wanyu/IteraTeR_full_sent huggingface dataset:
Original:  Using a diverse group of econometric and portfolio models across multiple datasets, we show that a majority of models achieve significantly higher Sharpe ratios and lower portfolio volatility  relative to the na\"{\i rule, even after controlling for turnover costs.
Revised:  Using a diverse group of econometric and portfolio models across multiple datasets, most models achieve higher Sharpe ratios and lower portfolio volatility relative to the na\"{\i rule, even after controlling for turnover costs.
Edit intent: clarity
Original:  Using a diverse group of econometric and portfolio models across multiple datasets, we show that a majority of models achieve significantly higher Sharpe ratios and lower portfolio volatility  relative to the na\"{\i rule, even after controlling for turnover costs.
Revised:  Using a diverse group of econometric and portfolio models across multiple datasets, we show that a majority of models achieve significantly higher Sharpe ratios and lower portfolio volatility that are statistically and economically significant relative to the na\"{\i rule, even after controlling for turnover costs.
Edit intent: meaning-changed
Original:  Using a diverse group of econometric and portfolio models across multiple datasets, we show that a majority of models achieve significantly higher Sharpe ratios and lower portfolio volatility  relative to the na\"{\i rule, even after controlling for turnover costs.
Revised:  Using a diverse group of econometric and portfolio models across multiple datasets, we show that a majority of models achieve significantly higher Sharpe ratios and lower portfolio volatility relative to the naive rule, even after controlling for turnover costs.
Edit intent: fluency
Original:  Our results suggest that there are benefits to employing more sophisticated econometric models than the sample covariance matrix, and that mean-variance strategies often outperform the na\"{\i portfolio across multiple datasets and assessment criteria.
Revised:  Our results suggest benefits to employing more sophisticated econometric models than the sample covariance matrix, and that mean-variance strategies often outperform the na\"{\i portfolio across multiple datasets and assessment criteria.
Edit intent: clarity
Original:  Our results suggest that there are benefits to employing more sophisticated econometric models than the sample covariance matrix, and that mean-variance strategies often outperform the na\"{\i portfolio across multiple datasets and assessment criteria.
Revised:  Our results suggest that there are benefits to employing more sophisticated econometric models than the sample covariance matrix, and that mean-variance strategies often outperform the naive portfolio across multiple datasets and assessment criteria.
Edit intent: fluency
Original: Visualization-oriented natural language interfaces (V-NLIs) have been explored and developed in recent years. One challenge faced by V-NLIs is in the formation of effective design decisions that usually requires a deep understanding of user queries. Learning-based approaches have shown potential in V-NLIs and reached state-of-the-art performance in various NLP tasks. However, because of the lack of sufficient training samples that cater to visual data analytics, cutting-edge techniques have rarely been employed to facilitate the development of V-NLIs. We present a new dataset, called Quda,  to help V-NLIs understand free-form natural language  .
Revised: Visualization-oriented natural language interfaces (V-NLIs) to suggest effective visualizations. However, it is challenging due to the ambiguity and complexity nature of human language. To address this challenge, we present a new dataset, called Quda, to help V-NLIs understand free-form natural language .
Edit intent: coherence
Original:  We demonstrate the usefulness of Quda in building V-NLIs by creating a prototype that makes effective design decisions for free-form user queries. We also show that Qudacan be beneficial for a wide range of applications in the visualizationcommunity by analyzing the design tasks described in academic publications .
Revised:  We demonstrate the usefulness of Quda through three applications. This work is the first attempt to construct a large-scale corpus for recognizing analytic tasks. With the release of Quda, we hope it will boost the research and development of V-NLIs in data analysis and visualization .
Edit intent: meaning-changed
Original: In causal settings, such as instrumental variable settings, it is well known that estimators based on ordinary least squares (OLS) can yield biased and non-consistent estimates of the causal parameters. This is partially overcome by two-stage least squares (TSLS) estimators. These are, under weak assumptions, consistent but do not have desirable finite sample properties: in many models, for example, they do not have finite moments. The set of K-class estimators can be seen as a non-linear interpolation between OLS and TSLS and are known to have improved finite sample properties.
Edit intent: meaning-changed
Original:  Recently, in causal discovery, invariance properties such as the moment criterion which TSLS estimators leverage have been exploited for causal structure learning: e.g., in cases, where the causal parameter is not identifiable, some structure of the non-zero components may be identified, and coverage guarantees are available.
Revised:  Recently, in causal discovery, invariance properties such as the moment criterion which two-stage least square estimator leverage have been exploited for causal structure learning: e.g., in cases, where the causal parameter is not identifiable, some structure of the non-zero components may be identified, and coverage guarantees are available.
Edit intent: meaning-changed
Original:  Our dataset is built upon the TV drama "Another Miss Oh" and it contains 16,191 QA pairs from 23,928 various length video clips, with each QA pair belonging to one of four difficulty levels.
Revised:  Our dataset is built upon the TV drama "Another Miss Oh" and it contains 17,983 QA pairs from 23,928 various length video clips, with each QA pair belonging to one of four difficulty levels.
Edit intent: meaning-changed
Original:  Additionally, we provide analyses of the dataset as well as Dual Matching Multistream model which effectively learns character-centered representations of video to answer questions about the video. We are planning to release our dataset and model publicly for research purposes and expect that our work will provide a new perspective on video story understanding research.
Revised:  Additionally, we provide analyses of the dataset as well as Dual Matching Multistream model which effectively learns character-centered representations of video to answer questions . We release our dataset and model publicly for research purposes and expect that our work will provide a new perspective on video story understanding research.
Edit intent: clarity
Original: In this paper we study a single machine scheduling problem on a set of independent jobs whose execution time is not known, but guaranteed to be either short or long , for two given processing times. At every time step, the scheduler has the possibility either to test a job, by querying a processing time oracle , which reveals its processing time , and occupies one time unit on the schedule .
Revised: In this paper we study a single machine scheduling problem on a set of independent jobs whose execution time is not known, but guaranteed to be either short or long . This information is necessary to produce the optimal schedule. However it is initially hidden to the algorithm, only the execution of a processing time oracle , which reveals its processing time , and occupies one time unit on the schedule .
Edit intent: meaning-changed
Original:  At every time step, the scheduler has the possibility either to test a job, by querying a processing time oracle , which reveals its processing time , and occupies one time unit on the schedule . Or the scheduler can execute a job, might it be previously tested or not .
Revised:  At every time step, the scheduler has the possibility either to test a job, by querying a processing time oracle , which reveals its processing time , and occupies one time unit on the schedule , therefore the algorithm must decide for which jobs it will call the processing time oracle .
Edit intent: meaning-changed
Original:  In both models we provide optimal polynomial time two-phase algorithms, which consist of a first phase where jobs are tested, and a second phase where jobs are executed untested . Experiments give strong evidence that optimal algorithms have this structure.
Revised:  In both models we provide optimal polynomial time two-phase algorithms, which consist of a first phase where jobs are tested, and a second phase where jobs are executed obliviously . Experiments give strong evidence that optimal algorithms have this structure.
Edit intent: clarity
Original:   For this model system, we find that random stimulation produces stable oscillations relatively often. In our model system, self-sustained patterns of excitation are generated with some frequency by random stimulation, leading us to suggest that such patterns could appear spontaneously in living tissue , either cardiac or neural, with negative consequences .
Revised:  For this model , even random spots of stimulation result in periodic rotating patterns relatively often, leading us to suggest that such patterns could appear spontaneously in living tissue , either cardiac or neural, with negative consequences .
Edit intent: clarity
Original:  In our model system, self-sustained patterns of excitation are generated with some frequency by random stimulation, leading us to suggest that such patterns could appear spontaneously in living tissue , either cardiac or neural, with negative consequences .
Revised:  In our model system, self-sustained patterns of excitation are generated with some frequency by random stimulation, leading us to suggest that this could happen in living tissue , either cardiac or neural, with negative consequences .
Edit intent: clarity
Original:  Finally we study the behavior of the ratio infected over swabs , and we show as studying this parameter we recover the generalized Logistic model used in [1]  . We think that this trend could be useful for a future epidemic of this coronavirus.
Revised:  Finally we study the behavior of the ratio infected over swabs for Italy, Germany and USA, and we show as studying this parameter we recover the generalized Logistic model used in [1] . We think that this trend could be useful for a future epidemic of this coronavirus.
Edit intent: meaning-changed
Original:  Finally we study the behavior of the ratio infected over swabs , and we show as studying this parameter we recover the generalized Logistic model used in [1]  . We think that this trend could be useful for a future epidemic of this coronavirus.
Revised:  Finally we study the behavior of the ratio infected over swabs , and we show as studying this parameter we recover the generalized Logistic model used in [1] for these three countries . We think that this trend could be useful for a future epidemic of this coronavirus.
Edit intent: meaning-changed
Original:  Using an open-source co-optimization model of the power sector and four supply chains for hydrogen at filling stations, we find a trade-off between energy efficiency and temporal flexibility: for lower shares of renewables and hydrogen, more energy-efficient decentralized electrolysis is optimal.
Revised:  Using an open-source co-optimization model of the power sector and four options for supplying hydrogen at German filling stations, we find a trade-off between energy efficiency and temporal flexibility: for lower shares of renewables and hydrogen, more energy-efficient decentralized electrolysis is optimal.
Edit intent: clarity
Original:  Using an open-source co-optimization model of the power sector and four supply chains for hydrogen at filling stations, we find a trade-off between energy efficiency and temporal flexibility: for lower shares of renewables and hydrogen, more energy-efficient decentralized electrolysis is optimal.
Revised:  Using an open-source co-optimization model of the power sector and four supply chains for hydrogen at filling stations, we find a trade-off between energy efficiency and temporal flexibility: for lower shares of renewables and hydrogen, more energy-efficient and less flexible small-scale on-site electrolysis is optimal.
Edit intent: meaning-changed
Original: Danish is a North Germanic/Scandinavian language spoken primarily in Denmark, a country with a tradition of technological and scientific innovation. However, from a technological perspective, the Danish language has received relatively little attention and, as a result, Danish language technology is hard to develop, in part due to a lack of large or broad-coverage Danish corpora .
Revised: Danish language technology has been hindered by a lack of broad-coverage Danish corpora .
Edit intent: clarity
Original:  However, from a technological perspective, the Danish language has received relatively little attention and, as a result, Danish language technology is hard to develop, in part due to a lack of large or broad-coverage Danish corpora .
Revised:  However, from a technological perspective, the Danish language has received relatively little attention and, as a result, Danish language technology is hard to develop, in part due to a lack of large or broad-coverage corpora at the scale modern NLP prefers .
Edit intent: meaning-changed
Original:  This paper describes the Danish Gigaword project, which aims to construct a freely-available one billion word corpus of Danish text that represents the breadth of the written language .
Revised:  This paper describes the Danish Gigaword project, which aims to construct a freely-available one billion word corpus of Danish text . The Danish Gigaword corpus covers a wide array of time periods, domains, speakers' socio-economic status, and Danish dialects .
Edit intent: meaning-changed
Original: In response to the coronavirus disease (COVID-19) outbreak , there is an ever-increasing number of national governments that are rolling out contact-tracing Apps to aid the containment of the virus.
Revised: To address the massive spike in uncertainties triggered by the coronavirus disease (COVID-19) outbreak , there is an ever-increasing number of national governments that are rolling out contact-tracing Apps to aid the containment of the virus.
Edit intent: meaning-changed
Original:  The first hugely contentious issue facing the Apps is the deployment framework, i.e. centralised or decentralised . Based on this, the debate branches out to the corresponding technologies that underpin these architectures, i.e. GPS, QR codes, and Bluetooth.
Revised:  The first hugely contentious issue facing the Apps is the deployment framework, i.e. centralized or decentralized . Based on this, the debate branches out to the corresponding technologies that underpin these architectures, i.e. GPS, QR codes, and Bluetooth.
Edit intent: clarity
Original: In Canada, financial advisors and dealers  by provincial securities commissions , and those URLanizations charged with direct regulation over investment dealers and mutual fund dealers, respectively to collect and maintain Know Your Client (KYC) information, such as their age or risk tolerance, for investor accounts.
Revised: In Canada, financial advisors and dealers are required by provincial securities commissions , and those URLanizations charged with direct regulation over investment dealers and mutual fund dealers, respectively to collect and maintain Know Your Client (KYC) information, such as their age or risk tolerance, for investor accounts.
Edit intent: clarity
Original: In Canada, financial advisors and dealers  by provincial securities commissions , and those URLanizations charged with direct regulation over investment dealers and mutual fund dealers, respectively to collect and maintain Know Your Client (KYC) information, such as their age or risk tolerance, for investor accounts.
Revised: In Canada, financial advisors and dealers by provincial securities commissions and URLanizations--charged with direct regulation over investment dealers and mutual fund dealers, respectively to collect and maintain Know Your Client (KYC) information, such as their age or risk tolerance, for investor accounts.
Edit intent: clarity
Original: In Canada, financial advisors and dealers  by provincial securities commissions , and those URLanizations charged with direct regulation over investment dealers and mutual fund dealers, respectively to collect and maintain Know Your Client (KYC) information, such as their age or risk tolerance, for investor accounts.
Revised: In Canada, financial advisors and dealers by provincial securities commissions , and those URLanizations charged with direct regulation over investment dealers and mutual fund dealers--to respectively collect and maintain Know Your Client (KYC) information, such as their age or risk tolerance, for investor accounts.
Edit intent: fluency
Original:  Unlike gene expression methods  that capture aging-specific information but study genes in isolation, or protein-protein interaction (PPI) network methods  that account for PPIs but the PPIs are context-unspecific, we recently integrated the two data types into an aging-specific PPI subnetwork, which yielded more accurate aging-related gene predictions.
Revised:  Unlike gene expression methods for this task that capture aging-specific information but study genes in isolation, or protein-protein interaction (PPI) network methods that account for PPIs but the PPIs are context-unspecific, we recently integrated the two data types into an aging-specific PPI subnetwork, which yielded more accurate aging-related gene predictions.
Edit intent: clarity
Original:  Unlike gene expression methods  that capture aging-specific information but study genes in isolation, or protein-protein interaction (PPI) network methods  that account for PPIs but the PPIs are context-unspecific, we recently integrated the two data types into an aging-specific PPI subnetwork, which yielded more accurate aging-related gene predictions.
Revised:  Unlike gene expression methods that capture aging-specific information but ignore interactions between genes (i.e., their protein products), or protein-protein interaction (PPI) network methods that account for PPIs but the PPIs are context-unspecific, we recently integrated the two data types into an aging-specific PPI subnetwork, which yielded more accurate aging-related gene predictions.
Edit intent: meaning-changed
Original:  Unlike gene expression methods  that capture aging-specific information but study genes in isolation, or protein-protein interaction (PPI) network methods  that account for PPIs but the PPIs are context-unspecific, we recently integrated the two data types into an aging-specific PPI subnetwork, which yielded more accurate aging-related gene predictions.
Revised:  Unlike gene expression methods that capture aging-specific information but study genes in isolation, or protein-protein interaction (PPI) network methods for this task that account for PPIs but the PPIs are context-unspecific, we recently integrated the two data types into an aging-specific PPI subnetwork, which yielded more accurate aging-related gene predictions.
Edit intent: meaning-changed
Original:  So, here, we propose computational advances towards improving prediction accuracy from a dynamic aging-specific subnetwork . We develop a supervised learning model that when applied to a dynamic subnetwork yields extremely high prediction performance, with F-score of 91.4\%, while the best model on any static subnetwork yields F-score of "only" 74.3\%. Hence, our predictive model could guide with high confidence the discovery of novel aging-related gene candidates for future wet lab validation .
Revised:  So, here, we propose computational advances towards improving prediction accuracy from a dynamic aging-specific subnetwork using a methodologically more advanced notion of network propagation (NP), which improved upon Induced dynamic aging-specific subnetwork in a different task, that of unsupervised analyses of the aging process. Here, we evaluate whether our existing NP-based dynamic subnetwork will improve upon the dynamic as well as static subnetwork constructed by the Induced approach in the considered task of supervised prediction of aging-related gene candidates for future wet lab validation .
Edit intent: meaning-changed
Original:  Hence, our predictive model could guide with high confidence the discovery of novel aging-related gene candidates for future wet lab validation .
Revised:  Hence, our predictive model could guide with high confidence the discovery of novel aging-related genes. The existing NP-based subnetwork is unweighted, i.e., it gives equal importance to each of the aging-specific PPIs. Because accounting for aging-specific edge weights might be important, we additionally propose a weighted NP-based dynamic aging-specific subnetwork. We demonstrate that a predictive machine learning model trained and tested on the weighted subnetwork yields higher accuracy when predicting aging-related genes than predictive models run on the existing unweighted dynamic or static subnetworks, regardless of whether the existing subnetworks were inferred using NP or the Induced approach .
Edit intent: meaning-changed
Original: State-of-the-art neural network models have achieved dizzyingly low perplexity scores on major language modeling benchmarks, but it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge.
Revised: While state-of-the-art neural network models have achieved dizzyingly low perplexity scores on major language modeling benchmarks, but it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge.
Edit intent: coherence
Original: State-of-the-art neural network models have achieved dizzyingly low perplexity scores on major language modeling benchmarks, but it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge.
Revised: State-of-the-art neural network models continue to achieve lower perplexity scores on major language modeling benchmarks, but it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge.
Edit intent: clarity
Original: State-of-the-art neural network models have achieved dizzyingly low perplexity scores on major language modeling benchmarks, but it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge.
Revised: State-of-the-art neural network models have achieved dizzyingly low perplexity scores on language modeling benchmarks, but it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge.
Edit intent: clarity
Original: State-of-the-art neural network models have achieved dizzyingly low perplexity scores on major language modeling benchmarks, but it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge.
Revised: State-of-the-art neural network models have achieved dizzyingly low perplexity scores on major language modeling benchmarks, it remains unknown whether optimizing for broad-coverage predictive performance leads to human-like syntactic knowledge.
Edit intent: coherence