring 20 days in March to give insights into the issues that resonate with the public, and the role Twitter may play in social distancing campaigns. It reports a thematic analysis of  English-language tweets  March 10-29, 2020, mentioning COVID-19 or coronavirus and with over 100,000 retweets.
Revised:  This article investigates important issues reflected on Twitter. Design/methodology/approach: A thematic analysis of English-language tweets March 10-29, 2020, mentioning COVID-19 or coronavirus and with over 100,000 retweets.
Edit intent: clarity
Original:  It reports a thematic analysis of  English-language tweets  March 10-29, 2020, mentioning COVID-19 or coronavirus and with over 100,000 retweets.
Revised:  It reports a thematic analysis of the most retweeted English-language tweets March 10-29, 2020, mentioning COVID-19 or coronavirus and with over 100,000 retweets.
Edit intent: meaning-changed
Original:  It reports a thematic analysis of  English-language tweets  March 10-29, 2020, mentioning COVID-19 or coronavirus and with over 100,000 retweets.
Revised:  It reports a thematic analysis of English-language tweets on Twitter mentioning COVID-19 during March 10-29, 2020, mentioning COVID-19 or coronavirus and with over 100,000 retweets.
Edit intent: clarity
Original:  This article investigates important issues reflected on Twitter  . Design/methodology/approach: A thematic analysis of the most retweeted English-language tweets on Twitter mentioning COVID-19 during March 10-29, 2020.
Revised:  This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19 . Design/methodology/approach: A thematic analysis of the most retweeted English-language tweets on Twitter mentioning COVID-19 during March 10-29, 2020.
Edit intent: meaning-changed
Original:  This article investigates important issues reflected on Twitter  . Design/methodology/approach: A thematic analysis of the most retweeted English-language tweets on Twitter mentioning COVID-19 during March 10-29, 2020.
Revised:  This article investigates important issues reflected on Twitter . Design/methodology/approach: A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020.
Edit intent: fluency
Original:  Our results are established through a potential argument that leverages a convex optimization perspective of Osborne's algorithm, and relates the per-iteration progress to the current imbalance as measured in Hellinger distance.
Revised:  Our results are established through an intuitive potential argument that leverages a convex optimization perspective of Osborne's algorithm, and relates the per-iteration progress to the current imbalance as measured in Hellinger distance.
Edit intent: meaning-changed
Original:   We augment the ED string with sources (individuals' indexes) and propose an extension of the SOPanG (Shift-Or for Pan-Genome) tool to report only true positive matches, omitting those not occurring in any of the haplotypes.
Revised:  Results: We augment the ED string with sources (individuals' indexes) and propose an extension of the SOPanG (Shift-Or for Pan-Genome) tool to report only true positive matches, omitting those not occurring in any of the haplotypes.
Edit intent: fluency
Original: We use anonymized and aggregated data from Facebook to show that areas with stronger social  ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March30, 2020.
Revised: We use aggregated data from Facebook to show that areas with stronger social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March30, 2020.
Edit intent: clarity
Original: We use anonymized and aggregated data from Facebook to show that areas with stronger social  ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March30, 2020.
Revised: We use anonymized and aggregated data from Facebook to show that COVID-19 is more likely to spread between regions with stronger social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March30, 2020.
Edit intent: meaning-changed
Original: We use anonymized and aggregated data from Facebook to show that areas with stronger social  ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March30, 2020.
Revised: We use anonymized and aggregated data from Facebook to show that areas with stronger social network connections. Areas with more social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March30, 2020.
Edit intent: clarity
Original: We use anonymized and aggregated data from Facebook to show that areas with stronger social  ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March30, 2020.
Revised: We use anonymized and aggregated data from Facebook to show that areas with stronger social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally had more confirmed COVID-19 cases as of March30, 2020.
Edit intent: fluency
Original: We use anonymized and aggregated data from Facebook to show that areas with stronger social  ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March30, 2020.
Revised: We use anonymized and aggregated data from Facebook to show that areas with stronger social ties to two early COVID-19 "hotspots" (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases by the end of March.
Edit intent: meaning-changed
Original:   These results suggest that data from online social networks may prove useful to epidemiologists and others hoping to forecast the spread of communicable diseases such as COVID-19.
Revised:  As the pandemic progressed in the U.S., a county's social proximity to recent COVID-19 cases and deaths predicts future outbreaks over and above physical proximity and demographics. In part due to its broad coverage, social connectedness data provides additional predictive power to measures based on smartphone location or online search data. These results suggest that data from online social networks may prove useful to epidemiologists and others hoping to forecast the spread of communicable diseases such as COVID-19.
Edit intent: meaning-changed
Original:  A data intermediary pays consumers for information about their preferencesand sells the information so acquired to firms that use it to tailor their products and prices .
Revised: We propose a model of data intermediation to analyze the incentives for sharing individual data in the presence of informational externalities. A data intermediary pays consumers for information about their preferencesand sells the information so acquired to firms that use it to tailor their products and prices .
Edit intent: meaning-changed
Original:  Specifically, given n observations from the discrete distribution, if some estimator incurs an error \varepsilon with probability at most \delta, then plugging in the PML distribution incurs an error 2\varepsilon with probability at most \delta  \exp(3n).
Revised:  Specifically, given n observations from the discrete distribution, if some estimator incurs an error \varepsilon with probability at most \delta, then plugging in the PML distribution incurs an error 2\varepsilon with probability at most \delta \cdot \exp(3n).
Edit intent: meaning-changed
Original:  In this paper, we strengthen the above result and show that using a careful chaining argument, the error probability can be reduced to \delta^{1-c}  \exp(c'n^{1/3+c}) for arbitrarily small constants c>0 and some constant c'>0.
Revised:  In this paper, we strengthen the above result and show that using a careful chaining argument, the error probability can be reduced to \delta^{1-c} \cdot \exp(c'n^{1/3+c}) for arbitrarily small constants c>0 and some constant c'>0.
Edit intent: meaning-changed
Original:  In particular, we show that the PML distribution is an optimal estimator of the sorted true distribution: it is \varepsilon-close in sorted \ell_1 distance to the true distribution with support size k for any n=\Omega(k/(\varepsilon^2 \log k)) and \varepsilon \gg n^{-1/3}, which are the information-theoretically optimal sample complexity and the largest error regime where the classical empirical distribution is sub-optimal, respectively.
Revised:  In particular, we show that the PML distribution is an optimal estimator of the sorted distribution: it is \varepsilon-close in sorted \ell_1 distance to the true distribution with support size k for any n=\Omega(k/(\varepsilon^2 \log k)) and \varepsilon \gg n^{-1/3}, which are the information-theoretically optimal sample complexity and the largest error regime where the classical empirical distribution is sub-optimal, respectively.
Edit intent: fluency
Original:  In order to strengthen the analysis of the PML, a key ingredient is to employ novel " continuity" properties of the PML distributions and construct a chain of suitable quantized PMLs, or " coverings".
Revised:  In order to strengthen the analysis of the PML, a key ingredient is to employ novel `` continuity" properties of the PML distributions and construct a chain of suitable quantized PMLs, or " coverings".
Edit intent: fluency
Original:  In order to strengthen the analysis of the PML, a key ingredient is to employ novel " continuity" properties of the PML distributions and construct a chain of suitable quantized PMLs, or " coverings".
Revised:  In order to strengthen the analysis of the PML, a key ingredient is to employ novel " continuity" properties of the PML distributions and construct a chain of suitable quantized PMLs, or `` coverings".
Edit intent: fluency
Original:  We also construct a novel approximation-based estimator for the sorted distribution with a near-optimal concentration property without any sample splitting, where as a byproduct we obtain tight trade-offs between the polynomial approximation error and the maximum magnitude of coefficients in the Poisson approximation of 1-Lipschitz functions.
Revised:  We also construct a novel approximation-based estimator for the sorted distribution with a near-optimal concentration property without any sample splitting, where as a byproduct we obtain better trade-offs between the polynomial approximation error and the maximum magnitude of coefficients in the Poisson approximation of 1-Lipschitz functions.
Edit intent: clarity
Original:  In order to strengthen the analysis of the PML, a key ingredient is to employ novel `` continuity" properties of the PML distributions and construct a chain of suitable quantized PMLs, or `` coverings".
Revised:  In order to strengthen the analysis of the PML, a key ingredient is to employ novel " continuity" properties of the PML distributions and construct a chain of suitable quantized PMLs, or `` coverings".
Edit intent: fluency
Original:  In order to strengthen the analysis of the PML, a key ingredient is to employ novel `` continuity" properties of the PML distributions and construct a chain of suitable quantized PMLs, or `` coverings".
Revised:  In order to strengthen the analysis of the PML, a key ingredient is to employ novel `` continuity" properties of the PML distributions and construct a chain of suitable quantized PMLs, or " coverings".
Edit intent: fluency
Original:  In our work, we survey existing research on FaaS performance evaluation and present results from a multivocal literature review (MLR) covering 112 studies from academic (51) and grey literature (61)  .
Revised:  In our work, we survey existing research on FaaS performance evaluation and present results from a multivocal literature review (MLR) covering 112 studies from academic (51) and grey (61) .
Edit intent: clarity
Original:  In our work, we survey existing research on FaaS performance evaluation and present results from a multivocal literature review (MLR) covering 112 studies from academic (51) and grey literature (61)  .
Revised:  In our work, we survey existing research on FaaS performance evaluation and present results from a multivocal literature review (MLR) covering 112 studies from academic (51) and grey literature (61) literature .
Edit intent: clarity
Original:  Further, we identify a mismatch between academic and industrial sources on tested platform configurations, conclude that function triggers remain insufficiently studied, and list HTTP API gateways and cloud storages as the most used external service integrations.
Revised:  Further, we discover a mismatch between academic and industrial sources on tested platform configurations, conclude that function triggers remain insufficiently studied, and list HTTP API gateways and cloud storages as the most used external service integrations.
Edit intent: clarity
Original:  Further, we identify a mismatch between academic and industrial sources on tested platform configurations, conclude that function triggers remain insufficiently studied, and list HTTP API gateways and cloud storages as the most used external service integrations.
Revised:  Further, we identify a mismatch between academic and industrial sources on tested platform configurations, find that function triggers remain insufficiently studied, and list HTTP API gateways and cloud storages as the most used external service integrations.
Edit intent: clarity