wanyu/IteraTeR_full_sent huggingface dataset:
Original:  The empirical results reveal that (1) the joint degree of market efficiency in the prewar Japanese stock market fluctuated over time because of external events such as policy changes and wars, (2) the semi-strong form EMH is almost supported in the prewar Japanese stock market, and (3) the markets rapidly reflect the information of the external events through time. Therefore, we conclude that Lo's (2004) adaptive market hypothesis is supported in the prewar Japanese stock market even if we consider that the public information affects the stock market.
Revised:  The empirical results reveal that (1) the joint degree of market efficiency in the prewar Japanese stock market fluctuated over time because of external events such as policy changes and wars, (2) the semi-strong form EMH is almost supported in the prewar Japanese stock market, and (3) Lo's (2004) adaptive market hypothesis is supported in the prewar Japanese stock market even if we consider that the public information affects the stock market.
Edit intent: coherence
Original:  Therefore, we conclude that Lo's (2004) adaptive market hypothesis is supported in the prewar Japanese stock market even if we consider that the public information affects the stock market.
Revised:  Therefore, we conclude that Lo's (2004) adaptive market hypothesis is supported in the prewar Japanese stock market even if we consider that the public information affects the financial markets, and (4) the prewar Japanese financial markets lost the price formation function in 1932 and that was a turning point in the market.
Edit intent: meaning-changed
Original:  The model attempts to incorporate the known scope of physical factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia  .
Revised:  The model employs basic concepts from fluid dynamics and incorporates the known scope of physical factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia .
Edit intent: meaning-changed
Original:  The model attempts to incorporate the known scope of physical factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia  .
Revised:  The model attempts to incorporate the known scope of factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia .
Edit intent: clarity
Original:  The model attempts to incorporate the known scope of physical factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia  .
Revised:  The model attempts to incorporate the known scope of physical factors involved in the airborne transmission of such diseases . Simplicity in the mathematical form of the model is by design, so that it can serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia .
Edit intent: coherence
Original:  The model attempts to incorporate the known scope of physical factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia  .
Revised:  The model attempts to incorporate the known scope of physical factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but , also be understandable by a broad audience outside science and academia .
Edit intent: fluency
Original:  The model attempts to incorporate the known scope of physical factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia  .
Revised:  The model attempts to incorporate the known scope of physical factors involved in the airborne transmission of such diseases , and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia . The model is used to assess the protection from transmission afforded by face coverings made from a variety of fabrics. In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity of the host and/or the susceptible in enhancing transmission risk, is also examined .
Edit intent: meaning-changed
Original:  Simplicity in the mathematical form of the model is by design, so that it can serve not only as a common basis for scientific inquiry across disciplinary boundaries, but , also be understandable by a broad audience outside science and academia.
Revised:  Simplicity in the mathematical form of the model is by design, so that it can serve not only as a common basis for scientific inquiry across disciplinary boundaries, but also be understandable by a broad audience outside science and academia.
Edit intent: fluency
Original:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity  of the host and /or the susceptible in enhancing transmission risk, is also examined .
Revised:  The reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity of the host and /or the susceptible in enhancing transmission risk, is also examined .
Edit intent: coherence
Original:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity  of the host and /or the susceptible in enhancing transmission risk, is also examined .
Revised:  In addition, the reduction in transmission risk associated with increased physical distance between the host and susceptible as well as the level of physical activity of the host and /or the susceptible in enhancing transmission risk, is also examined .
Edit intent: clarity
Original:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity  of the host and /or the susceptible in enhancing transmission risk, is also examined .
Revised:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible is also quantified by coupling the model with available data on scalar dispersion in canonical flows. Finally, the effect of the level of physical activity of the host and /or the susceptible in enhancing transmission risk, is also examined .
Edit intent: meaning-changed
Original:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity  of the host and /or the susceptible in enhancing transmission risk, is also examined .
Revised:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity (or exercise intensity) of the host and /or the susceptible in enhancing transmission risk, is also examined .
Edit intent: meaning-changed
Original:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity  of the host and /or the susceptible in enhancing transmission risk, is also examined .
Revised:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity of the host and the susceptible in enhancing transmission risk, is also examined .
Edit intent: coherence
Original:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity  of the host and /or the susceptible in enhancing transmission risk, is also examined .
Revised:  In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity of the host and /or the susceptible in enhancing transmission risk, is also assessed .
Edit intent: clarity
Original:  We demonstrate a method of learning performance models from a corpus of tensor computation graph programs for the Tensor Processing Unit (TPU) . We train a neural network over kernel-level sub-graphs from the corpus and find that the learned model is competitive to a heavily-optimized analytical cost model used in the production XLA compiler .
Revised:  We demonstrate a method of learning performance models from a corpus of tensor computation graph programs for Tensor Processing Unit (TPU) . We train a neural network over kernel-level sub-graphs from the corpus and find that the learned model is competitive to a heavily-optimized analytical cost model used in the production XLA compiler .
Edit intent: fluency
Original:  We demonstrate a method of learning performance models from a corpus of tensor computation graph programs for the Tensor Processing Unit (TPU) . We train a neural network over kernel-level sub-graphs from the corpus and find that the learned model is competitive to a heavily-optimized analytical cost model used in the production XLA compiler .
Revised:  We demonstrate a method of learning performance models from a corpus of tensor computation graph programs for the Tensor Processing Unit (TPU) instances. We show that our learned model outperforms a heavily-optimized analytical cost model used in the production XLA compiler .
Edit intent: clarity
Original:  We demonstrate a method of learning performance models from a corpus of tensor computation graph programs for the Tensor Processing Unit (TPU) . We train a neural network over kernel-level sub-graphs from the corpus and find that the learned model is competitive to a heavily-optimized analytical cost model used in the production XLA compiler .
Revised:  We demonstrate a method of learning performance models from a corpus of tensor computation graph programs for the Tensor Processing Unit (TPU) . We train a neural network over kernel-level sub-graphs from the corpus and find that the learned model is competitive to a heavily-optimized analytical performance model on two tasks -- tile-size selection and operator fusion -- and that it helps an autotuner discover faster programs in a setting where access to TPUs is limited or expensive .
Edit intent: meaning-changed
Original:  Dynamical systems can be used to generate a model to predict gene expression using epigenetic data and a gene regulatory network (GRN)  . Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN. 
Revised:  Despite active research, studies to date have focused on using statistical models to predict gene expression from methylation data. In contrast, dynamical systems can be used to generate a model to predict gene expression using epigenetic data and a gene regulatory network (GRN) . Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN. 
Edit intent: meaning-changed
Original:  Dynamical systems can be used to generate a model to predict gene expression using epigenetic data and a gene regulatory network (GRN)  . Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN. 
Revised:  Dynamical systems can be used to generate a model to predict gene expression using epigenetic data and a gene regulatory network (GRN) which can also serve as a mechanistic hypothesis . Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN. 
Edit intent: meaning-changed
Original:  Dynamical systems can be used to generate a model to predict gene expression using epigenetic data and a gene regulatory network (GRN)  . Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN. 
Revised:  Dynamical systems can be used to generate a model to predict gene expression using epigenetic data and a gene regulatory network (GRN) . Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN. Software for dataset preparation, model parameter fitting and prediction generation, and reporting are available at URL
Edit intent: meaning-changed
Original:  Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN  . Software for dataset preparation, model parameter fitting and prediction generation, and reporting are available at URL
Revised:  Here we present a novel stochastic dynamical systems model that predicts gene expression levels from methylation data of genes in a given GRN . We provide an evaluation of the model using real patient data and a GRN created from robust reference sources . Software for dataset preparation, model parameter fitting and prediction generation, and reporting are available at URL
Edit intent: meaning-changed
Original:  Even though there exist numerous nonequivalent definitions of graph curvature, none is rigorously known to converge in any limit to any traditional definition of curvature of a Riemannian manifold.
Revised:  Even though there exist numerous nonequivalent definitions of graph curvature, none is known to converge in any limit to any traditional definition of curvature of a Riemannian manifold.
Edit intent: clarity
Original:  Here we show that Ollivier curvature of random geometric graphs in any Riemannian manifold converges in the continuum limit to Ricci curvature of the underlying manifold  .
Revised:  Here we show that Ollivier curvature of random geometric graphs in any Riemannian manifold converges in the continuum limit to Ricci curvature of the underlying manifold , but only if the definition of Ollivier graph curvature is properly generalized to apply to mesoscopic graph neighborhoods .
Edit intent: meaning-changed
Original:  To solve this problem, we propose Taking Notes on the Fly (TNF) . TNF takes notes for rare words on the fly during pre-training to help the model understand them when they occur next time.
Revised:  To mitigate this problem, we propose Taking Notes on the Fly (TNF) . TNF takes notes for rare words on the fly during pre-training to help the model understand them when they occur next time.
Edit intent: clarity
Original:  To solve this problem, we propose Taking Notes on the Fly (TNF) . TNF takes notes for rare words on the fly during pre-training to help the model understand them when they occur next time.
Revised:  To solve this problem, we propose Taking Notes on the Fly (TNF) , which takes notes for rare words on the fly during pre-training to help the model understand them when they occur next time.
Edit intent: coherence
Original:  In this paper, we investigate the incomplete utterance restoration since it has brought general improvement over multi-turn dialogue systems in different domains. In the task , we propose a novel semi autoregressive generator (SARG) with the high efficiency and flexibility , which is inspired by the autoregression for generation and the sequence labeling for overlapped rewriting .
Revised:  In this paper, we investigate the incomplete utterance restoration since it has brought general improvement over multi-turn dialogue systems in recent studies. Inspired by the autoregression for generation and the sequence labeling for text editing , we propose a novel semi autoregressive generator (SARG) with the high efficiency and flexibility , which is inspired by the autoregression for generation and the sequence labeling for overlapped rewriting .
Edit intent: clarity
Original: Dialogue systems in the open domain have achieved great success due to large conversation data and the development of deep learning, but  multi-turn scenarios are still a challenge because of the frequent coreference and information omission.
Revised: Dialogue systems in the open domain have achieved great success due to the easily obtained single-turn corpus and the development of deep learning, but multi-turn scenarios are still a challenge because of the frequent coreference and information omission.
Edit intent: meaning-changed
Original: Dialogue systems in the open domain have achieved great success due to large conversation data and the development of deep learning, but  multi-turn scenarios are still a challenge because of the frequent coreference and information omission.
Revised: Dialogue systems in the open domain have achieved great success due to large conversation data and the development of deep learning, but the multi-turn scenarios are still a challenge because of the frequent coreference and information omission.
Edit intent: fluency
Original: Dialogue systems in the open domain have achieved great success due to large conversation data and the development of deep learning, but  multi-turn scenarios are still a challenge because of the frequent coreference and information omission.
Revised: Dialogue systems in the open domain have achieved great success due to large conversation data and the development of deep learning, but multi-turn scenario is still a challenge because of the frequent coreference and information omission.
Edit intent: fluency
Original:  In the context of one-shot robot teaching, the contributions of the paper are: 1) to propose a framework that 1) covers various tasks in grasp-manipulation-release class household operations and 2) mimics human postures during the operations.
Revised:  In the context of one-shot robot teaching, the contributions of the paper is to propose a framework that 1) covers various tasks in grasp-manipulation-release class household operations and 2) mimics human postures during the operations.
Edit intent: fluency
Original:  We use a public database of 93 users, containing 1142 to 3209 Tweets per user. We also evaluate the influence of the number of Tweets per user for enrolment and testing. If the amount is sufficient (>500), a Rank 1 of 97-99\%is achieved.
Revised:  We use a public database of 93 and 3957 authors, respectively. We test varying sized author sets and varying amounts of training/test texts per author. Performance is further improved by feature combination via automatic selection. With a large number of training Tweets (>500), a Rank 1 of 97-99\%is achieved.
Edit intent: meaning-changed
Original:  If the amount is sufficient (>500), a Rank 1 of 97-99\%is achieved. If data is scarce (e.g. 20 Tweetsfor testing), the Rank 1 with the best individual feature method ranges from 54.9\% (100 Tweetsfor enrolment)to 70.6\% (1000 Tweets). By combining the available features, a substantial improvement is observed, reaching a Rank 1 of 70\% when using 100 Tweets for enrolment and only 20 for testing. With a bigger hit list size, accuracy of the latter case increases to 86.4\% (Rank 5) or 95\% (Rank 20). This demonstrates the feasibility of identifying writers of digital texts, even with few data available .
Revised:  If the amount is sufficient (>500), a good accuracy (Rank-5>80\%) is achievable with only a few dozens of test Tweets, even with several thousands of authors. With smaller sample sizes (10-20 training Tweets), the search space can be diminished by 9-15\% while keeping a high chance that the correct author is retrieved among the candidates. In such cases, automatic attribution can provide significant time savings to experts in suspect search. For completeness, we report verification results. With few training/test Tweets, the EER is above 20-25\%, which is reduced to < 15\% if hundreds of training Tweets are available. We also quantify the computational complexity and time permanence of the employed features .
Edit intent: meaning-changed
Original:  We identify 518 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including PPE , medicines (e.g., hydroxyclorochine), and medical frauds(e.g., vaccines).
Revised:  We identify 518 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE) , medicines (e.g., hydroxyclorochine), and medical frauds(e.g., vaccines).
Edit intent: clarity
Original:  We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs, especially when real vaccines or cures become available and  potentially in short supply.
Revised:  We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs, especially when real vaccines or cures become available and are potentially in short supply.
Edit intent: fluency
Original:  We identify 518 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds (e. g., vaccines).
Revised:  We identify 788 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds (e. g., vaccines).
Edit intent: meaning-changed
Original:  We identify 518 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds (e. g., vaccines).
Revised:  We identify 518 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds .
Edit intent: coherence
Original: Recently, Chudnovsky, Spirkl and Zhong  proved that List 3-Colouring is polynomial-time solvable for (K_{1,s}^1,P_t)-free graphs for every t\geq 1 and s\geq 1.
Revised: Recently, Chudnovsky, Spirkl and Zhong (DM 2020) proved that List 3-Colouring is polynomial-time solvable for (K_{1,s}^1,P_t)-free graphs for every t\geq 1 and s\geq 1.
Edit intent: meaning-changed
Original:  Our result also generalizes the known result that for every k\geq 1 and s\geq 0, List k-Colouring is polynomial-time solvable for (sP_1+P_5)-free graphs  .
Revised:  Our result also generalizes the known result that for every k\geq 1 and s\geq 0, List k-Colouring is polynomial-time solvable for (sP_1+P_5)-free graphs , which was proven for s=0 by Ho\`ang, Kami\'nski, Lozin, Sawada, and Shu (Algorithmica 2010) and for every s\geq 1 by Couturier, Golovach, Kratsch and Paulusma (Algorithmica 2015) .
Edit intent: meaning-changed