wanyu/IteraTeR_v2 huggingface dataset:
Original:  From physics  we introduce type constraints, analogous to the constraints that disqualify adding meters to seconds in physics . From functional programming, we require that strongly-typed architectures factorize into stateless learnware and state-dependent firmware, thereby ameliorating the impact of side-effects.
Revised:  From physics , we introduce type constraints, analogous to the constraints that disqualify adding meters to seconds in physics . From functional programming, we require that strongly-typed architectures factorize into stateless learnware and state-dependent firmware, thereby ameliorating the impact of side-effects.
Edit intent: fluency
Original:  From physics  we introduce type constraints, analogous to the constraints that disqualify adding meters to seconds in physics . From functional programming, we require that strongly-typed architectures factorize into stateless learnware and state-dependent firmware, thereby ameliorating the impact of side-effects.
Revised:  From physics we introduce type constraints, analogous to the constraints that forbids adding meters to seconds in physics . From functional programming, we require that strongly-typed architectures factorize into stateless learnware and state-dependent firmware, thereby ameliorating the impact of side-effects.
Edit intent: clarity
Original:  From physics  we introduce type constraints, analogous to the constraints that disqualify adding meters to seconds in physics . From functional programming, we require that strongly-typed architectures factorize into stateless learnware and state-dependent firmware, thereby ameliorating the impact of side-effects.
Revised:  From physics we introduce type constraints, analogous to the constraints that disqualify adding meters to seconds . From functional programming, we require that strongly-typed architectures factorize into stateless learnware and state-dependent firmware, thereby ameliorating the impact of side-effects.
Edit intent: fluency
Original:  From physics  we introduce type constraints, analogous to the constraints that disqualify adding meters to seconds in physics . From functional programming, we require that strongly-typed architectures factorize into stateless learnware and state-dependent firmware, thereby ameliorating the impact of side-effects.
Revised:  From physics we introduce type constraints, analogous to the constraints that disqualify adding meters to seconds in physics . From functional programming, we require that strongly-typed architectures factorize into stateless learnware and state-dependent firmware, reducing the impact of side-effects.
Edit intent: clarity
Original:  Finally, experiments show that, despite being more constrained, strongly-typed architectures achieve lower training error and comparable generalization error to classical architectures.
Revised:  Finally, experiments show that, despite being more constrained, strongly-typed architectures achieve lower training and comparable generalization error to classical architectures.
Edit intent: fluency
Original: Hidalgo and Hausmann's  Economic Complexity Index  measures the complexity of national economies in terms of product groups.
Revised: Hidalgo Hausmann's Economic Complexity Index measures the complexity of national economies in terms of product groups.
Edit intent: clarity
Original:  We measure ECI, PatCI, and THCI during the period from 2000 to 2014 for the 34 OECD member states, the BRICS countries, and a group of emerging economies  .
Revised:  We measure ECI, PatCI, and THCI during the period 2000-2014 for the 34 OECD member states, the BRICS countries, and a group of emerging economies .
Edit intent: clarity
Original:  The positive correlation between ECI and average income claimed as an argument for the predictive value of economic complexity index cannot be confirmed using our data.
Revised:  The positive correlation between ECI and average income claimed as an argument for the predictive value of ECI cannot be confirmed using our data.
Edit intent: clarity
Original: Hidalgo Hausmann's (2009) Economic Complexity Index (ECI   ) measures the complexity of national economies in terms of product groups.
Revised:  Hausmann's (2009) Economic Complexity Index (ECI ) measures the complexity of national economies in terms of product groups.
Edit intent: clarity
Original: Hidalgo Hausmann's (2009) Economic Complexity Index (ECI   ) measures the complexity of national economies in terms of product groups.
Revised: Hidalgo The Economic Complexity Index (ECI ) measures the complexity of national economies in terms of product groups.
Edit intent: clarity
Original:  Analogously to ECI, we develop the Patent Complexity Index (PatCI)  on the basis of a matrix of nations versus patent classes.
Revised:  Analogously to ECI, the Patent Complexity Index (PatCI) on the basis of a matrix of nations versus patent classes.
Edit intent: clarity
Original:  Using linear algebra, the three dimensions  countries, product groups, and patent classes can be combined into an integrated ( "Triple Helix" ) measure of complexity (THCI) .
Revised:  Using linear algebra, the three dimensions - countries, product groups, and patent classes can be combined into an integrated ( "Triple Helix" ) measure of complexity (THCI) .
Edit intent: fluency
Original:  Using linear algebra, the three dimensions  countries, product groups, and patent classes can be combined into an integrated ( "Triple Helix" ) measure of complexity (THCI) .
Revised:  Using linear algebra, the three dimensions countries, product groups, and patent classes can be combined into a measure of "Triple Helix" ) measure of complexity (THCI) .
Edit intent: clarity
Original:  Using linear algebra, the three dimensions  countries, product groups, and patent classes can be combined into an integrated ( "Triple Helix" ) measure of complexity (THCI) .
Revised:  Using linear algebra, the three dimensions countries, product groups, and patent classes can be combined into an integrated ( "Triple Helix" complexity (THCI) .
Edit intent: clarity
Original:  The three complexity indicators are significantly correlated between themselves , yet each captures another aspect of the complexity.
Revised:  The three complexity indicators are correlated between themselves , yet each captures another aspect of the complexity.
Edit intent: clarity
Original:  Analogously to ECI, the Patent Complexity Index (PatCI) can be developed on the basis of a matrix of nations versus patent classes.
Revised:  Analogously to ECI, a Patent Complexity Index (PatCI) can be developed on the basis of a matrix of nations versus patent classes.
Edit intent: fluency
Original:  Using linear algebra, the three dimensions - countries, product groups, and patent classes can be combined into a measure of "Triple Helix" complexity (THCI) including the trilateral interaction terms between knowledge production, wealth generation, and (national) control.
Revised:  Using linear algebra, the three dimensions : countries, product groups, and patent classes can be combined into a measure of "Triple Helix" complexity (THCI) including the trilateral interaction terms between knowledge production, wealth generation, and (national) control.
Edit intent: fluency
Original:  However, node similarity between nodes in different graphs (inter-graph nodes) has not been investigated adequately yet.
Revised:  However, node similarity between nodes in different graphs (inter-graph nodes) has not received a lot of attention yet.
Edit intent: clarity
Original:  The inter-graph node similarity is important in learning a new graph based on the knowledge of an existing graph (transfer learning in graphs) and has applications in biological, communication, and social networks.
Revised:  The inter-graph node similarity is important in learning a new graph based on the knowledge of an existing graph (transfer learning on graphs) and has applications in biological, communication, and social networks.
Edit intent: clarity
Original:  In NED, two inter-graph nodes are compared according to their local neighborhood topological structures which are unlabeled unordered k-adjacent trees  . Since the computation problem of tree edit distance on unordered trees is NP-Complete .
Revised:  In NED, two nodes are compared according to their local neighborhood topological structures which are unlabeled unordered k-adjacent trees . Since the computation problem of tree edit distance on unordered trees is NP-Complete .
Edit intent: clarity
Original:  In NED, two inter-graph nodes are compared according to their local neighborhood topological structures which are unlabeled unordered k-adjacent trees  . Since the computation problem of tree edit distance on unordered trees is NP-Complete .
Revised:  In NED, two inter-graph nodes are compared according to their local neighborhood structures which are unlabeled unordered k-adjacent trees . Since the computation problem of tree edit distance on unordered trees is NP-Complete .
Edit intent: clarity
Original:  In NED, two inter-graph nodes are compared according to their local neighborhood topological structures which are unlabeled unordered k-adjacent trees  . Since the computation problem of tree edit distance on unordered trees is NP-Complete .
Revised:  In NED, two inter-graph nodes are compared according to their local neighborhood topological structures which are represented as unordered k-adjacent trees . Since the computation problem of tree edit distance on unordered trees is NP-Complete .
Edit intent: clarity
Original:  In this paper , we propose a modified tree edit distance, called TED*  for comparing neighborhood trees.
Revised:  In this paper , we propose a modified tree edit distance, called TED* , for comparing neighborhood trees.
Edit intent: fluency
Original:  The TED* is also a metric distance  as the original tree edit distance  but more importantly, TED* is polynomially computable.
Revised:  TED* is also a metric distance as the original tree edit distance but more importantly, TED* is polynomially computable.
Edit intent: coherence
Original:  The TED* is also a metric distance  as the original tree edit distance  but more importantly, TED* is polynomially computable.
Revised:  The TED* is a metric distance as the original tree edit distance but more importantly, TED* is polynomially computable.
Edit intent: clarity
Original:  The TED* is also a metric distance  as the original tree edit distance  but more importantly, TED* is polynomially computable.
Revised:  The TED* is also a metric distance , as the original tree edit distance but more importantly, TED* is polynomially computable.
Edit intent: fluency
Original:  The TED* is also a metric distance  as the original tree edit distance  but more importantly, TED* is polynomially computable.
Revised:  The TED* is also a metric distance as the original tree edit distance , but more importantly, TED* is polynomially computable.
Edit intent: fluency
Original:  Compared to existing inter-graph node similarity measures, not only NED is a metric for nodes that can admit efficient indexingmethods, but also by using topological information, NED is a more precise measure for real-world applications such as graph de-anonymization.
Revised:  As a metric distance, NED admits efficient indexing, provides interpretable results, and shows to perform better than existing approaches on a number of data analysis tasks, including graph de-anonymization.
Edit intent: clarity
Original:  The efficiency and effectiveness of NED are empirically demonstrated by using real-world graphs.
Revised:  Finally, the efficiency and effectiveness of NED are empirically demonstrated by using real-world graphs.
Edit intent: coherence
Original:  The efficiency and effectiveness of NED are empirically demonstrated by using real-world graphs.
Revised:  The efficiency and effectiveness of NED are empirically demonstrated using real-world graphs.
Edit intent: fluency
Original:  The acquired data was irrevocably placed in the public domain and is available freely at URL 
Revised:  The acquired data was irrevocably placed in the public domain and is available freely at URL .
Edit intent: fluency
Original:  In so-called " opinion formation games ", when underlying networks are directed , a bounded price of anarchy is only known for weighted Eulerian graphs , which may not be the most general class of directed graphs that give a bounded price of anarchy .
Revised:  In so-called " opinion formation games with directed graphs , a bounded price of anarchy is only known for weighted Eulerian graphs , which may not be the most general class of directed graphs that give a bounded price of anarchy .
Edit intent: clarity
Original:  In so-called " opinion formation games ", when underlying networks are directed , a bounded price of anarchy is only known for weighted Eulerian graphs , which may not be the most general class of directed graphs that give a bounded price of anarchy .
Revised:  In so-called " opinion formation games ", when underlying networks are directed , a bounded price of anarchy is only known for weighted Eulerian graphs .
Edit intent: clarity
Original:  Thus, we aim to bound the price of anarchy for games with directed graphs more general than weighted Eulerian graphs in this paper.
Revised:  Thus, we bound the price of anarchy for games with directed graphs more general than weighted Eulerian graphs in this paper.
Edit intent: clarity
Original:  We first bound the price of anarchy for a more general class of directed graphs with conditions intuitively meaning that each node does not influence the others more than she is influenced by herself and the others , where the bounds depend on such influence differences.
Revised:  We first bound the price of anarchy for a more general class of directed graphs with conditions intuitively meaning that each node does not influence the others more than she is influenced , where the bounds depend on such influence differences.
Edit intent: clarity
Original:  We then show that there exists an example that just slightly violates the conditions with an unbounded price of anarchy .
Revised:  We then show that there exists an example just slightly violating the conditions with an unbounded price of anarchy .
Edit intent: fluency
Original: In clinical data sets we often find static information (e.g. gender of the patients , blood type, etc.) combined with sequences of data that are recorded during multiple hospital visits (e.g. medications prescribed, tests performed, etc.).
Revised: In clinical data sets we often find static information (e.g. patient gender , blood type, etc.) combined with sequences of data that are recorded during multiple hospital visits (e.g. medications prescribed, tests performed, etc.).
Edit intent: clarity
Original:  In this work we present an approach based on RNNs that is specifically designed for the clinical domain and that combines static and dynamic information in order to predict future events.
Revised:  In this work we present an approach based on RNNs , specifically designed for the clinical domain and that combines static and dynamic information in order to predict future events.
Edit intent: fluency
Original:  In this work we present an approach based on RNNs that is specifically designed for the clinical domain and that combines static and dynamic information in order to predict future events.
Revised:  In this work we present an approach based on RNNs that is specifically designed for the clinical domain , that combines static and dynamic information in order to predict future events.
Edit intent: fluency
Original:  We work with a database collected in the Charit\'{e} Hospital in Berlin that contains all the information concerning patients that underwent a kidney transplantation.
Revised:  We work with a database collected in the Charit\'{e} Hospital in Berlin that contains complete information concerning patients that underwent a kidney transplantation.
Edit intent: clarity
Original:  Our goal is to predict, given the Electronic Health Record of each patient, whether any of those endpoints will occur within the next six or twelve months after each visit to the clinic.
Revised:  Our goal is to predict, based on information recorded in the Electronic Health Record of each patient, whether any of those endpoints will occur within the next six or twelve months after each visit to the clinic.
Edit intent: clarity
Original:  We compared different types of RNNs that we developed for this work,  a model based on a Feedforward Neural Network and a Logistic Regression model.
Revised:  We compared different types of RNNs that we developed for this work, with a model based on a Feedforward Neural Network and a Logistic Regression model.
Edit intent: coherence
Original:  We also performed an additional experiment using these models to predict next actions and found that for such use case the model based on a Feedforward Neural Network outperformed the other models.
Revised:  We also used the same models for a second task, i.e., next event prediction, and found that for such use case the model based on a Feedforward Neural Network outperformed the other models.
Edit intent: clarity
Original:  We also performed an additional experiment using these models to predict next actions and found that for such use case the model based on a Feedforward Neural Network outperformed the other models.
Revised:  We also performed an additional experiment using these models to predict next actions and found that here the model based on a Feedforward Neural Network outperformed the other models.
Edit intent: clarity
Original: Repeated games have a long tradition in  behavioral sciences and evolutionary biology.
Revised: Repeated games have a long tradition in the behavioral sciences and evolutionary biology.
Edit intent: fluency
Original:  Here, we extend this theory of autocratic (or zero-determinant  ) strategies to alternating games, which are often more biologically relevant than synchronous games.
Revised:  Here, we extend this theory of " zero-determinant ) strategies to alternating games, which are often more biologically relevant than synchronous games.
Edit intent: clarity
Original:  Here, we extend this theory of autocratic (or zero-determinant  ) strategies to alternating games, which are often more biologically relevant than synchronous games.
Revised:  Here, we extend this theory of autocratic (or zero-determinant ) strategies to alternating games, which are often biologically more relevant than traditional synchronous games.
Edit intent: clarity
Original:  Furthermore, we show that autocratic strategies exist  for (iii) games with randomly-alternating moves.
Revised:  Furthermore, we show that autocratic strategies exist even for (iii) games with randomly-alternating moves.
Edit intent: coherence
Original:  Either scenario can be captured by the continuous Donation Game, where a player pays a cost to provide benefits to the opponent according to its continuous cooperative investment level.
Revised:  Either scenario can be captured by the continuous Donation Game, in which a player pays a cost to provide benefits to the opponent according to its continuous cooperative investment level.
Edit intent: fluency
Original:  Either scenario can be captured by the continuous Donation Game, where a player pays a cost to provide benefits to the opponent according to its continuous cooperative investment level.
Revised:  Either scenario can be captured by the continuous Donation Game, where a player pays a cost to provide a benefit to the opponent according to its continuous cooperative investment level.
Edit intent: fluency
Original:  Either scenario can be captured by the continuous Donation Game, where a player pays a cost to provide benefits to the opponent according to its continuous cooperative investment level.
Revised:  Either scenario can be captured by the continuous Donation Game, where a player pays a cost to provide benefits to the opponent according to a continuous cooperative investment level.
Edit intent: clarity
Original:  Such asymmetries could , for example, easily arise from dominance hierarchies, and we show that they  endow subordinate players with more autocratic strategies than dominant players , which, in turn, permits subordinate players to exert a surprising amount of control over asymmetric interactions .
Revised:  Such asymmetries could , for example, easily arise from dominance hierarchies, and we show that they can endow subordinate players with more autocratic strategies than dominant players , which, in turn, permits subordinate players to exert a surprising amount of control over asymmetric interactions .
Edit intent: clarity
Original:  Such asymmetries could , for example, easily arise from dominance hierarchies, and we show that they  endow subordinate players with more autocratic strategies than dominant players , which, in turn, permits subordinate players to exert a surprising amount of control over asymmetric interactions .
Revised:  Such asymmetries could , for example, easily arise from dominance hierarchies, and we show that they endow subordinate players with more autocratic strategies than dominant players .
Edit intent: clarity
Original:  While solution to this problem is not always uniquely defined and there exist multiple methods for tree/network construction, it becomes important to measure how well  constructed networks capture the given character relationship across the species.
Revised:  While solution to this problem is not always uniquely defined and there exist multiple methods for tree/network construction, it becomes important to measure how well the constructed networks capture the given character relationship across the species.
Edit intent: clarity
Original:  Value iteration networks are suitable for making predictions about outcomes that involve planning-based reasoning, such as predicting a desired trajectory from an observation of a map . Key to our approach is a novel differentiable approximation of the value-iteration algorithm, which can be represented as a convolutional neural network, and trained end-to-end using standard backpropagation.
Revised:  Value iteration networks are suitable for predicting outcomes that involve planning-based reasoning, such as predicting a desired trajectory from an observation of a map . Key to our approach is a novel differentiable approximation of the value-iteration algorithm, which can be represented as a convolutional neural network, and trained end-to-end using standard backpropagation.
Edit intent: clarity
Original:  Value iteration networks are suitable for making predictions about outcomes that involve planning-based reasoning, such as predicting a desired trajectory from an observation of a map . Key to our approach is a novel differentiable approximation of the value-iteration algorithm, which can be represented as a convolutional neural network, and trained end-to-end using standard backpropagation.
Revised:  Value iteration networks are suitable for making predictions about outcomes that involve planning-based reasoning, such as policies for reinforcement learning . Key to our approach is a novel differentiable approximation of the value-iteration algorithm, which can be represented as a convolutional neural network, and trained end-to-end using standard backpropagation.
Edit intent: clarity
Original:  We show that this 3/2-law holds very precisely across 12 futures contracts and 300 single US stocks, and across a wide range of times scales.
Revised:  We show that this 3/2-law holds very precisely across 12 futures contracts and 300 single US stocks, and across a wide range of time scales.
Edit intent: fluency
Original:  However, we find that the "trading invariant" I=W/N^{3/2} proposed by Kyle and Obfizhaeva (2010) is in fact quite different for different contracts, in particular between futures and single stocks.
Revised:  However, we find that the "trading invariant" I=W/N^{3/2} proposed by Kyle and Obizhaeva is in fact quite different for different contracts, in particular between futures and single stocks.
Edit intent: clarity