wanyu/IteraTeR_v2 huggingface dataset:
Original:  We observe broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that do not directly control the BCI ( ' non-control units ' ).
Revised:  We observed broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that do not directly control the BCI ( ' non-control units ' ).
Edit intent: fluency
Original:  We observe broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that do not directly control the BCI ( ' non-control units ' ).
Revised:  We observe broad changes in tuning of both units used to drive the BCI directly ( control units ) and units that do not directly control the BCI ( ' non-control units ' ).
Edit intent: fluency
Original:  We observe broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that do not directly control the BCI ( ' non-control units ' ).
Revised:  We observe broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that did not directly control the BCI ( ' non-control units ' ).
Edit intent: fluency
Original:  We observe broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that do not directly control the BCI ( ' non-control units ' ).
Revised:  We observe broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that do not directly control the BCI ( non-control units ' ).
Edit intent: fluency
Original:  We observe broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that do not directly control the BCI ( ' non-control units ' ).
Revised:  We observe broad changes in tuning of both units used to drive the BCI directly ( 'control units' ) and units that do not directly control the BCI ( ' non-control units ).
Edit intent: fluency
Original:  Using transfer entropy, a measure of effective connectivity , we observe control-unit-specific dissociation from other units.
Revised:  Using a measure of effective connectivity , we observe control-unit-specific dissociation from other units.
Edit intent: clarity
Original:  Using transfer entropy, a measure of effective connectivity , we observe control-unit-specific dissociation from other units.
Revised:  Using transfer entropy, a measure of effective connectivity we observed control-unit-specific dissociation from other units.
Edit intent: fluency
Original:  Through an analysis of variance we find that the intrinsic variability of the control units has a significant effect on task proficiency.
Revised:  Through an analysis of variance we found that the intrinsic variability of the control units has a significant effect on task proficiency.
Edit intent: fluency
Original:  Using a measure of effective connectivity we observed control-unit-specific dissociation from other units .
Revised:  Using a measure of effective connectivity , we observed that control units decrease their connectivity .
Edit intent: clarity
Original:  Thus, provided this is accounted for, motor cortical activity is flexible enough to perform novel BCI tasks that require active decoupling of natural associations to wrist motion  .
Revised:  When this variance is accounted for, motor cortical activity is flexible enough to perform novel BCI tasks that require active decoupling of natural associations to wrist motion .
Edit intent: clarity
Original: Allosteric molecules serve as regulators of cellular activity across all domains of life .
Revised: Allosteric regulation is found across all domains of life .
Edit intent: clarity
Original: We derive an explicit closed-form representation of mean-variance hedging strategies for models whose asset price follows an exponential additive process.
Revised: We focus on mean-variance hedging strategies for models whose asset price follows an exponential additive process.
Edit intent: clarity
Original: We derive an explicit closed-form representation of mean-variance hedging strategies for models whose asset price follows an exponential additive process.
Revised: We derive an explicit closed-form representation of mean-variance hedging problem for models whose asset price follows an exponential additive process.
Edit intent: clarity
Original:  Our representation is given in terms of Malliavin calculus for L\'evy processes .
Revised:  Our representation is given in terms of Malliavin derivatives .
Edit intent: clarity
Original:  In addition, we develop an approximation method to compute mean-variance hedging strategies for exponential L\'evy models , and illustrate numerical results .
Revised:  In addition, we illustrate numerical results for exponential L\'evy models , and illustrate numerical results .
Edit intent: coherence
Original:  In addition, we develop an approximation method to compute mean-variance hedging strategies for exponential L\'evy models , and illustrate numerical results .
Revised:  In addition, we develop an approximation method to compute mean-variance hedging strategies for exponential L\'evy models .
Edit intent: coherence
Original:  We propose an epidemic model based on the preferential attachment model , which adds nodes sequentially by simple rules to generate a network .
Revised:  We propose an epidemic model based on the preferential attachment model .
Edit intent: clarity
Original:  A simulation study based on the subsequent Markov Chain Monte Carlo algorithm reveals an identifiability issue with the model parameters , so an alternative parameterisation is suggested .
Revised:  A simulation study based on the subsequent Markov Chain Monte Carlo algorithm reveals an identifiability issue with the model parameters .
Edit intent: coherence
Original: In the recent years, significant progress has been made in explaining  apparent hardness of improving over naive solutions for many fundamental polynomially solvable problems.
Revised: In recent years, significant progress has been made in explaining apparent hardness of improving over naive solutions for many fundamental polynomially solvable problems.
Edit intent: fluency
Original: In the recent years, significant progress has been made in explaining  apparent hardness of improving over naive solutions for many fundamental polynomially solvable problems.
Revised: In the recent years, significant progress has been made in explaining the apparent hardness of improving over naive solutions for many fundamental polynomially solvable problems.
Edit intent: fluency
Original: In the recent years, significant progress has been made in explaining  apparent hardness of improving over naive solutions for many fundamental polynomially solvable problems.
Revised: In the recent years, significant progress has been made in explaining apparent hardness of improving upon the naive solutions for many fundamental polynomially solvable problems.
Edit intent: clarity
Original:  This came in the form of conditional lower bounds - reductions to one of problems assumed to be hard.
Revised:  This progress has come in the form of conditional lower bounds - reductions to one of problems assumed to be hard.
Edit intent: clarity
Original:  This came in the form of conditional lower bounds - reductions to one of problems assumed to be hard.
Revised:  This came in the form of conditional lower bounds -- reductions from a problem assumed to be hard.
Edit intent: clarity
Original:  These include 3SUM, All-Pairs Shortest Paths, SATand Orthogonal Vectors, and others.
Revised:  These include 3SUM, All-Pairs Shortest Path, SAT, Orthogonal Vectors, and others.
Edit intent: fluency
Original:  In the ( min ,+)-convolution problem, the goal is to compute a sequence (c[i])^{n-1}_{i=0}, where c[k] = i=0,\ldots,k \{a[i] + b[k-i]\}, given sequences (a[i])^{n-1}_{i=0} and (b[i])_{i=0}^{n-1}.
Revised:  In the ( \min ,+)-convolution problem, the goal is to compute a sequence (c[i])^{n-1}_{i=0}, where c[k] = i=0,\ldots,k \{a[i] + b[k-i]\}, given sequences (a[i])^{n-1}_{i=0} and (b[i])_{i=0}^{n-1}.
Edit intent: fluency
Original:  This can easily be done in O(n^2) time, but no O(n^{2-\varepsilon}) algorithm is known for \varepsilon > 0. In this paper  we undertake a systematic study of the ( min ,+)-convolution problem as a hardness assumption.
Revised:  This can easily be done in O(n^2) time, but no O(n^{2-\varepsilon}) algorithm is known for \varepsilon > 0. In this paper , we undertake a systematic study of the ( min ,+)-convolution problem as a hardness assumption.
Edit intent: fluency
Original:  This can easily be done in O(n^2) time, but no O(n^{2-\varepsilon}) algorithm is known for \varepsilon > 0. In this paper  we undertake a systematic study of the ( min ,+)-convolution problem as a hardness assumption.
Revised:  This can easily be done in O(n^2) time, but no O(n^{2-\varepsilon}) algorithm is known for \varepsilon > 0. In this paper we undertake a systematic study of the ( \min ,+)-convolution problem as a hardness assumption.
Edit intent: fluency
Original:  As the first step , we establish  equivalence of this problem to a group of other problems, including variants of the classic knapsack problem and problems related to subadditive sequences.
Revised:  First , we establish equivalence of this problem to a group of other problems, including variants of the classic knapsack problem and problems related to subadditive sequences.
Edit intent: coherence
Original:  As the first step , we establish  equivalence of this problem to a group of other problems, including variants of the classic knapsack problem and problems related to subadditive sequences.
Revised:  As the first step , we establish the equivalence of this problem to a group of other problems, including variants of the classic knapsack problem and problems related to subadditive sequences.
Edit intent: fluency
Original:  The ( min ,+)-convolution  has been used as a building block in algorithms for many problems, notably problems in stringology.
Revised:  The ( min ,+)-convolution problem has been used as a building block in algorithms for many problems, notably problems in stringology.
Edit intent: clarity
Original:  It has also already appeared as an ad hoc hardness assumption.
Revised:  It has also appeared as an ad hoc hardness assumption.
Edit intent: fluency
Original:  We investigate some of these connections and provide new reductions and other results  .
Revised:  Second, we investigate some of these connections and provide new reductions and other results .
Edit intent: coherence
Original:  The network structure of the physical porous scaffold is often incorporated in an averaged way through parameters in these models, either phenomenologically or through techniques like mathematical homogenization.
Revised:  The network structure of the physical porous scaffold is often incorporated through parameters in these models, either phenomenologically or through techniques like mathematical homogenization.
Edit intent: clarity
Original:  We derive a model on a simple square grid lattice to demonstrate the importance of explicitly modelling the network structure of the porous scaffold, and compare results from this model with those from a modified continuum model from the literature.
Revised:  We derive a model on a square grid lattice to demonstrate the importance of explicitly modelling the network structure of the porous scaffold, and compare results from this model with those from a modified continuum model from the literature.
Edit intent: clarity
Original:  We explore a range of parameters for both models, and demonstrate quantitative and qualitative differences between predictions from each of these approaches, including spatial pattern formation on different timescales and local oscillations in cell density present only in the lattice model.
Revised:  We explore a range of parameters for both models, and demonstrate quantitative and qualitative differences between predictions from each of these approaches, including spatial pattern formation and local oscillations in cell density present only in the lattice model.
Edit intent: clarity
Original:  These results suggest that for some parameter regimes, corresponding to specific cell types and scaffold geometries, the lattice model gives qualitatively different model predictions than typical continuum models  .
Revised:  These differences suggest that for some parameter regimes, corresponding to specific cell types and scaffold geometries, the lattice model gives qualitatively different model predictions than typical continuum models .
Edit intent: clarity
Original:  The key idea of this reformulation is to break symmetry on each recursion level by enumerating all so-called one-level packings, i.e., packings of circles into other circles, and by dynamically generating packings of circles into rectangles.
Revised:  The key idea of this reformulation is to break symmetry on each recursion level by enumerating one-level packings, i.e., packings of circles into other circles, and by dynamically generating packings of circles into rectangles.
Edit intent: clarity
Original:  Extensive computational experiments on a large test set show that our method not only computes exact dual bounds, but often produces primal solutions better than  computed by heuristics from the literature.
Revised:  Extensive computational experiments on a large test set show that our method not only computes tight dual bounds, but often produces primal solutions better than computed by heuristics from the literature.
Edit intent: clarity
Original:  Extensive computational experiments on a large test set show that our method not only computes exact dual bounds, but often produces primal solutions better than  computed by heuristics from the literature.
Revised:  Extensive computational experiments on a large test set show that our method not only computes exact dual bounds, but often produces primal solutions better than those computed by heuristics from the literature.
Edit intent: clarity
Original: We present an approach to adaptively utilize deep neural networks in order to reduce the evaluation time on new examples without loss of classification performance . Rather than attempting to redesign or approximate existing networks, we propose two schemes that adaptively utilize networks.
Revised: We present an approach to adaptively utilize deep neural networks in order to reduce the evaluation time on new examples without loss of accuracy . Rather than attempting to redesign or approximate existing networks, we propose two schemes that adaptively utilize networks.
Edit intent: clarity
Original:  First, we pose an adaptive network evaluation scheme, where we learn a system to adaptively choose the components of a deep network to be evaluated for each example.
Revised:  We first pose an adaptive network evaluation scheme, where we learn a system to adaptively choose the components of a deep network to be evaluated for each example.
Edit intent: coherence
Original:  Building upon this approach, we then learn a network selection system that adaptively selects the network to be evaluated for each example.
Revised:  We extend this to learn a network selection system that adaptively selects the network to be evaluated for each example.
Edit intent: clarity
Original:  By avoiding evaluation of these complex networks for a large fraction of examples, computational time can be dramatically reduced . Empirically, these approaches yield dramatic reductions in computational cost, with up to a 2.8x speedup on state-of-the-art networks from the ImageNet image recognition challenge with minimal ( less than 1\%) loss of  accuracy.
Revised:  By avoiding evaluation of these complex networks for a large fraction of examples, computational time can be dramatically reduced . Empirically, these approaches yield dramatic reductions in computational cost, with up to a 2.8x speedup on state-of-the-art networks from the ImageNet image recognition challenge with minimal ( < 1\%) loss of accuracy.
Edit intent: clarity
Original: In this paper, we propose a novel generic model of opinion dynamics over a social network , in the presence of communication among the users leading to interpersonal influence i.e.,  peer pressure.
Revised: In this paper, we study a model of opinion dynamics over a social network , in the presence of communication among the users leading to interpersonal influence i.e., peer pressure.
Edit intent: clarity
Original: In this paper, we propose a novel generic model of opinion dynamics over a social network , in the presence of communication among the users leading to interpersonal influence i.e.,  peer pressure.
Revised: In this paper, we propose a novel generic model of opinion dynamics in a social network , in the presence of communication among the users leading to interpersonal influence i.e., peer pressure.
Edit intent: clarity
Original: In this paper, we propose a novel generic model of opinion dynamics over a social network , in the presence of communication among the users leading to interpersonal influence i.e.,  peer pressure.
Revised: In this paper, we propose a novel generic model of opinion dynamics over a social network in the presence of communication among the users leading to interpersonal influence i.e., peer pressure.
Edit intent: fluency
Original: In this paper, we propose a novel generic model of opinion dynamics over a social network , in the presence of communication among the users leading to interpersonal influence i.e.,  peer pressure.
Revised: In this paper, we propose a novel generic model of opinion dynamics over a social network , in the presence increasing interpersonal influence, i.e., peer pressure.
Edit intent: clarity
Original:  Each individual in the social network has a distinct objective function representing a weighted sum of internal and external  pressures.
Revised:  Each agent in the social network has a distinct objective function representing a weighted sum of internal and external pressures.
Edit intent: clarity
Original:  We  prove conditions under which a connected group of users converges to a fixed opinion distribution, and under which conditions the group reaches consensus.
Revised:  We prove conditions under which a connected group of agents converge to a fixed opinion distribution, and under which conditions the group reaches consensus.
Edit intent: clarity
Original:   Through simulation, we study the rate of convergence on large scale-free networks as well as the impact of user stubbornness on convergence in a simple political model.
Revised:  Through simulation, we study the rate of convergence on a scale-free networks as well as the impact of user stubbornness on convergence in a simple political model.
Edit intent: clarity
Original:  The sides of such an equation contain both exactly the same variables , occurring in the same order (but separated by potentially distinct constant factors).
Revised:  In such equations, each variable occurs at most once in each side and the order of the variables occurring in both sides is the preserved (the variables can be, however, separated by potentially distinct constant factors).
Edit intent: coherence
Original:  Surprisingly, we obtain that solving even such simple equations  is NP-hard.
Revised:  Surprisingly, we obtain that solving such simple equations is NP-hard.
Edit intent: clarity
Original:  By considerations regarding the combinatorial structure of the minimal solutions of the more general quadratic equations we obtain that the satisfiability problem for regular-ordered equations is in NP. Finally, a series of related arguments allow us to show that a related class of simple word equations, that generalises one-variable equations, is in P.
Revised:  By considerations regarding the combinatorial structure of the minimal solutions of the more general quadratic equations we obtain that the satisfiability problem for regular-ordered equations is in NP. Finally, we also show that a related class of simple word equations, that generalises one-variable equations, is in P.
Edit intent: clarity
Original:  We achieve this by using graph-preserving unitary operations, which are the quantum analogue of stochastic operations preserving the graph.
Revised:  We achieve this by using graph-preserving quantum operations, which are the quantum analogue of stochastic operations preserving the graph.
Edit intent: clarity
Original:  We achieve this by using graph-preserving unitary operations, which are the quantum analogue of stochastic operations preserving the graph.
Revised:  We achieve this by using graph-preserving unitary operations, which are the quantum analogues of stochastic operations preserving the graph.
Edit intent: fluency
Original:  By extending them to  controlled operations, we define a quantum controlled Cop and Robber game, which expands the classical Cop and Robber game, as well as  classically controlled quantum Cop and Robber game.
Revised:  By extending them to the controlled operations, we define a quantum controlled Cop and Robber game, which expands the classical Cop and Robber game, as well as classically controlled quantum Cop and Robber game.
Edit intent: fluency
Original:  By extending them to  controlled operations, we define a quantum controlled Cop and Robber game, which expands the classical Cop and Robber game, as well as  classically controlled quantum Cop and Robber game.
Revised:  By extending them to controlled operations, we define a quantum-controlled Cop and Robber game, which expands the classical Cop and Robber game, as well as classically controlled quantum Cop and Robber game.
Edit intent: fluency
Original:  By extending them to  controlled operations, we define a quantum controlled Cop and Robber game, which expands the classical Cop and Robber game, as well as  classically controlled quantum Cop and Robber game.
Revised:  By extending them to controlled operations, we define a quantum controlled Cop and Robber game, which expands the classical Cop and Robber game, as well as the classically controlled quantum Cop and Robber game.
Edit intent: fluency
Original:  Moreover, the chances of catching the Robber decreases for classically cop-win graphs.
Revised:  Moreover, the chances of catching the Robber decrease for classical cop-win graphs.
Edit intent: fluency
Original:  The result does not depend on the chosen model of evolution.
Revised:  This result does not depend on the chosen model of evolution.
Edit intent: fluency
Original:  On the other hand, the possibility to execute controlled quantum operations allows catching the Robber on almost all classically cop-win graphs.
Revised:  On the other hand, the possibility to execute controlled quantum operations allows catching the Robber on almost all classical cop-win graphs.
Edit intent: fluency
Original:  To provide interesting, non-trivial quantized Cop and Robber game, we need to enrich the structure of correlations between the players' systems .
Revised:  By this, we demonstrate that it is necessary to enrich the structure of correlations between the players' systems .
Edit intent: coherence
Original:  This result demonstrates that the ability to utilise quantum controlled operations is significantly stronger that the control restricted operating on classical selecting quantum operationsonly .
Revised:  This result demonstrates that the ability to utilise quantum controlled operations offer a significant advantage over the classically controlled quantum operations .
Edit intent: clarity
Original:  We propose a meta-algorithm called \emph{Iterative Local Voting for collective decision-making in this setting, in which voters are sequentially sampled and asked to modify a candidate solution within some local neighborhood of its current value, as defined by a ball in some chosen norm.
Revised:  We propose a meta-algorithm called \emph{Iterative Local Voting for collective decision-making in this setting, in which voters are sequentially sampled and asked to modify a candidate solution within some local neighborhood of its current value, as defined by a ball in some chosen norm.
Edit intent: fluency