wanyu/IteraTeR_v2 huggingface dataset:
Original:  The amount of data increases in lockstep with computational efficiency multiplied by the amount of available computational resources, which shifts the bottleneck within the scientific process from data acquisition to data post-processing and analysis.
Revised:  The amount of data increases in lockstep with computational efficiency multiplied by the amount of available computational resources, which shifts the bottleneck within the scientific process from data acquisition to data processing and analysis.
Edit intent: clarity
Original:  The signac framework provides all basic components required to create a well-defined and thus collectively accessible  data space, simplifying data access and modification through a homogeneous data interface , largely agnostic of the data source, i.e., computation or experiment.
Revised:  The signac framework provides all basic components required to create a well-defined and thus collectively accessible data space, simplifying data access and modification through a homogeneous data interface that is largely agnostic to the data source, i.e., computation or experiment.
Edit intent: fluency
Original:  The framework's data model is designed not to require absolute commitment to the presented implementation, simplifying adaption into existing data sets and workflows.
Revised:  The framework's data model is designed to not require absolute commitment to the presented implementation, simplifying adaption into existing data sets and workflows.
Edit intent: fluency
Original: The spectra of signed matrices have played a fundamental role in social sciences, graph theory  and control theory.
Revised: The spectra of signed matrices have played a fundamental role in social sciences, graph theory , and control theory.
Edit intent: fluency
Original:  Our main results are : (a) NP-completeness of three problems: verifying whether a given matrix has a  signing that is positive semi-definite/singular/has bounded eigenvalues , (b) a polynomial-time algorithm to verify whether a given matrix has a signingthat is invertible, and (c) a polynomial-time algorithm to find a minimum increase in support of a given symmetric matrix so that it has an invertible  signing.
Revised:  Our results are twofold: 1. We show NP-completeness of three problems: verifying whether a given matrix has a signing that is positive semi-definite/singular/has bounded eigenvalues , (b) a polynomial-time algorithm to verify whether a given matrix has a signingthat is invertible, and (c) a polynomial-time algorithm to find a minimum increase in support of a given symmetric matrix so that it has an invertible signing.
Edit intent: coherence
Original:  Our main results are : (a) NP-completeness of three problems: verifying whether a given matrix has a  signing that is positive semi-definite/singular/has bounded eigenvalues , (b) a polynomial-time algorithm to verify whether a given matrix has a signingthat is invertible, and (c) a polynomial-time algorithm to find a minimum increase in support of a given symmetric matrix so that it has an invertible  signing.
Revised:  Our main results are : (a) NP-completeness for the following three problems: verifying whether a given matrix has a signing that is positive semi-definite/singular/has bounded eigenvalues , (b) a polynomial-time algorithm to verify whether a given matrix has a signingthat is invertible, and (c) a polynomial-time algorithm to find a minimum increase in support of a given symmetric matrix so that it has an invertible signing.
Edit intent: clarity
Original:  Our main results are : (a) NP-completeness of three problems: verifying whether a given matrix has a  signing that is positive semi-definite/singular/has bounded eigenvalues , (b) a polynomial-time algorithm to verify whether a given matrix has a signingthat is invertible, and (c) a polynomial-time algorithm to find a minimum increase in support of a given symmetric matrix so that it has an invertible  signing.
Revised:  Our main results are : (a) NP-completeness of three problems: verifying whether a given matrix has a symmetric signing that is positive semi-definite/singular/has bounded eigenvalues , (b) a polynomial-time algorithm to verify whether a given matrix has a signingthat is invertible, and (c) a polynomial-time algorithm to find a minimum increase in support of a given symmetric matrix so that it has an invertible signing.
Edit intent: fluency
Original:  Our main results are : (a) NP-completeness of three problems: verifying whether a given matrix has a  signing that is positive semi-definite/singular/has bounded eigenvalues , (b) a polynomial-time algorithm to verify whether a given matrix has a signingthat is invertible, and (c) a polynomial-time algorithm to find a minimum increase in support of a given symmetric matrix so that it has an invertible  signing.
Revised:  Our main results are : (a) NP-completeness of three problems: verifying whether a given matrix has a signing that is positive semi-definite/singular/has bounded eigenvalues , (b) a polynomial-time algorithm to verify whether a given matrix has a signingthat is invertible, and (c) a polynomial-time algorithm to find a minimum increase in support of a given symmetric matrix so that it has an invertible symmetric signing.
Edit intent: fluency
Original: The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets  .
Revised: The past analyses of datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets .
Edit intent: clarity
Original: The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets  .
Revised: The past analyses of available datasets for social networks have enabled us to make empirical findings of a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets .
Edit intent: clarity
Original: The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets  .
Revised: The past analyses of available datasets for social networks have given rise to a number of aspects of human society, yet leaving the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets .
Edit intent: clarity
Original: The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets  .
Revised: The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored . For deeper insight into human society there is either need for more comprehensive datasets .
Edit intent: clarity
Original: The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets  .
Revised: The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets or modeling .
Edit intent: clarity
Original:  In order to model the whole social network, we assume that some properties of the network are reflected in empirical findings that are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations.
Revised:  In order to model the whole social network, we assume that some properties of the network are reflected in empirical findings and are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations.
Edit intent: coherence
Original:  In order to model the whole social network, we assume that some properties of the network are reflected in empirical findings that are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations.
Revised:  In order to model the whole social network, we assume that some properties of the network are reflected in empirical findings that are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations.
Edit intent: fluency
Original:  Several models have been studied to generate the stylized facts, but  most of them focus on the processes or mechanisms behind stylized facts.
Revised:  Several models have been studied to generate the stylized facts, but so far most of them focus on the processes or mechanisms behind stylized facts.
Edit intent: clarity
Original:  Several models have been studied to generate the stylized facts, but  most of them focus on the processes or mechanisms behind stylized facts.
Revised:  Several models have been studied to generate the stylized facts, but most of them have focused on the processes or mechanisms behind stylized facts.
Edit intent: fluency
Original:  In this paper, we take an alternative approach by devising a  static model for the whole social network, for which we randomly assign a number of communities to a given set of isolated nodes using a few assumptions , i.e., the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  Here we take an alternative approach by devising a static model for the whole social network, for which we randomly assign a number of communities to a given set of isolated nodes using a few assumptions , i.e., the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Edit intent: coherence
Original:  In this paper, we take an alternative approach by devising a  static model for the whole social network, for which we randomly assign a number of communities to a given set of isolated nodes using a few assumptions , i.e., the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  In this paper, we take an alternative approach by devising a static model for the whole social network, for which we randomly assign a number of communities to a given set of isolated nodes using a few assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Edit intent: clarity
Original:  With these assumptions, we are able to generate realistic social networks that show most stylized facts for a wide range of parameters.
Revised:  Only with these few assumptions, we are able to generate realistic social networks that show most stylized facts for a wide range of parameters.
Edit intent: clarity
Original:  We also obtain analytic results for various network quantities that turn out to be comparable with the numerical results.
Revised:  We also obtain analytical results for various network quantities that turn out to be comparable with the numerical results.
Edit intent: fluency
Original:  Several models have been studied to generate the stylized facts , but so far most of them have focused on the processes or mechanisms behind stylized facts .
Revised:  Several models have been studied to generate the stylized facts .
Edit intent: clarity
Original:  Here we take an alternative approach by devising a community-based static model for the whole social network , for which we randomly assign a number of communities to a given set of isolated nodes using a few  assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  In this paper, in order to model the whole social network, we take an alternative approach by devising a community-based static model for the whole social network , for which we randomly assign a number of communities to a given set of isolated nodes using a few assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Edit intent: coherence
Original:  Here we take an alternative approach by devising a community-based static model for the whole social network , for which we randomly assign a number of communities to a given set of isolated nodes using a few  assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  Here we take an alternative approach by devising a community-based static model , for which we randomly assign a number of communities to a given set of isolated nodes using a few assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Edit intent: clarity
Original:  Here we take an alternative approach by devising a community-based static model for the whole social network , for which we randomly assign a number of communities to a given set of isolated nodes using a few  assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  Here we take an alternative approach by devising a community-based static model for the whole social network , for which a number of communities to a given set of isolated nodes using a few assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Edit intent: clarity
Original:  Here we take an alternative approach by devising a community-based static model for the whole social network , for which we randomly assign a number of communities to a given set of isolated nodes using a few  assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  Here we take an alternative approach by devising a community-based static model for the whole social network , for which we randomly assign a number of communities are randomly assigned to isolated nodes using a few assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Edit intent: clarity
Original:  Here we take an alternative approach by devising a community-based static model for the whole social network , for which we randomly assign a number of communities to a given set of isolated nodes using a few  assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  Here we take an alternative approach by devising a community-based static model for the whole social network , for which we randomly assign a number of communities to a given set of isolated nodes using a few reasonable assumptions such that the community size is heterogeneous, and larger communities are assigned with smaller link density and smaller characteristic link weight.
Edit intent: clarity
Original:  Only with these few assumptions, we are able to generate realistic social networks that show most stylized facts for a wide range of parameters .
Revised:  With these few assumptions, we are able to generate realistic social networks that show most stylized facts for a wide range of parameters .
Edit intent: coherence
Original:  In contrast to the dynamical generative models, our community-based static model is simple to implement and easily scalable .
Revised:  Since our community-based static model is simple to implement and easily scalable .
Edit intent: coherence
Original: The past analyses of datasets for social networks have enabled us to make empirical findings of a number of aspects of human society, which are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations.
Revised: The past analyses of datasets of social networks have enabled us to make empirical findings of a number of aspects of human society, which are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations.
Edit intent: fluency
Original:  Since the structure of the whole social network is yet largely unexplored , for deeper insight into human society there is need for more comprehensive datasets and modeling of the stylized facts .
Revised:  Since the understanding of the structure of these complex social networks is far from complete , for deeper insight into human society there is need for more comprehensive datasets and modeling of the stylized facts .
Edit intent: clarity
Original:  Since the structure of the whole social network is yet largely unexplored , for deeper insight into human society there is need for more comprehensive datasets and modeling of the stylized facts .
Revised:  Since the structure of the whole social network is yet largely unexplored , for deeper insight into human society more comprehensive datasets and modeling of the stylized facts .
Edit intent: clarity
Original:  In this paper, in order to model the whole social network, we take an alternative approach by devising a community-based static model , for which a number of communities are randomly assigned to isolated nodes using a few reasonable assumptions such that the community size is heterogeneous , and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  In this paper, in order to model the whole social network, we take an alternative approach by devising a community-based static model with heterogeneous community sizes and larger communities are assigned with smaller link density and smaller characteristic link weight.
Edit intent: clarity
Original:  In this paper, in order to model the whole social network, we take an alternative approach by devising a community-based static model , for which a number of communities are randomly assigned to isolated nodes using a few reasonable assumptions such that the community size is heterogeneous , and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  In this paper, in order to model the whole social network, we take an alternative approach by devising a community-based static model , for which a number of communities are randomly assigned to isolated nodes using a few reasonable assumptions such that the community size is heterogeneous , and larger communities having smaller link density and smaller characteristic link weight.
Edit intent: clarity
Original:  In this paper, in order to model the whole social network, we take an alternative approach by devising a community-based static model , for which a number of communities are randomly assigned to isolated nodes using a few reasonable assumptions such that the community size is heterogeneous , and larger communities are assigned with smaller link density and smaller characteristic link weight.
Revised:  In this paper, in order to model the whole social network, we take an alternative approach by devising a community-based static model , for which a number of communities are randomly assigned to isolated nodes using a few reasonable assumptions such that the community size is heterogeneous , and larger communities are assigned with smaller link density and weight.
Edit intent: clarity
Original:  With these few assumptions , we are able to generate realistic social networks that show most stylized facts for a wide range of parameters, which in turn can explain why the stylized facts are so commonly observed.
Revised:  With these few assumptions we are able to generate realistic social networks that show most stylized facts for a wide range of parameters, which in turn can explain why the stylized facts are so commonly observed.
Edit intent: fluency
Original:  Since our community-based static model is simple to implement and easily scalable, it can be used as a reference system, benchmark, or testbed for further applications in physics, computer science, and social sciences .
Revised:  Since our community-based static model is simple to implement and easily scalable, it can be used as a reference system, benchmark, or testbed for further applications .
Edit intent: clarity
Original:  We provide a proof of principle that the resulting model for binding through assembly pointers can be implemented  in networks of spiking neurons , and supports basic operations of brain computations, such as structured information retrieval and copying of information .
Revised:  We provide a proof of principle that this model can be implemented in networks of spiking neurons , and supports basic operations of brain computations, such as structured information retrieval and copying of information .
Edit intent: clarity
Original:  We provide a proof of principle that the resulting model for binding through assembly pointers can be implemented  in networks of spiking neurons , and supports basic operations of brain computations, such as structured information retrieval and copying of information .
Revised:  We provide a proof of principle that the resulting model for binding through assembly pointers can be implemented even in networks of spiking neurons , and supports basic operations of brain computations, such as structured information retrieval and copying of information .
Edit intent: clarity
Original:  We provide a proof of principle that the resulting model for binding through assembly pointers can be implemented  in networks of spiking neurons , and supports basic operations of brain computations, such as structured information retrieval and copying of information .
Revised:  We provide a proof of principle that the resulting model for binding through assembly pointers can be implemented in networks of spiking neurons . It enables structured information retrieval and copying of information .
Edit intent: coherence
Original: Currently existing neural network models lack an important computational capability of networks of neurons in the brain: the capability to reason on an abstract level , and to structure information according to abstract categories.
Revised: Humans possess the capability to reason on an abstract level , and to structure information according to abstract categories.
Edit intent: clarity