wanyu/IteraTeR_v2 huggingface dataset:
Original:  In this work we describe how to classify subgraphs in multiplex networks , and we extend motif analysis to networks with many layers.
Revised:  In this work we describe how to classify the subgraphs of a multiplex network , and we extend motif analysis to networks with many layers.
Edit intent: clarity
Original:  In this work we describe how to classify subgraphs in multiplex networks , and we extend motif analysis to networks with many layers.
Revised:  In this work we describe how to classify subgraphs in multiplex networks , and we extend motif analysis to networks with an arbitrary number of layers.
Edit intent: clarity
Original:  Results indicate the statistically significance of subgraphs where the presence of a physical connection between two areas (link at the structural layer) coexists with positive correlations in their activity (positive link in the functional layer) .
Revised:  Results indicate that subgraphs in which the presence of a physical connection between two areas (link at the structural layer) coexists with positive correlations in their activity (positive link in the functional layer) .
Edit intent: clarity
Original:  Results indicate the statistically significance of subgraphs where the presence of a physical connection between two areas (link at the structural layer) coexists with positive correlations in their activity (positive link in the functional layer) .
Revised:  Results indicate the statistically significance of subgraphs where the presence of a physical connection between brain areas (links at the structural layer) coexists with positive correlations in their activity (positive link in the functional layer) .
Edit intent: clarity
Original:  Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the presence of a link in one layer depends on the intensity of the connection in the other one.
Revised:  Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the probability to find a link in one layer depends on the intensity of the connection in the other one.
Edit intent: clarity
Original:  The immediate answer might be "not that much", but in reality they are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents, namely individuals, computers, or neurons  .
Revised:  They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents, namely individuals, computers, or neurons .
Edit intent: coherence
Original:  Here we provide an overview of some of the measures proposed so far to characterise the structure of multiplex networks, and a selection of models aiming at reproducing those structural properties and at quantifying their statistical significance.
Revised:  Here we provide an overview of some of the measures proposed so far to characterise the structure of multiplex networks, and a selection of models aiming at reproducing those structural properties and quantifying their statistical significance.
Edit intent: fluency
Original: Profile pictures on social networks are users' opportunity to present themselves and to affect how others judge them.
Revised: Profile images on social networks are users' opportunity to present themselves and to affect how others judge them.
Edit intent: fluency
Original:  In most social networks, profile pictures are public by default . 1,122 Facebook users completed a matrices intelligence test and shared their current Facebook profile picture . Strangers also rated the images for perceived intelligence.
Revised:  We examine what Facebook images say about users' perceived and measured intelligence . 1,122 Facebook users completed a matrices intelligence test and shared their current Facebook profile picture . Strangers also rated the images for perceived intelligence.
Edit intent: clarity
Original:  In most social networks, profile pictures are public by default . 1,122 Facebook users completed a matrices intelligence test and shared their current Facebook profile picture . Strangers also rated the images for perceived intelligence.
Revised:  In most social networks, profile pictures are public by default . 1,122 Facebook users completed a matrices intelligence test and shared their current Facebook profile image . Strangers also rated the images for perceived intelligence.
Edit intent: clarity
Original:  We use automatically extracted features from profile pictures to predict both measured and perceived intelligence.
Revised:  We use automatically extracted image features to predict both measured and perceived intelligence.
Edit intent: clarity
Original:  Our results give insights into inaccurate stereotyping from profile pictures and also have implications for privacy  .
Revised:  Our results give insights into inaccurate stereotyping from profile images and also have implications for privacy .
Edit intent: fluency
Original:  The techniques are based on the blocked  scheme proposed by P.-G. Martinsson and S. Voronin, and produce a QB factorization as well.
Revised:  The techniques are based on the blocked scheme proposed by P.-G. Martinsson and S. Voronin, producing a QB factorization as well.
Edit intent: coherence
Original:  With an economic error indicator employed and the applications of A moved out of the loop, the techniques result in two algorithms called randQB_EI and randQB_FP.
Revised:  With an economic error indicator and moving A moved out of the loop, the techniques result in two algorithms called randQB_EI and randQB_FP.
Edit intent: clarity
Original:  With an economic error indicator employed and the applications of A moved out of the loop, the techniques result in two algorithms called randQB_EI and randQB_FP.
Revised:  With an economic error indicator employed and the applications of A out of the loop, the techniques result in two algorithms called randQB_EI and randQB_FP.
Edit intent: clarity
Original:  The randQB_FP algorithm also owns the pass-efficient merit .
Revised:  The randQB_FP algorithm also owns the merit of pass-efficiency .
Edit intent: clarity
Original:  Numerical experiments on a multi-core parallel computing server show that the proposed algorithms have the similar accuracy as the blocked randQB scheme, but cost several times less runtime and memory usage .
Revised:  Numerical experiments on a multi-core parallel computing server show that the proposed algorithms have the similar accuracy as the blocked randQB scheme, but cost several times less runtime and memory .
Edit intent: clarity
Original:  The benefits are even larger ( go up to 20X) for handling large sparse matrices.
Revised:  The benefits are even larger ( up to 20X) for handling large sparse matrices.
Edit intent: clarity
Original:  Compared with the adaptive range finder algorithm, the proposed methods output much smaller and close to optimal rank while satisfying the set accuracy tolerance.
Revised:  Compared with the adaptive range finder algorithm, the proposed methods output much smaller and close to optimal rank while satisfying the preset accuracy tolerance.
Edit intent: clarity
Original: In this paper, randomized techniques for computing low-rank factorizations are presented.
Revised: Randomized algorithms for low-rank factorizations are presented.
Edit intent: clarity
Original:  The proposed methods take in a tolerance \varepsilon and an m \times n matrix , and output an approximate low-rank factorization of%DIFDELCMD < A%%% , whose error measured in the Frobenius norm is within \varepsilon.
Revised:  The proposed methods take in a tolerance \varepsilon and an m \times n matrix %DIFDELCMD < A%%% , whose error measured in the Frobenius norm is within \varepsilon.
Edit intent: clarity
Original:  The techniques are based on the blocked randQB scheme proposed by P.-G. Martinsson and S. Voronin, producing a QB factorization.
Revised:  The techniques are based on the blocked randQB algorithm by P.-G. Martinsson and S. Voronin, producing a QB factorization.
Edit intent: clarity
Original:  Compared with the adaptive range finder algorithm , the proposed methods output much smaller and close to optimal rank while satisfying the preset accuracy tolerance .
Revised:  Compared with the adaptive range finder algorithm for solving the fixed-precision problem .
Edit intent: clarity
Original:  We say  a Bell inequality is normalized if its absolute value does not exceed 1 for any classical (i.e. local) distribution.
Revised:  We say that a Bell inequality is normalized if its absolute value does not exceed 1 for any classical (i.e. local) distribution.
Edit intent: fluency
Original:  We show how to derive large violations from any gap between classical and quantum communication complexity, provided the lower bound on classical communication is proven using these lower bounds .
Revised:  We show how to derive large violations from any gap between classical and quantum communication complexity, provided the lower bound on classical communication is proven using these lower bound techniques .
Edit intent: clarity
Original: In this paper, we extend neural Turing machine (NTM)  into a dynamic neural Turing machine (D-NTM) by introducing a trainable memory addressing scheme.
Revised: We extend neural Turing machine (NTM) into a dynamic neural Turing machine (D-NTM) by introducing a trainable memory addressing scheme.
Edit intent: clarity
Original: In this paper, we extend neural Turing machine (NTM)  into a dynamic neural Turing machine (D-NTM) by introducing a trainable memory addressing scheme.
Revised: In this paper, we extend neural Turing machine (NTM) model into a dynamic neural Turing machine (D-NTM) by introducing a trainable memory addressing scheme.
Edit intent: clarity
Original:  This  scheme maintains for each memory cell two separate vectors, content and address vectors.
Revised:  This addressing scheme maintains for each memory cell two separate vectors, content and address vectors.
Edit intent: clarity
Original:  We investigate the mechanisms and effects for learning to read and write to a memory through experiments on Facebook bAbI tasks using both a feedforward and GRU-controller .
Revised:  We investigate the mechanisms and effects of learning to read and write to a memory through experiments on Facebook bAbI tasks using both a feedforward and GRU-controller .
Edit intent: fluency
Original:  We investigate the mechanisms and effects for learning to read and write to a memory through experiments on Facebook bAbI tasks using both a feedforward and GRU-controller .
Revised:  We investigate the mechanisms and effects for learning to read and write into a memory through experiments on Facebook bAbI tasks using both a feedforward and GRU-controller .
Edit intent: fluency
Original:  We investigate the mechanisms and effects for learning to read and write to a memory through experiments on Facebook bAbI tasks using both a feedforward and GRU-controller .
Revised:  We investigate the mechanisms and effects for learning to read and write to a memory through experiments on Facebook bAbI tasks using both a feedforward and GRUcontroller .
Edit intent: fluency
Original:  The D-NTM is evaluated on a set of the Facebook bAbI tasks and shown to outperform NTM and LSTM baselines  .
Revised:  The D-NTM is evaluated on a set of Facebook bAbI tasks and shown to outperform NTM and LSTM baselines .
Edit intent: fluency
Original: Convolutional neural networks (CNNs) are revolutionizing a variety of machine learningtasks , but they present significant computational challenges.
Revised: Convolutional neural networks (CNNs) are revolutionizing machine learning , but they present significant computational challenges.
Edit intent: clarity
Original:  Recently,  FPGA-based accelerators have been proposed to improve the speed and efficiency of CNNs. Current approaches construct a single processor that computes the CNN layers one at a time;
Revised:  Recently, many FPGA-based accelerators have been proposed to improve the speed and efficiency of CNNs. Current approaches construct a single processor that computes the CNN layers one at a time;
Edit intent: clarity
Original:  Recently,  FPGA-based accelerators have been proposed to improve the speed and efficiency of CNNs. Current approaches construct a single processor that computes the CNN layers one at a time;
Revised:  Recently, FPGA-based accelerators have been proposed to improve the performance and efficiency of CNNs. Current approaches construct a single processor that computes the CNN layers one at a time;
Edit intent: clarity
Original:  this single processor is optimized to maximize the overall throughput at which the collection of layers are computed.
Revised:  the processor is optimized to maximize the overall throughput at which the collection of layers are computed.
Edit intent: clarity
Original:  this single processor is optimized to maximize the overall throughput at which the collection of layers are computed.
Revised:  this single processor is optimized to maximize the throughput at which the collection of layers are computed.
Edit intent: clarity
Original:  this single processor is optimized to maximize the overall throughput at which the collection of layers are computed.
Revised:  this single processor is optimized to maximize the overall throughput at which the collection of layers is computed.
Edit intent: fluency
Original:  Using the same FPGA resources as a single large processor, multiple smaller specialized processors result in increased computational efficiency and lead to a higher overall throughput.
Revised:  Using the same FPGA resources as a single large processor, multiple smaller specialized processors increase computational efficiency and lead to a higher overall throughput.
Edit intent: clarity
Original:  Our design methodology achieves 1.51 x higher throughput than the state of the art approach on evaluating the popular AlexNet CNN on a Xilinx Virtex-7 FPGA.
Revised:  Our design methodology achieves 1.51 x higher throughput than the state-of-the-art approach on evaluating the popular AlexNet CNN on a Xilinx Virtex-7 FPGA.
Edit intent: fluency
Original:  We then deduce existence of the calibrated model by extending the results in Figalli (2008).
Revised:  Finally, we deduce existence of the calibrated model by extending the results in Figalli (2008).
Edit intent: coherence
Original: This article introduces two Tensor Train-based iterative algorithms for the identification of high order discrete-time nonlinear MIMO Volterra systems.
Revised: This article introduces two Tensor Train-based iterative algorithms for the identification of high-order discrete-time nonlinear MIMO Volterra systems.
Edit intent: fluency
Original: This article introduces two Tensor Train-based iterative algorithms for the identification of high order discrete-time nonlinear MIMO Volterra systems.
Revised: This article introduces two Tensor Train-based iterative algorithms for the identification of high order discrete-time nonlinear multiple-input multiple-output (MIMO) Volterra systems.
Edit intent: clarity
Original:  The presented algorithms are guaranteed to monotonically converge and numerical stability is ensured through the use of orthogonal matrix factorizations.
Revised:  The proposed algorithms are guaranteed to monotonically converge and numerical stability is ensured through the use of orthogonal matrix factorizations.
Edit intent: clarity
Original:  The performance and accuracy of the two identification algorithms is illustrated by means of two experiments, where accurate degree-10 MIMO Volterra models are identified in about 1 second  .
Revised:  The performance and accuracy of the two identification algorithms are illustrated by numerical experiments, where accurate degree-10 MIMO Volterra models are identified in about 1 second .
Edit intent: clarity
Original: I consider the problem of representing integers in close to optimal number of bits to support increment and decrement operations efficiently as described in BGPS2014%DIFDELCMD < ]%%% . The problem is studied in the bit probe model.
Revised: I consider the problem of representing integers in close to optimal number of bits BGPS2014%DIFDELCMD < ]%%% . The problem is studied in the bit probe model.
Edit intent: coherence
Original: I consider the problem of representing integers in close to optimal number of bits to support increment and decrement operations efficiently as described in BGPS2014%DIFDELCMD < ]%%% . The problem is studied in the bit probe model.
Revised: I consider the problem of representing integers in close to optimal number of bits to support increment and decrement operations efficiently as described in %DIFDELCMD < ]%%% . The problem is studied in the bit probe model.
Edit intent: clarity
Original:  The article BGPS2014%DIFDELCMD < ] %%% contains two basic constructions: one uses n bits to represent exactly 2^n values and requires n-1 reads in the worst case , the other one is redundant (represents less than 2^n values), but requires only a logarithmic number of reads for incrementing.
Revised:  The article %DIFDELCMD < ] %%% contains two basic constructions: one uses n bits to represent exactly 2^n values and requires n-1 reads in the worst case , the other one is redundant (represents less than 2^n values), but requires only a logarithmic number of reads for incrementing.
Edit intent: clarity
Original: We present the first linear lower bound for the number of bits required to be accessed in the worst case to increment an integer in an arbitrary space-optimal binary representation.
Revised: We present the first linear lower bound for the number of bits required to be accessed in the worst case to increment an integer in an arbitrary space- optimal binary representation.
Edit intent: fluency
Original: The notion of online space complexity , introduced by Karp in 1967, quantifies the amount of space required to solve a given problem using an online algorithm,  represented by a Turing machine which scans the input exactly once from left to right  .
Revised: The notion of online space complexity , introduced by Karp in 1967, quantifies the amount of states required to solve a given problem using an online algorithm, represented by a Turing machine which scans the input exactly once from left to right .
Edit intent: clarity
Original: The notion of online space complexity , introduced by Karp in 1967, quantifies the amount of space required to solve a given problem using an online algorithm,  represented by a Turing machine which scans the input exactly once from left to right  .
Revised: The notion of online space complexity , introduced by Karp in 1967, quantifies the amount of space required to solve a given problem using an online algorithm, which is represented by a Turing machine which scans the input exactly once from left to right .
Edit intent: coherence
Original:  In this paper, we study alternating algorithms as introduced by Chandra, Kozen and Stockmeyer in 1976.
Revised:  In this paper, we extend the setting to alternating machines as introduced by Chandra, Kozen and Stockmeyer in 1976.
Edit intent: clarity
Original:  The first is a hierarchy theorem for languages of polynomial alternating online space complexity , and the second is a linear lower bound on the alternating online space complexity of the prime numbers written in binary.
Revised:  The first is a hierarchy theorem for languages of polynomial alternating online space complexity , and the second is a linear lower bound on the alternating online state complexity of the prime numbers written in binary.
Edit intent: fluency
Original:  Our implementation also supports multithreading using an approach identical to that used for MM in BLIS, with similar performance characteristics.
Revised:  Our implementation supports multithreading using an approach identical to that used for MM in BLIS, with similar performance characteristics.
Edit intent: clarity
Original: Tensor computations--in particular tensor contraction (TC)--are important kernels in many scientific computing applications (SCAs) .
Revised: Tensor computations--in particular tensor contraction (TC)--are important kernels in many scientific computing applications .
Edit intent: clarity
Original:  The complexity of managing tensor-to-matrix transformations is also handled automatically in our approach, greatly simplifying its use in SCAs .
Revised:  The complexity of managing tensor-to-matrix transformations is also handled automatically in our approach, greatly simplifying its use in scientific applications .
Edit intent: clarity
Original: The hierarchical interpolative factorization ( HIF ) offers an efficient way for solving or preconditioning elliptic partial differential equations.
Revised: The hierarchical interpolative factorization ( HIF ) offers an efficient way for solving or preconditioning elliptic partial differential equations.
Edit intent: fluency
Original:  In this paper, the distributed-memory HIF (%DIFDELCMD < {%%% DHIF ) is introduced as a parallel and distributed-memory implementation of the HIF.
Revised:  In this paper, the distributed-memory (%DIFDELCMD < {%%% DHIF ) is introduced as a parallel and distributed-memory implementation of the HIF.
Edit intent: fluency
Original:  In this paper, the distributed-memory HIF (%DIFDELCMD < {%%% DHIF ) is introduced as a parallel and distributed-memory implementation of the HIF.
Revised:  In this paper, the distributed-memory HIF %DIFDELCMD < {%%% DHIF ) is introduced as a parallel and distributed-memory implementation of the HIF.
Edit intent: fluency
Original:  Extensive numerical examples are performed on the TACC Stampede system with up to 4096 processes.
Revised:  Extensive numerical examples are performed on the TACC Stampede system with up to 4096 processes.
Edit intent: fluency
Original:  The numerical results agree with the complexity analysis and demonstrate the efficiency and scalability of the DHIF .
Revised:  The numerical results agree with the complexity analysis and demonstrate the efficiency and scalability of the DHIF .
Edit intent: fluency
Original:  Such large-scale deformations emerge from processes such as cell shape changes, cell rearrangements, cell divisions, and cell extrusions.
Revised:  Such large-scale deformations emerge from many individual cellular events such as cell shape changes, cell rearrangements, cell divisions, and cell extrusions.
Edit intent: clarity
Original:  Using this Triangle Method, we exactly decompose large-scale material deformation into contributions from cellular processes .
Revised:  Using this Triangle Method, we exactly decompose large-scale material deformation .
Edit intent: clarity
Original: How common is self-citation in scholarly publication  and does the practice vary by gender?
Revised: How common is self-citation in scholarly publication , and does the practice vary by gender?
Edit intent: fluency
Original:  Using novel methods and a dataset of 1.5 million research papers in the scholarly database JSTOR published between 1779-2011, we find that nearly 10 \% of references are self-citations by a paper's authors.
Revised:  Using novel methods and a data set of 1.5 million research papers in the scholarly database JSTOR published between 1779-2011, we find that nearly 10 \% of references are self-citations by a paper's authors.
Edit intent: clarity
Original:  Using novel methods and a dataset of 1.5 million research papers in the scholarly database JSTOR published between 1779-2011, we find that nearly 10 \% of references are self-citations by a paper's authors.
Revised:  Using novel methods and a dataset of 1.5 million research papers in the scholarly database JSTOR published between 1779 and 2011, the authors find that nearly 10 \% of references are self-citations by a paper's authors.
Edit intent: clarity