wanyu/IteraTeR_v2 huggingface dataset:
Original:  Exchange of macromolecules between the nucleus and the surrounding cytoplasm does not involve crossing a lipid bilayer membrane.
Revised:  Exchange of macromolecules between the nucleus and the surrounding cytoplasm does not involve traversing a lipid bilayer membrane.
Edit intent: clarity
Original:  In contrast to conventional approaches to demixing such as reverse osmosis or dialysis, the biological system operates continuously, without application of cyclic changes in pressure or solution exchange.
Revised:  In contrast to conventional approaches to demixing such as reverse osmosis or dialysis, the biological system operates continuously, without application of cyclic changes in pressure or solvent exchange.
Edit intent: fluency
Original: The two most fundamental problems in computational game theory are computing a Nash equilibrium and learning to exploit opponents given observations of their play ( aka opponent exploitation).
Revised: Two fundamental problems in computational game theory are computing a Nash equilibrium and learning to exploit opponents given observations of their play ( aka opponent exploitation).
Edit intent: clarity
Original: The two most fundamental problems in computational game theory are computing a Nash equilibrium and learning to exploit opponents given observations of their play ( aka opponent exploitation).
Revised: The two most fundamental problems in computational game theory are computing a Nash equilibrium and learning to exploit opponents given observations of their play ( opponent exploitation).
Edit intent: coherence
Original:  The latter is perhaps even more important than the former: Nash equilibrium does not have a compelling theoretical justification in game classes other than two-player zero-sum, and furthermore for all games one can potentially do better by exploiting perceived weaknesses of the opponent than by following a static equilibrium strategy throughout the match.
Revised:  The latter is perhaps even more important than the former: Nash equilibrium does not have a compelling theoretical justification in game classes other than two-player zero-sum, and for all games one can potentially do better by exploiting perceived weaknesses of the opponent than by following a static equilibrium strategy throughout the match.
Edit intent: coherence
Original:  An exact polynomial-time algorithm is known for best-responding to the posterior distribution for an opponent assuming a Dirichlet prior with multinomial sampling in the case of normal-form games;
Revised:  An exact polynomial-time algorithm is known for best-responding to the posterior distribution for an opponent assuming a Dirichlet prior with multinomial sampling in normal-form games;
Edit intent: coherence
Original:  however, for the case of imperfect-information games the best known algorithm is a sampling algorithm based on approximating an infinite integral without theoretical guarantees.
Revised:  however, for imperfect-information games the best known algorithm is a sampling algorithm based on approximating an infinite integral without theoretical guarantees.
Edit intent: clarity
Original:  however, for the case of imperfect-information games the best known algorithm is a sampling algorithm based on approximating an infinite integral without theoretical guarantees.
Revised:  however, for the case of imperfect-information games the best known algorithms are sampling-based without theoretical guarantees.
Edit intent: clarity
Original:  The main result is the first exact algorithm for accomplishing this in imperfect-information games.
Revised:  We present the first exact algorithm for accomplishing this in imperfect-information games.
Edit intent: clarity
Original:  The main result is the first exact algorithm for accomplishing this in imperfect-information games.
Revised:  The main result is the first exact algorithm for a class of imperfect-information games.
Edit intent: clarity
Original:  We also present an algorithm for another natural setting where the prior is the uniform distribution over a polyhedron.
Revised:  We also present an algorithm for another natural setting where the prior is uniform over a polyhedron.
Edit intent: clarity
Original:  however, for imperfect-information games the best known algorithm is a sampling algorithm based on approximating an infinite integral without theoretical guarantees.
Revised:  however, for imperfect-information games the best known algorithm is based on approximating an infinite integral without theoretical guarantees.
Edit intent: clarity
Original:  We also present an algorithm for another natural setting where the prior is uniform over a polyhedron .
Revised:  We also present an algorithm for the uniform prior setting .
Edit intent: clarity
Original:  Although many methods have been proposed, no consensus on the notion of a directed module has been reached.
Revised:  Although many notions of a directed module have been proposed, no consensus on the notion of a directed module has been reached.
Edit intent: clarity
Original:  Although many methods have been proposed, no consensus on the notion of a directed module has been reached.
Revised:  Although many methods have been proposed, no consensus has been reached.
Edit intent: clarity
Original:  To address this issue, we propose a generic method to find the so-called truss structures in directed networks.
Revised:  To address this issue, we propose a generic notion of the so-called truss structures in directed networks.
Edit intent: clarity
Original:  Our method is able to extract two distinct types of trusses, named the cycle truss and the flow truss, from a unified framework.
Revised:  Our definition of truss is able to extract two distinct types of trusses, named the cycle truss and the flow truss, from a unified framework.
Edit intent: clarity
Original:  [2016] investigate the essential requirements for community in preference networks , and defined six axioms on community detection rules (or community functions).
Revised:  [2016] investigated essential requirements for community in preference networks , and defined six axioms on community detection rules (or community functions).
Edit intent: fluency
Original:  [2016] investigate the essential requirements for community in preference networks , and defined six axioms on community detection rules (or community functions).
Revised:  [2016] investigate the essential requirements for communities in preference networks , and defined six axioms on community detection rules (or community functions).
Edit intent: fluency
Original:  [2016] investigate the essential requirements for community in preference networks , and defined six axioms on community detection rules (or community functions).
Revised:  [2016] investigate the essential requirements for community in preference networks . They defined six axioms on community detection rules (or community functions).
Edit intent: coherence
Original:  Most strikingly , the new axioms enable to easily find constructive and consistent community functions.
Revised:  More importantly , the new axioms enable to easily find constructive and consistent community functions.
Edit intent: coherence
Original:  Most strikingly , the new axioms enable to easily find constructive and consistent community functions.
Revised:  Most strikingly , the new axioms provide a general approach to constructing consistent community functions.
Edit intent: clarity
Original:  Membership of a given structure to any of the classes can be tested in \Theta(n) time, including the generation of a solution sequence for 2 Jozef Hale\v{s positive instances.
Revised:  Membership of a given structure to any of the classes can be tested in \Theta(n) time, including the generation of a solution sequence for positive instances.
Edit intent: clarity
Original:  We derive the threshold function associated with the proposed penalty and discuss its properties.
Revised:  We derive the threshold function associated with the proposed penalty and study its properties.
Edit intent: clarity
Original:  We provide convergent algorithms for both formulations and compare the performance with well-known state-of-the-art methods.
Revised:  We provide convergent algorithms for both formulations and compare the performance with state-of-the-art methods.
Edit intent: clarity
Original:  Once  in this configuration, the network performs efficiently on a specific application both in terms of (i) low prediction error and (ii) high short-term memory capacity.
Revised:  Once the network operates in this configuration, the network performs efficiently on a specific application both in terms of (i) low prediction error and (ii) high short-term memory capacity.
Edit intent: clarity
Original:  Once  in this configuration, the network performs efficiently on a specific application both in terms of (i) low prediction error and (ii) high short-term memory capacity.
Revised:  Once in this configuration, it performs efficiently on a specific application both in terms of (i) low prediction error and (ii) high short-term memory capacity.
Edit intent: clarity
Original:  The paper exploits a recently-developed non-parametric estimator of the Fisher information matrix and provides a method to determine the critical region of echo state networks, a particular class of recurrent networks.
Revised:  The paper takes advantage of a recently-developed non-parametric estimator of the Fisher information matrix and provides a method to determine the critical region of echo state networks, a particular class of recurrent networks.
Edit intent: fluency
Original:  The considered control parameters, which indirectly affect the echo state network performance, are suitably controlled to identify a collection of network configurations lying on the edge of criticality and, as such, maximizing Fisher information and computational performance  .
Revised:  The considered control parameters, which indirectly affect the echo state network performance, are explored to identify those configurations lying on the edge of criticality and, as such, maximizing Fisher information and computational performance .
Edit intent: clarity
Original:  We end up displaying some recent biological applications of coalescent point processes to the inference of species diversification, to conservation biology , to epidemiology and to population genetics .
Revised:  We end up displaying some recent biological applications of coalescent point processes to the inference of species diversification, to conservation biology and to epidemiology .
Edit intent: clarity
Original:  Network functional connectivity is often estimated by calculating the  correlation between blood-oxygen-level dependent (BOLD) signals at different regions of interest , which however cannot characterize the causality and the direction of information flow between regions.
Revised:  Network functional connectivity is often estimated by calculating the correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest , which however cannot characterize the causality and the direction of information flow between regions.
Edit intent: clarity
Original:  Network functional connectivity is often estimated by calculating the  correlation between blood-oxygen-level dependent (BOLD) signals at different regions of interest , which however cannot characterize the causality and the direction of information flow between regions.
Revised:  Network functional connectivity is often estimated by calculating the correlation between blood-oxygen-level dependent (BOLD) signals at different regions of interest , which however cannot characterize the direction of information flow between regions.
Edit intent: clarity
Original:  In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal linear model driven by the other BOLD signal.
Revised:  In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal linear model driven by another BOLD signal.
Edit intent: fluency
Original:  Testing the method on a "common driver" situation shows that prediction correlation does not introduce false connections between the non-interacting driven ROIs.
Revised:  Testing the method on a "common driver" problem, prediction correlation did not introduce false connections between the non-interacting driven ROIs.
Edit intent: clarity
Original:  Testing the method on a "common driver" situation shows that prediction correlation does not introduce false connections between the non-interacting driven ROIs.
Revised:  Testing the method on a "common driver" situation shows that prediction correlation does not introduce false connections between non-interacting driven ROIs.
Edit intent: fluency
Original:  These results provide an initial validation that prediction correlation can capture causality information, the direction of information flow , and the possibility of extended temporal delays of information flow in BOLD signals .
Revised:  These results provide an initial validation that prediction correlation can capture the direction of information flow , and the possibility of extended temporal delays of information flow in BOLD signals .
Edit intent: clarity
Original:  These results provide an initial validation that prediction correlation can capture causality information, the direction of information flow , and the possibility of extended temporal delays of information flow in BOLD signals .
Revised:  These results provide an initial validation that prediction correlation can capture causality information, the direction of information flow and estimate the duration of extended temporal delays of information flow in BOLD signals .
Edit intent: clarity
Original:  This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also achieves the accurate estimation of connection directionality .
Revised:  This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain .
Edit intent: clarity
Original:  In this paper, we introduce and test a new method , prediction correlation, to estimate effective connectivity  from rs-fMRI.
Revised:  In this paper, we introduce and test a new concept , prediction correlation, to estimate effective connectivity from rs-fMRI.
Edit intent: clarity
Original:  In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal linear model driven by another BOLD signal.
Revised:  In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal.
Edit intent: clarity
Original: Information and understanding of fishing activities at sea is a fundamental component of marine knowledge and maritime situational awareness.
Revised: Information and understanding of fishing activities at sea are fundamental components of marine knowledge and maritime situational awareness.
Edit intent: fluency
Original: Brain research has been driven by inquiry for principles of brain structure organization and its control mechanisms.
Revised: Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms.
Edit intent: fluency
Original:  In this model, HVC is organized into functional syllable units , each of which provides the basis for the production of one syllable in vocalization.
Revised:  In this model, HVC is organized into FSUs , each of which provides the basis for the production of one syllable in vocalization.
Edit intent: clarity
Original:  Within each unit , the inhibitory neuron population takes one of two operational states: (A) synchronous firing wherein all inhibitory neurons fire simultaneously, and (B) competitive firing of the inhibitory neurons.
Revised:  Within each FSU , the inhibitory neuron population takes one of two operational states: (A) synchronous firing wherein all inhibitory neurons fire simultaneously, and (B) competitive firing of the inhibitory neurons.
Edit intent: clarity
Original:  Within each unit , the inhibitory neuron population takes one of two operational states: (A) synchronous firing wherein all inhibitory neurons fire simultaneously, and (B) competitive firing of the inhibitory neurons.
Revised:  Within each unit , the inhibitory neuron population takes one of two operational states: (A) simultaneous firing wherein all inhibitory neurons fire simultaneously, and (B) competitive firing of the inhibitory neurons.
Edit intent: fluency
Original:  We present experimental results on large scale datasets that demonstrate the effectiveness of the proposed method and show it provides a similarity measure that is competitive with SVD.
Revised:  We present experimental results on large scale datasets that demonstrate the effectiveness of the proposed method and show it is competitive with SVD.
Edit intent: clarity
Original:  Recently, several works in the field of Natural Language Processing  suggested to learn a latent representation of words using neural embedding algorithms.
Revised:  Recently, several works in the field of Natural Language Processing (NLP) suggested to learn a latent representation of words using neural embedding algorithms.
Edit intent: clarity
Original:  Among them, the Skip-gram with Negative Sampling (SGNS), also known as Word2Vec , was shown to provide state-of-the-art results on various linguistics tasks.
Revised:  Among them, the Skip-gram with Negative Sampling (SGNS), also known as word2vec , was shown to provide state-of-the-art results on various linguistics tasks.
Edit intent: fluency
Original:  Inspired by SGNS, we describe a method we name Item2Vec for item-based CF that produces embedding for items in a latent space.
Revised:  Inspired by SGNS, we describe a method we name item2vec for item-based CF that produces embedding for items in a latent space.
Edit intent: fluency
Original:  The method is capable of inferring item-to-item relations even when user information is not available.
Revised:  The method is capable of inferring item-item relations even when user information is not available.
Edit intent: fluency
Original:  We present experimental results on large scale datasets that demonstrate the effectiveness of the Item2Vec method and show it is competitive with SVD.
Revised:  We present experimental results that demonstrate the effectiveness of the Item2Vec method and show it is competitive with SVD.
Edit intent: clarity
Original:  We present experimental results on large scale datasets that demonstrate the effectiveness of the Item2Vec method and show it is competitive with SVD.
Revised:  We present experimental results on large scale datasets that demonstrate the effectiveness of the item2vec method and show it is competitive with SVD.
Edit intent: fluency
Original: In computer graphics, Wang tiles are used as a tool to generate non periodic textures and patterns .
Revised: In computer graphics, Wang tiles are used as a tool to generate textures and patterns .
Edit intent: clarity
Original:  In particular, we apply our methodology to a special kind of Wang tiles, called Brick Wang tiles, introduced by Derouet-Jourdan et al. in 2015 to model wall patterns.
Revised:  In particular, we apply our methodology to a special set of Wang tiles, called Brick Wang tiles, introduced by Derouet-Jourdan et al. in 2015 to model wall patterns.
Edit intent: clarity
Original:   To our best knowledge, this is the first large-scale study of news photos by the GDELT project and deep learning-based vision APIs.
Revised:  To our best knowledge, this is the first large-scale study of news photo contents using deep learning-based vision APIs.
Edit intent: clarity
Original:  We address this question by observing that edges, not vertices, act as the statistical units in most network datasets, making a theory of edge labeled networks more natural for most applications.
Revised:  We address this question by observing that edges, not vertices, act as the statistical units in many network datasets, making a theory of edge labeled networks more natural for most applications.
Edit intent: clarity
Original:  We address this question by observing that edges, not vertices, act as the statistical units in most network datasets, making a theory of edge labeled networks more natural for most applications.
Revised:  We address this question by observing that edges, not vertices, act as the statistical units in most network datasets, making a theory of edge labeled networks more natural for these applications.
Edit intent: clarity
Original:  Within this context we introduce the new invariance principle of {\em edge exchangeability}, which unlike its vertex exchangeable counterpart can produce networks with sparse and/or power law structure.
Revised:  Within this context we introduce the new invariance principle of {\em edge exchangeability}, which unlike its vertex exchangeable counterpart admits models for networks with sparse and/or power law structure.
Edit intent: clarity
Original:  We characterize the class of all edge exchangeable network models and identify a particular two parameter family of models with suitable theoretical properties for statistical inference.
Revised:  With this, we settle a longstanding question in statistical network modeling. We characterize all edge exchangeable network models and identify a particular two parameter family of models with suitable theoretical properties for statistical inference.
Edit intent: clarity
Original:  We characterize the class of all edge exchangeable network models and identify a particular two parameter family of models with suitable theoretical properties for statistical inference.
Revised:  We characterize the class of all edge exchangeable network models and identify a particular two parameter family of distributions with suitable theoretical properties for statistical inference.
Edit intent: clarity
Original:  Within this context we introduce the new invariance principle of {\em edge exchangeability}, which unlike its vertex exchangeable counterpart admits models for networks with sparse and/or power law structure.
Revised:  In this context we introduce the new invariance principle of {\em edge exchangeability}, which unlike its vertex exchangeable counterpart admits models for networks with sparse and/or power law structure.
Edit intent: fluency
Original:  We  identify a tractable two parameter family of distributions with  suitable theoretical properties, which we demonstrate in estimationand predictionproblems on real datasets .
Revised:  We also identify a tractable two parameter family of distributions with suitable theoretical properties, which we demonstrate in estimationand predictionproblems on real datasets .
Edit intent: coherence
Original: Exchangeable models for vertex labeled graphs cannot replicate the large sample behaviors of sparsity and power law degree distributions observed in many network datasets.
Revised: Exchangeable models for countable vertex-labeled graphs cannot replicate the large sample behaviors of sparsity and power law degree distributions observed in many network datasets.
Edit intent: clarity
Original: Exchangeable models for vertex labeled graphs cannot replicate the large sample behaviors of sparsity and power law degree distributions observed in many network datasets.
Revised: Exchangeable models for vertex labeled graphs cannot replicate the large sample behaviors of sparsity and power law degree distribution observed in many network datasets.
Edit intent: fluency