wanyu/IteraTeR_full_sent huggingface dataset:
Original:  However, the deployment and execution costs of a smart contract strictly depend on the  choices done by developers while implementing it . Unappropriated design choices -- e.g., in the data structures and the specific instructions used -- could lead to higher gas consumption than necessary.
Revised:  However, the deployment and execution costs of a smart contract depend on the choices done by developers while implementing it . Unappropriated design choices -- e.g., in the data structures and the specific instructions used -- could lead to higher gas consumption than necessary.
Edit intent: coherence
Original:  However, the deployment and execution costs of a smart contract strictly depend on the  choices done by developers while implementing it . Unappropriated design choices -- e.g., in the data structures and the specific instructions used -- could lead to higher gas consumption than necessary.
Revised:  However, the deployment and execution costs of a smart contract strictly depend on the implementation choices done by developers while implementing it . Unappropriated design choices -- e.g., in the data structures and the specific instructions used -- could lead to higher gas consumption than necessary.
Edit intent: fluency
Original:  However, the deployment and execution costs of a smart contract strictly depend on the  choices done by developers while implementing it . Unappropriated design choices -- e.g., in the data structures and the specific instructions used -- could lead to higher gas consumption than necessary.
Revised:  However, the deployment and execution costs of a smart contract strictly depend on the choices done by developers . Unappropriated design choices -- e.g., in the data structures and the specific instructions used -- could lead to higher gas consumption than necessary.
Edit intent: clarity
Original:  However, the deployment and execution costs of a smart contract strictly depend on the  choices done by developers while implementing it . Unappropriated design choices -- e.g., in the data structures and the specific instructions used -- could lead to higher gas consumption than necessary.
Revised:  However, the deployment and execution costs of a smart contract strictly depend on the choices done by developers while implementing it . Unappropriated design choices could lead to higher gas consumption than necessary.
Edit intent: coherence
Original:  In this paper, we systematically identify a set of 20 Solidity code smells that could affect the deployment and transaction costs of a smart contract, i. e.,\textit{cost smells .
Revised:  In this paper, we (i) identify a set of 20 Solidity code smells that could affect the deployment and transaction costs of a smart contract, i. e.,\textit{cost smells .
Edit intent: clarity
Original:  In this paper, we systematically identify a set of 20 Solidity code smells that could affect the deployment and transaction costs of a smart contract, i. e.,\textit{cost smells .
Revised:  In this paper, we systematically identify a set of 19 Solidity code smells that could affect the deployment and transaction costs of a smart contract, i. e.,\textit{cost smells .
Edit intent: meaning-changed
Original:  In this paper, we systematically identify a set of 20 Solidity code smells that could affect the deployment and transaction costs of a smart contract, i. e.,\textit{cost smells .
Revised:  In this paper, we systematically identify a set of 20 Solidity code smells affecting the deployment and transaction costs of a smart contract, i. e.,\textit{cost smells .
Edit intent: clarity
Original:  In this paper, we systematically identify a set of 20 Solidity code smells that could affect the deployment and transaction costs of a smart contract, i. e.,\textit{cost smells .
Revised:  In this paper, we systematically identify a set of 20 Solidity code smells that could affect the deployment and transaction costs of a smart contract, i. e.,\textit{cost smells and (ii) assess the relevance of such smells through a survey involving 34 participants.
Edit intent: meaning-changed
Original:  In an experiment involving 2,186 real-world smart contracts , we demonstrate that the proposed metrics (i) have direct associations with deployment costs , and (ii) they could be used to properly identify the level of gas consumption of a smart contract without the need for deploying it .
Revised:  An experiment involving 2,186 real-world smart contracts , we demonstrate that the proposed metrics (i) have direct associations with deployment costs , and (ii) they could be used to properly identify the level of gas consumption of a smart contract without the need for deploying it .
Edit intent: fluency
Original:  In an experiment involving 2,186 real-world smart contracts , we demonstrate that the proposed metrics (i) have direct associations with deployment costs , and (ii) they could be used to properly identify the level of gas consumption of a smart contract without the need for deploying it .
Revised:  In an experiment involving 2,186 smart contracts demonstrates that the proposed metrics (i) have direct associations with deployment costs , and (ii) they could be used to properly identify the level of gas consumption of a smart contract without the need for deploying it .
Edit intent: clarity
Original:  In an experiment involving 2,186 real-world smart contracts , we demonstrate that the proposed metrics (i) have direct associations with deployment costs , and (ii) they could be used to properly identify the level of gas consumption of a smart contract without the need for deploying it .
Revised:  In an experiment involving 2,186 real-world smart contracts , we demonstrate that the proposed metrics have direct associations with deployment costs , and (ii) they could be used to properly identify the level of gas consumption of a smart contract without the need for deploying it .
Edit intent: fluency
Original:  In an experiment involving 2,186 real-world smart contracts , we demonstrate that the proposed metrics (i) have direct associations with deployment costs , and (ii) they could be used to properly identify the level of gas consumption of a smart contract without the need for deploying it .
Revised:  In an experiment involving 2,186 real-world smart contracts , we demonstrate that the proposed metrics (i) have direct associations with deployment costs . The metrics in our suite can be used for more easily identifying source code segments that need optimizations .
Edit intent: meaning-changed
Original:  We provide new econometric results showing identification of a large class of models that includes our household model. We cover fixed-T panel models  where the response variable is an unknown monotonic function of a linear latent variable with fixed effects, regressors, and a nonparametric error term .
Revised:  We provide new econometric results showing identification of a large class of fixed-T panel models where the response variable is an unknown monotonic function of a linear latent variable with fixed effects, regressors, and a nonparametric error term .
Edit intent: clarity
Original:  We cover fixed-T panel models  where the response variable is an unknown monotonic function of a linear latent variable with fixed effects, regressors, and a nonparametric error term .
Revised:  We cover fixed-T panel models where the response variable is an unknown , weakly monotone, time-varying transformation of a latent linear index of fixed effects, regressors, and a nonparametric error term .
Edit intent: meaning-changed
Original:  We cover fixed-T panel models  where the response variable is an unknown monotonic function of a linear latent variable with fixed effects, regressors, and a nonparametric error term . The function may be weakly monotonic and time-varying, and the fixed effects are unrestricted. We identify the structural parameters and features of the distribution of  fixed effects.
Revised:  We cover fixed-T panel models where the response variable is an unknown monotonic function of a linear latent variable with fixed effects, regressors, and an error term drawn from an unknown stationary distribution. Our results identify the transformation, the coefficient on regressors, and features of the distribution of fixed effects.
Edit intent: meaning-changed
Original:  In our household model, these correspond to features of the distribution of resource shares . Using Bangladeshi data, we show : women's resource shares decline with household budgets ;
Revised:  In our household model, where the implied quantity demand equations are time-varying functions of a linear index. The fixed effects in this index equal logged resource shares, defined as the fractions of household expenditure enjoyed by each household member . Using Bangladeshi data, we show : women's resource shares decline with household budgets ;
Edit intent: meaning-changed
Original:  In our household model, these correspond to features of the distribution of resource shares . Using Bangladeshi data, we show : women's resource shares decline with household budgets ; and , half the variation in women's resource shares is due to unobserved  heterogeneity.
Revised:  In our household model, these correspond to features of the distribution of resource shares . Using Bangladeshi data, we show : women's resource shares decline with household budgets and that half of the variation in women's resource shares is due to unobserved heterogeneity.
Edit intent: coherence
Original:  The recently proposed machine learning algorithm, deep fictitious play, provides a novel efficient tool for finding Markovian Nash equilibrium of large N-player asymmetric stochastic differential games [J. Han and R. Hu, Mathematical and Scientific Machine Learning Conference,  2020].
Revised:  The recently proposed machine learning algorithm, deep fictitious play, provides a novel efficient tool for finding Markovian Nash equilibrium of large N-player asymmetric stochastic differential games [J. Han and R. Hu, Mathematical and Scientific Machine Learning Conference, pages 221-245, PMLR, 2020].
Edit intent: meaning-changed
Original:  We present a novel model in which the principal aim is to optimize graph structure to affect such targeted diffusion. We present an algorithmic approach for solving this problem at scale, using a gradient-based approach that leverages Rayleigh quotients and pseudospectrum theory.
Revised:  We present a novel model in which the principal aim is to optimize graph structure to achieve such targeted attacks. We propose an algorithm POTION-ALG for solving the model at scale, using a gradient-based approach that leverages Rayleigh quotients and pseudospectrum theory.
Edit intent: meaning-changed
Original:  This is established by analyzing linear-size cuts using techniques of Jagannath and Sen \mbox{%DIFAUXCMD jagannath2017unbalanced derived from ideas from statistical physics and analyzing small cuts via martingale inequalities.
Revised:  This is established by analyzing linear-size cuts using techniques of Jagannath-Sen '17 derived from ideas from statistical physics and analyzing small cuts via martingale inequalities.
Edit intent: clarity
Original:  We also prove that every spectral sparsifier of the clique having average degree d and a certain high "pseudo-girth" property has an approximation error that is at least the "Ramanujan bound" (2-o_{n,d}(1))/\sqrt d, which is met by d-regular Ramanujan graphs, generalizing a lower bound of Srivastava and Trevisan \mbox{%DIFAUXCMD ST18 Together, these results imply a separation between spectral sparsification and cut sparsification.
Revised:  We also prove that every spectral sparsifier of the clique having average degree d and a certain high "pseudo-girth" property has an approximation error that is at least the "Ramanujan bound" (2-o_{n,d}(1))/\sqrt d, which is met by d-regular Ramanujan graphs, generalizing a lower bound of Srivastava-Trevisan '18. Together, these results imply a separation between spectral sparsification and cut sparsification.
Edit intent: coherence
Original:  The default version is loosely calibrated to resemble a specific (but anonymous) Auto Bodily Injury portfolio  , but the general structure is suitable for most lines of business, with some amendment of modules.
Revised:  The default version is parameterized so as to include a broad (though not numerically precise) resemblance to the major features of experience of a specific (but anonymous) Auto Bodily Injury portfolio , but the general structure is suitable for most lines of business, with some amendment of modules.
Edit intent: meaning-changed
Original:  The default version is loosely calibrated to resemble a specific (but anonymous) Auto Bodily Injury portfolio  , but the general structure is suitable for most lines of business, with some amendment of modules.
Revised:  The default version is loosely calibrated to resemble a specific (but anonymous) Auto Bodily Injury portfolio . It thus reflects a number of desirable (but complicated) data features , but the general structure is suitable for most lines of business, with some amendment of modules.
Edit intent: meaning-changed
Original:  At the extremely simple end would be chain-ladder-compatible data, and so the alternative data structures available enable proposed loss reserving models to be tested against more challenging data sets. Indeed, the user may generate a collection of data sets that provide a spectrum of complexity, and the collection may be used to present a model under test with a steadily increasing challenge.
Revised:  The user may generate a collection of data sets that provide a spectrum of complexity, and the collection may be used to present a model under test with a steadily increasing challenge.
Edit intent: clarity
Original: A simulator of individual claim experience called SynthETIC is described. It is publicly available, open source and fills a gap in the non-life actuarial toolkit. It simulates, for each claim, occurrence, notification, the timing and magnitude of individual partial payments, and closure. Inflation, including (optionally) superimposed inflation, is incorporated in payments. Superimposed inflation may occur over calendar or accident periods. The claim data are summarized by accident and payment "periods" whose duration is an arbitrary choice (e. g. month, quarter, etc.) available to the user. The code is structured as eight modules (occurrence, notification, etc.), any one or more of which may be re-designed according to the user's requirements. The default version is parameterized so as to include a broad (though not numerically precise) resemblance to the major features of experience of a specific (but anonymous) Auto Bodily Injury portfolio. It thus reflects a number of desirable (but complicated) data features , but the general structure is suitable for most lines of business, with some amendment of modules.
Revised: Recent years have seen rapid increase in the application of machine learning to insurance loss reserving. They yield most value when applied to large data sets, such as individual claims, or large claim triangles. In short, they are likely to be useful in the analysis of any data set whose volume is sufficient to obscure a naked-eye view of its features. Unfortunately, such large data sets are in short supply in the actuarial literature. Accordingly, one needs to turn to synthetic data. Although the ultimate objective of these methods is application to real data, the use of synthetic data containing features commonly observed in real data is also to be encouraged. While there are a number of claims simulators in existence, each valuable within its own context, the inclusion of a number of desirable (but complicated) data features , but the general structure is suitable for most lines of business, with some amendment of modules.
Edit intent: meaning-changed
Original:  It thus reflects a number of desirable (but complicated) data features , but the general structure is suitable for most lines of business, with some amendment of modules. The structure of the simulator enables the inclusion of a number of important dependencies between the variables related to an individual claim , e. g. dependence of notification delay on claim size, of the size of a partial payment on the sizes of those preceding, etc .
Revised:  It thus reflects a number of desirable (but complicated) data features requires further development. Accordingly, in this paper we review those desirable features, and propose a new simulator of individual claim experience called SynthETIC. Our simulator is publicly available, open source, and fills a gap in the non-life actuarial toolkit. The simulator specifically allows for desirable (but optionally complicated) data features typically occurring in practice, such as variations in rates of settlements and development patterns; as with superimposed inflation, and various discontinuities, and also enables various dependencies between variables .
Edit intent: meaning-changed
Original:  As a result, the complexity of the data set generated (meaning the level of difficulty of analysis) may be dialled anywhere from extremely simple to extremely complex . The user may generate a collection of data sets that provide a spectrum of complexity, and the collection may be used to present a model under test with a steadily increasing challenge .
Revised:  As a result, the complexity of the data set generated (meaning the level of difficulty of analysis) may be dialled anywhere from extremely simple to extremely complex .
Edit intent: coherence
Original:  In the dense graph model, a similar picture is long known (Alon, Fisher , Krivelevich, Szegedy, Combinatoria 2000), despite the very different nature of the two models.
Revised:  In the dense graph model, a similar picture is long known (Alon, Fischer , Krivelevich, Szegedy, Combinatoria 2000), despite the very different nature of the two models.
Edit intent: fluency
Original:  In the dense graph model, a similar picture is long known (Alon, Fisher , Krivelevich, Szegedy, Combinatoria 2000), despite the very different nature of the two models.
Revised:  In the dense graph model, a similar picture is long known (Alon, Fisher , Krivelevich, Szegedy, Combinatorica 2000), despite the very different nature of the two models.
Edit intent: fluency
Original:  The corresponding decision problem, that asks whether a given graph is Hamiltonian (i. e. admits a Hamiltonian cycle), is one of Karp's famous NP-complete problems.
Revised:  The corresponding decision problem, that asks whether a given graph is Hamiltonian (i. \,e.\ admits a Hamiltonian cycle), is one of Karp's famous NP-complete problems.
Edit intent: fluency
Original:  In this paper we study graphs of bounded degree that are far from being Hamiltonian, where a graph G on n vertices is far from being Hamiltonian, if modifying a constant fraction of n edges is necessary to make G Hamiltonian.
Revised:  In this paper we study graphs of bounded degree that are far from being Hamiltonian, where a graph G on n vertices is far from being Hamiltonian, if modifying a constant fraction of n edges is necessary to make G Hamiltonian.
Edit intent: fluency
Original:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, i. e.  every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian.
Revised:  We give an explicit deterministic construction of a class of graphs of bounded degree that are locally Hamiltonian, i. e. every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian.
Edit intent: meaning-changed
Original:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, i. e.  every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian.
Revised:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, but (globally) far from being Hamiltonian. Here, every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian.
Edit intent: meaning-changed
Original:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, i. e.  every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian.
Revised:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, i. e.locally Hamiltonian every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian.
Edit intent: meaning-changed
Original:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, i. e.  every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian.
Revised:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, i. e. means that every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian.
Edit intent: meaning-changed
Original:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, i. e.  every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph , but that are far from being Hamiltonian. We then use these classes to obtain a lower bound in property testing. We show that in the bounded-degree graphmodel, Hamiltonicity is not testable with one-sided error probability and query complexity o(n) . This contrasts the known fact that on planar (or minor-free) graph classes, Hamiltonicity is testable with constant query complexity in the bounded-degree graph model with two-sided error .
Revised:  We exhibit classes of graphs of bounded degree that are locally Hamiltonian, i. e. every subgraph induced by the neighbourhood of a small vertex set appears in some Hamiltonian graph . More precisely, we obtain graphs which differ in \Theta(n) edges from any Hamiltonian graph, but non-Hamiltonicity cannot be detected in the neighbourhood of o(n) . This contrasts the known fact that on planar (or minor-free) graph classes, Hamiltonicity is testable with constant query complexity in the bounded-degree graph model with two-sided error .
Edit intent: meaning-changed
Original:  We show that in the bounded-degree graphmodel, Hamiltonicity is not testable with one-sided error probability and query complexity o(n) . This contrasts the known fact that on planar (or minor-free) graph classes, Hamiltonicity is testable with constant query complexity in the bounded-degree graph model with two-sided error .
Revised:  We show that in the bounded-degree graphmodel, Hamiltonicity is not testable with one-sided error probability and query complexity o(n) vertices. Our class of graphs yields a class of hard instances for one-sided error property testers with linear query complexity. It is known that any property tester (even with two-sided error .
Edit intent: meaning-changed