wanyu/IteraTeR_full_sent huggingface dataset:
Original: Objective: Sliding and tapered sliding window methods are the most often used approaches in computing dynamic correlations in biomedical signals such as the brain resting-state fMRI  . However,  due to the discrete nature of windows, the window methods suffer spurious high-frequency fluctuations and the zig-zag pattern in dynamic correlations.
Revised: Objective: Sliding and tapered sliding window methods are the most often used approaches in computing dynamic correlations in biomedical signals such as the brain resting-state fMRI . However, the direct use of the sample correlation matrices is not reliable due to the discrete nature of windows, the window methods suffer spurious high-frequency fluctuations and the zig-zag pattern in dynamic correlations.
Edit intent: meaning-changed
Original: Objective: Sliding and tapered sliding window methods are the most often used approaches in computing dynamic correlations in biomedical signals such as the brain resting-state fMRI  . However,  due to the discrete nature of windows, the window methods suffer spurious high-frequency fluctuations and the zig-zag pattern in dynamic correlations.
Revised: Objective: Sliding and tapered sliding window methods are the most often used approaches in computing dynamic correlations in biomedical signals such as the brain resting-state fMRI . However, due to the image acquisition, processing noises and the use of discrete windows that often introduce spurious high-frequency fluctuations and the zig-zag pattern in dynamic correlations.
Edit intent: meaning-changed
Original: Objective: Sliding and tapered sliding window methods are the most often used approaches in computing dynamic correlations in biomedical signals such as the brain resting-state fMRI  . However,  due to the discrete nature of windows, the window methods suffer spurious high-frequency fluctuations and the zig-zag pattern in dynamic correlations. Methods: To address the problem and obtain more stable correlation estimates, we propose a novel windowless approach for computing dynamic correlations via heat kernel smoothing.
Revised: Objective: Sliding and tapered sliding window methods are the most often used approaches in computing dynamic correlations in biomedical signals such as the brain resting-state fMRI . However, due to the discrete nature of windows, the window methods suffer spurious high-frequency fluctuations and the zig-zag pattern in the estimated time-varying correlation measures. To address the problem and obtain more stable correlation estimates, we propose a novel windowless approach for computing dynamic correlations via heat kernel smoothing.
Edit intent: clarity
Original:  Methods: To address the problem and obtain more stable correlation estimates, we propose a novel windowless approach for computing dynamic correlations via heat kernel smoothing. The heat kernel, the natural generalization of the Gaussian kernel to manifolds, is used to defined a smoothing kernel without boundary or end points. Results: We show that the proposed windowless approach smooths out the unwanted high-frequency noise in correlation estimations and is more stable in identifying and discriminating state spaces in resting-state fMRI.
Revised:  Methods: To address the problem and obtain more stable correlation estimates, we propose the heat kernel based dynamic correlations. We demonstrate that the proposed windowless approach smooths out the unwanted high-frequency noise in correlation estimations and is more stable in identifying and discriminating state spaces in resting-state fMRI.
Edit intent: coherence
Original:  Results: We show that the proposed windowless approach smooths out the unwanted high-frequency noise in correlation estimations and is more stable in identifying and discriminating state spaces in resting-state fMRI.
Revised:  Results: We show that the proposed heat kernel method can smooth out the unwanted high-frequency noise in correlation estimations and is more stable in identifying and discriminating state spaces in resting-state fMRI.
Edit intent: meaning-changed
Original:  Results: We show that the proposed windowless approach smooths out the unwanted high-frequency noise in correlation estimations and is more stable in identifying and discriminating state spaces in resting-state fMRI.
Revised:  Results: We show that the proposed windowless approach smooths out the unwanted high-frequency fluctuations in correlation estimations and is more stable in identifying and discriminating state spaces in resting-state fMRI.
Edit intent: clarity
Original:  Results: We show that the proposed windowless approach smooths out the unwanted high-frequency noise in correlation estimations and is more stable in identifying and discriminating state spaces in resting-state fMRI. The proposed method is applied to the study of interhemispheric connectivity and whole-brain network analysis. Conclusion: We present a novel framework using heat kernel to compute the windowless dynamic correlation, which is more stable with less high-frequency fluctuations than windowed methods. Significance: The proposed windowless approach reduced the spurious rapid changes in the state space of brain connectivity, and identified the strongest connections in brain networks and symmetry in interhemispheric connectivity .
Revised:  Results: We show that the proposed windowless approach smooths out the unwanted high-frequency noise in correlation estimations and achieve higher accuracy in identifying dynamically changing distinct states. The method is further used in determining if such dynamic state change is genetically heritable using a large-scale twin study. Various methodological challenges for analyzing paired twin dynamic networks are addressed .
Edit intent: clarity
Original:   We provide a complete analytical framework, including a detailed study of discounted exponential moments of CBI processes.
Revised:  In particular, we introduce multi-curve models driven by a flow of CBI processes. Such models are especially parsimonious and tractable, and can generate contagion effects among different spreads. We provide a complete analytical framework, including a detailed study of discounted exponential moments of CBI processes.
Edit intent: meaning-changed
Original:  By adapting direct coupling analysis (DCA) to treat in tandem sequences written in two alphabets, nucleotides and amino acids, we could analyze StpA-RNA interactions and identify a two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Revised:  By adapting direct coupling analysis (DCA) to treat in tandem sequences written in two alphabets, nucleotides and amino acids, we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Edit intent: meaning-changed
Original:  Moreover, the interaction is governed by the charge pattern: negatively charged regions in the destabilizing StpA N-terminal affect a few specific positions in the RNA, located in stems and in the pseudoknot.
Revised:  Moreover, the interactions are strongly associated with the charge pattern: negatively charged regions in the destabilizing StpA N-terminal affect a few specific positions in the RNA, located in stems and in the pseudoknot.
Edit intent: clarity
Original:  By adapting direct coupling analysis (DCA) to\betaDCA  treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Revised:  We adapted direct coupling analysis (DCA) to\betaDCA treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Edit intent: fluency
Original:  By adapting direct coupling analysis (DCA) to\betaDCA  treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Revised:  By adapting direct coupling analysis (DCA) into the \alpha\betaDCA treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Edit intent: meaning-changed
Original:  By adapting direct coupling analysis (DCA) to\betaDCA  treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Revised:  By adapting direct coupling analysis (DCA) to\betaDCA method that can treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Edit intent: meaning-changed
Original:  By adapting direct coupling analysis (DCA) to\betaDCA  treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Revised:  By adapting direct coupling analysis (DCA) to\betaDCA treat in tandem sequences written in two alphabets, nucleotides and amino acids . With \alpha\betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Edit intent: meaning-changed
Original:  By adapting direct coupling analysis (DCA) to\betaDCA  treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Revised:  By adapting direct coupling analysis (DCA) to\betaDCA treat in tandem sequences written in two alphabets, nucleotides and amino acids \betaDCA , we could analyze StpA-RNA interactions and show consistency with a previously proposed two-pronged mechanism: StpA disrupts specific positions in the group I intron while globally and loosely binding to the entire structure.
Edit intent: fluency
Original:   Applying the proposed technique to clinical time series data, we discover variables that commonly-used LSTM models do not rely on for their prediction, especially when the LSTM is trained to be adversarially robust  .
Revised:  We theoretically analyze the correctness of the algorithm and the structure of the solutions. Applying the proposed technique to clinical time series data, we discover variables that commonly-used LSTM models do not rely on for their prediction, especially when the LSTM is trained to be adversarially robust .
Edit intent: meaning-changed
Original:   Applying the proposed technique to clinical time series data, we discover variables that commonly-used LSTM models do not rely on for their prediction, especially when the LSTM is trained to be adversarially robust  .
Revised:  Applying the proposed technique to clinical time series data, we discover variables that commonly-used LSTM models do not rely on for their prediction, especially when the LSTM is trained to be adversarially robust . We also analyze the invariances of BioBERT on clinical notes and discover words that it is invariant to .
Edit intent: meaning-changed
Original: Natural language systems often rely on a single, potentially ambiguous input to make one final prediction, which may simplify the problem but degrade end user experience. Instead of making predictions with the natural languagequery only, we ask the user for additional information using a small number of binary and multiple-choice questionsin order to better help users accomplish their goals while minimizing their effort .
Revised: We study the potential for interaction in natural language classification. We add a limited form of interaction for intent classification, where users provide an initial query using natural language, and the system asks for additional information using a small number of binary and multiple-choice questionsin order to better help users accomplish their goals while minimizing their effort .
Edit intent: coherence
Original:  Our approach enables bootstrapping the system using simple crowdsourcing annotations without expensive human-to-human interaction data. Evaluation demonstrates that our method substantially increases classification accuracy, while effectively balancing the number of questions with the improvement to final accuracy .
Revised:  The simplicity of the model allows for bootstrapping of the system without interaction data, instead relying on simple crowdsourcing tasks. We evaluate our approach on two domains, showing the benefit of interaction and the advantage of learning to balance between asking additional questions and making the final prediction .
Edit intent: clarity
Original:  When the potential outcome is a linear function of a unit effect, a time effect, and observed discrete covariates, we provide an analytically feasible solution to the  design problem where the variance of the estimator for the treatment effect is at most 1+O(1/N^2) times the variance of the optimal design, where N is the number of units.
Revised:  When the potential outcome is a linear function of unit and time effects, and discrete observed/latent covariates, we provide an analytically feasible solution to the design problem where the variance of the estimator for the treatment effect is at most 1+O(1/N^2) times the variance of the optimal design, where N is the number of units.
Edit intent: clarity
Original:  When the potential outcome is a linear function of a unit effect, a time effect, and observed discrete covariates, we provide an analytically feasible solution to the  design problem where the variance of the estimator for the treatment effect is at most 1+O(1/N^2) times the variance of the optimal design, where N is the number of units.
Revised:  When the potential outcome is a linear function of a unit effect, a time effect, and observed discrete covariates, we provide an analytically feasible solution to the optimal treatment design problem where the variance of the estimator for the treatment effect is at most 1+O(1/N^2) times the variance of the optimal design, where N is the number of units.
Edit intent: fluency
Original:  When the potential outcome is a linear function of a unit effect, a time effect, and observed discrete covariates, we provide an analytically feasible solution to the  design problem where the variance of the estimator for the treatment effect is at most 1+O(1/N^2) times the variance of the optimal design, where N is the number of units.
Revised:  When the potential outcome is a linear function of a unit effect, a time effect, and observed discrete covariates, we provide an analytically feasible solution to the design problem where the variance of the treatment effect estimator is at most 1+O(1/N^2) times the variance of the optimal design, where N is the number of units.
Edit intent: clarity
Original:  When the potential outcome is a linear function of a unit effect, a time effect, and observed discrete covariates, we provide an analytically feasible solution to the  design problem where the variance of the estimator for the treatment effect is at most 1+O(1/N^2) times the variance of the optimal design, where N is the number of units.
Revised:  When the potential outcome is a linear function of a unit effect, a time effect, and observed discrete covariates, we provide an analytically feasible solution to the design problem where the variance of the estimator for the treatment effect is at most 1+O(1/N^2) times the variance using the optimal treatment design, where N is the number of units.
Edit intent: clarity
Original:  This solution assigns units in a staggered treatment adoption pattern , where the proportion treated is a linear function of time .
Revised:  This solution assigns units in a staggered treatment adoption pattern - if the treatment only affects one period, the optimal fraction of treated units in each period increases linearly in time; if the treatment affects multiple periods, the optimal fraction increases non-linearly in time, smaller at the beginning and larger at the end .
Edit intent: meaning-changed
Original:  We demonstrate that our approach improves upon benchmark experimental designs through synthetic experiments on real-world data sets from several domains, including healthcare, finance, and retail. Finally, we consider the case where the treatment effect changes with the time of treatment, showing that the optimal design treats a smaller fraction of units at the beginning and a greater share at the end .
Revised:  We demonstrate that our approach improves upon benchmark experimental designs via synthetic interventions on the influenza occurrence rate and synthetic experiments on interventions for in-home medical services and grocery expenditure .
Edit intent: meaning-changed
Original:  In particular, we measure the time-varying degree of market efficiency using new datasets of the stock price index estimated by Hirayama (2017a,b, 2018, 2019a  ).
Revised:  In particular, we measure the time-varying degree of market efficiency using new datasets of the stock price index estimated by Hirayama (2017a,b, 2018, 2019a , 2020 ).
Edit intent: meaning-changed
Original:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004)  AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old /new TSE shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Revised:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variations corresponded with major historical events, (2) Lo's (2004) AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old /new TSE shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Edit intent: fluency
Original:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004)  AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old /new TSE shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Revised:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004) the AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old /new TSE shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Edit intent: fluency
Original:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004)  AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old /new TSE shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Revised:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004) AMH is supported in the prewar Japanese stock market, (3) the differences in market efficiency between the old /new TSE shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Edit intent: fluency
Original:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004)  AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old /new TSE shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Revised:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004) AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old and new Tokyo Stock Exchange (TSE) shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Edit intent: clarity
Original:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004)  AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old /new TSE shares and the EQPI depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Revised:  the degree of market efficiency in the prewar Japanese stock market varied with time and that its variation corresponded with major historical events, (2) Lo's (2004) AMH is supported in the prewar Japanese stock market, (3) the difference in market efficiency between the old /new TSE shares and the equity performance index (EQPI) depends on the manner in which the price index is constructed, and (4) the price control policy beginning in the early 1930s suppressed price volatility and improved market efficiency.
Edit intent: clarity
Original:  However, little efforts have been made to develop a scalable and high-performance scheme for computing the Jaccard Similarity for today's large data sets. To address this issue, we design and implement SimilarityAtScale, the first communicationefficient distributed algorithm for computing the Jaccard Similarity.
Revised:  We design and implement SimilarityAtScale, the first communicationefficient distributed algorithm for computing the Jaccard Similarity.
Edit intent: coherence