wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our results demonstrate the optimality of the FILT rule in most cases, underpinned by the rule's error-filtering mechanism which provides smooth convergence during learning.
Revised:  Our results demonstrate the high performance of FILT in most cases, underpinned by the rule's error-filtering mechanism which provides smooth convergence during learning.
Edit intent: clarity
Original:  We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision.
Revised:  We also find FILT to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision.
Edit intent: clarity
Original:  In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule , but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.
Revised:  In comparison with existing work, we determine the performance of FILT to be consistent with that of the highly efficient E-learning Chronotron rule , but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.
Edit intent: fluency
Original:  In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule , but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.
Revised:  In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron , but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.
Edit intent: fluency
Original:  In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule , but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.
Revised:  In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule , but with the distinct advantage that FILT is also implementable as an online method for increased biological realism.
Edit intent: clarity
Original:  This is a relatively minor technical condition, and the typical structure of G(D) when D does not satisfy this condition, is simple and also discussed.
Revised:  This is a relatively minor technical condition, and when D does not satisfy this condition, is simple and also discussed.
Edit intent: clarity
Original: Estimating the confidence for a link is a critical task for Knowledge Graph construction.
Edit intent: coherence
Original:  Link prediction, or predicting the likelihood of a link in a knowledge graph based on prior state is a key research direction within this area.
Revised:  Link prediction, or predicting the likelihood of a link in a knowledge graph based on its existing state is a key research direction within this area.
Edit intent: clarity
Original:  We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate . Experimental results on large-scale knowledge bases such as YAGO2 show that our  approach achieves substantially higher performance than several state-of-art approaches.
Revised:  We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique . Experimental results on large-scale knowledge bases such as YAGO2 show that our approach achieves substantially higher performance than several state-of-art approaches.
Edit intent: coherence
Original:  We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate . Experimental results on large-scale knowledge bases such as YAGO2 show that our  approach achieves substantially higher performance than several state-of-art approaches.
Revised:  We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate . Experimental results on large-scale knowledge bases such as YAGO2 show that our link prediction approach achieves substantially higher performance than several state-of-art approaches.
Edit intent: clarity
Original:  Furthermore, we also study the performance of the link prediction algorithm in terms of topological properties of the Knowledge Graph and present a linear regression model to reason about its expected level of accuracy .
Revised:  We also show that for a given predicate the topological properties of the Knowledge Graph and present a linear regression model to reason about its expected level of accuracy .
Edit intent: clarity
Original:  In this paper , we present a  real-time method to query and visualise regions of networks that are closely related to a set of input vertices.
Revised:  In this article , we present a real-time method to query and visualise regions of networks that are closely related to a set of input vertices.
Edit intent: fluency
Original:  Our method allows analysts to interactively explore strongly associated regions of large networks in real time.
Revised:  Our method allows exploration of strongly associated regions of large networks in real time.
Edit intent: clarity
Original:  Motivated by problems in economics and finance, in particular modeling of limit order books, we consider a stochastic and non-linear extension of the classical Stefan-problem in one space dimension, where the paths of the moving interface might have unbounded variation.
Revised:  Driven by problems in economics and finance, in particular modeling of limit order books, we consider a stochastic and non-linear extension of the classical Stefan-problem in one space dimension, where the paths of the moving interface might have unbounded variation.
Edit intent: clarity
Original: Arguably data is a new natural resource in the enterprise world with an unprecedented degree of proliferation.
Revised: Arguably data is the new natural resource in the enterprise world with an unprecedented degree of proliferation.
Edit intent: fluency
Original:  Being extensively inspired by the scientific advances in the human visual perception and neuroaesthetics, we design the Brain-Inspired Deep Networks (BDN) for this task.
Revised:  Inspired by the scientific advances in the human visual perception and neuroaesthetics, we design the Brain-Inspired Deep Networks (BDN) for this task.
Edit intent: coherence
Original:  Being extensively inspired by the scientific advances in the human visual perception and neuroaesthetics, we design the Brain-Inspired Deep Networks (BDN) for this task.
Revised:  Being extensively inspired by the scientific advances in the human visual perception and neuroaesthetics, we design Brain-Inspired Deep Networks (BDN) for this task.
Edit intent: fluency
Original:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to  effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Revised:  since aesthetics ratings are often subjective . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Edit intent: clarity
Original:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to  effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Revised:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to an effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Edit intent: fluency
Original:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to  effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Revised:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to effective data augmentation approach . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Edit intent: fluency
Original:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to  effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Revised:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired and task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Edit intent: fluency
Original:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to  effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model leads to significantly improved performances , compared to other state-of-the-art models with the same or higher parameter capacity.
Revised:  since aesthetics ratings often vary somewhat from observer to observer . Another highlight is our first-of-its-kind study of label-preserving transformations in the context of aesthetics assessment, which leads to effective data augmentation approaches . Experimental results on the AVA dataset show that our biological inspired , task-specific BDN model gains significantly performance improvement , compared to other state-of-the-art models with the same or higher parameter capacity.
Edit intent: clarity
Original:  Although the massive MIMO system is based on innovations in the physical layer, the upper layer techniques also play important roles on harvesting the performance gains of massive MIMO.
Revised:  Although the massive MIMO system is based on innovations in the physical layer, the upper layer techniques also play important roles in harvesting the performance gains of massive MIMO.
Edit intent: fluency
Original:  In this paper , we begin with an analysis of the benefits and challenges of massive MIMO systems.
Revised:  In this article , we begin with an analysis of the benefits and challenges of massive MIMO systems.
Edit intent: fluency
Original:  We conclude this paper with a discussion of open and potential problems for future research.
Revised:  We conclude this article with a discussion of open and potential problems for future research.
Edit intent: fluency
Original: Twitter provides an extremely rich and open source of data for studying human behaviour at scale .
Revised: Twitter provides an open and rich source of data for studying human behaviour at scale .
Edit intent: clarity
Original:  We generalize this to the entire Twitter network by showing that age can be predicted based on what or whom they follow.
Revised:  We generalize this to the entire network based on what or whom they follow.
Edit intent: clarity
Original:  We generalize this to the entire Twitter network by showing that age can be predicted based on what or whom they follow.
Revised:  We generalize this to the entire Twitter network by showing that age can be predicted based on what / whom they follow.
Edit intent: fluency
Original:  Working within this paradigm we have successfully applied age detection to 700 million Twitter accounts with an F1 Score of 0.86 .
Revised:  Working within this paradigm we have successfully applied age detection to 700 million Twitter accounts with high accuracy .
Edit intent: clarity
Original:   Moreover, our analysis reveals simple relations between optimal high dimensional inference and low dimensional scalar Bayesian inference, insights into the nature of generalization and predictive power in high dimensions,  phase transitions in quadratic inference,  connections to central mathematical objects in convex optimization theory , and information theoretic limits on compressed sensing .
Revised:  Moreover, our analysis reveals simple relations between optimal high dimensional inference and low dimensional scalar Bayesian inference, insights into the nature of generalization and predictive power in high dimensions, information theoretic limits on compressed sensing, phase transitions in quadratic inference, connections to central mathematical objects in convex optimization theory , and information theoretic limits on compressed sensing .
Edit intent: fluency
Original:   Moreover, our analysis reveals simple relations between optimal high dimensional inference and low dimensional scalar Bayesian inference, insights into the nature of generalization and predictive power in high dimensions,  phase transitions in quadratic inference,  connections to central mathematical objects in convex optimization theory , and information theoretic limits on compressed sensing .
Revised:  Moreover, our analysis reveals simple relations between optimal high dimensional inference and low dimensional scalar Bayesian inference, insights into the nature of generalization and predictive power in high dimensions, phase transitions in quadratic inference, and connections to central mathematical objects in convex optimization theory , and information theoretic limits on compressed sensing .
Edit intent: coherence
Original: In modern wireless networks, interference is common problem that can degrade the performance of such networks .
Revised: Nowadays, providing higher data rate is a momentous goal for wireless communications systems. Interference is one of the important obstacles to reach this purpose .
Edit intent: clarity
Original:  Interference alignment is a management technique that align interference from other transmitters in the least possibly dimension subspace at each receiver and as a result, provide the remaining dimensions for free interference signal.
Revised:  Interference alignment is a management technique that align interference from other transmitters in the least possible dimension subspace at each receiver and as a result, provide the remaining dimensions for free interference signal.
Edit intent: fluency
Original:  Uncoordinated interference is as an example of interference which cannot coordinately aligned with interference from coordinated part  .
Revised:  An uncoordinated interference is an example of interference which cannot coordinately aligned with interference from coordinated part .
Edit intent: clarity
Original:  Uncoordinated interference is as an example of interference which cannot coordinately aligned with interference from coordinated part  .
Revised:  Uncoordinated interference is as an example of interference which cannot be aligned coordinately with interference from coordinated part .
Edit intent: fluency
Original:  Firstly, sparsity of the objective function is studied and new objective function is proposed then, a new class of convex relaxation is proposed with respect to uncoordinated interferences . Moreover, we use schatten-p-norm as surrogate of rank function and we implement iteratively reweighted algorithm to solve optimization problem.
Revised:  Firstly, a new objective function is proposed then, a new class of convex relaxation is proposed with respect to uncoordinated interferences . Moreover, we use schatten-p-norm as surrogate of rank function and we implement iteratively reweighted algorithm to solve optimization problem.
Edit intent: coherence
Original:  Firstly, sparsity of the objective function is studied and new objective function is proposed then, a new class of convex relaxation is proposed with respect to uncoordinated interferences . Moreover, we use schatten-p-norm as surrogate of rank function and we implement iteratively reweighted algorithm to solve optimization problem.
Revised:  Firstly, sparsity of the objective function is studied and new objective function is chosen then, a new class of convex relaxation is proposed with respect to uncoordinated interferences . Moreover, we use schatten-p-norm as surrogate of rank function and we implement iteratively reweighted algorithm to solve optimization problem.
Edit intent: clarity
Original:   Finally, our simulation results show that  proposed methods can obtain considerably higher multiplexing gain  than other approaches in the interference alignment framework  .
Revised:  Finally, our simulation results show that our proposed methods can obtain considerably higher multiplexing gain than other approaches in the interference alignment framework .
Edit intent: fluency
Original:  Preliminarily results are shown with three real patient data.
Revised:  Preliminarily results are shown using real data.
Edit intent: clarity
Original:  While this participatory gender gap has been studied extensively in the literature, this work sets out to \emph{assess potential gender inequalities in Wikipedia articles} along different dimensions: notability, topical focus, linguistic bias, structural properties  and meta-data presentation.
Revised:  While this participatory gender gap has been studied extensively in the literature, this work sets out to \emph{assess potential gender inequalities in Wikipedia articles} along different dimensions: notability, topical focus, linguistic bias, structural properties , and meta-data presentation.
Edit intent: fluency
Original:  We find that (i) women in Wikipedia are more notable than men  which we interpret as the outcome of a subtle glass ceiling effect;
Revised:  We find that (i) women in Wikipedia are more notable than men , which we interpret as the outcome of a subtle glass ceiling effect;
Edit intent: fluency
Original:  (ii) family-, gender-  and relationship-related topics are more present in biographies about women;
Revised:  (ii) family-, gender- , and relationship-related topics are more present in biographies about women;
Edit intent: fluency
Original:  (iii) linguistic biases manifest in Wikipedia since abstract terms tend to be used to describe positive aspects in the biographies of men and negative aspects in the biographies of women;
Revised:  (iii) linguistic bias manifests in Wikipedia since abstract terms tend to be used to describe positive aspects in the biographies of men and negative aspects in the biographies of women;
Edit intent: fluency
Original:  The implications of such differences are discussed , specially having Wikipedia contribution policies in mind.
Revised:  The implications of such differences are discussed having Wikipedia contribution policies in mind.
Edit intent: coherence
Original:  We hope that our work contributes to increase awareness about, first, gender issues in the content of Wikipedia, and second, the different levels on which gender biases can manifest on the Web.
Revised:  We hope that the present work will contribute to increased awareness about, first, gender issues in the content of Wikipedia, and second, the different levels on which gender biases can manifest on the Web.
Edit intent: clarity
Original:    Here we study the fixed-parameter  approximability of the problem: given an instance and an integer k, one has to find a solution of size at most g(k) in time f(k) \cdot n^{O(1)} if a solution of size at most k exists.
Revised:  . Here we study the fixed-parameter approximability of the problem: given an instance and an integer k, one has to find a solution of size at most g(k) in time f(k) \cdot n^{O(1)} if a solution of size at most k exists.
Edit intent: fluency
Original:    Here we study the fixed-parameter  approximability of the problem: given an instance and an integer k, one has to find a solution of size at most g(k) in time f(k) \cdot n^{O(1)} if a solution of size at most k exists.
Revised:  Here we study the fixed-parameter approximability of the problem: given an instance and an integer k, one has to find a solution of size at most g(k) in time f(k) n^{O(1)} if a solution of size at most k exists.
Edit intent: coherence
Original:  Our main result classifies each finite constraint language \Gamma into one of three classes: MinCSP(\Gamma) has a constant-factor FP-approximation .
Revised:  Our main result classifies each finite constraint language \Gamma into one of three classes: MinCSP(\Gamma) has a constant-factor FP-approximation for
Edit intent: clarity
Original:  MinCSP(\Gamma) has a (constant-factor) FP-approximation if and only if Nearest Codeword has a (constant-factor) FP-approximation.
Revised:  MinCSP(\Gamma) ; or we prove that
Edit intent: coherence
Original:  MinCSP(\Gamma) has no  FP-approximation , unless FPT=W[ P ].
Revised:  MinCSP(\Gamma) has no FP-approximation unless FPT=W[ P ].
Edit intent: fluency
Original:  We give some evidence that problems in the second class do not have constant-factor FP-approximations: we show that there is no such approximation if both the Exponential-Time Hypothesis (ETH) and the Linear PCP Conjecture (LPC) are true, and we also show that such an approximation would imply the existence of an FP-approximation for the k-Densest Subgraph problem with ratio 1-\epsilon for any \epsilon>0. ] ]  ] ]
Revised:  In particular, we show that there is no such approximation if both the Exponential-Time Hypothesis (ETH) and the Linear PCP Conjecture (LPC) are true, and we also show that such an approximation would imply the existence of an FP-approximation for the k-Densest Subgraph problem with ratio 1-\epsilon for any \epsilon>0. ] ] ] ]
Edit intent: coherence