wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our results provide fundamental information about the nature of multi-winner rules , andin particular about the necessary tradeoffs when choosing such a rule.
Revised:  Our results provide fundamental information about the nature of multiwinner rules and, in particular, about the necessary tradeoffs when choosing such a rule.
Edit intent: fluency
Original:  Our unbiased fragment-based docking method successfully predicted the emergence of the key EFRH epitopecommonly observed when ABeta binds to anti-ABeta antibodies.
Revised:  Our unbiased fragment-based docking method successfully predicted the emergence of the common EFRH epitope,
Edit intent: clarity
Original:  Two out of our four proposed mutations stabilized binding.
Revised:  Two out of four proposed mutations stabilized binding.
Edit intent: clarity
Original:  Our study demonstrates that a computational approach can predict beneficial mutations which may lead to an improved drug candidate for AD in the future.
Revised:  Our study demonstrates that a computational approach may lead to an improved drug candidate for AD in the future.
Edit intent: clarity
Original: Deep Evolutionary Network Structured Representation (DENSER) is a novel approach to automatically design Artificial Neural Networks (ANNs) using Evolutionary Computation (EC) .
Revised: Deep Evolutionary Network Structured Representation (DENSER) is a novel approach to automatically design Artificial Neural Networks (ANNs) using Evolutionary Computation .
Edit intent: clarity
Original:  The allowed layers and hyper-parameter value ranges are defined by means of a human-readable Context-Free Grammar.
Revised:  The allowed layers and range of the hyper-parameters values are defined by means of a human-readable Context-Free Grammar.
Edit intent: clarity
Original:  DENSER was used to evolve ANNs for two widely used image classification benchmarks obtaining an average accuracy result of up to 94.27\%on the CIFAR-10 dataset, and of 78.75\% on the CIFAR-100  .
Revised:  DENSER was used to evolve ANNs for CIFAR-10, obtaining an average accuracy result of up to 94.27\%on the CIFAR-10 dataset, and of 78.75\% on the CIFAR-100 .
Edit intent: clarity
Original:  The networks evolved for the CIFAR-10 are tested on the MNIST, Fashion-MNIST, and CIFAR-100;
Revised:  The networks evolved for the CIFA--10 are tested on the MNIST, Fashion-MNIST, and CIFAR-100;
Edit intent: clarity
Original:  To the best of our knowledge, our CIFAR-100 results are the highest performing models generated by methods that aim at the automatic design of Convolutional Neural Networks (CNNs), and is amongst the best for manually designed and fine-tuned CNNs.
Revised:  To the best of our knowledge, our CIFAR-100 results are the highest performing models generated by methods that aim at the automatic design of Convolutional Neural Networks (CNNs), and are amongst the best for manually designed and fine-tuned CNNs.
Edit intent: fluency
Original: Immutable and consistent sharing of data across organization boundariesenabl es a new class of applications . Because conventional datastores cannot provide this functionality, blockchain s have been proposed as one possible solution.
Revised: Many applications require the immutable and consistent sharing of data across organization boundariesenabl es a new class of applications . Because conventional datastores cannot provide this functionality, blockchain s have been proposed as one possible solution.
Edit intent: clarity
Original: Immutable and consistent sharing of data across organization boundariesenabl es a new class of applications . Because conventional datastores cannot provide this functionality, blockchain s have been proposed as one possible solution.
Revised: Immutable and consistent sharing of data across organizational boundaries . Because conventional datastores cannot provide this functionality, blockchain s have been proposed as one possible solution.
Edit intent: clarity
Original: Immutable and consistent sharing of data across organization boundariesenabl es a new class of applications . Because conventional datastores cannot provide this functionality, blockchain s have been proposed as one possible solution.
Revised: Immutable and consistent sharing of data across organization boundariesenabl es a new class of applications . Because conventional datastores cannot provide this functionality, blockchains have been proposed as one possible solution.
Edit intent: fluency
Original:  Yet public blockchains are energy inefficient, hard to scale and suffer from limited throughput and high latencies, while permissioned blockchains depend on specially designated nodes, potentially le ak meta-information, and also suffer from scale and performance bottlenecks.
Revised:  Yet public blockchains are energy inefficient, hard to scale and suffer from limited throughput and high latencies, while permissioned blockchains depend on specially designated nodes, potentially leak meta-information, and also suffer from scale and performance bottlenecks.
Edit intent: fluency
Original:  This paper presents CreDB, a datastore that provides blockchain-like guarante es of integrity using trusted execution environments.
Revised:  This paper presents CreDB, a datastore that provides blockchain-like guarantees of integrity using trusted execution environments.
Edit intent: fluency
Original:  First, it creates a permanent record of every transaction, known as a witness, that clients can then use not only to audit the database , but to prove to thi rd parties that desired actions took place.
Revised:  First, it creates a permanent record of every transaction, known as a witness, that clients can then use not only to audit the database but to prove to thi rd parties that desired actions took place.
Edit intent: fluency
Original:  First, it creates a permanent record of every transaction, known as a witness, that clients can then use not only to audit the database , but to prove to thi rd parties that desired actions took place.
Revised:  First, it creates a permanent record of every transaction, known as a witness, that clients can then use not only to audit the database , but to prove to third parties that desired actions took place.
Edit intent: fluency
Original:  Second, it associates with every object an inseparable and inviolable securit y policy, which not only performs access control but enables the datastore to i mplement state machines whose behavior is amenable to analysis.
Revised:  Second, it associates with every object an inseparable and inviolable policy, which not only performs access control but enables the datastore to i mplement state machines whose behavior is amenable to analysis.
Edit intent: fluency
Original:  Second, it associates with every object an inseparable and inviolable securit y policy, which not only performs access control but enables the datastore to i mplement state machines whose behavior is amenable to analysis.
Revised:  Second, it associates with every object an inseparable and inviolable securit y policy, which not only performs access control but enables the datastore to implement state machines whose behavior is amenable to analysis.
Edit intent: fluency
Original: Mader (1985) proved that every strongly k-connected n-vertex digraph contains a strongly k-connected spanning subgraph with at most 2kn - 2k^2 edges, and this is sharp } . For dense strongly k-connected digraphs, the bound can be significantly improved for dense strongly k-connected digraphs.
Revised: Mader proved that every strongly k-connected n-vertex digraph contains a strongly k-connected spanning subgraph with at most 2kn - 2k^2 edges, and this is sharp } . For dense strongly k-connected digraphs, the bound can be significantly improved for dense strongly k-connected digraphs.
Edit intent: coherence
Original: Mader (1985) proved that every strongly k-connected n-vertex digraph contains a strongly k-connected spanning subgraph with at most 2kn - 2k^2 edges, and this is sharp } . For dense strongly k-connected digraphs, the bound can be significantly improved for dense strongly k-connected digraphs.
Revised: Mader (1985) proved that every strongly k-connected n-vertex digraph contains a strongly k-connected spanning subgraph with at most 2kn - 2k^2 edges, and this is sharp DK} . For dense strongly k-connected digraphs, the bound can be significantly improved for dense strongly k-connected digraphs.
Edit intent: clarity
Original: Mader (1985) proved that every strongly k-connected n-vertex digraph contains a strongly k-connected spanning subgraph with at most 2kn - 2k^2 edges, and this is sharp } . For dense strongly k-connected digraphs, the bound can be significantly improved for dense strongly k-connected digraphs.
Revised: Mader (1985) proved that every strongly k-connected n-vertex digraph contains a strongly k-connected spanning subgraph with at most 2kn - 2k^2 edges, and this is sharp } . For dense strongly k-connected digraphs, this upper bound can be significantly improved for dense strongly k-connected digraphs.
Edit intent: clarity
Original:  In particular, it follows that every strongly k-connected n-vertex semicomplete digraph contains a strongly k-connected spanning subgraph with at most kn + 800k^2 edges, improving the recent result of Kang, Kim, Kim, and Suh (2017) for tournaments and establishing the tight bound, as 800k^2 cannot be improved to the number less than k(k-1)/2.
Revised:  In particular, it follows that every strongly k-connected n-vertex semicomplete digraph contains a strongly k-connected spanning subgraph with at most kn + 800k^2 edges, which is essentially optimal since 800k^2 cannot be improved to the number less than k(k-1)/2.
Edit intent: clarity
Original:  In particular, it follows that every strongly k-connected n-vertex semicomplete digraph contains a strongly k-connected spanning subgraph with at most kn + 800k^2 edges, improving the recent result of Kang, Kim, Kim, and Suh (2017) for tournaments and establishing the tight bound, as 800k^2 cannot be improved to the number less than k(k-1)/2.
Revised:  In particular, it follows that every strongly k-connected n-vertex semicomplete digraph contains a strongly k-connected spanning subgraph with at most kn + 800k^2 edges, improving the recent result of Kang, Kim, Kim, and Suh (2017) for tournaments and establishing the tight bound, as 800k^2 cannot be reduced to the number less than k(k-1)/2.
Edit intent: clarity
Original: We introduce the simulation tool SABCEMM ( Simulate Agent-Based Computational Economic Market Models) for agent-based computational economic market (ABCEM) models.
Revised: We introduce the simulation tool SABCEMM ( Simulator for Agent-Based Computational Economic Market Models) for agent-based computational economic market (ABCEM) models.
Edit intent: clarity
Original:  Our simulation tool is implemented in C++ and we can easily run ABCEM models with up to several million agents.
Revised:  Our simulation tool is implemented in C++ and we can easily run ABCEM models with several million agents.
Edit intent: clarity
Original:  Thanks to the object-oriented software design , this tool enables the user to design and compare multiple ABCEM modelsfrom a unified perspective.
Revised:  The object-oriented software design , this tool enables the user to design and compare multiple ABCEM modelsfrom a unified perspective.
Edit intent: coherence
Original:  Finally, we show the great impact of different random number generators on the run time of ABCEM models and even on the qualitative output of the model .
Revised:  Finally, we show the great impact of different random number generators on the run time of ABCEM models .
Edit intent: clarity
Original:  The code can be downloaded from GitHub URL such that all results can be reproduced by the reader 
Revised:  The code can be downloaded from GitHub URL such that all results can be reproduced by the reader .
Edit intent: fluency
Original:  A universal and objective metric , which is crucial and necessary to evaluate qualities of nanoscopy images and performances of localization algorithms , has not yet been established.
Revised:  A universal and objective metric is crucial and necessary to evaluate qualities of nanoscopy images and performances of localization algorithms , has not yet been established.
Edit intent: clarity
Original: Tensor Train decomposition is used across many branches of machine learning , but until now it lacked an implementation with GPU support , batch processing, automatic differentiation, and versatile functionality for  Riemannian optimization framework, which takes in account the underlying manifold structure in order to construct efficient optimization methods.
Revised: Tensor Train decomposition is used across many branches of machine learning , but until now it lacked an implementation with GPU support , batch processing, automatic differentiation, and versatile functionality for the Riemannian optimization framework, which takes in account the underlying manifold structure in order to construct efficient optimization methods.
Edit intent: fluency
Original: Tensor Train decomposition is used across many branches of machine learning , but until now it lacked an implementation with GPU support , batch processing, automatic differentiation, and versatile functionality for  Riemannian optimization framework, which takes in account the underlying manifold structure in order to construct efficient optimization methods.
Revised: Tensor Train decomposition is used across many branches of machine learning , but until now it lacked an implementation with GPU support , batch processing, automatic differentiation, and versatile functionality for Riemannian optimization framework, which takes into account the underlying manifold structure in order to construct efficient optimization methods.
Edit intent: fluency
Original: Tensor Train decomposition is used across many branches of machine learning , but until now it lacked an implementation with GPU support , batch processing, automatic differentiation, and versatile functionality for  Riemannian optimization framework, which takes in account the underlying manifold structure in order to construct efficient optimization methods.
Revised: Tensor Train decomposition is used across many branches of machine learning , but until now it lacked an implementation with GPU support , batch processing, automatic differentiation, and versatile functionality for Riemannian optimization framework, which takes in account the underlying manifold structure to construct efficient optimization methods.
Edit intent: coherence
Original:  In this work, we propose a library that aims to fix it and makes machine learning papers that rely on  Tensor Train decomposition easier to implement.
Revised:  The library makes it easier to implement machine learning papers that rely on Tensor Train decomposition easier to implement.
Edit intent: coherence
Original:  In this work, we propose a library that aims to fix it and makes machine learning papers that rely on  Tensor Train decomposition easier to implement.
Revised:  In this work, we propose a library that aims to fix it and makes machine learning papers that rely on the Tensor Train decomposition easier to implement.
Edit intent: fluency
Original:  The objective is to jointly minimize the stall / skip duration of the video, maximize the average quality, and minimize the number of quality switches .
Revised:  The objective is to to optimize a QoE metric that maintains a tradeoff between maximizing the playback rate of every chunk and ensuring fairness among chunks. The QoE is a weighted some of the following metrics: skip / skip duration of the video, maximize the average quality, and minimize the number of quality switches .
Edit intent: clarity
Original: We propose two numerical algorithms for minimizing the sum of a smooth function and the composition of a nonsmooth function with a linear operator in the fully nonconvex setting .
Revised: We propose two numerical algorithms in the fully nonconvex setting for the minimization of the sum of a smooth function and the composition of a nonsmooth function with a linear operator in the fully nonconvex setting .
Edit intent: fluency
Original: We propose two numerical algorithms for minimizing the sum of a smooth function and the composition of a nonsmooth function with a linear operator in the fully nonconvex setting .
Revised: We propose two numerical algorithms for minimizing the sum of a smooth function and the composition of a nonsmooth function with a linear operator .
Edit intent: clarity
Original:  The proximal terms are introduced through variable metrics, which facilitates the derivation of proximal splitting algorithms for nonconvex complexly structured optimization problems  as particular instances of the general schemes.
Revised:  The proximal terms are introduced via variable metrics, which facilitates the derivation of proximal splitting algorithms for nonconvex complexly structured optimization problems as particular instances of the general schemes.
Edit intent: fluency
Original:  The proximal terms are introduced through variable metrics, which facilitates the derivation of proximal splitting algorithms for nonconvex complexly structured optimization problems  as particular instances of the general schemes.
Revised:  The proximal terms are introduced through variable metrics, a fact which allows us to derive new proximal splitting algorithms for nonconvex complexly structured optimization problems as particular instances of the general schemes.
Edit intent: clarity
Original:  The proximal terms are introduced through variable metrics, which facilitates the derivation of proximal splitting algorithms for nonconvex complexly structured optimization problems  as particular instances of the general schemes.
Revised:  The proximal terms are introduced through variable metrics, which facilitates the derivation of proximal splitting algorithms for nonconvex structured optimization problems as particular instances of the general schemes.
Edit intent: clarity
Original:  The proximal terms are introduced through variable metrics, which facilitates the derivation of proximal splitting algorithms for nonconvex complexly structured optimization problems  as particular instances of the general schemes.
Revised:  The proximal terms are introduced through variable metrics, which facilitates the derivation of proximal splitting algorithms for nonconvex complexly structured optimization problems , as particular instances of the general schemes.
Edit intent: fluency
Original:  Convergence of the iterates to a KKT point of the objective function is proved under mild conditions on the sequence of variable metrics and by assuming that a regularization of the associated augmented Lagrangian has the Kurdyka-Lojasiewicz property .
Revised:  Under mild conditions on the sequence of variable metrics and by assuming that a regularization of the associated augmented Lagrangian has the Kurdyka-Lojasiewicz property .
Edit intent: coherence
Original:  If the augmented Lagrangian has the Lojasiewicz property, then convergence rates of both augmented Lagrangian and iterates are derived .
Revised:  If the augmented Lagrangian has the Lojasiewicz property, we also derive convergence rates for both the augmented Lagrangian and iterates are derived .
Edit intent: clarity
Original:  If the augmented Lagrangian has the Lojasiewicz property, then convergence rates of both augmented Lagrangian and iterates are derived .
Revised:  If the augmented Lagrangian has the Lojasiewicz property, then convergence rates of both augmented Lagrangian and the iterates .
Edit intent: clarity
Original: Bayesian agents learn about a moving target, such as a commodity price, using private signals and their network neighbors' estimates.
Revised: Agents learn about a moving target, such as a commodity price, using private signals and their network neighbors' estimates.
Edit intent: clarity
Original: Bayesian agents learn about a moving target, such as a commodity price, using private signals and their network neighbors' estimates.
Revised: Bayesian agents learn about a state using private signals and their network neighbors' estimates.
Edit intent: clarity
Original:  We ask: when can a group aggregate information quickly, keeping up with the changing environment ?
Revised:  We ask: when can a group aggregate information quickly, keeping up with the changing state ?
Edit intent: clarity
Original:  The resulting tractability can facilitate structural estimation of equilibrium learning models and testing against behavioral alternatives , as well as the analysis of welfare and influence .
Revised:  We discuss how the resulting tractability is useful for structural estimation of equilibrium learning models and testing against behavioral alternatives , as well as the analysis of welfare and influence .
Edit intent: clarity
Original:  The resulting tractability can facilitate structural estimation of equilibrium learning models and testing against behavioral alternatives , as well as the analysis of welfare and influence .
Revised:  The resulting tractability can facilitate structural estimation of equilibrium learning models and testing against behavioral alternatives .
Edit intent: coherence
Original: Agents learn about a  state using private signals and the past actions of their neighbors .
Revised: Agents learn about a changing state using private signals and the past actions of their neighbors .
Edit intent: clarity
Original: Agents learn about a  state using private signals and the past actions of their neighbors .
Revised: Agents learn about a state using private signals and past actions of their neighbors .
Edit intent: fluency
Original:  Third, good aggregation requires agents who understand correlations in neighbors' actions with the sophistication needed to concentrate on recent developments and filter out older, outdated information.
Revised:  Third, good aggregation requires a sophisticated understanding of correlations in neighbors' actions with the sophistication needed to concentrate on recent developments and filter out older, outdated information.
Edit intent: clarity
Original: This paper defines and studies a special kind of equilibrium termed as " balancing equilibrium" which arises in the power allocation game  in allocation.
Revised: This paper studies a special kind of equilibrium termed as " balancing equilibrium" which arises in the power allocation game in allocation.
Edit intent: clarity
Original: This paper defines and studies a special kind of equilibrium termed as " balancing equilibrium" which arises in the power allocation game  in allocation.
Revised: This paper defines and studies a special kind of equilibrium termed as " balanced equilibrium" which arises in the power allocation game in allocation.
Edit intent: fluency
Original: This paper defines and studies a special kind of equilibrium termed as " balancing equilibrium" which arises in the power allocation game  in allocation.
Revised: This paper defines and studies a special kind of equilibrium termed as " balancing equilibrium" which arises in the power allocation game defined in allocation.
Edit intent: clarity
Original:  In the equilibrium, all countries in antagonism have to use all of their own power to counteract the received threats, and the threat made to each adversary only equalizes the threat received from that adversary.
Revised:  In the equilibrium, all countries in antagonism have to use all of its own power to counteract the received threats, and the threat made to each adversary only equalizes the threat received from that adversary.
Edit intent: fluency
Original:  In the equilibrium, all countries in antagonism have to use all of their own power to counteract the received threats, and the threat made to each adversary only equalizes the threat received from that adversary.
Revised:  In the equilibrium, all countries in antagonism have to use all of their own power to counteract received threats, and the threat made to each adversary only equalizes the threat received from that adversary.
Edit intent: fluency