wanyu/IteraTeR_v2 huggingface dataset:
Original:  Our experiments show that we can reduce the amount of resources that need to be provisioned by almost 25\% with less than 1\% overall service unavailability  due to blocking , and still deliver similar response times as  an over-provisioned system.
Revised:  Our experiments show that we can reduce the amount of resources that need to be provisioned by almost 25\% with less than 1\% overall service unavailability ( due to blocking , and still deliver similar response times as an over-provisioned system.
Edit intent: fluency
Original:  Our experiments show that we can reduce the amount of resources that need to be provisioned by almost 25\% with less than 1\% overall service unavailability  due to blocking , and still deliver similar response times as  an over-provisioned system.
Revised:  Our experiments show that we can reduce the amount of resources that need to be provisioned by almost 25\% with less than 1\% overall service unavailability due to blocking ) while delivering similar response times as an over-provisioned system.
Edit intent: coherence
Original:  Our experiments show that we can reduce the amount of resources that need to be provisioned by almost 25\% with less than 1\% overall service unavailability  due to blocking , and still deliver similar response times as  an over-provisioned system.
Revised:  Our experiments show that we can reduce the amount of resources that need to be provisioned by almost 25\% with less than 1\% overall service unavailability due to blocking , and still deliver similar response times as those of an over-provisioned system.
Edit intent: clarity
Original:  In most cases of interest, the number of equations is infinite or too large, and  cannot be solved analytically or numerically.
Revised:  In most cases of interest, the number of equations is infinite or too large, and the equations cannot be solved analytically or numerically.
Edit intent: clarity
Original:  We conclude by elaborating on computational trade-offs associated with error control and some open questions.
Revised:  We conclude by discussing computational trade-offs associated with error control and some open questions.
Edit intent: clarity
Original:  We conclude by elaborating on computational trade-offs associated with error control and some open questions.
Revised:  We conclude by elaborating on computational trade-offs associated with error control and several open questions.
Edit intent: clarity
Original: We investigate the outcome of  Lotka-Volterra dynamics of ecological communities with random interaction coefficients and non-linear functional response .
Revised: We investigate the outcome of Lotka-Volterra dynamics of ecological communities with random interaction coefficients and non-linear feedback .
Edit intent: clarity
Original:  We investigate in detail the combined effects of the mean and variance of the random interaction coefficients, the cut-off parameter of the non-linear response , and a symmetry parameter .
Revised:  We investigate in detail the combined effects of the mean and variance of the random interaction coefficients, the cut-off parameter of the non-linear response .
Edit intent: clarity
Original:  We find that stability and diversity increases with the introduction of functional response , where decreasing the functional response parameter has a similar effect to decreasing the symmetry parameter .
Revised:  We find that stability and diversity increases with the introduction of non-linear feedback , where decreasing the functional response parameter has a similar effect to decreasing the symmetry parameter .
Edit intent: clarity
Original:  We find that stability and diversity increases with the introduction of functional response , where decreasing the functional response parameter has a similar effect to decreasing the symmetry parameter .
Revised:  We find that stability and diversity increases with the introduction of functional response , where decreasing the functional response parameter has a similar effect to decreasing the co-variance .
Edit intent: clarity
Original:  Finally, we describe  our deterministic parallel abstract interpreter PIKOS . We evaluate the performance  of PIKOS on a suite of 207 C programs.
Revised:  Finally, we describe PIKOS, our deterministic parallel abstract interpreter PIKOS . We evaluate the performance of PIKOS on a suite of 207 C programs.
Edit intent: clarity
Original:  The de facto approach for computing the approximation of this fixpoint uses a sequential algorithm based on weak topological order (WTO).
Revised:  The de facto approach for computing this approximation uses a sequential algorithm based on weak topological order (WTO).
Edit intent: clarity
Original:  We introduce an algorithm that produces a snapping fixture with such properties in O(n ^5) time , if a snapping fixture exists , and an efficient and robust implementation of this algorithm .
Revised:  We introduce an algorithm running in O(n ^5) time , if a snapping fixture exists , and an efficient and robust implementation of this algorithm .
Edit intent: clarity
Original:  We introduce an algorithm that produces a snapping fixture with such properties in O(n ^5) time , if a snapping fixture exists , and an efficient and robust implementation of this algorithm .
Revised:  We introduce an algorithm that produces a snapping fixture with such properties in O(n ^5) time , if a snapping fixture exists . We also provide an efficient and robust implementation of this algorithm .
Edit intent: coherence
Original:  Here, we present a node embedding technique aimed at providing low-dimensional feature vectors that are informative of dynamical processes occurring over temporal networks - rather than of the network structure itself - with the goal of enabling prediction tasks related to the evolution and outcome of these processes.
Revised:  Here, we present a node embedding technique aimed at providing low-dimensional feature vectors that are informative of dynamical processes occurring over temporal networks -- rather than of the network structure itself - with the goal of enabling prediction tasks related to the evolution and outcome of these processes.
Edit intent: fluency
Original:  Here, we present a node embedding technique aimed at providing low-dimensional feature vectors that are informative of dynamical processes occurring over temporal networks - rather than of the network structure itself - with the goal of enabling prediction tasks related to the evolution and outcome of these processes.
Revised:  Here, we present a node embedding technique aimed at providing low-dimensional feature vectors that are informative of dynamical processes occurring over temporal networks - rather than of the network structure itself -- with the goal of enabling prediction tasks related to the evolution and outcome of these processes.
Edit intent: fluency
Original:  In particular, we illustrate the performance of our approach for the prediction of nodes' epidemic states in a single instance of the spreading process.
Revised:  In particular, we illustrate the performance of our approach for the prediction of nodes' epidemic states in a single instance of a spreading process.
Edit intent: fluency
Original:  Numerical results verify the validity of the theoretical results, and indicate that the approximate solutions generated by the proposed PWDG method possess high accuracies .
Revised:  Numerical results verify the validity of the theoretical results, and indicate that the approximate solutions generated by the proposed PWDG method possess high accuracy .
Edit intent: fluency
Original: Entity resolution (ER ) ( record linkage or de-duplication ) is the process of merging together noisy databases,
Revised: Entity resolution (ER ; also known as record linkage or de-duplication ) is the process of merging together noisy databases,
Edit intent: clarity
Original: Entity resolution (ER ) ( record linkage or de-duplication ) is the process of merging together noisy databases,
Revised: Entity resolution (ER ) ( record linkage or deduplication ) is the process of merging together noisy databases,
Edit intent: fluency
Original: Entity resolution (ER ) ( record linkage or de-duplication ) is the process of merging together noisy databases,
Revised: Entity resolution (ER ) ( record linkage or de-duplication ) is the process of merging noisy databases,
Edit intent: clarity
Original:  often in the absence of a unique identifier . A major advancement in ER methodology has been the application of Bayesian generative models . Such models provide a natural framework for clustering records to unobserved (latent ) entities , while providing exact uncertainty quantification and tight performance bounds . Despite these advancements , existing models do not scale to realistically-sized databases (larger than 1000 records) and they do not incorporate probabilistic blocking.
Revised:  often in the absence of unique identifiers . A major advancement in ER methodology has been the application of Bayesian generative models . Such models provide a natural framework for clustering records to unobserved (latent ) entities , while providing exact uncertainty quantification and tight performance bounds . Despite these advancements , existing models do not scale to realistically-sized databases (larger than 1000 records) and they do not incorporate probabilistic blocking.
Edit intent: fluency
Original:  often in the absence of a unique identifier . A major advancement in ER methodology has been the application of Bayesian generative models . Such models provide a natural framework for clustering records to unobserved (latent ) entities , while providing exact uncertainty quantification and tight performance bounds . Despite these advancements , existing models do not scale to realistically-sized databases (larger than 1000 records) and they do not incorporate probabilistic blocking.
Revised:  often in the absence of a unique identifier . A major advancement in ER methodology has been the application of Bayesian generative models , which provide a natural framework for clustering records to unobserved (latent ) entities , while providing exact uncertainty quantification and tight performance bounds . Despite these advancements , existing models do not scale to realistically-sized databases (larger than 1000 records) and they do not incorporate probabilistic blocking.
Edit intent: clarity
Original:  often in the absence of a unique identifier . A major advancement in ER methodology has been the application of Bayesian generative models . Such models provide a natural framework for clustering records to unobserved (latent ) entities , while providing exact uncertainty quantification and tight performance bounds . Despite these advancements , existing models do not scale to realistically-sized databases (larger than 1000 records) and they do not incorporate probabilistic blocking.
Revised:  often in the absence of a unique identifier . A major advancement in ER methodology has been the application of Bayesian generative models . Such models provide a natural framework for inferring latent entities with rigorous quantification of uncertainty . Despite these advancements , existing models do not scale to realistically-sized databases (larger than 1000 records) and they do not incorporate probabilistic blocking.
Edit intent: clarity
Original:  often in the absence of a unique identifier . A major advancement in ER methodology has been the application of Bayesian generative models . Such models provide a natural framework for clustering records to unobserved (latent ) entities , while providing exact uncertainty quantification and tight performance bounds . Despite these advancements , existing models do not scale to realistically-sized databases (larger than 1000 records) and they do not incorporate probabilistic blocking.
Revised:  often in the absence of a unique identifier . A major advancement in ER methodology has been the application of Bayesian generative models . Such models provide a natural framework for clustering records to unobserved (latent ) entities , while providing exact uncertainty quantification and tight performance bounds . Despite these advantages , existing models do not scale to realistically-sized databases (larger than 1000 records) and they do not incorporate probabilistic blocking.
Edit intent: clarity
Original:  We make several novel contributions ,  including: (i) incorporating probabilistic blocking directly into the model through auxiliary partitions ;
Revised:  We make several novel contributions , including: (i) an auxiliary variable representation that induces a partition of the entities and records into blocks ;
Edit intent: clarity
Original:  Finally, we conduct experiments on five data sets which show that d-blink can achieve significant efficiency gains -- in excess of 300\times -- when compared to existing non-distributed methods.
Revised:  Finally, we conduct experiments on five data sets show that d-blink can achieve significant efficiency gains -- in excess of 300\times -- when compared to existing non-distributed methods.
Edit intent: clarity
Original:  Finally, we conduct experiments on five data sets which show that d-blink can achieve significant efficiency gains -- in excess of 300\times -- when compared to existing non-distributed methods.
Revised:  Finally, we conduct experiments on five data sets which show that d-blink can achieve significant efficiency gains---in excess of 300\times -- when compared to existing non-distributed methods.
Edit intent: fluency
Original:  Finally, we conduct experiments on five data sets which show that d-blink can achieve significant efficiency gains -- in excess of 300\times -- when compared to existing non-distributed methods.
Revised:  Finally, we conduct experiments on five data sets which show that d-blink can achieve significant efficiency gains -- in excess of 300\times ---when compared to existing non-distributed methods.
Edit intent: fluency
Original:  Finally, we conduct experiments on five data sets which show that d-blink can achieve significant efficiency gains -- in excess of 300\times -- when compared to existing non-distributed methods.
Revised:  Finally, we conduct experiments on five data sets which show that d-blink can achieve significant efficiency gains -- in excess of 300\times -- when compared to existing methods.
Edit intent: clarity
Original:  also known as record linkage or deduplication ) is the process of merging noisy databases, often in the absence of unique identifiers.
Revised:  also known as record linkage or de-duplication ) is the process of merging noisy databases, often in the absence of unique identifiers.
Edit intent: clarity
Original:  However, previous studies on NER are limited to a particular genre , using small manually-annotated or large but low-quality datasets.
Revised:  However, previous studies on NER are limited to particular genres , using small manually-annotated or large but low-quality datasets.
Edit intent: fluency
Original:  We evaluate our trained model on six NER datasets and our experimental results show that we have obtained state-of-the-art open-domain performances --- on top of the strong baselines BERT-base and BERT-large, we achieve relative improvements of 4.66\% and 3.07\% respectively .
Revised:  We evaluate our trained model on six NER datasets and our experimental results show that we have obtained state-of-the-art performances in the open-domain setting .
Edit intent: clarity
Original:  The convergence of the method is established and a prototype implementation is discussed . Encouraging preliminary computational results are reported for solving large low-rank semidefinite programs .
Revised:  The convergence of the method is established . A prototype implementation is discussed . Encouraging preliminary computational results are reported for solving large low-rank semidefinite programs .
Edit intent: coherence
Original:  The convergence of the method is established and a prototype implementation is discussed . Encouraging preliminary computational results are reported for solving large low-rank semidefinite programs .
Revised:  The convergence of the method is established and a prototype implementation is discussed and encouraging preliminary computational results are reported for solving large low-rank semidefinite programs .
Edit intent: coherence
Original:  In this work, we propose a high-level logical architecture that will help to reason about the most important components of a RS Task Environment, identify the differences between Environments, datasets and simulations , and most importantly, understand what needs to be shared about Environments to achieve reproducible experiments.
Revised:  In this work, we propose a high-level logical architecture that will help to reason about the core components of a RS Task Environment, identify the differences between Environments, datasets and simulations , and most importantly, understand what needs to be shared about Environments to achieve reproducible experiments.
Edit intent: clarity
Original:  In this work, we propose a high-level logical architecture that will help to reason about the most important components of a RS Task Environment, identify the differences between Environments, datasets and simulations , and most importantly, understand what needs to be shared about Environments to achieve reproducible experiments.
Revised:  In this work, we propose a high-level logical architecture that will help to reason about the most important components of a RS Task Environment, identify the differences between Environments, datasets and simulations ; and most importantly, understand what needs to be shared about Environments to achieve reproducible experiments.
Edit intent: fluency
Original: A one-parameter unitary-valued interpolation between any two unitary matrices (e.g., quantum gates) is constructed based on the Cayley transformation, which extends our previous work 15%DIFDELCMD < ]%%% . We prove that this path provides scrambled unitaries with probability distributions arbitrarily close to the Haar measure.
Revised: A one-parameter unitary-valued interpolation between any two unitary matrices (e.g., quantum gates) is constructed based on the Cayley transformation, which extends our 15%DIFDELCMD < ]%%% . We prove that this path provides scrambled unitaries with probability distributions arbitrarily close to the Haar measure.
Edit intent: clarity
Original: A one-parameter unitary-valued interpolation between any two unitary matrices (e.g., quantum gates) is constructed based on the Cayley transformation, which extends our previous work 15%DIFDELCMD < ]%%% . We prove that this path provides scrambled unitaries with probability distributions arbitrarily close to the Haar measure.
Revised: A one-parameter unitary-valued interpolation between any two unitary matrices (e.g., quantum gates) is constructed based on the Cayley transformation, which extends our previous work %DIFDELCMD < ]%%% . We prove that this path provides scrambled unitaries with probability distributions arbitrarily close to the Haar measure.
Edit intent: fluency
Original:  We show that  previous work based on the truncations of the power series representation of the exponential function does not provide practical robustness.
Revised:  We show that a previous work based on the truncations of the power series representation of the exponential function does not provide practical robustness.
Edit intent: fluency
Original:  Explicit bound on noise resilience is proved, which for an n-qubit device with the near term experimental parameters is 2^{- \Theta (n ^{3.51 )} robustness with respect to additive error.
Revised:  Explicit bounds on noise resilience is proved, which for an n-qubit device with the near term experimental parameters is 2^{- \Theta (n ^{3.51 )} robustness with respect to additive error.
Edit intent: fluency
Original:  Explicit bound on noise resilience is proved, which for an n-qubit device with the near term experimental parameters is 2^{- \Theta (n ^{3.51 )} robustness with respect to additive error.
Revised:  Explicit bound on noise resilience are proved, which for an n-qubit device with the near term experimental parameters is 2^{- \Theta (n ^{3.51 )} robustness with respect to additive error.
Edit intent: fluency
Original:  Explicit bound on noise resilience is proved, which for an n-qubit device with the near term experimental parameters is 2^{- \Theta (n ^{3.51 )} robustness with respect to additive error.
Revised:  Explicit bound on noise resilience is proved, which on a grid of n\timesn qubits with circuit depth n is 2^{- \Theta (n ^{3.51 )} robustness with respect to additive error.
Edit intent: clarity
Original:  In this paper, we present a new population-based algorithm, namely Anytime Evolutionary DCOP (AED), that adapts evolutionary optimization to solve DCOPs.
Revised:  In this paper, we present a novel population-based algorithm, namely Anytime Evolutionary DCOP (AED), that adapts evolutionary optimization to solve DCOPs.
Edit intent: clarity
Original:  In this paper, we present a new population-based algorithm, namely Anytime Evolutionary DCOP (AED), that adapts evolutionary optimization to solve DCOPs.
Revised:  In this paper, we present a new population-based algorithm, Anytime Evolutionary DCOP (AED), that adapts evolutionary optimization to solve DCOPs.
Edit intent: coherence
Original:  In this paper, we present a new population-based algorithm, namely Anytime Evolutionary DCOP (AED), that adapts evolutionary optimization to solve DCOPs.
Revised:  In this paper, we present a new population-based algorithm, namely Anytime Evolutionary DCOP (AED), that uses evolutionary optimization to solve DCOPs.
Edit intent: clarity
Original:  In AED, the agents cooperatively construct an initial set of random solutions and gradually improve them through a new mechanism that considers the optimistic approximation of local benefits.
Revised:  In AED, the agents cooperatively construct an initial set of random solutions and gradually improve them through a new mechanism that considers an optimistic approximation of local benefits.
Edit intent: fluency
Original:  Moreover, we propose a new anytime update mechanism for AED that identifies the best among a distributed set of candidate solutions and notifies all the agents when a new best is found.
Revised:  Moreover, we present a new anytime update mechanism for AED that identifies the best among a distributed set of candidate solutions and notifies all the agents when a new best is found.
Edit intent: clarity
Original:  This leads to an efficient and convergent numerical procedure for indifference pricing which applies to a wide range of payoffs, a large range of time steps and all magnitudes of transaction costs.
Revised:  This leads to efficient and convergent numerical procedure for indifference pricing which applies to a wide range of payoffs, a large range of time steps and all magnitudes of transaction costs.
Edit intent: fluency
Original:  This leads to an efficient and convergent numerical procedure for indifference pricing which applies to a wide range of payoffs, a large range of time steps and all magnitudes of transaction costs.
Revised:  This leads to an efficient and convergent numerical procedures for indifference pricing which applies to a wide range of payoffs, a large range of time steps and all magnitudes of transaction costs.
Edit intent: fluency
Original: Isolation has been shown to be a valuable concept in the world of clique enumeration .
Revised: Isolation is a concept from the world of clique enumeration .
Edit intent: clarity
Original:  Motivated by recent work on enumerating cliques in temporal (or time-varying) graphs , we lift the isolation concept to this setting.
Revised:  Motivated by recent work on enumerating cliques in temporal networks , we lift the isolation concept to this setting.
Edit intent: clarity