wanyu/IteraTeR_v2 huggingface dataset:
Original:  Since the seminal paper by Ostrovsky, Rabani, Schulman and Swamy FOCS 2006%DIFDELCMD < ]%%% , much progress has been made to characterize real-world instances.
Revised:  Since the seminal paper by Ostrovsky, Rabani, Schulman and Swamy %DIFDELCMD < ]%%% , much progress has been made to characterize real-world instances.
Edit intent: coherence
Original:  We distinguish the three main definitions -- Distribution Stability (  Awasthi, Blum,  Sheffet, FOCS 2010) -- Spectral Separability ( Kumar, Kannan, FOCS 2010) -- Perturbation Resilience ( Bilu, Linial, ICS 2010) We show that Local Search performs well on the instances with the aforementioned stability properties.
Revised:  We distinguish the three main definitions -- Distribution Stability ( Awasthi, Blum, and Sheffet, FOCS 2010) -- Spectral Separability ( Kumar, Kannan, FOCS 2010) -- Perturbation Resilience ( Bilu, Linial, ICS 2010) We show that Local Search performs well on the instances with the aforementioned stability properties.
Edit intent: coherence
Original:  We distinguish the three main definitions -- Distribution Stability (  Awasthi, Blum,  Sheffet, FOCS 2010) -- Spectral Separability ( Kumar, Kannan, FOCS 2010) -- Perturbation Resilience ( Bilu, Linial, ICS 2010) We show that Local Search performs well on the instances with the aforementioned stability properties.
Revised:  We distinguish the three main definitions -- Distribution Stability ( Awasthi, Blum, Sheffet, FOCS 2010) , Spectral Separability ( Kumar, Kannan, FOCS 2010) -- Perturbation Resilience ( Bilu, Linial, ICS 2010) We show that Local Search performs well on the instances with the aforementioned stability properties.
Edit intent: fluency
Original:  We distinguish the three main definitions -- Distribution Stability (  Awasthi, Blum,  Sheffet, FOCS 2010) -- Spectral Separability ( Kumar, Kannan, FOCS 2010) -- Perturbation Resilience ( Bilu, Linial, ICS 2010) We show that Local Search performs well on the instances with the aforementioned stability properties.
Revised:  We distinguish the three main definitions -- Distribution Stability ( Awasthi, Blum, Sheffet, FOCS 2010) -- Spectral Separability ( Kumar, Kannan, FOCS 2010) , Perturbation Resilience ( Bilu, Linial, ICS 2010) We show that Local Search performs well on the instances with the aforementioned stability properties.
Edit intent: fluency
Original:  We distinguish the three main definitions -- Distribution Stability (  Awasthi, Blum,  Sheffet, FOCS 2010) -- Spectral Separability ( Kumar, Kannan, FOCS 2010) -- Perturbation Resilience ( Bilu, Linial, ICS 2010) We show that Local Search performs well on the instances with the aforementioned stability properties.
Revised:  We distinguish the three main definitions -- Distribution Stability ( Awasthi, Blum, Sheffet, FOCS 2010) -- Spectral Separability ( Kumar, Kannan, FOCS 2010) -- Perturbation Resilience ( introduced by Bilu and Linial, ICS 2010) We show that Local Search performs well on the instances with the aforementioned stability properties.
Edit intent: clarity
Original:  This is a significant step toward understanding the success of Local Search heuristics in clustering applications and supports the legitimacy of the stability conditions: They characterize some of the structure of real-world instances that make Local Search a popular heuristic .
Revised:  This is a significant step toward understanding the success of local search heuristics in clustering applications and supports the legitimacy of the stability conditions: They characterize some of the structure of real-world instances that make Local Search a popular heuristic .
Edit intent: fluency
Original:  This is a significant step toward understanding the success of Local Search heuristics in clustering applications and supports the legitimacy of the stability conditions: They characterize some of the structure of real-world instances that make Local Search a popular heuristic .
Revised:  This is a significant step toward understanding the success of Local Search heuristics in clustering applications .
Edit intent: coherence
Original:  We then propose an almost exact algorithm TipTop, which has an approximation ratio of (1 - \epsilon).
Revised:  We then propose our solution TipTop, which has an approximation ratio of (1 - \epsilon).
Edit intent: clarity
Original:  While obtaining an almost exact solution, TipTop is very scalable, running on billion-scale networks such as Twitter under three hours .
Revised:  While obtaining an almost exact solution, TipTop is very scalable, running on billion-scale networks such as Twitter .
Edit intent: clarity
Original: In this paper, we study the Cost-aware Target Viral Marketing (CTVM) problem, a generalization of Influence Maximization (IM) , a well-known problem in viral marketing . CTVM asks for the most cost-effective users to influence the most relevant users.
Revised: In this paper, we study the Cost-aware Target Viral Marketing (CTVM) problem, a generalization of Influence Maximization (IM) . CTVM asks for the most cost-effective users to influence the most relevant users.
Edit intent: clarity
Original:  Instead of approximating the problem as done in the literature, we attempt to offer exact solutions.
Revised:  In contrast to the vast literature, we attempt to offer exact solutions.
Edit intent: clarity
Original:  As the problem is in NP-hard, clearly the exact solution is not in polynomial time, thusthe most challenge is to design the scalable exact solution, which can be run on large-scale networks.
Revised:  As the problem is NP-hard, clearly the exact solution is not in polynomial time, thusthe most challenge is to design the scalable exact solution, which can be run on large-scale networks.
Edit intent: fluency
Original:  While the majority of prior works focus on the modeling and learning of these processes , we consider the problem of how to design the optimal control policy for general point process with stochastic intensities , such that the stochastic system driven by the process is steered to a target state.
Revised:  In this paper , we consider the problem of how to design the optimal control policy for general point process with stochastic intensities , such that the stochastic system driven by the process is steered to a target state.
Edit intent: clarity
Original:  While the majority of prior works focus on the modeling and learning of these processes , we consider the problem of how to design the optimal control policy for general point process with stochastic intensities , such that the stochastic system driven by the process is steered to a target state.
Revised:  While the majority of prior works focus on the modeling and learning of these processes , we consider the problem of how to design the optimal control policy for point processes , such that the stochastic system driven by the process is steered to a target state.
Edit intent: clarity
Original:  In particular, we exploit the novel insight from the information theoretic formulations of stochastic optimal control  .
Revised:  In particular, we exploit the key insight to view the stochastic optimal control .
Edit intent: clarity
Original:  We further propose a novel convex optimization framework and a highly efficient online algorithm to update the policy adaptively to the current system state.
Revised:  We further propose a convex optimization framework and a highly efficient online algorithm to update the policy adaptively to the current system state.
Edit intent: clarity
Original:  We further propose a novel convex optimization framework and a highly efficient online algorithm to update the policy adaptively to the current system state.
Revised:  We further propose a novel convex optimization framework and an efficient algorithm to update the policy adaptively to the current system state.
Edit intent: clarity
Original: Temporal point processes are powerful tools to model event occurrences and have a plethora of applications in social sciences .
Revised: Temporal point processes have been widely applied to model event occurrences and have a plethora of applications in social sciences .
Edit intent: clarity
Original:  In this paper, we consider the problem of how to design the optimal control policy for point processes, such that the stochastic system driven by the  process is steered to a target state.
Revised:  In this paper, we consider the problem of how to design the optimal control policy for point processes, such that the stochastic system driven by the point process is steered to a target state.
Edit intent: fluency
Original:  In particular, we demonstrate why well-established formal procedures for model selection, such as those based on standard information criteria, tend to favor models with undesirably large numbers of states  .
Revised:  In particular, we demonstrate why well-established formal procedures for model selection, such as those based on standard information criteria, tend to favor models with numbers of states .
Edit intent: clarity
Original:  For a convenient embedding into a general finite element code  the B\'ezier extraction operator for LR NURBS is formulated.
Revised:  For a convenient embedding into general finite element code the B\'ezier extraction operator for LR NURBS is formulated.
Edit intent: fluency
Original:  For a convenient embedding into a general finite element code  the B\'ezier extraction operator for LR NURBS is formulated.
Revised:  For a convenient embedding into a general finite element code , the B\'ezier extraction operator for LR NURBS is formulated.
Edit intent: fluency
Original:  This technique is automatically controlled and allows a robust adaptive local refinement and coarsening of LR NURBS discretizations .
Revised:  This technique is automatically controlled and allows a robust adaptive local refinement and coarsening of LR NURBS .
Edit intent: clarity
Original:  For the solids LR NURBS-enriched finite elements are used to discretize the contact surfaces with LR NURBS finite elements  while the rest of the body is discretized by linear Lagrange finite elements.
Revised:  For the solids LR NURBS-enriched finite elements are used to discretize the contact surfaces with LR NURBS finite elements , while the rest of the body is discretized by linear Lagrange finite elements.
Edit intent: fluency
Original:   Various numerical examples are shown, and they demonstrate the benefit of using LR NURBS discretizations : Compared to uniform refinement, LR NURBS can achieve high accuracy at much lower computational cost.
Revised:  Various numerical examples are shown, and they demonstrate the benefit of using LR NURBS : Compared to uniform refinement, LR NURBS can achieve high accuracy at much lower computational cost.
Edit intent: clarity
Original:   Various numerical examples are shown, and they demonstrate the benefit of using LR NURBS discretizations : Compared to uniform refinement, LR NURBS can achieve high accuracy at much lower computational cost.
Revised:  Various numerical examples are shown, and they demonstrate the benefit of using LR NURBS discretizations : Compared to uniform refinement, LR NURBS can achieve high accuracy at lower computational cost.
Edit intent: clarity
Original:  As an application, we study the utility maximization problem with transaction costs for non-Markovian dynamics.
Revised:  As an application, we study the utility maximisation problem with transaction costs for non-Markovian dynamics.
Edit intent: fluency
Original: Item recommendation task predicts a personalized ranking over a set of items for  individual user.
Revised: Item recommendation task predicts a personalized ranking over a set of items for each individual user.
Edit intent: fluency
Original:  This paradigm uses widely available implicit feedback but it usually ignores some important information: item reviews.
Revised:  This paradigm takes advantage of widely available implicit feedback but it usually ignores some important information: item reviews.
Edit intent: clarity
Original:  This paradigm uses widely available implicit feedback but it usually ignores some important information: item reviews.
Revised:  This paradigm uses widely available implicit feedback . It, however, usually ignores a kind of important information: item reviews.
Edit intent: coherence
Original:  In this paper, we propose two novel and simple models to integrate item reviews into matrix factorization based Bayesian personalized ranking (BPR-MF) . In each model, we make use of text features extracted from item reviews via word embeddings.
Revised:  In this paper, we propose two novel and simple models to integrate item reviews into Bayesian personalized ranking (BPR-MF) . In each model, we make use of text features extracted from item reviews via word embeddings.
Edit intent: clarity
Original:  In this paper, we propose two novel and simple models to integrate item reviews into matrix factorization based Bayesian personalized ranking (BPR-MF) . In each model, we make use of text features extracted from item reviews via word embeddings.
Revised:  In this paper, we propose two novel and simple models to integrate item reviews into matrix factorization based Bayesian personalized ranking . In each model, we make use of text features extracted from item reviews via word embeddings.
Edit intent: clarity
Original:  In this paper, we propose two novel and simple models to integrate item reviews into matrix factorization based Bayesian personalized ranking (BPR-MF) . In each model, we make use of text features extracted from item reviews via word embeddings.
Revised:  In this paper, we propose two novel and simple models to integrate item reviews into matrix factorization based Bayesian personalized ranking (BPR-MF) . In each model, we make use of text features extracted from item reviews using word embeddings.
Edit intent: fluency
Original:  On top of text features we uncover the review dimensions that explain the variation in users' feedback and these review factors represent a prior preference of a user . Experiments on  real-world data sets show the benefits of leveraging item reviews on ranking prediction.
Revised:  On top of text features we uncover the review dimensions that explain the variation in users' feedback and these review factors represent a prior preference of users . Experiments on real-world data sets show the benefits of leveraging item reviews on ranking prediction.
Edit intent: fluency
Original: In this study, we introduce an explicit trading-volume process into the Almgren--Chriss model, which is a standard model for optimal execution.
Revised: In this study, we introduce an explicit trading-volume process into the Almgren-Chriss model, which is a standard model for optimal execution.
Edit intent: fluency
Original:  We propose a penalization method of deriving a verification theorem for an adaptive optimization problem.
Revised:  We propose a penalization method for deriving a verification theorem for an adaptive optimization problem.
Edit intent: fluency
Original:  We show that with a cluster size of N=4 on Resnet-101, can achieve 71.8\% TOP-1 accuracy, within 6\% of the best full precision results while replacing \approx 85\% of all multiplications with 8-bit accumulations.
Revised:  We show that with a cluster size of N=4 on Resnet-101, can achieve 71.8\% TOP-1 accuracy, within 6\% of the best full precision results while replacing ~ 85\% of all multiplications with 8-bit accumulations.
Edit intent: clarity
Original:  We also study the impact of the size of the cluster on both performance and accuracy, larger cluster sizes N=64 can replace \approx 98\% of the multiplications with ternary operations but introduces significant drop in accuracy which necessitates fine tuning the parameters with retraining the network at lower precision.
Revised:  We also study the impact of the size of the cluster on both performance and accuracy, larger cluster sizes N=64 can replace ~ 98\% of the multiplications with ternary operations but introduces significant drop in accuracy which necessitates fine tuning the parameters with retraining the network at lower precision.
Edit intent: clarity
Original:  Moreover, through extensive simulation , the performance of Local Voting is further investigated , in comparison with several representative scheduling algorithms from the literature.
Revised:  Moreover, through extensive simulations , the performance of Local Voting is further investigated , in comparison with several representative scheduling algorithms from the literature.
Edit intent: fluency
Original:  Moreover, through extensive simulation , the performance of Local Voting is further investigated , in comparison with several representative scheduling algorithms from the literature.
Revised:  Moreover, through extensive simulation , the performance of Local Voting is further investigated in comparison with several representative scheduling algorithms from the literature.
Edit intent: fluency
Original:  Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms , in terms of average delay, maximum delay, and fairness.
Revised:  Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness.
Edit intent: fluency
Original:  For systems with different degrees of cooperativity we show that in general bursts are associated  more robust oscillations, but when they are too short and intense they can have the opposite effect.
Revised:  For systems with different degrees of cooperativity we show that in general bursts are associated with more robust oscillations, but when they are too short and intense they can have the opposite effect.
Edit intent: fluency
Original: Inferring and comparing complex, multivariable probability density functions is a fundamental problem in several fields, including probabilistic learning, network theory, and data analysis.
Revised: Inferring and comparing complex, multivariable probability density functions is fundamental to problems in several fields, including probabilistic learning, network theory, and data analysis.
Edit intent: clarity
Original:  We take an approach here that simplifies many aspects of these problems by presenting a structured  series expansion of the Kullback-Leibler divergence - a function central to information theory - and devise a distance metric based on this divergence.
Revised:  We take an approach here that simplifies many aspects of these problems by presenting a structured , series expansion of the Kullback-Leibler divergence - a function central to information theory - and devise a distance metric based on this divergence.
Edit intent: fluency
Original:  Finally, the expansion is shown to generate a hierarchy of metrics and connects it to information geometry formalisms.
Revised:  Finally, the expansion is shown to generate a hierarchy of metrics and connects this work to information geometry formalisms.
Edit intent: clarity
Original:  Orthogonal matrices preserve gradient norm during backpropagation and can therefore be a desirable property ;
Revised:  Orthogonal matrices preserve gradient norm during backpropagation and may therefore be a desirable property ;
Edit intent: clarity
Original:  This paper explores the issues of optimization convergence, speed and gradient stability using a variety of different methods for encouraging or enforcing orthogonality.
Revised:  This paper explores issues with optimization convergence, speed and gradient stability using a variety of different methods for encouraging or enforcing orthogonality.
Edit intent: fluency
Original:  This paper explores the issues of optimization convergence, speed and gradient stability using a variety of different methods for encouraging or enforcing orthogonality.
Revised:  This paper explores the issues of optimization convergence, speed and gradient stability when encouraging or enforcing orthogonality.
Edit intent: clarity
Original: We study the problem of edit similarity joins, where given a set of strings and a threshold value K, we need to output all the pairs of strings whose edit distances are at most K. Edit similarity join is a fundamental operation in numerous applications such as data cleaning/integration, bioinformatics,  natural language processing, and has been identified as a primitive operator for database systems.
Revised: We study the problem of edit similarity joins, where given a set of strings and a threshold value K, we want to output all the pairs of strings whose edit distances are at most K. Edit similarity join is a fundamental operation in numerous applications such as data cleaning/integration, bioinformatics, natural language processing, and has been identified as a primitive operator for database systems.
Edit intent: clarity
Original: We study the problem of edit similarity joins, where given a set of strings and a threshold value K, we need to output all the pairs of strings whose edit distances are at most K. Edit similarity join is a fundamental operation in numerous applications such as data cleaning/integration, bioinformatics,  natural language processing, and has been identified as a primitive operator for database systems.
Revised: We study the problem of edit similarity joins, where given a set of strings and a threshold value K, we need to output all pairs of strings whose edit distances are at most K. Edit similarity join is a fundamental operation in numerous applications such as data cleaning/integration, bioinformatics, natural language processing, and has been identified as a primitive operator for database systems.
Edit intent: fluency
Original: We study the problem of edit similarity joins, where given a set of strings and a threshold value K, we need to output all the pairs of strings whose edit distances are at most K. Edit similarity join is a fundamental operation in numerous applications such as data cleaning/integration, bioinformatics,  natural language processing, and has been identified as a primitive operator for database systems.
Revised: We study the problem of edit similarity joins, where given a set of strings and a threshold value K, we need to output all the pairs of strings whose edit distances are at most K. Edit similarity join is a fundamental problem in data cleaning/integration, bioinformatics, natural language processing, and has been identified as a primitive operator for database systems.
Edit intent: clarity
Original: We study the problem of edit similarity joins, where given a set of strings and a threshold value K, we need to output all the pairs of strings whose edit distances are at most K. Edit similarity join is a fundamental operation in numerous applications such as data cleaning/integration, bioinformatics,  natural language processing, and has been identified as a primitive operator for database systems.
Revised: We study the problem of edit similarity joins, where given a set of strings and a threshold value K, we need to output all the pairs of strings whose edit distances are at most K. Edit similarity join is a fundamental operation in numerous applications such as data cleaning/integration, bioinformatics, collaborative filtering and natural language processing, and has been identified as a primitive operator for database systems.
Edit intent: clarity
Original:  However, we  observed that all the existing algorithms fall short on long strings and large distance thresholds.
Revised:  However, we have observed that all the existing algorithms fall short on long strings and large distance thresholds.
Edit intent: coherence
Original:  For example, on a collection of 20,000 real-world DNA sequences each of length 20,000 and a distance threshold that is 1%DIFDELCMD < \\%%% %DIF < of the string length (1\\% errors), the previous best algorithms that we have tested cannot finish in 10 hours, while%DIFDELCMD < \ebdjoin%%% \ finished in less than 6 minutes.
Revised:  For example, on a collection of 20,000 real-world DNA sequences each of length 20,000 and a distance threshold that is 1%DIFDELCMD < \\%%% %DIF < of the string length (1\\% errors), the previous best algorithms that we %DIFDELCMD < \ebdjoin%%% \ finished in less than 6 minutes.
Edit intent: coherence