wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We then compare the intra-personal equilibrium strategy in the case of \alpha=1/2, namely under median maximization , to some other strategies and apply it to explain why more wealthy people invest more precentage of wealth in risky assets . Finally, we extend our model to account for multiple terminal time .
Revised:  We then compare the intra-personal equilibrium strategy in the case of \alpha=1/2, namely under median maximization , to some other strategies and apply it to explain why more wealthy people invest more precentage of wealth in risky assets .
Edit intent: clarity
Original:  We observe that the lack of mass testing could potentially lead to a pandemic in case of asymptomatic diseases  .
Revised:  We observe that the lack of mass testing could potentially lead to a pandemic in case of asymptomatic diseases . Network topology also seems to play an important role. We further observe that the final fraction of proactive individuals depends on the initial fraction of both infected as well as proactive individuals. Additionally, edge density can significantly influence the overall outcome. Our findings are in broad agreement with the lessons learnt from the ongoing COVID-19 pandemic .
Edit intent: meaning-changed
Original: This work uses projective mapping with n=349 consumers to evaluate nine commercial chocolate chips cookies , including a blind duplicate of a multinational best-selling brand and seven private labels.
Revised: The so-called rapid sensory methods have proved to be useful for the sensory study of foods by different types of panels, from trained assessors to unexperienced consumers. Data from these methods have been traditionally analyzed using statistical techniques, with some recent works proposing the use of geometric techniques and graph theory. The present work aims to deepen this line of research introducing a new method, mixing tools from statistics and graph theory, for the analysis of data from Projective Mapping. In addition, a large number of n=349 consumers to evaluate nine commercial chocolate chips cookies , including a blind duplicate of a multinational best-selling brand and seven private labels.
Edit intent: meaning-changed
Original: This work uses projective mapping with n=349 consumers to evaluate nine commercial chocolate chips cookies , including a blind duplicate of a multinational best-selling brand and seven private labels.
Revised: This work uses projective mapping with n=349 unexperienced consumers is considered for the first time in Projective Mapping, evaluating nine commercial chocolate chips cookies , including a blind duplicate of a multinational best-selling brand and seven private labels.
Edit intent: meaning-changed
Original:  The data obtained are processed using both a statistical technique , Multiple Factor Analysis , and two geometric techniques, the recently appeared  method SensoGraph using Gabriel clustering, and a novel variant introduced here which is based on the pairwise distances between samples.
Revised:  The data obtained are processed using the standard statistical technique Multiple Factor Analysis , and two geometric techniques, the recently appeared method SensoGraph using Gabriel clustering, and a novel variant introduced here which is based on the pairwise distances between samples.
Edit intent: clarity
Original:  The data obtained are processed using both a statistical technique , Multiple Factor Analysis , and two geometric techniques, the recently appeared  method SensoGraph using Gabriel clustering, and a novel variant introduced here which is based on the pairwise distances between samples.
Revised:  The data obtained are processed using both a statistical technique , Multiple Factor Analysis (MFA), the recently appeared method SensoGraph using Gabriel clustering, and a novel variant introduced here which is based on the pairwise distances between samples.
Edit intent: clarity
Original:  The data obtained are processed using both a statistical technique , Multiple Factor Analysis , and two geometric techniques, the recently appeared  method SensoGraph using Gabriel clustering, and a novel variant introduced here which is based on the pairwise distances between samples.
Revised:  The data obtained are processed using both a statistical technique , Multiple Factor Analysis , and two geometric techniques, the recently appeared geometric method SensoGraph using Gabriel clustering, and a novel variant introduced here which is based on the pairwise distances between samples.
Edit intent: meaning-changed
Original:  The data obtained are processed using both a statistical technique , Multiple Factor Analysis , and two geometric techniques, the recently appeared  method SensoGraph using Gabriel clustering, and a novel variant introduced here which is based on the pairwise distances between samples.
Revised:  The data obtained are processed using both a statistical technique , Multiple Factor Analysis , and two geometric techniques, the recently appeared method SensoGraph using Gabriel clustering, and the novel variant introduced here which is based on the pairwise distances between samples.
Edit intent: fluency
Original:  The results show that all the consensus graphics provide the same groups of samples, depending mostly on the proportion of chocolate chips, with the blind duplicates being correctly identified as the closest pair of samples, more clearly when using geometric techniques. The groups given by SensoGraph with distances are a bit clearer than those provided by SensoGraph with Gabriel clustering, although this latter positioning is shown to be closer to the one given by MFA, using Procrustes distance and RV coefficient. Last, but not least, for such a large number of consumers the computation time turns out to be considerably smaller for the geometric techniques than for the statistical one, as theoretically predicted before .
Revised:  The results show that all the consensus graphics provide the same groups of samples, depending mostly on the proportion of chocolate chips, with the blind duplicates appearing close together. Finally, the stability of the results is studied using bootstrapping and the RV and Mantel coefficients. The results suggest that, even for unexperienced consumers, highly stable results can be achieved for MFA and SensoGraph when considering a large enough number of assessors, around 200 for the consensus map of MFA or the global similarity matrix of SensoGraph .
Edit intent: clarity
Original:  We show that the first algorithm, which is a generalization of 22 to the T level case, can achieve a sample complexity of O(1/\epsilon^6) by using mini-batches of samples in each iteration.
Revised:  We show that the first algorithm, which is a generalization of \mbox{%DIFAUXCMD GhaRuswan20 to the T level case, can achieve a sample complexity of O(1/\epsilon^6) by using mini-batches of samples in each iteration.
Edit intent: meaning-changed
Original:  To the best of our knowledge, this is the first time that such an online algorithm designed for the (un)constrained multi-level setting, obtains the same sample complexity of the smooth single-level setting, under mild assumptions on the stochastic first-order oracle.
Revised:  To the best of our knowledge, this is the first time that such an online algorithm designed for the (un)constrained multi-level setting, obtains the same sample complexity of the smooth single-level setting, under standard assumptions (unbiasedness and boundedness of the second moments) on the stochastic first-order oracle.
Edit intent: meaning-changed
Original:  We further show that the techniques developed in this work can also lead to simple algorithms for the All Pairs Non-Decreasing Paths Problem (APNP) on undirected graphs, matching the asymptotically optimal running time of O(n^2) provided in the recent work of Duan et al. (ICALP'19).
Revised:  We further show that the techniques developed in this work can also lead to simple algorithms for the All Pairs Non-Decreasing Paths Problem (APNP) on undirected graphs, matching the near-optimal running time of O(n^2) provided in the recent work of Duan et al. (ICALP'19).
Edit intent: clarity
Original: Online platforms are using warning messages to counter disinformation, but current approaches are not evidence-based and appear ineffective. We designed and empirically evaluated new disinformation warnings by drawing from the research that led to effective security warnings.
Revised: Disinformation is proliferating on the internet, and platforms are responding by attaching warnings to content. There is little evidence, however, that these warnings help users identify or avoid disinformation. In this work, we adapt methods and results from the information security warning literature in order to design and evaluate effective disinformation warnings.
Edit intent: clarity
Original:  This second study validated that interstitial warnings have a strong effect and found that while warningdesign impacts comprehension and risk perception, neither attribute resulted in a significant behavioral difference .
Revised:  We confirmed a significant impact on user information-seeking behavior, and we found that a warning's design could effectively inform users or convey a risk of harm. We also found, however, that neither user comprehension nor fear of harm moderated behavioral effects .
Edit intent: clarity
Original:  Our work provides the first empirical evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for  effective warnings, and contributes scalable, repeatable methods for establishing evidence on the effectsof disinformation warnings .
Revised:  Our work provides evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for effective warnings, and contributes scalable, repeatable methods for establishing evidence on the effectsof disinformation warnings .
Edit intent: clarity
Original:  Our work provides the first empirical evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for  effective warnings, and contributes scalable, repeatable methods for establishing evidence on the effectsof disinformation warnings .
Revised:  Our work provides the first empirical evidence that disinformation warnings can---when designed well---help users identify and avoid disinformation. We show a path forward for effective warnings, and contributes scalable, repeatable methods for establishing evidence on the effectsof disinformation warnings .
Edit intent: meaning-changed
Original:  Our work provides the first empirical evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for  effective warnings, and contributes scalable, repeatable methods for establishing evidence on the effectsof disinformation warnings .
Revised:  Our work provides the first empirical evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for designing effective warnings, and contributes scalable, repeatable methods for establishing evidence on the effectsof disinformation warnings .
Edit intent: clarity
Original:  Our work provides the first empirical evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for  effective warnings, and contributes scalable, repeatable methods for establishing evidence on the effectsof disinformation warnings .
Revised:  Our work provides the first empirical evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for effective warnings, and we contribute repeatable methods for establishing evidence on the effectsof disinformation warnings .
Edit intent: clarity
Original:  Our work provides the first empirical evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for  effective warnings, and contributes scalable, repeatable methods for establishing evidence on the effectsof disinformation warnings .
Revised:  Our work provides the first empirical evidence that disinformation warnings can have a strong effect on users ' information-seeking behaviors, shows a path forward for effective warnings, and contributes scalable, repeatable methods for evaluating behavioral effects. We also surface a possible dilemma: disinformation warnings might be able to inform users and guide behavior, but the behavioral effects might result from user experience friction, not informed decision making .
Edit intent: meaning-changed
Original: Understanding collective human behavior and dynamics at urban-scale has drawn broad interest in physics, engineering, and social sciences. Social physics often adopts a statistical perspective and treats individuals as interactive elementary units, while the economics perspective sees individuals as strategic decision makers . Here we provide a microscopic mechanism of city-scale dynamics, interpret the collective outcome in a thermodynamic framework, and verify its various implications empirically.
Revised: Understanding driver behavior in on-demand mobility services is crucial for designing efficient and sustainable transport models. Drivers' delivery strategy is well understood, but their search strategy and learning process still lack an empirically validated model . Here we provide a microscopic mechanism of city-scale dynamics, interpret the collective outcome in a thermodynamic framework, and verify its various implications empirically.
Edit intent: meaning-changed
Original:  Social physics often adopts a statistical perspective and treats individuals as interactive elementary units, while the economics perspective sees individuals as strategic decision makers . Here we provide a microscopic mechanism of city-scale dynamics, interpret the collective outcome in a thermodynamic framework, and verify its various implications empirically.
Revised:  Social physics often adopts a statistical perspective and treats individuals as interactive elementary units, while the economics perspective sees individuals as strategic decision makers . Here we provide a game-theoretic model of driver search strategy and learning dynamics, interpret the collective outcome in a thermodynamic framework, and verify its various implications empirically.
Edit intent: meaning-changed
Original:  We capture the decisions of taxi drivers in a game-theoretic model, prove the existence, uniqueness, and global asymptotic stability of Nash equilibrium . We offer a macroscopic view of this equilibrium with laws of thermodynamics.
Revised:  We capture driver search strategies in a multi-market oligopoly model, which has a unique Nash equilibrium and is globally asymptotically stable. The equilibrium can therefore be obtained via heuristic learning rules where drivers pursue the incentive gradient or simply imitate others. To help understand city-scale phenomena, we offer a macroscopic view of this equilibrium with laws of thermodynamics.
Edit intent: meaning-changed
Original:  With 870 million trips of over 50k drivers in New York City, we verify this equilibrium in space and time, estimate an empirical constitutive relation  , and examine the learning process at individual and collective levels.
Revised:  With 870 million trips of over 50k drivers in New York City, we show that the equilibrium well explains the spatiotemporal patterns of driver search behavior, and estimate an empirical constitutive relation , and examine the learning process at individual and collective levels.
Edit intent: meaning-changed
Original:  With 870 million trips of over 50k drivers in New York City, we verify this equilibrium in space and time, estimate an empirical constitutive relation  , and examine the learning process at individual and collective levels.
Revised:  With 870 million trips of over 50k drivers in New York City, we verify this equilibrium in space and time, estimate an empirical constitutive relation . We find that new drivers learn the equilibrium within a year, and those who stay longer learn better. The collective response to new competition is also as predicted. Among empirical studies of driver strategy in on-demand services , and examine the learning process at individual and collective levels.
Edit intent: meaning-changed
Original:  With 870 million trips of over 50k drivers in New York City, we verify this equilibrium in space and time, estimate an empirical constitutive relation  , and examine the learning process at individual and collective levels. Connecting two perspectives, our work shows a promising approach to understand collective behavior of subpopulations .
Revised:  With 870 million trips of over 50k drivers in New York City, we verify this equilibrium in space and time, estimate an empirical constitutive relation , our work shows a promising approach to understand collective behavior of subpopulations .
Edit intent: coherence
Original:  If the frequency surrogates are constructed by minimal rational interpolation , frequency and parameters can both be sampled in a greedy fashion, by employing a fully non-intrusive "look-ahead" strategy.
Revised:  If the frequency surrogates are constructed by a suitable rational interpolation strategy , frequency and parameters can both be sampled in a greedy fashion, by employing a fully non-intrusive "look-ahead" strategy.
Edit intent: clarity
Original:  If the frequency surrogates are constructed by minimal rational interpolation , frequency and parameters can both be sampled in a greedy fashion, by employing a fully non-intrusive "look-ahead" strategy. We explain how our proposed technique can be applied even in a high-dimensional setting , by employing locally-refined sparse grids  to weaken the curse of dimensionality.
Revised:  If the frequency surrogates are constructed by minimal rational interpolation , frequency and parameters can both be sampled in an adaptive fashion. This, in general, yields frequency surrogates with different numbers of poles, a situation addressed by our proposed algorithm. Moreover, we explain how our proposed technique can be applied even in a high-dimensional setting , by employing locally-refined sparse grids to weaken the curse of dimensionality.
Edit intent: meaning-changed
Original:  We develop a temporal complex network to quantify US county level spread dynamics of Covid-19. We conduct the analysis by using the following sequence of methods: Spearman's rank correlation, Granger causality, Random Forest (RF) model, and EGARCH (1,1) model .
Revised:  We develop a temporal complex network to quantify US county level spread dynamics of COVID-19. The objective is to study the effects of the local spread dynamics, COVID-19 cases and death, and Google search activities on the US stock market. We use both conventional econometric and Machine Learning (ML) models .
Edit intent: meaning-changed
Original:  However, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Revised:  In addition, incorporating information about local spread significantly improves the performance of forecasting models of the abnormal stock prices at longer forecasting horizons. On the other hand, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Edit intent: meaning-changed
Original:  However, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Revised:  However, although a few COVID-19 related variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Edit intent: clarity
Original:  However, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Revised:  However, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationships on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Edit intent: fluency
Original:  However, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Revised:  However, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, COVID-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Edit intent: clarity
Original:  However, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread spreads of Covid-19 , and Google search activities do not have impacts on price volatility.
Revised:  However, although a few of Covid-19 variables, e.g., US total deaths and US new cases exhibit causal relationship on price volatility, EGARCH model suggests that Covid-19 cases and deaths, local spread of COVID-19 , and Google search activities do not have impacts on price volatility.
Edit intent: clarity
Original:  Although traditional custody service is typically endorsed by centralized authorities, decentralized custody scheme has become technically feasible since the emergence of digital assets, and furthermore it is badly needed by new applications such as blockchain and DeFi (Decentralized Finance).
Revised:  Although traditional custody service is typically endorsed by centralized authorities, decentralized custody scheme has become technically feasible since the emergence of digital assets, and furthermore , it is greatly needed by new applications such as blockchain and DeFi (Decentralized Finance).
Edit intent: clarity
Original:  PAGE is easy to implement as it is designed via a small adjustment to vanilla SGD: in each iteration, PAGE uses the vanilla minibatch SGD update with probability p and reuses the previous gradient with a small adjustment, at a much lower computational cost, with probability 1-p.
Revised:  PAGE is easy to implement as it is designed via a small adjustment to vanilla SGD: in each iteration, PAGE uses the vanilla minibatch SGD update with probability p or reuses the previous gradient with a small adjustment, at a much lower computational cost, with probability 1-p.
Edit intent: clarity