wanyu/IteraTeR_v2 huggingface dataset:
Original:  In specific , the given queries are first expanded by searching in the Google Books Ngrams Corpus to obtain a richer semantic description, from which the visually non-salient and less relevant expansions are filtered out.
Revised:  Specifically , the given queries are first expanded by searching in the Google Books Ngrams Corpus to obtain a richer semantic description, from which the visually non-salient and less relevant expansions are filtered out.
Edit intent: coherence
Original:  In specific , the given queries are first expanded by searching in the Google Books Ngrams Corpus to obtain a richer semantic description, from which the visually non-salient and less relevant expansions are filtered out.
Revised:  In specific , the given queries are first expanded by searching the Google Books Ngrams Corpus to obtain a richer semantic description, from which the visually non-salient and less relevant expansions are filtered out.
Edit intent: clarity
Original:  In specific , the given queries are first expanded by searching in the Google Books Ngrams Corpus to obtain a richer semantic description, from which the visually non-salient and less relevant expansions are filtered out.
Revised:  In specific , the given queries are first expanded by searching in the Google Books Ngrams Corpus to obtain a rich semantic description, from which the visually non-salient and less relevant expansions are filtered out.
Edit intent: fluency
Original:  By treating each unfiltered expansion as a "bag" and the retrieved images as "instances", image selection can be formulated as a multi-instance learning problem with constrained positive bags.
Revised:  By treating each selected expansion as a "bag" and the retrieved images as "instances", image selection can be formulated as a multi-instance learning problem with constrained positive bags.
Edit intent: clarity
Original:  Using this approach, images from different distributions will be retained while noisy images will be filtered out.
Revised:  By using this approach, images from different distributions will be retained while noisy images will be filtered out.
Edit intent: fluency
Original:  Using this approach, images from different distributions will be retained while noisy images will be filtered out.
Revised:  Using this approach, images from different distributions can be kept while noisy images will be filtered out.
Edit intent: clarity
Original:  Using this approach, images from different distributions will be retained while noisy images will be filtered out.
Revised:  Using this approach, images from different distributions will be retained while noisy images are filtered out.
Edit intent: fluency
Original:  To verify the effectiveness of our proposed approach, we build a domain-robust image dataset with 20 categories , which we refer to as DRID-20.
Revised:  To verify the effectiveness of our proposed approach, we build an image dataset with 20 categories , which we refer to as DRID-20.
Edit intent: coherence
Original:  We say that two non-empty families are \mathcal A, \mathcal B\subset {[n]\choose k} are s-cross-intersecting {\it  , if for any A\in\mathcal A,B\in \mathcal B we have |A\cap B|\ge s.
Revised:  We say that two non-empty families are \mathcal A, \mathcal B\subset {[n]\choose k} are {\it , if for any A\in\mathcal A,B\in \mathcal B we have |A\cap B|\ge s.
Edit intent: clarity
Original:  We say that two non-empty families are \mathcal A, \mathcal B\subset {[n]\choose k} are s-cross-intersecting {\it  , if for any A\in\mathcal A,B\in \mathcal B we have |A\cap B|\ge s.
Revised:  We say that two non-empty families are \mathcal A, \mathcal B\subset {[n]\choose k} are s-cross-intersecting {\it s-cross-intersecting , if for any A\in\mathcal A,B\in \mathcal B we have |A\cap B|\ge s.
Edit intent: fluency
Original: In this paper, we study the so-called zero-one laws for the Erdo s-R \'{e}nyi random graph model G(n,p) in the case when p = n^{-\alpha} for \alpha>0.
Revised: In this paper, we study the so-called zero-one laws for the Erdo s--R \'{e}nyi random graph model G(n,p) in the case when p = n^{-\alpha} for \alpha>0.
Edit intent: fluency
Original:  For a given class of properties and p , we say that G(n,p) obeys the zero-one law if any formula from the class) if each sentence \varphi\inK } either a.a.s. holds or a.a.s. does not hold in G(n,p).
Revised:  For a given class of properties and p , we say that G(n,p) obeys the zero-one law if any formula from the class) if each sentence \varphi\inK } either a.a.s. holds or a.a.s. false for G(n,p).
Edit intent: clarity
Original:  We also show that, contrary to the case of the 3-law, there are infinitely many values of \alpha for which the zero-one 4-law for MSO properties does not hold.
Revised:  We also show that, in contrast to the case of the 3-law, there are infinitely many values of \alpha for which the zero-one 4-law for MSO properties does not hold.
Edit intent: fluency
Original: In this paper, we study the so-called zero-one laws for the Erdos--R\'{e}nyi random graph model G(n,p) in the case when p = n^{-\alpha} for \alpha>0.
Revised: In this paper, we study zero-one laws for the Erdos--R\'{e}nyi random graph model G(n,p) in the case when p = n^{-\alpha} for \alpha>0.
Edit intent: clarity
Original:  For a given class K of sentences in the logic of graphs and a given function p=p(n), we say that G(n,p) obeys the zero-one law (w.r.t. the class K) if each sentence \varphi\inK either a.a.s. true or a.a.s. false for G(n,p).
Revised:  For a given class K of logical sentences about graphs and a given function p=p(n), we say that G(n,p) obeys the zero-one law (w.r.t. the class K) if each sentence \varphi\inK either a.a.s. true or a.a.s. false for G(n,p).
Edit intent: clarity
Original:  Zero-one laws for properties of quantifier depth k we call the zero-one k-laws .
Revised:  Zero-one laws for properties of quantifier depth k we call the zero-one k-laws .
Edit intent: fluency
Original:  Studying these zero-one laws forces us to analyze the evolution of certain properties of G(n,p) , which may be of independent interest.
Revised:  To this end, we analyze the evolution of certain properties of G(n,p) , which may be of independent interest.
Edit intent: clarity
Original:  Studying these zero-one laws forces us to analyze the evolution of certain properties of G(n,p) , which may be of independent interest.
Revised:  Studying these zero-one laws forces us to analyze the evolution of certain properties of G(n,p) that may be of independent interest.
Edit intent: fluency
Original:  The various boundary conditions such as Dirichlet, Neumann, Robin, mixed and multi--point boundary conditions, have been considered .
Revised:  The various boundary conditions in the modeling of some problems in engineering and physical science .
Edit intent: clarity
Original:  It can improve the applications of existing methods based on  radial basis functions especially the pseudospectral radial basis function method to handling the differential equations with more complicated boundary conditions.
Revised:  It can improve the applications of existing methods based on radial basis functions especially the pseudospectral radial basis function method for handling the differential equations with more complicated boundary conditions.
Edit intent: fluency
Original:  Several examples of one, two , and three dimensional problems with various boundary conditions  have been considered to show the efficacy and versatility of the proposed method.
Revised:  Several examples of one, two , and three dimensional problems with various boundary conditions .onditions have been considered to show the efficacy and versatility of the proposed method.
Edit intent: fluency
Original:  The proposed method is applied to a singularly perturbed steady-state convection-diffusion problem, two and three dimensional Poisson's equations with various boundary conditions. onditions have been considered to show the efficacy and versatility of the proposed method.
Revised:  The proposed method is applied to a singularly perturbed steady-state convection-diffusion problem, two and three dimensional Poisson's equations with various boundary conditions. 
Edit intent: coherence
Original:  In this paper we explore a new approach to correlation clustering by considering how to solve the problem when the data to be clustered can be represented by a low-rank matrix.
Revised:  In this paper we explore how to solve the problem when the data to be clustered can be represented by a low-rank matrix.
Edit intent: coherence
Original:  Many real-world datasets are known to be inherently low-dimensional, and our goal is to establish a tractable approach to correlation clustering in this important setting.
Edit intent: coherence
Original:  Based on our theoretical results, we develop an algorithm for efficiently solving low-rank positive semidefinite correlation clustering by employing a procedure for zonotope vertex enumeration.
Revised:  Based on our theoretical results, we develop an algorithm for efficiently "solving" low-rank positive semidefinite correlation clustering by employing a procedure for zonotope vertex enumeration.
Edit intent: clarity
Original: We present a survey on the developments on Groebner basesshowing explicit examples in CoCoA.
Revised: We present a survey on the developments related to Groebner bases, and show explicit examples in CoCoA.
Edit intent: clarity
Original:  The CoCoA project dates back to 1987: its aim was to create a mathematician-friendly laboratory for studying Commutative Algebra, most especially Groebner bases.
Revised:  The CoCoA project dates back to 1987: its aim was to create a "mathematician"-friendly computational laboratory for studying Commutative Algebra, most especially Groebner bases.
Edit intent: clarity
Original:  Since then, always maintaining this "friendly" tradition, it has evolved and has been completely rewritten.
Revised:  Always maintaining this "friendly" tradition, it has evolved and has been completely rewritten.
Edit intent: coherence
Original:  Since then, always maintaining this "friendly" tradition, it has evolved and has been completely rewritten.
Revised:  Since then, always maintaining this "friendly" tradition, the project has grown and evolved, and the software has been completely rewritten.
Edit intent: clarity
Original: Multidimensional-scaling (MDS) is a dimensionality reduction tool used for information analysis, data visualization and manifold learning.
Revised: Multidimensional scaling (MDS) is a dimensionality reduction tool used for information analysis, data visualization and manifold learning.
Edit intent: fluency
Original:  Most MDS procedures find embedding of data points in low dimensional Euclidean (flat) domains, such that distances between the points are as close as possible to given inter-points dissimilarities.
Revised:  Most MDS procedures embed data points in low dimensional Euclidean (flat) domains, such that distances between the points are as close as possible to given inter-points dissimilarities.
Edit intent: clarity
Original:  Most MDS procedures find embedding of data points in low dimensional Euclidean (flat) domains, such that distances between the points are as close as possible to given inter-points dissimilarities.
Revised:  Most MDS procedures find embedding of data points in low-dimensional Euclidean (flat) domains, such that distances between the points are as close as possible to given inter-points dissimilarities.
Edit intent: fluency
Original:  Most MDS procedures find embedding of data points in low dimensional Euclidean (flat) domains, such that distances between the points are as close as possible to given inter-points dissimilarities.
Revised:  Most MDS procedures find embedding of data points in low dimensional Euclidean (flat) domains, such that distances between the points are as close as possible to given inter-point dissimilarities.
Edit intent: fluency
Original:  We present an efficient solver for Classical Scaling , a specific MDS model, by extrapolating the information provided by distances measured from a subset of the points to the rest .
Revised:  We present an efficient solver for classical scaling , a specific MDS model, by extrapolating the information provided by distances measured from a subset of the points to the rest .
Edit intent: fluency
Original:  We present an efficient solver for Classical Scaling , a specific MDS model, by extrapolating the information provided by distances measured from a subset of the points to the rest .
Revised:  We present an efficient solver for Classical Scaling , a specific MDS model, by extrapolating the information provided by distances measured from a subset of the points to the remainder .
Edit intent: fluency
Original:  The computational and space complexities of the new MDS procedures are be thereby reduced from quadratic to quasi-linear in the number of data points.
Revised:  The computational and space complexities of the new MDS methods are thereby reduced from quadratic to quasi-linear in the number of data points.
Edit intent: clarity
Original:  Incorporating both local and global information about the data allows us to construct a low rank approximation to the inter-geodesic distances between the data points.
Revised:  Incorporating both local and global information about the data allows us to construct a low-rank approximation of the inter-geodesic distances between the data points.
Edit intent: fluency
Original:  Since it is often unclear , what points are "interesting", human labelling cannot be used to find a truly unbiased solution.
Revised:  Since it is often unclear what points are "interesting", human labelling cannot be used to find a truly unbiased solution.
Edit intent: fluency
Original: Networking on white spaces (i.e., locally unused spectrum) relies on active monitoring of spatio-temporal spectrum usage.
Revised: Networking on white spaces (i.e., locally unused spectrum) relies on active monitoring of spectrum usage.
Edit intent: clarity
Original:  Spectrum databases based on empirical radio propagation models are widely adopted but shown to be error-prone, since they do not account for local environments like trees and man-made buildings.
Revised:  Spectrum databases based on empirical radio propagation models are widely adopted but shown to be error-prone, since they do not account for built environments like trees and man-made buildings.
Edit intent: clarity
Original:  As an economically viable alternative , crowd-sensed radio mapping acquires more accurate local spectrum data from spatially distributed users and constructs radio maps using spatial models such as Kriging and Gaussian Process.
Revised:  As an economically viable option , crowd-sensed radio mapping acquires more accurate local spectrum data from spatially distributed users and constructs radio maps using spatial models such as Kriging and Gaussian Process.
Edit intent: fluency
Original:  In this work, we design a crowd-sensing system for radio mapping, and develop several pricing mechanisms that maximize the expected utility , which trades off sampling performance (e.g., sample location and data quality) against sensing costs.
Revised:  In this work, we consider the scenario where the platform who constructs radio environment maps makes one-time offers to selected users, and collects data from those who accept the offers. We design pricing mechanisms based on expected utility (EU) maximization, where EU captures the tradeoff between radio mapping performance ( location and data quality) against sensing costs.
Edit intent: clarity
Original:  Specifically, we develop optimal pricing with sequential offering, and probable-acceptance pricing with single-/multi- batch offering .
Revised:  Specifically, we consider sequential offering, and probable-acceptance pricing with single-/multi- batch offering .
Edit intent: clarity
Original:  Specifically, we develop optimal pricing with sequential offering, and probable-acceptance pricing with single-/multi- batch offering .
Revised:  Specifically, we develop optimal pricing with sequential offering, where one best price offer is sent to the best user in each round, and batched offering, where a batch of multiple offers are made in each round .
Edit intent: clarity
Original:  We illustrate the models via a series of applications including testing for incentives to form cross-caste relationships in rural India, testing to see whether network structure is used to enforce risk-sharing, testing as to whether networks change in response to a community's exposure to microcredit, and show that these models significantly outperform stochastic block models in matching observed network characteristics .
Revised:  We illustrate the models via a series of applications including testing for incentives to form cross-caste relationships in rural India, testing to see whether network structure helps enforce risk-sharing, testing as to whether networks change in response to a community's exposure to microcredit, and show that these models significantly outperform stochastic block models in matching observed network characteristics .
Edit intent: clarity
Original:  We also establish asymptotic properties of the models and various estimators, which requires proving a new Central Limit Theorem for correlated random variables  .
Revised:  We also develop a new central limit theorem for correlated random variables .
Edit intent: clarity
Original:  Rather than manipulating representations living on a single spatial grid, our network layers operate across scale space, on a pyramid of tensors .
Revised:  Rather than manipulating representations living on a single spatial grid, our network layers operate across scale space, on a pyramid of grids .
Edit intent: clarity
Original:  On CIFAR image classification , flipping from single to multigrid within standard CNN architectures improves accuracyat modest compute and parameter increase .
Revised:  On CIFAR and ImageNet classification tasks , flipping from single to multigrid within standard CNN architectures improves accuracyat modest compute and parameter increase .
Edit intent: clarity
Original:  On CIFAR image classification , flipping from single to multigrid within standard CNN architectures improves accuracyat modest compute and parameter increase .
Revised:  On CIFAR image classification , flipping from a single grid to multigrid within standard CNN architectures improves accuracyat modest compute and parameter increase .
Edit intent: fluency
Original:  On CIFAR image classification , flipping from single to multigrid within standard CNN architectures improves accuracyat modest compute and parameter increase .
Revised:  On CIFAR image classification , flipping from single to multigrid within the standard CNN paradigm improves accuracy, while being compute and parameter increase .
Edit intent: clarity
Original:  On CIFAR image classification , flipping from single to multigrid within standard CNN architectures improves accuracyat modest compute and parameter increase .
Revised:  On CIFAR image classification , flipping from single to multigrid within standard CNN architectures improves accuracyat modest compute and parameter efficient .
Edit intent: clarity
Original:  we show synergistic results in combination with residual connections.
Revised:  we show synergy in combination with residual connections.
Edit intent: clarity
Original:  Strikingly, we show that relatively shallow multigrid networks can learn to directly perform spatial transformation tasks, where, in contrast, current CNNs fail.
Revised:  Most strikingly, relatively shallow multigrid networks can learn to directly perform spatial transformation tasks, where, in contrast, current CNNs fail.
Edit intent: coherence
Original:  Together, our results suggest that continuous evolution of features on a multigrid pyramid could replace virtually all existing CNN designs  .
Revised:  Together, our results suggest that continuous evolution of features on a multigrid pyramid is a more powerful alternative to existing CNN designs .
Edit intent: clarity
Original:  We learn the model parameters by using an efficient EM algorithm, which distributes over the users.
Revised:  We learn the model parameters using an efficient EM algorithm, which distributes over the users.
Edit intent: fluency
Original:  Experiments on synthetic and real data gathered from Foursquare show that the proposed inference algorithm learns the parameters efficiently and our method models the real data better than other alternatives .
Revised:  Experiments on synthetic and real data gathered from Foursquare show that the proposed inference algorithm learns the parameters efficiently and our model outperforms the other alternatives in the prediction of time and location of check-ins .
Edit intent: clarity
Original: Community detection, the decomposition of a graph into meaningful building blocks, has been a core research topic in network science over the past years.
Revised: Community detection, the decomposition of a graph into essential building blocks, has been a core research topic in network science over the past years.
Edit intent: clarity
Original: Since a precise notion of what constitutes a community has remained evasive, community detection algorithms have often been compared on benchmark graphs with a particular form of community structure, and classified based on the mathematical techniques they employ.
Revised: Since a precise notion of what constitutes a community has remained evasive, community detection algorithms have often been compared on benchmark graphs with a particular form of assortative community structure and classified based on the mathematical techniques they employ.
Edit intent: clarity
Original:  However, this  can be misleading because apparent similarities in their mathematical machinery can disguise entirely different objectives .
Revised:  However, this comparison can be misleading because apparent similarities in their mathematical machinery can disguise entirely different objectives .
Edit intent: coherence
Original:  Here we provide a focused review of the different motivations that underpin community detection.
Revised:  Here we provide a focused review of these different motivations that underpin community detection.
Edit intent: fluency
Original:  Moreover, highlighting the different facets of community detection also delineates the many lines of research , and points out open directions and avenues for future research.
Revised:  Moreover, highlighting the different facets of community detection also delineates the many lines of research and points out open directions and avenues for future research.
Edit intent: fluency
Original:  Our results show that there are three scaling regimes for the downlink signal-to-interference-plus-noise ratio (SINR), coverage probability, and area spectral efficiency .
Revised:  First, our results show that there are three scaling regimes for the downlink signal-to-interference-plus-noise ratio (SINR), coverage probability, and area spectral efficiency .
Edit intent: coherence
Original:   Furthermore, we provide ordering results for both coverage and average rate as a means to qualitatively compare different transmission techniques that may though exhibit the same performance scaling.
Revised:  Furthermore, we provide ordering results for both coverage and average rate as a means to qualitatively compare different transmission techniques that may exhibit the same performance scaling.
Edit intent: coherence
Original:  Our results, which are validated by simulations, provide succinct insights and valuable design guidelines for the deployment of 5G UDNs.
Revised:  Our results, which are verified by simulations, provide succinct insights and valuable design guidelines for the deployment of 5G UDNs.
Edit intent: clarity
Original:  However, it has been shown that to maintain a bounded cell size distribution, cells that grow exponentially at the single-cell level need to adopt cell size regulation, leading to a negative correlation of mother-daughter generation time.
Revised:  However, existing theories fail to account for the experimentally observed correlations between mother-daughter generation time.
Edit intent: coherence