wanyu/IteraTeR_v2 huggingface dataset:
Original:  By applying our results about optimal networks, we show that players with low edge-costs drive players with high edge-costs out of the game, and that hub-and-spoke networks that are commonly observed in real-world transportation systems arise as Nash equilibria in this game.
Revised:  By applying our results about optimal networks, we show that players with low edge costs drive players with high edge-costs out of the game, and that hub-and-spoke networks that are commonly observed in real-world transportation systems arise as Nash equilibria in this game.
Edit intent: fluency
Original:  By applying our results about optimal networks, we show that players with low edge-costs drive players with high edge-costs out of the game, and that hub-and-spoke networks that are commonly observed in real-world transportation systems arise as Nash equilibria in this game.
Revised:  By applying our results about optimal networks, we show that players with low edge-costs drive players with high edge costs out of the game, and that hub-and-spoke networks that are commonly observed in real-world transportation systems arise as Nash equilibria in this game.
Edit intent: fluency
Original:  By applying our results about optimal networks, we show that players with low edge-costs drive players with high edge-costs out of the game, and that hub-and-spoke networks that are commonly observed in real-world transportation systems arise as Nash equilibria in this game.
Revised:  By applying our results about optimal networks, we show that players with low edge-costs drive players with high edge-costs out of the game, and that hub-and-spoke networks that are commonly observed in transportation systems arise as Nash equilibria in this game.
Edit intent: clarity
Original:  We introduce a program logic with L\"ob induction for reasoning about the contextual equivalence of programs.
Revised:  We introduce a program logic with L\"{o induction for reasoning about the contextual equivalence of programs.
Edit intent: fluency
Original:  Here we present the first implementation of a photonic reservoir computer based on a coherently driven passive fiber cavity processing analog signals.
Revised:  Here we present a photonic implementation of a photonic reservoir computer based on a coherently driven passive fiber cavity processing analog signals.
Edit intent: clarity
Original:  Here we present the first implementation of a photonic reservoir computer based on a coherently driven passive fiber cavity processing analog signals.
Revised:  Here we present the first implementation of a reservoir computer based on a coherently driven passive fiber cavity processing analog signals.
Edit intent: clarity
Original:  Furthermore, the analytical model describing our experiment is also of interest, as it arguably constitutes the simplest high performance reservoir computer algorithm introduced so far .
Revised:  Furthermore, the analytical model describing our experiment is also of interest, as it constitutes a very simple high performance reservoir computer algorithm introduced so far .
Edit intent: clarity
Original:  Furthermore, the analytical model describing our experiment is also of interest, as it arguably constitutes the simplest high performance reservoir computer algorithm introduced so far .
Revised:  Furthermore, the analytical model describing our experiment is also of interest, as it arguably constitutes the simplest high performance reservoir computer algorithm .
Edit intent: clarity
Original:  The present experiment, given its remarkable performances, low energy consumption and conceptual simplicity, confirms the great potential of photonic reservoir computing for information processing applications ranging from artificial intelligence to telecommunications.
Revised:  The present experiment, given its good performances, low energy consumption and conceptual simplicity, confirms the great potential of photonic reservoir computing for information processing applications ranging from artificial intelligence to telecommunications.
Edit intent: clarity
Original:  The present experiment, given its good performances, low energy consumption and conceptual simplicity, confirms the great potential of photonic reservoir computing for information processing applications ranging from artificial intelligence to telecommunications .
Revised:  The present experiment, given its good performances, low energy consumption and conceptual simplicity, confirms the great potential of photonic reservoir computing for information processing applications ranging from artificial intelligence to telecommunications 
Edit intent: fluency
Original: Bayesian models of cognition hypothesize that human brains make sense of data by representing probability distributions and applying Bayes' rule to find the best explanation for any given data.
Revised: Bayesian models of cognition hypothesize that human brains make sense of data by representing probability distributions and applying Bayes' rule to find the best explanation for available data.
Edit intent: clarity
Original:  Understanding the neural mechanisms underlying probabilistic models remains important because Bayesian models essentially provide a computational framework, rather than specifying processes at the algorithmic level .
Revised:  Understanding the neural mechanisms underlying probabilistic models remains important because Bayesian models provide a computational framework, rather than specifying processes at the algorithmic level .
Edit intent: clarity
Original:  Understanding the neural mechanisms underlying probabilistic models remains important because Bayesian models essentially provide a computational framework, rather than specifying processes at the algorithmic level .
Revised:  Understanding the neural mechanisms underlying probabilistic models remains important because Bayesian models essentially provide a computational framework, rather than specifying mechanistic processes .
Edit intent: clarity
Original:  Our model is psychologically plausible because, similar to humans, it learns to represent probabilities without receiving any representation of them from the external world, but rather by experiencing  individual events.
Revised:  Our model is psychologically plausible because, similar to humans, it learns to represent probabilities without receiving any representation of them from the external world, but rather by experiencing the occurrence patterns of individual events.
Edit intent: clarity
Original:  Moreover, we show that our neural implementation of probability matching can be paired with a neural module applying Bayes' rule, forming a comprehensive neural scheme to simulate human Bayesian learning and inference.
Revised:  Our neural implementation of probability matching can be paired with a neural module applying Bayes' rule, forming a comprehensive neural scheme to simulate human Bayesian learning and inference.
Edit intent: coherence
Original:  Moreover, we show that our neural implementation of probability matching can be paired with a neural module applying Bayes' rule, forming a comprehensive neural scheme to simulate human Bayesian learning and inference.
Revised:  Moreover, we show that our neural implementation of probability matching is paired with a neural module applying Bayes' rule, forming a comprehensive neural scheme to simulate human Bayesian learning and inference.
Edit intent: coherence
Original:  Our model also provides novel explanations of several deviations from Bayes, including base-rate neglect and overweighting of rare events .
Revised:  Our model also provides novel explanations of base-rate neglect and overweighting of rare events .
Edit intent: clarity
Original:  Finally we show that words with at least one valid plane tree are unusual, in the sense that the proportion of words with at least one valid plane tree goes to zero as the word size increases.
Revised:  Finally we show that the proportion of words with at least one valid plane tree goes to zero as the word size increases.
Edit intent: clarity
Original:  Open questionsand conjectures are given throughout the document .
Revised:  We also give some open questions .
Edit intent: clarity
Original:  For this reason, we use the rGCROT method . rGCROT is an algorithm that improves restarted GMRES by recycling a selected subspace of the search space from one restartof GMRES(m) to the next as well as building and recycling this outer vector space from one problem to the next (subsequent time steps in this context).
Revised:  Therefore, we evaluate the rGCROT method . rGCROT is an algorithm that improves restarted GMRES by recycling a selected subspace of the search space from one restartof GMRES(m) to the next as well as building and recycling this outer vector space from one problem to the next (subsequent time steps in this context).
Edit intent: clarity
Original:  For this reason, we use the rGCROT method . rGCROT is an algorithm that improves restarted GMRES by recycling a selected subspace of the search space from one restartof GMRES(m) to the next as well as building and recycling this outer vector space from one problem to the next (subsequent time steps in this context).
Revised:  For this reason, we use the rGCROT method for these systems. This method recycles a selected subspace of the search space from one restartof GMRES(m) to the next as well as building and recycling this outer vector space from one problem to the next (subsequent time steps in this context).
Edit intent: clarity
Original:  Thus we have used a novel hybrid approach in which we get the benefits of the robustness of the GMRES(m) algorithm and the economical iterations of BiCGStab .
Revised:  Thus we have used a novel hybrid approach in which we get the benefits of the robustness of rGCROT .
Edit intent: clarity
Original:  For the first few time steps , the algorithm builds an outer vector spaceusing rGCROT and then it recycles that space for the rBiCGStab solver.
Revised:  For the first few time steps , the algorithm builds an outer vector spaceusing rGCROT and then it recycles that space in the rBiCGStab solver.
Edit intent: clarity
Original: We consider a stochastic volatility model which captures relevant stylized facts of financial series, including the multiscaling of moments.
Revised: We consider a stochastic volatility model which captures relevant stylized facts of financial series, including the multi-scaling of moments.
Edit intent: fluency
Original:  Even if the price has continuous paths, we show that out-of-the-money implied volatility diverges for small maturity, producing a very pronounced smile .
Revised:  Even if the price has continuous paths, out-of-the-money implied volatility diverges for small maturity, producing a very pronounced smile .
Edit intent: coherence
Original:  The aerodynamic behaviour of sand dunes in atmospheric boundary layer belongs to the class of bluff bodies . Because of their simple geometry and their frequent occurrence in desert area, transverse sand dunes are usually adopted in literature as a benchmark to investigate dune aerodynamics by means of both computational or experimental approach , usually in nominally 2D setups.
Revised:  The aerodynamic behaviour of sand dunes in atmospheric boundary layer belongs to the class of bluff bodies . Because of their simple geometry and their frequent occurrence in desert area, transverse sand dunes are usually adopted in literature as a benchmark to investigate dune aerodynamics by means of both computational or experimental approaches , usually in nominally 2D setups.
Edit intent: fluency
Original:  The present study aims at evaluating the 3D flow features of an idealised transverse dune under different setup conditions by means of computational simulations and to compare the obtained results with experimental measurements  .
Revised:  The present study aims at evaluating 3D flow features of an idealised transverse dune under different setup conditions by means of computational simulations and to compare the obtained results with experimental measurements .
Edit intent: fluency
Original:  The present study aims at evaluating the 3D flow features of an idealised transverse dune under different setup conditions by means of computational simulations and to compare the obtained results with experimental measurements  .
Revised:  The present study aims at evaluating the 3D flow features in the wake of a idealised transverse dune under different setup conditions by means of computational simulations and to compare the obtained results with experimental measurements .
Edit intent: clarity
Original: We present a purely geometric notion of auxetic one-parameter deformation of a periodic framework.
Revised: We formulate a mathematical theory of auxetic behavior based on one-parameter deformation of a periodic framework.
Edit intent: clarity
Original:  Indeed, in recent experiments on adapted populations of asexual mutators, beneficial mutations that lower the mutation rates have been observed to get fixed . Using a multitype branching process and a deterministic argument , we calculate the time to fix the wildtype mutation rate in an asexual population of mutators, and find it to be a%DIFDELCMD < {\tt %%% U -shaped function of the population size.
Revised:  Indeed, in recent experiments on adapted populations of asexual mutators, beneficial mutations that lower the mutation rates have been observed to get fixed . Using a multitype branching process , we calculate the time to fix the wildtype mutation rate in an asexual population of mutators, and find it to be a%DIFDELCMD < {\tt %%% U -shaped function of the population size.
Edit intent: clarity
Original:  Indeed, in recent experiments on adapted populations of asexual mutators, beneficial mutations that lower the mutation rates have been observed to get fixed . Using a multitype branching process and a deterministic argument , we calculate the time to fix the wildtype mutation rate in an asexual population of mutators, and find it to be a%DIFDELCMD < {\tt %%% U -shaped function of the population size.
Revised:  Indeed, in recent experiments on adapted populations of asexual mutators, beneficial mutations that lower the mutation rates have been observed to get fixed . Using a multitype branching process and a deterministic argument , we calculate the time to fix the wildtype mutation rate in an asexual population of mutators, and find %DIFDELCMD < {\tt %%% U -shaped function of the population size.
Edit intent: coherence
Original:  Indeed, in recent experiments on adapted populations of asexual mutators, beneficial mutations that lower the mutation rates have been observed to get fixed . Using a multitype branching process and a deterministic argument , we calculate the time to fix the wildtype mutation rate in an asexual population of mutators, and find it to be a%DIFDELCMD < {\tt %%% U -shaped function of the population size.
Revised:  Indeed, in recent experiments on adapted populations of asexual mutators, beneficial mutations that lower the mutation rates have been observed to get fixed . Using a multitype branching process and a deterministic argument , we calculate the time to fix the wildtype mutation rate in an asexual population of mutators, and find it to be a%DIFDELCMD < {\tt %%% -shaped function of the population size.
Edit intent: clarity
Original:  On comparing these two time scales , we find that a critical population size exists below which the mutators prevail, while the mutation rate remains low in larger populations .
Revised:  On comparing these two time scales , we find a novel relationship between the mutation rates and the population size .
Edit intent: clarity
Original:  The perturbations are arbitrary continuous maps within  distance r from f for a given r> 0 in the max-norm.
Revised:  The perturbations are arbitrary continuous maps within distance r from f for a given r> 0.
Edit intent: clarity
Original:  The main drawback of the approach is that the computability of well groups has been shown only when dim K=n or n=1.
Revised:  The main drawback of the approach is that the computability of well groups was shown only when dim K=n or n=1.
Edit intent: clarity
Original:  As for the first part, we identify a computable subgroup of  well group that is obtained by cap product with the pullback of the orientation of \mathbb{R ^n by f.
Revised:  For the first part, we identify a computable subgroup of well group that is obtained by cap product with the pullback of the orientation of \mathbb{R ^n by f.
Edit intent: coherence
Original:  As for the first part, we identify a computable subgroup of  well group that is obtained by cap product with the pullback of the orientation of \mathbb{R ^n by f.
Revised:  As for the first part, we identify a computable subgroup of the well group that is obtained by cap product with the pullback of the orientation of \mathbb{R ^n by f.
Edit intent: fluency
Original:  When f is smooth and dim K<2n-2, our approximation of  (dim K-n)th well group is exact \to  .
Revised:  When f is smooth and dim K<2n-2, our approximation of the (dim K-n)th well group is exact \to .
Edit intent: fluency
Original:  Even tough we do not solve analytically the full optimization problem, we present explicit and simple analytical recipes which approximate the full solution and are easy to implement in practice.
Revised:  Even though we do not solve analytically the full optimization problem, we present explicit and simple analytical recipes which approximate the full solution and are easy to implement in practice.
Edit intent: fluency
Original:  Normalized Mutual Information (NMI) has been widely used to evaluate  accuracy of community detection algorithms.
Revised: The Normalized Mutual Information (NMI) has been widely used to evaluate accuracy of community detection algorithms.
Edit intent: fluency
Original:  Normalized Mutual Information (NMI) has been widely used to evaluate  accuracy of community detection algorithms.
Revised:  Normalized Mutual Information (NMI) has been widely used to evaluate the accuracy of community detection algorithms.
Edit intent: fluency
Original:  In this notes we show that  NMI is seriously affected by systematic error due to finite size of networks, and may give  wrong estimate of performance of algorithms in some cases.
Revised:  However in this article we show that NMI is seriously affected by systematic error due to finite size of networks, and may give wrong estimate of performance of algorithms in some cases.
Edit intent: clarity
Original:  In this notes we show that  NMI is seriously affected by systematic error due to finite size of networks, and may give  wrong estimate of performance of algorithms in some cases.
Revised:  In this notes we show that the NMI is seriously affected by systematic error due to finite size of networks, and may give wrong estimate of performance of algorithms in some cases.
Edit intent: fluency
Original:  In this notes we show that  NMI is seriously affected by systematic error due to finite size of networks, and may give  wrong estimate of performance of algorithms in some cases.
Revised:  In this notes we show that NMI is seriously affected by systematic errors due to finite size of networks, and may give wrong estimate of performance of algorithms in some cases.
Edit intent: fluency
Original:  In this notes we show that  NMI is seriously affected by systematic error due to finite size of networks, and may give  wrong estimate of performance of algorithms in some cases.
Revised:  In this notes we show that NMI is seriously affected by systematic error due to finite size of networks, and may give a wrong estimate of performance of algorithms in some cases.
Edit intent: fluency
Original:  We suggest to use a new measure to accuracy of community detection, namely  relative Normalized Mutual Information (rNMI), which is NMI minus the expected NMI of random partitions.
Revised:  We suggest to use a new measure to accuracy of community detection, namely the relative Normalized Mutual Information (rNMI), which is NMI minus the expected NMI of random partitions.
Edit intent: fluency
Original:  This measure is very close to zero for two random partitions even with a short length, so it can overcome the problem of NMI.
Revised:  Our numerical experiments show that the rNMI overcomes the finite-size effect of the NMI.
Edit intent: clarity
Original: In this article we present a data mining framework for detection of sleeping cells caused by random access channel failure in Long Term Evolution (LTE) for Universal Mobile Telecommunications System networks .
Revised: This article presents an automatic malfunction detection framework based on data mining approach to analysis of network event sequences. The considered environment is Long Term Evolution (LTE) for Universal Mobile Telecommunications System networks .
Edit intent: clarity
Original:  Sleeping cell problem implies unavailability of network service without triggered alarm.
Revised:  Sleeping cell problem means unavailability of network service without triggered alarm.
Edit intent: fluency
Original:  The core of the proposed detection framework is N-gram based analysis of sequences of network events.
Revised:  The proposed detection framework is N-gram based analysis of sequences of network events.
Edit intent: clarity
Original:  The core of the proposed detection framework is N-gram based analysis of sequences of network events.
Revised:  The core of the proposed detection framework uses N-gram based analysis of sequences of network events.
Edit intent: fluency
Original:  The core of the proposed detection framework is N-gram based analysis of sequences of network events.
Revised:  The core of the proposed detection framework is N-gram analysis for identification of abnormal behavior in sequences of network events.
Edit intent: clarity
Original:  These events are collected with Minimization of Drive Test (MDT) functionality standardized in 3rd Generation Partnership Project (3GPP) .
Revised:  These events are collected with Minimization of Drive Tests (MDT) functionality standardized in 3rd Generation Partnership Project (3GPP) .
Edit intent: fluency
Original:  Further processing applies dimensionality reduction, anomaly detection with K-Nearest Neighbors (K-NN) , cross-validation and post-processing techniques  . Efficiency of different approaches of anomaly detection results interpretation are developed and thoroughly compared to each other .
Revised:  Further processing applies dimensionality reduction, anomaly detection with k-nearest neighbor , cross-validation and post-processing techniques . Efficiency of different approaches of anomaly detection results interpretation are developed and thoroughly compared to each other .
Edit intent: clarity
Original:  Further processing applies dimensionality reduction, anomaly detection with K-Nearest Neighbors (K-NN) , cross-validation and post-processing techniques  . Efficiency of different approaches of anomaly detection results interpretation are developed and thoroughly compared to each other .
Revised:  Further processing applies dimensionality reduction, anomaly detection with K-Nearest Neighbors (K-NN) , cross-validation , post-processing techniques . Efficiency of different approaches of anomaly detection results interpretation are developed and thoroughly compared to each other .
Edit intent: coherence
Original:  Further processing applies dimensionality reduction, anomaly detection with K-Nearest Neighbors (K-NN) , cross-validation and post-processing techniques  . Efficiency of different approaches of anomaly detection results interpretation are developed and thoroughly compared to each other .
Revised:  Further processing applies dimensionality reduction, anomaly detection with K-Nearest Neighbors (K-NN) , cross-validation and post-processing techniques . 
Edit intent: coherence