wanyu/IteraTeR_v2 huggingface dataset:
Original: We propose a resource-constrained network growth model that explains the emergence of key structural properties of real-world directed networks: heavy-tailed indegree distribution, high local clusteringand degree-clustering relationship .
Revised: We propose a resource-constrained network growth model that explains the emergence of rich structural properties found in real-world directed networks: heavy-tailed indegree distribution, high local clusteringand degree-clustering relationship .
Edit intent: clarity
Original:  The difference between the average values at vertices (high-low) is set as its weight.
Revised:  The difference between the average values at vertices (high-low) is set as the edge's weight.
Edit intent: clarity
Original:  On the contrary, many real interactions are dynamic: people know that they will have a chance to lie, but they do not initially know the exact consequencesof the available actions.
Revised:  On the contrary, many real interactions are dynamic: people know that they can lie, but they do not initially know the exact consequencesof the available actions.
Edit intent: clarity
Original:  On the contrary, many real interactions are dynamic: people know that they will have a chance to lie, but they do not initially know the exact consequencesof the available actions.
Revised:  On the contrary, many real interactions are dynamic: people know that they will have a chance to lie, but do not initially know the exact consequencesof the available actions.
Edit intent: fluency
Original:  And they have to invest resources (e.g., time ) to find them out.
Revised:  And they have to invest time to find them out.
Edit intent: clarity
Original:  We report numerous findings, the most intriguing of which is that, in our setting, people can be divided in three types: Good people , who act honestly without even looking at the payoffs associated with lying versus telling the truth;
Revised:  We report numerous findings, the most intriguing of which is that, in our setting, people can be divided in three types: the Good , who act honestly without even looking at the payoffs associated with lying versus telling the truth;
Edit intent: clarity
Original:  Angry people , who first look at the payoff corresponding to telling the truth and then lie only if this payoff is low;
Revised:  the Angry , who first look at the payoff corresponding to telling the truth and then lie only if this payoff is low;
Edit intent: clarity
Original:  Angry people , who first look at the payoff corresponding to telling the truth and then lie only if this payoff is low;
Revised:  Angry people , who first look at the payoff for telling the truth and then lie only if this payoff is low;
Edit intent: clarity
Original: We introduce a novel decision problem to experimentally study situations where people know that they can lie, but  do not initially know the economic consequences : they have to invest time to find them out.
Revised: We introduce a novel decision problem to experimentally study situations where people know that they will have a chance to lie, but do not initially know the economic consequences : they have to invest time to find them out.
Edit intent: clarity
Original: We introduce a novel decision problem to experimentally study situations where people know that they can lie, but  do not initially know the economic consequences : they have to invest time to find them out.
Revised: We introduce a novel decision problem to experimentally study situations where people know that they can lie, but they do not initially know the economic consequences : they have to invest time to find them out.
Edit intent: fluency
Original: We introduce a novel decision problem to experimentally study situations where people know that they can lie, but  do not initially know the economic consequences : they have to invest time to find them out.
Revised: We introduce a novel decision problem to experimentally study situations where people know that they can lie, but do not initially know the economic consequences : they have to invest resources (e.g., time) to find them out.
Edit intent: clarity
Original:  We report numerous findings, the most intriguing of which is that, in our setting , people can be divided in three types: the Good , who act honestly independently of the corresponding payoff ;
Revised:  We report numerous findings, the most intriguing of which is that, in our decision context , people can be divided in three types: the Good , who act honestly independently of the corresponding payoff ;
Edit intent: clarity
Original:  We report numerous findings, the most intriguing of which is that, in our setting , people can be divided in three types: the Good , who act honestly independently of the corresponding payoff ;
Revised:  We report numerous findings, the most intriguing of which is that, in our setting , people can be divided in three types: Good people , who act honestly independently of the corresponding payoff ;
Edit intent: clarity
Original:  the Angry , who first look at the payoff for telling the truth and then lie only if that is low .
Revised:  Angry people , who first look at the payoff for telling the truth and then lie only if that is low .
Edit intent: clarity
Original:  the Angry , who first look at the payoff for telling the truth and then lie only if that is low .
Revised:  the Angry , who first look at the exact payoff corresponding to telling the truth and then lie only if that is low .
Edit intent: clarity
Original:  However, these studies are static: subjects are either fully aware of the  consequences of all available actions , or they are uncertain, but the uncertainty cannot be cleared .
Revised:  However, these studies are static: subjects are either fully aware of the consequences of all available actions , or they are uncertain, but this uncertainty cannot be cleared .
Edit intent: fluency
Original:  On the contrary, many real interactions are dynamic: people know that they will have a chance to lie, but they do not initially know the exact consequences of the available actions .
Revised:  On the contrary, in reality, people oftentimes know that they will have a chance to lie, but they do not initially know the exact consequences of the available actions .
Edit intent: clarity
Original:  Here we capture the essence of this type of interactions by means of a novel decision problem in the context of relatively small lies (maximum payoff = 90 cents).
Revised:  Here we capture the essence of this type of situations by means of a novel decision problem in the context of relatively small lies (maximum payoff = 90 cents).
Edit intent: clarity
Original: Crowd simulation is a daunting task due to the lack of a comprehensive analysis of crowd movement.
Edit intent: coherence
Original:  In this paper, we present a novel unified model for crowd simulation involving human physiological, psychological, and physical factors.
Revised:  In this paper, we present a novel unified model for crowd simulation that comprehensively considers physiological, psychological, and physical factors.
Edit intent: clarity
Original:  Physiological , psychological, and physical factors are integrated into the comprehensive model , and the relationship among every part is determined.
Revised:  Physiological , psychological, and physical factors together in a unified manner , and the relationship among every part is determined.
Edit intent: clarity
Original:  Physiological , psychological, and physical factors are integrated into the comprehensive model , and the relationship among every part is determined.
Revised:  Physiological , psychological, and physical factors are integrated into the comprehensive model , and the relationship between each other is explicitly determined.
Edit intent: clarity
Original:  It can  reliably predict the  physical strength and emotion of a crowd in an emergency  .
Revised:  It can also reliably predict the physical strength and emotion of a crowd in an emergency .
Edit intent: coherence
Original:  It can  reliably predict the  physical strength and emotion of a crowd in an emergency  .
Revised:  It can reliably predict the changes in the physical strength and emotion of a crowd in an emergency .
Edit intent: clarity
Original: In this paper, we present a novel CubeP model for crowd simulation that comprehensively considers physiological, psychological, and physical factors.
Revised: We present a unified model for crowd simulation that comprehensively considers physiological, psychological, and physical factors.
Edit intent: clarity
Original: In this paper, we present a novel CubeP model for crowd simulation that comprehensively considers physiological, psychological, and physical factors.
Revised: In this paper, we present a novel CubeP model for crowd simulation , CubeP, which comprehensively considers physiological, psychological, and physical factors.
Edit intent: coherence
Original:  Inspired by the theory of "the devoted actor ",our model determines the movement of each individual  by modeling the physical influence from physical strength and emotion .
Revised:  Inspired by the theory of "the devoted actor ," the movements of each individual by modeling the physical influence from physical strength and emotion .
Edit intent: clarity
Original:  In particular, human physical strength is efficiently computed with a physiology-based method.
Revised:  In particular, human physical strength consumption is computed using a physics-based numerical method.
Edit intent: clarity
Original:  Inspired by  James-Lange theory, the emotion is determined by means of an enhanced susceptible-infectious-recovered model that leverages the inherent relation between the physical strength and the psychological emotion.
Revised:  Inspired by the James-Lange theory, the emotion is determined by means of an enhanced susceptible-infectious-recovered model that leverages the inherent relation between the physical strength and the psychological emotion.
Edit intent: fluency
Original:  Inspired by  James-Lange theory, the emotion is determined by means of an enhanced susceptible-infectious-recovered model that leverages the inherent relation between the physical strength and the psychological emotion.
Revised:  Inspired by James-Lange theory, panic emotion is estimated by means of an enhanced susceptible-infectious-recovered model that leverages the inherent relation between the physical strength and the psychological emotion.
Edit intent: clarity
Original:  Inspired by  James-Lange theory, the emotion is determined by means of an enhanced susceptible-infectious-recovered model that leverages the inherent relation between the physical strength and the psychological emotion.
Revised:  Inspired by James-Lange theory, the emotion is determined by means of an enhanced emotional contagion model that leverages the inherent relation between the physical strength and the psychological emotion.
Edit intent: clarity
Original:  As far as we know, this is the first time that we integrate physiological, psychological, and physical factors together in a unified manner, and the relationship between each other is explicitly determined.
Revised:  As far as we know, this is the first method that integrates physiological, psychological, and physical factors together in a unified manner, and the relationship between each other is explicitly determined.
Edit intent: clarity
Original:  As far as we know, this is the first time that we integrate physiological, psychological, and physical factors together in a unified manner, and the relationship between each other is explicitly determined.
Revised:  As far as we know, this is the first time that we integrate physiological, psychological, and physical factors together and exploits the relationship between each other is explicitly determined.
Edit intent: clarity
Original:  Inspired by the theory of "the devoted actor," the movements of each individual in our model are determined by modeling the physical influence of physical strength consumption and the emotion of panic.
Revised:  Inspired by the theory of "the devoted actor," the movements of each individual in our model are determined by modeling the influence of physical strength consumption and the emotion of panic.
Edit intent: fluency
Original:  Inspired by the James-Lange theory, panic emotion is estimated by means of an enhanced emotional contagion model that leverages the inherent relation between physical strength consumption and panic emotion .
Revised:  Inspired by the James-Lange theory, panic levels are estimated by means of an enhanced emotional contagion model that leverages the inherent relation between physical strength consumption and panic emotion .
Edit intent: clarity
Original:  Inspired by the James-Lange theory, panic emotion is estimated by means of an enhanced emotional contagion model that leverages the inherent relation between physical strength consumption and panic emotion .
Revised:  Inspired by the James-Lange theory, panic emotion is estimated by means of an enhanced emotional contagion model that leverages the inherent relationship between physical strength consumption and panic emotion .
Edit intent: fluency
Original:  Inspired by the James-Lange theory, panic emotion is estimated by means of an enhanced emotional contagion model that leverages the inherent relation between physical strength consumption and panic emotion .
Revised:  Inspired by the James-Lange theory, panic emotion is estimated by means of an enhanced emotional contagion model that leverages the inherent relation between physical strength consumption and panic .
Edit intent: fluency
Original:  We highlight the performance on different scenarios and compare the resulting behavior with real-world video sequences.
Revised:  We highlight the performance on different scenarios and compare the resulting behaviors with real-world video sequences.
Edit intent: fluency
Original:  Our approach can reliably predict the changes in physical strength consumption and panic emotion of individuals in an emergency situation.
Revised:  Our approach can reliably predict changes in physical strength consumption and panic emotion of individuals in an emergency situation.
Edit intent: fluency
Original:  Our approach can reliably predict the changes in physical strength consumption and panic emotion of individuals in an emergency situation.
Revised:  Our approach can reliably predict the changes in physical strength consumption and panic levels of individuals in an emergency situation.
Edit intent: clarity
Original:  We also generalize this result to multiple stopping problems of swing type, that is, when successive exercise opportunities are separated by i.i.d. random refraction times.
Revised:  We also generalize this result to multiple stopping problems of Swing type, that is, when successive exercise opportunities are separated by i.i.d. random refraction times.
Edit intent: fluency
Original:  We conduct  extensive numerical analysis for the Black-Scholes model and the jump-diffusion model with exponentially distributed jumps.
Revised:  We conduct an extensive numerical analysis for the Black-Scholes model and the jump-diffusion model with exponentially distributed jumps.
Edit intent: fluency
Original:  These solutions are used for  verification of the numerical simulation .
Revised:  These solutions are used for the verification of the numerical simulation .
Edit intent: fluency
Original:  These solutions are used for  verification of the numerical simulation .
Revised:  These solutions are used for verification of the numerical results .
Edit intent: clarity
Original:  The modal analysis is performed for a square plate under pure dilatation or uniaxial stretch, a circular plate under pure dilatation or under the effects of an adhesive substrate, and carbon nanotubes under uniaxial compression or stretch.
Revised:  Modal analysis is performed for a square plate under pure dilatation or uniaxial stretch, a circular plate under pure dilatation or under the effects of an adhesive substrate, and carbon nanotubes under uniaxial compression or stretch.
Edit intent: clarity
Original:  The modal analysis is performed for a square plate under pure dilatation or uniaxial stretch, a circular plate under pure dilatation or under the effects of an adhesive substrate, and carbon nanotubes under uniaxial compression or stretch.
Revised:  The modal analysis is performed for square plates under pure dilatation or uniaxial stretch, a circular plate under pure dilatation or under the effects of an adhesive substrate, and carbon nanotubes under uniaxial compression or stretch.
Edit intent: fluency
Original:  The modal analysis is performed for a square plate under pure dilatation or uniaxial stretch, a circular plate under pure dilatation or under the effects of an adhesive substrate, and carbon nanotubes under uniaxial compression or stretch.
Revised:  The modal analysis is performed for a square plate under pure dilatation or uniaxial stretch, circular plates under pure dilatation or under the effects of an adhesive substrate, and carbon nanotubes under uniaxial compression or stretch.
Edit intent: fluency
Original: Text representation using neural word embeddings has proven efficacy in many NLP applications.
Revised: Text representations using neural word embeddings has proven efficacy in many NLP applications.
Edit intent: fluency
Original: Text representation using neural word embeddings has proven efficacy in many NLP applications.
Revised: Text representation using neural word embeddings have proven effective in many NLP applications.
Edit intent: clarity
Original:  Recently, a lot of research interest goes beyond word embeddings by adapting the traditional word embedding models to learn vectors of multiword expressions (concepts/entities).
Revised:  Recent researches adapt the traditional word embedding models to learn vectors of multiword expressions (concepts/entities).
Edit intent: clarity
Original:  However, current methods are limited to textual knowledge bases only (e.g., Wikipedia).
Revised:  However, these methods are limited to textual knowledge bases only (e.g., Wikipedia).
Edit intent: clarity
Original:  However, current methods are limited to textual knowledge bases only (e.g., Wikipedia).
Revised:  However, current methods are limited to textual knowledge bases (e.g., Wikipedia).
Edit intent: clarity
Original:  We evaluate our concept embedding models intrinsically on two tasks:  1) analogical reasoning  where we achieve a state-of-the-art performance of 91\% on semantic analogies,  2) concept categorization  where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Revised:  We evaluate our concept embedding models on two tasks: 1) analogical reasoning where we achieve a state-of-the-art performance of 91\% on semantic analogies, 2) concept categorization where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Edit intent: clarity
Original:  We evaluate our concept embedding models intrinsically on two tasks:  1) analogical reasoning  where we achieve a state-of-the-art performance of 91\% on semantic analogies,  2) concept categorization  where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Revised:  We evaluate our concept embedding models intrinsically on two tasks: ( 1) analogical reasoning where we achieve a state-of-the-art performance of 91\% on semantic analogies, 2) concept categorization where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Edit intent: fluency
Original:  We evaluate our concept embedding models intrinsically on two tasks:  1) analogical reasoning  where we achieve a state-of-the-art performance of 91\% on semantic analogies,  2) concept categorization  where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Revised:  We evaluate our concept embedding models intrinsically on two tasks: 1) analogical reasoning , where we achieve a state-of-the-art performance of 91\% on semantic analogies, 2) concept categorization where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Edit intent: fluency
Original:  We evaluate our concept embedding models intrinsically on two tasks:  1) analogical reasoning  where we achieve a state-of-the-art performance of 91\% on semantic analogies,  2) concept categorization  where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Revised:  We evaluate our concept embedding models intrinsically on two tasks: 1) analogical reasoning where we achieve a state-of-the-art performance of 91\% on semantic analogies, ( 2) concept categorization where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Edit intent: fluency
Original:  We evaluate our concept embedding models intrinsically on two tasks:  1) analogical reasoning  where we achieve a state-of-the-art performance of 91\% on semantic analogies,  2) concept categorization  where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Revised:  We evaluate our concept embedding models intrinsically on two tasks: 1) analogical reasoning where we achieve a state-of-the-art performance of 91\% on semantic analogies, 2) concept categorization , where we achieve a state-of-the-art performance on two benchmark datasets achieving categorization accuracy of 100\% on one and 98\% on the other.
Edit intent: fluency
Original:  Additionally, we present a case study to extrinsically evaluate our model on unsupervised argument type identification for neural semantic parsing.
Revised:  Additionally, we present a case study to evaluate our model on unsupervised argument type identification for neural semantic parsing.
Edit intent: clarity
Original: Restricted Boltzmann machines (RBMs) and their extensions, often called " deep-belief networks ", are very powerful neural networks that have found widespread applicability in the fields of machine learning and big data.
Revised: Restricted Boltzmann machines (RBMs) and their extensions, called ' deep-belief networks ", are very powerful neural networks that have found widespread applicability in the fields of machine learning and big data.
Edit intent: clarity
Original: Restricted Boltzmann machines (RBMs) and their extensions, often called " deep-belief networks ", are very powerful neural networks that have found widespread applicability in the fields of machine learning and big data.
Revised: Restricted Boltzmann machines (RBMs) and their extensions, often called " deep-belief networks ', are powerful neural networks that have found widespread applicability in the fields of machine learning and big data.
Edit intent: coherence
Original: Restricted Boltzmann machines (RBMs) and their extensions, often called " deep-belief networks ", are very powerful neural networks that have found widespread applicability in the fields of machine learning and big data.
Revised: Restricted Boltzmann machines (RBMs) and their extensions, often called " deep-belief networks ", are very powerful neural networks that have found applications in the fields of machine learning and big data.
Edit intent: clarity
Original:  In this paper, we show a very efficient alternative to contrastive divergence by means of simulations of digital memcomputing machines (DMMs).
Revised:  In this paper, we show an efficient alternative to contrastive divergence by means of simulations of digital memcomputing machines (DMMs).
Edit intent: clarity