wanyu/IteraTeR_v2 huggingface dataset:
Original:  We discuss how these results allow computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing  solutions to evolution PDEs such as the linear Schr\"odinger equation on L^2(R^d).
Revised:  We discuss how these methods allow the computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing solutions to evolution PDEs such as the linear Schr\"odinger equation on L^2(R^d).
Edit intent: clarity
Original:  We discuss how these results allow computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing  solutions to evolution PDEs such as the linear Schr\"odinger equation on L^2(R^d).
Revised:  We discuss how these results allow computation of objects such as the functional calculus , and how they generalise to a large class of partial differential operators, allowing solutions to evolution PDEs such as the linear Schr\"odinger equation on L^2(R^d).
Edit intent: coherence
Original:  We discuss how these results allow computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing  solutions to evolution PDEs such as the linear Schr\"odinger equation on L^2(R^d).
Revised:  We discuss how these results allow computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing , for example, solutions to evolution PDEs such as the linear Schr\"odinger equation on L^2(R^d).
Edit intent: coherence
Original:  We discuss how these results allow computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing  solutions to evolution PDEs such as the linear Schr\"odinger equation on L^2(R^d).
Revised:  We discuss how these results allow computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing solutions to evolution PDEs such as Schr\"odinger equation on L^2(R^d).
Edit intent: clarity
Original:  We discuss how these results allow computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing  solutions to evolution PDEs such as the linear Schr\"odinger equation on L^2(R^d).
Revised:  We discuss how these results allow computation of objects such as the functional calculus and generalise to a large class of partial differential operators, allowing solutions to evolution PDEs such as the linear Schr\"odinger equations on L^2(R^d).
Edit intent: fluency
Original:  Computational spectral problems in infinite dimensions have led to the Solvability Complexity Index (SCI ) hierarchy, which classifies the difficulty of computational problems.
Revised:  Computational spectral problems in infinite dimensions have led to the SCI hierarchy, which classifies the difficulty of computational problems.
Edit intent: clarity
Original:  We classify the computation of measures, measure decompositions, types of spectra, functional calculus, and Radon-Nikodym derivatives in the SCI hierarchy.
Revised:  We classify computation of measures, measure decompositions, types of spectra, functional calculus, and Radon-Nikodym derivatives in the SCI hierarchy.
Edit intent: fluency
Original:  We classify the computation of measures, measure decompositions, types of spectra, functional calculus, and Radon-Nikodym derivatives in the SCI hierarchy.
Revised:  We classify the computation of measures, measure decompositions, types of spectra, functional calculus, and Radon--Nikodym derivatives in the SCI hierarchy.
Edit intent: fluency
Original:  The new algorithms are demonstrated to be efficient on examples taken from orthogonal polynomials on the real line and unit circle , and are applied to evolution equations on a two-dimensional quasicrystal.
Revised:  The new algorithms are demonstrated to be efficient on examples taken from OPs on the real line and unit circle , and are applied to evolution equations on a two-dimensional quasicrystal.
Edit intent: clarity
Original:  The new algorithms are demonstrated to be efficient on examples taken from orthogonal polynomials on the real line and unit circle , and are applied to evolution equations on a two-dimensional quasicrystal.
Revised:  The new algorithms are demonstrated to be efficient on examples taken from orthogonal polynomials on the real line and unit circle , and are applied to evolution equations on a 2D quasicrystal.
Edit intent: fluency
Original:  By assigning time-critical I/O to the RTOS, we ensure that complementary services provided by Linux are sufficiently predictable to meet end-to-end service guarantees.
Revised:  By dedicating time-critical I/O to the RTOS, we ensure that complementary services provided by Linux are sufficiently predictable to meet end-to-end service guarantees.
Edit intent: clarity
Original:  In the online setting new factors come into place : the ordering of the dataset and whether n is known in advance or not.
Revised:  In the online setting new factors come into play : the ordering of the dataset and whether n is known in advance or not.
Edit intent: clarity
Original:  In the online setting new factors come into place : the ordering of the dataset and whether n is known in advance or not.
Revised:  In the online setting new factors come into place : the ordering of the dataset and whether the number of points, n, is known in advance or not.
Edit intent: clarity
Original: The world sees a proliferation of machine learning/deep learning (ML) models and their wide adoption in different application domainsrecently .
Revised: There has been a rapid proliferation of machine learning/deep learning (ML) models and their wide adoption in different application domainsrecently .
Edit intent: clarity
Original: The world sees a proliferation of machine learning/deep learning (ML) models and their wide adoption in different application domainsrecently .
Revised: The world sees a proliferation of machine learning/deep learning (ML) models and wide adoption of them in many application domains .
Edit intent: clarity
Original:  A thorough characterization requires understanding the behavior of the model execution across the HW/SW stack levels.
Edit intent: coherence
Original:  We coupled the profiling capability with an automatic analysis pipeline to systematically characterize 65 state-of-the-art ML models.
Revised:  We coupled the profiling capability with an automatic analysis pipeline to systematically analyze 65 state-of-the-art ML models.
Edit intent: clarity
Original:  Through this characterization, we show that our across-stack profiling solution provides insights (which are difficult to discern otherwise ) on the characteristics of ML models, ML frameworks, and GPU hardware .
Revised:  We demonstrate that XSP provides insights which would be difficult to discern otherwise ) on the characteristics of ML models, ML frameworks, and GPU hardware .
Edit intent: clarity
Original:  Through this characterization, we show that our across-stack profiling solution provides insights (which are difficult to discern otherwise ) on the characteristics of ML models, ML frameworks, and GPU hardware .
Revised:  Through this characterization, we show that our across-stack profiling solution provides insights (which are difficult to discern otherwise .
Edit intent: clarity
Original:  This paper proposes XSP --- an across-stack profiling design that gives a holistic and hierarchical view of ML model execution.
Revised:  This paper proposes XSP - an across-stack profiling design that gives a holistic and hierarchical view of ML model execution.
Edit intent: fluency
Original:  XSP leverages distributed tracing to aggregate and correlate profile data from different sources.
Revised:  XSP leverages distributed tracing to aggregate and correlates profile data from different sources.
Edit intent: fluency
Original:  The probability matrix (prototype) can describe general feedforward architectures and is equivalent to the population of models, while being simple to interpret and analyze.
Revised:  A matrix of probabilities is equivalent to the population of models, while being simple to interpret and analyze.
Edit intent: clarity
Original:  The probability matrix (prototype) can describe general feedforward architectures and is equivalent to the population of models, while being simple to interpret and analyze.
Revised:  The probability matrix (prototype) can describe general feedforward architectures and is equivalent to the population of models, but simpler to interpret and analyze.
Edit intent: coherence
Original:  Our algorithm is shown to discover models which are  competitive with those produced by existing architecture search methods, both in accuracy and computational costs, despite the conceptual simplicity and the comparatively limited scope of achievable designs .
Revised:  Our algorithm is shown to discover models which are competitive with those produced by existing architecture search methods, both in accuracy and computational costs, while being conceptually simple and highly extensible .
Edit intent: clarity
Original:  A matrix of probabilities is equivalent to the population of models, but simpler to interpret and analyze.
Revised:  Our matrix of probabilities is equivalent to the population of models, but simpler to interpret and analyze.
Edit intent: fluency
Original: This paper deals with the explicit design of the strategy formulations to make the best strategic choices from a conventional matrix form  .
Revised: This paper deals with the explicit design of strategy formulations to make the best strategic choices from a conventional matrix form .
Edit intent: fluency
Original:  The explicit strategy formulation is a new mathematical model which provides the analytical strategy framework to find the best moment for strategy shifting for preparing the rapid market changes.
Revised:  The explicit strategy formulation is a new mathematical model which provides the analytical strategy framework to find the best moment for strategy shifting to prepare rapid market changes.
Edit intent: fluency
Original:  These results enables to predict the moment for changing strategy in a matrix form and even predict the prior moment of changes .
Revised:  These results predict not only the moment for changing strategy in a matrix form and even predict the prior moment of changes .
Edit intent: clarity
Original:  These results enables to predict the moment for changing strategy in a matrix form and even predict the prior moment of changes .
Revised:  These results enables to predict the moment for changing strategy in a matrix form but also the prior moment of changes .
Edit intent: clarity
Original:  These results enables to predict the moment for changing strategy in a matrix form and even predict the prior moment of changes .
Revised:  These results enables to predict the moment for changing strategy in a matrix form and even predict the prior moment of the change .
Edit intent: fluency
Original:  This research helps strategy decision makers who want to find the optimal moments when the present strategy should be shifted .
Revised:  This research helps strategy decision makers who want to find the optimal moments of shifting present strategies .
Edit intent: clarity
Original: This paper deals with the explicit design of strategy formulations to make the best strategic choices from a conventional matrix form for managing strategies .
Revised: This paper deals with the explicit design of strategy formulations to make the best strategic choices from a conventional matrix form of representing strategic choices .
Edit intent: clarity
Original:  The explicit strategy formulation is a new mathematical model which provides the analytical strategy framework to find the best moment for strategy shifting to prepare rapid market changes.
Revised:  The explicit strategy formulation is an analytical model which is targeted to provide a mathematical strategy framework to find the best moment for strategy shifting to prepare rapid market changes.
Edit intent: clarity
Original:  This explicit model could be adapted into practically every strategic decision making situations which are described as a matrix form with the quantitative measures of the decision parameters .
Revised:  This explicit model could be adapted into practically any strategic decision making situations which are described as a matrix form with the quantitative measures of the decision parameters .
Edit intent: clarity
Original:  This explicit model could be adapted into practically every strategic decision making situations which are described as a matrix form with the quantitative measures of the decision parameters .
Revised:  This explicit model could be adapted into practically every strategic decision making situation when a strategic formulation is described as a matrix form with the quantitative measures of the decision parameters .
Edit intent: clarity
Original: Test automation can result in reduction in cost and human effort .
Revised: Test automation brings the potential to reduce costs and human effort .
Edit intent: clarity
Original:  However, source code or system models might not  be available at testing time.
Revised:  However, source code and system models might not be available at testing time.
Edit intent: fluency
Original:  However, source code or system models might not  be available at testing time.
Revised:  However, source code or system models might not always be available at testing time.
Edit intent: coherence
Original:  SaFReL learns the optimal policy  through an initial learning  , then reuses it during a transfer learning phase, while keeping the learning running in the long-term .
Revised:  SaFReL learns the optimal policy through an initial learning phase , then reuses it during a transfer learning phase, while keeping the learning running in the long-term .
Edit intent: fluency
Original: In many application settings involving networks, such as messages between users of an on-line social network or transactions between traders in financial markets, the observed data are in the form of relational events with timestamps , which form a continuous-time network.
Revised: In many application settings involving networks, such as messages between users of an on-line social network or transactions between traders in financial markets, the observed data consist of timestamped relational events , which form a continuous-time network.
Edit intent: clarity
Original:  In particular, we obtain explicit non-asymptotic upper bounds on the misclustering rates based on the separation conditions required on the parameters of the model for consistent community detection.
Edit intent: coherence
Original:  We also develop consistent and computationally efficient estimators for the parameters of the model .
Revised:  We also develop consistent and computationally efficient estimators for the model parameters .
Edit intent: clarity
Original:  We demonstrate that our proposed CHIP model and estimation procedure scales to large networks with tens of thousands of nodes and provides superior fits compared to existing continuous-time network models on several real networks.
Revised:  We demonstrate that our proposed CHIP model and estimation procedure scales to large networks with tens of thousands of nodes and provides superior fits than existing continuous-time network models on several real networks.
Edit intent: clarity
Original:  We show that applying spectral clustering to adjacency matrices constructed from relational events generated by the CHIP model provides consistent community detection for a growing number of nodes  .
Revised:  We show that applying spectral clustering to an aggregated adjacency matrix constructed from the CHIP model provides consistent community detection for a growing number of nodes .
Edit intent: clarity
Original: Most work on models for music transcription has focused on describing  local sequential dependence of notes in musical scores and failed to capture their global repetitive structure, which can be a useful guide for transcribing music.
Revised: Most work on models for music transcription has focused on describing the local sequential dependence of notes in musical scores and failed to capture their global repetitive structure, which can be a useful guide for transcribing music.
Edit intent: fluency
Original:  Focusing on the rhythm, we formulate several classes of Bayesian Markov models of musical scores that describe repetitions indirectly by sparse transition probabilities of notes or note patterns.
Revised:  Focusing on rhythm, we formulate several classes of Bayesian Markov models of musical scores that describe repetitions indirectly by sparse transition probabilities of notes or note patterns.
Edit intent: fluency
Original:  Focusing on the rhythm, we formulate several classes of Bayesian Markov models of musical scores that describe repetitions indirectly by sparse transition probabilities of notes or note patterns.
Revised:  Focusing on the rhythm, we formulate several classes of Bayesian Markov models of musical scores that describe repetitions indirectly using the sparse transition probabilities of notes or note patterns.
Edit intent: clarity
Original:  This enables us to construct piece-specific models for unseen scores with  unfixed repetitive structure and to derive tractable inference algorithms.
Revised:  This enables us to construct piece-specific models for unseen scores with an unfixed repetitive structure and to derive tractable inference algorithms.
Edit intent: fluency
Original:  Moreover, to describe approximate repetitions, we explicitly incorporate a process of modifying the repeated notes/note patterns.
Revised:  Moreover, to describe approximate repetitions, we explicitly incorporate a process for modifying the repeated notes/note patterns.
Edit intent: fluency
Original:  We apply these models as a prior music language model for rhythm transcription, where piece-specific score models are inferred from performed MIDI data by unsupervised learning, in contrast to the conventional supervised construction of score models.
Revised:  We apply these models as prior musical score models for rhythm transcription, where piece-specific score models are inferred from performed MIDI data by unsupervised learning, in contrast to the conventional supervised construction of score models.
Edit intent: clarity
Original:  Evaluations using  vocal melodies of popular music showed that the Bayesian models improved the transcription accuracy for most of the tested model types, indicating the universal efficacy of the proposed approach  .
Revised:  Evaluations using the vocal melodies of popular music showed that the Bayesian models improved the transcription accuracy for most of the tested model types, indicating the universal efficacy of the proposed approach .
Edit intent: fluency
Original:  We suggest that , in addition to providing new insights into  biological and cultural evolution , this model of symbiosis may have practical applications in evolutionary computation, such as in the task of learning deep neural network models .
Revised:  We suggest that the model may provide new insights into biological and cultural evolution , this model of symbiosis may have practical applications in evolutionary computation, such as in the task of learning deep neural network models .
Edit intent: clarity
Original:  We suggest that , in addition to providing new insights into  biological and cultural evolution , this model of symbiosis may have practical applications in evolutionary computation, such as in the task of learning deep neural network models .
Revised:  We suggest that , in addition to providing new insights into biological and cultural evolution .
Edit intent: clarity
Original:  The paper concludes that applying algorithmic optimizations on RNN models is vital while designing an embedded solution.
Revised:  Overall, applying algorithmic optimizations on RNN models is vital while designing an embedded solution.
Edit intent: clarity
Original:  Recently,  a strong interest has emerged to execute RNNs on embedded devices.
Revised:  Recently, there has been a strong interest has emerged to execute RNNs on embedded devices.
Edit intent: clarity
Original:  Recently,  a strong interest has emerged to execute RNNs on embedded devices.
Revised:  Recently, a strong interest in executing RNNs on embedded devices.
Edit intent: clarity
Original:  However, RNN requirements of high computational capability and  large memory space is difficult to be met .
Revised:  However, difficulties have arisen because RNN requires high computational capability and large memory space is difficult to be met .
Edit intent: clarity
Original:  However, RNN requirements of high computational capability and  large memory space is difficult to be met .
Revised:  However, RNN requirements of high computational capability and a large memory space is difficult to be met .
Edit intent: coherence
Original:  However, RNN requirements of high computational capability and  large memory space is difficult to be met .
Revised:  However, RNN requirements of high computational capability and large memory space .
Edit intent: clarity
Original:  In this paper, we review the existing implementations of RNN models on embedded platforms and discuss the methods adopted to overcome the limitations of embedded systems.
Revised:  In this paper, we review existing implementations of RNN models on embedded platforms and discuss the methods adopted to overcome the limitations of embedded systems.
Edit intent: fluency
Original:  We  define the objectives of mapping RNN algorithms on embedded platforms and the challenges facing their realization.
Revised:  We will define the objectives of mapping RNN algorithms on embedded platforms and the challenges facing their realization.
Edit intent: fluency
Original:  Then, we explain the components of RNNs models from an implementation perspective.
Revised:  Then, we explain the components of RNN models from an implementation perspective.
Edit intent: fluency
Original:  Furthermore, we discuss the optimizations applied on RNNs to run efficiently on embedded platforms.
Revised:  We also discuss the optimizations applied on RNNs to run efficiently on embedded platforms.
Edit intent: coherence
Original:  Furthermore, we discuss the optimizations applied on RNNs to run efficiently on embedded platforms.
Revised:  Furthermore, we discuss the optimizations applied to RNNs to run efficiently on embedded platforms.
Edit intent: fluency
Original:  Additionally , we compare the defined objectives with the implementations and highlight some open research questions and aspects currently not addressed for embedded RNNs.
Revised:  Finally , we compare the defined objectives with the implementations and highlight some open research questions and aspects currently not addressed for embedded RNNs.
Edit intent: coherence
Original:  Overall, applying algorithmic optimizations on RNN models and decreasing the memory access overhead is vital to reach high efficiency.
Revised:  Overall, applying algorithmic optimizations to RNN models and decreasing the memory access overhead is vital to reach high efficiency.
Edit intent: fluency
Original:  Overall, applying algorithmic optimizations on RNN models and decreasing the memory access overhead is vital to reach high efficiency.
Revised:  Overall, applying algorithmic optimizations on RNN models and decreasing the memory access overhead is vital to obtain high efficiency.
Edit intent: clarity
Original:  To further increase the achievable efficiency, the article points up the more promising optimizations to be applied in future research.
Revised:  To further increase the implementation efficiency, we point up the more promising optimizations to be applied in future research.
Edit intent: clarity