wanyu/IteraTeR_v2 huggingface dataset:
Original:  However, when generalising KAT to reason about concurrent programs , axioms native to KAT in conjunction with expected axioms for reasoning about concurrency lead to an unexpected equation.
Revised:  Generalising KAT to reason about concurrent programs , axioms native to KAT in conjunction with expected axioms for reasoning about concurrency lead to an unexpected equation.
Edit intent: coherence
Original:  However, when generalising KAT to reason about concurrent programs , axioms native to KAT in conjunction with expected axioms for reasoning about concurrency lead to an unexpected equation.
Revised:  However, when generalising KAT to reason about concurrent programs , axioms native to KAT in conjunction with expected axioms for concurrency lead to an unexpected equation.
Edit intent: fluency
Original:  However, when generalising KAT to reason about concurrent programs , axioms native to KAT in conjunction with expected axioms for reasoning about concurrency lead to an unexpected equation.
Revised:  However, when generalising KAT to reason about concurrent programs , axioms native to KAT in conjunction with expected axioms for reasoning about concurrency lead to an anomalous equation.
Edit intent: clarity
Original: The increased maturity level of technological achievements towards the realization of the Internet of Things (IoT) vision allowed sophisticated solutions to emerge, offering reliable monitoring in highly dynamic environments that lack well-defined and well-designed infrastructures , such as in the case of disaster scenarios .
Revised: The increased maturity level of technological achievements towards the realization of the Internet of Things (IoT) vision allowed sophisticated solutions to emerge, offering reliable monitoring in highly dynamic environments that lack well-defined and well-designed infrastructures .
Edit intent: clarity
Original:  Finally, a prototype of the full architecture was implemented  to demonstrate the applicability of the presented approach for monitoring in dynamic environments, but also the operability of the introduced tracking technique.
Revised:  Finally, a prototype of the full architecture was implemented not only to demonstrate the applicability of the presented approach for monitoring in dynamic environments, but also the operability of the introduced tracking technique.
Edit intent: clarity
Original:  Such allosteric pathways can be used as target for drug designs , generating considerable interest in inferring them from sequence alignment data.
Revised:  Such allosteric pathways can be used as target for drug design , generating considerable interest in inferring them from sequence alignment data.
Edit intent: fluency
Original:  Strikingly, it can predict short-range epistasis but fails to capture long-range epistasis, in agreement with empirical findings.
Revised:  Strikingly, it can predict short-range epistasis but fails to capture long-range epistasis, in consistence with empirical findings.
Edit intent: clarity
Original:  To this end, we introduce hynet, a Python-based open-source OPF framework for hybrid AC/DC grids with point-to-point and radial multi-terminal HVDC systems. hynet's software design promotes ease of use , extensibility, and a manifold of solving options, which range from interior-point methods to relaxation-based solution techniques.
Revised:  To this end, we introduce hynet, a Python-based open-source OPF framework for hybrid AC/DC grids with point-to-point and radial multi-terminal HVDC systems. hynet's design promotes ease of use , extensibility, and a manifold of solving options, which range from interior-point methods to relaxation-based solution techniques.
Edit intent: clarity
Original:  To support convex relaxation based OPF solution techniques, a state space relaxation is introduced to obtain a unified OPF formulation that resembles the OPF of AC power systems.
Revised:  To support convex relaxation based OPF solution techniques, a state space relaxation is introduced to obtain a unified OPF formulation that is analogous to the OPF of AC power systems.
Edit intent: clarity
Original:  This enables the direct generalization of convex relaxations for AC grids to hybrid AC/DC grids, which is shown for the semidefinite and second-order cone relaxation as well as some associated results on exactness and locational marginal prices.
Revised:  This enables the direct generalization of relaxation-related results for AC grids to hybrid AC/DC grids, which is shown for the semidefinite and second-order cone relaxation as well as some associated results on exactness and locational marginal prices.
Edit intent: clarity
Original:  This enables the direct generalization of convex relaxations for AC grids to hybrid AC/DC grids, which is shown for the semidefinite and second-order cone relaxation as well as some associated results on exactness and locational marginal prices.
Revised:  This enables the direct generalization of convex relaxations for AC grids to hybrid AC/DC grids, which is shown for the semidefinite and second-order cone relaxation as well as associated results on exactness and locational marginal prices.
Edit intent: clarity
Original: In this work , we propose numerical scheme for the Riesz space fractional advection-dispersion equations with delay (RFADED).
Revised: In this paper , we propose numerical scheme for the Riesz space fractional advection-dispersion equations with delay (RFADED).
Edit intent: clarity
Original:  Firstly, we find the analytical solution for RFADED in terms of the functions of Mittag-Leffler type  .
Revised:  Firstly, analytical solution for RFADED in terms of the functions of Mittag-Leffler type .
Edit intent: coherence
Original:  Secondly, we introduce fractional backward differential formulas (FBDF) method and shifted Grunwald method . Stability and convergency of these methods have been proved.
Revised:  Secondly, the fractional backward differential formulas (FBDF) method and shifted Grunwald method . Stability and convergency of these methods have been proved.
Edit intent: coherence
Original:  Secondly, we introduce fractional backward differential formulas (FBDF) method and shifted Grunwald method . Stability and convergency of these methods have been proved.
Revised:  Secondly, we introduce fractional backward differential formulas (FBDF) method and shifted Gr\"{u and convergency of these methods have been proved.
Edit intent: coherence
Original:  We prove that the scheme is conditionally stable and convergent with the order accuracy of O(k^2 {\rm  { + h^2 ).
Revised:  We prove that the scheme is conditionally stable and convergent with the order accuracy of O(k^2 {\rm ({ + h^2 ).
Edit intent: fluency
Original:  We prove that the scheme is conditionally stable and convergent with the order accuracy of O(k^2 {\rm  { + h^2 ).
Revised:  We prove that the scheme is conditionally stable and convergent with the order accuracy of O(k^2 {\rm { + h^2 ).
Edit intent: fluency
Original:  Finally, some numerical examples are given to show the effectiveness of the numerical method and the results are in excellent agreement with the theoretical analysis .
Revised:  Finally, some numerical results are given to show the effectiveness of the numerical method and the results are in excellent agreement with the theoretical analysis .
Edit intent: clarity
Original:  Finally, some numerical examples are given to show the effectiveness of the numerical method and the results are in excellent agreement with the theoretical analysis .
Revised:  Finally, some numerical examples are given to demonstrate that presented method is a computationally efficient and accurate method for solving RFADED .
Edit intent: clarity
Original: The seminal idea of quantum money due to Stephen Wiesner, the money not forgeable due to laws of Quantum Mechanics  , has laid foundations for the Quantum Information Theory in early '70s.
Revised: The seminal idea of quantum money not forgeable due to laws of Quantum Mechanics , has laid foundations for the Quantum Information Theory in early '70s.
Edit intent: coherence
Original:  As quantum technology develops, in parallel to crypto-currencies entering market, various other schemes for quantum currencies are being proposednowadays.
Revised:  Recently, several other schemes for quantum currencies are being proposednowadays.
Edit intent: clarity
Original: Predicting future clinical events , such as death, is an important task in medicine that helps physicians guide appropriate action.
Revised: Predicting future clinical events helps physicians guide appropriate action.
Edit intent: clarity
Original:  Finally, in a blinded, independent test set, the trained neural network was more accurate in discriminating 1-year survival outcomes than two expert cardiologists.
Revised:  Finally, we demonstrate that the trained neural network was more accurate in discriminating 1-year survival outcomes than two expert cardiologists.
Edit intent: clarity
Original:  Finally, in a blinded, independent test set, the trained neural network was more accurate in discriminating 1-year survival outcomes than two expert cardiologists.
Revised:  Finally, in a blinded, independent test set, the trained neural network was more accurate in mortality prediction than two expert cardiologists.
Edit intent: clarity
Original:  These results therefore highlight the potential of neural networks to add new predictive power to clinical image interpretations .
Revised:  These results highlight the potential of neural networks to add new predictive power to clinical image interpretations .
Edit intent: coherence
Original:  These results therefore highlight the potential of neural networks to add new predictive power to clinical image interpretations .
Revised:  These results therefore highlight the potential of neural networks to add new power to clinical image interpretations .
Edit intent: clarity
Original:  These results therefore highlight the potential of neural networks to add new predictive power to clinical image interpretations .
Revised:  These results therefore highlight the potential of neural networks to add new predictive power to clinical predictions .
Edit intent: clarity
Original: Populations of nonlinear oscillators are found in a variety of applications from physics, chemistry, biology, and engineering \mbox{ physics,kuramoto,winfree,Keener2009 The collective behavior of such oscillators varies, and includes synchronization, desynchronization , and clustering.
Revised:  The collective behavior of such oscillators varies, and includes synchronization, desynchronization , and clustering.
Edit intent: clarity
Original:  For example, synchronization in beta cells is crucial for efficient insulin secretion \mbox{ beta_synch the beating of the heart is regulated by constant pacing of synchronized cardiac pacemaker cells \mbox{ sn_synch1,sn_synch20pt , and neural synchrony is essential in visual and odor processing \mbox{ visual,odor}0pt , } and also in learning and memory recall \mbox{ learn,memory as well.
Revised:  For example, synchronization in beta cells is crucial for efficient insulin secretion \mbox{ beta_synch the beating of the heart 0pt , and neural synchrony is essential in visual and odor processing \mbox{ visual,odor}0pt , } and also in learning and memory recall \mbox{ learn,memory as well.
Edit intent: clarity
Original:  In this article, we devise a unified control framework to achieve all of these distinct collective behaviors observed in biological oscillators.
Revised:  In this article, we use a formulation that allows us to devise control frameworks to achieve all of these distinct collective behaviors observed in biological oscillators.
Edit intent: clarity
Original:  The control algorithm is based on the  partial differential equation governing the evolution of the phase distribution of a population of identical, uncoupled oscillators.
Revised:  This is based on the partial differential equation governing the evolution of the phase distribution of a population of identical, uncoupled oscillators.
Edit intent: clarity
Original:  However, visualization and understanding of GANs is largely missing .
Revised:  However, they have not been well visualized or understood .
Edit intent: clarity
Original:  We first identify a group of interpretable units that are closely related to object concepts with a segmentation-based network dissection method.
Revised:  We first identify a group of interpretable units that are closely related to object concepts using a segmentation-based network dissection method.
Edit intent: fluency
Original:  Finally, we examine the contextual relationship between these units and their surrounding by inserting the discovered object concepts into new images.
Revised:  We examine the contextual relationship between these units and their surrounding by inserting the discovered object concepts into new images.
Edit intent: coherence
Original:  Finally, we examine the contextual relationship between these units and their surrounding by inserting the discovered object concepts into new images.
Revised:  Finally, we examine the contextual relationship between these units and their surroundings by inserting the discovered object concepts into new images.
Edit intent: fluency
Original:  We show several practical applications enabled by our framework, from comparing internal representations across different layers, models, and datasets, to improving GANs by locating and removing artifact-causing units, to interactively manipulating objects in the scene.
Revised:  We show several practical applications enabled by our framework, from comparing internal representations across different layers, models, and datasets, to improving GANs by locating and removing artifact-causing units, to interactively manipulating objects in a scene.
Edit intent: fluency
Original:  We provide open source interpretation tools to help peer researchers and practitioners better understand their GAN models.
Revised:  We provide open source interpretation tools to help researchers and practitioners better understand their GAN models.
Edit intent: clarity
Original: In this paper, we present a new method for evolving video CNN models to find architectures that more optimally captures rich spatio-temporal information in videos.
Revised: We present a new method for evolving video CNN models to find architectures that more optimally captures rich spatio-temporal information in videos.
Edit intent: clarity
Original: In this paper, we present a new method for evolving video CNN models to find architectures that more optimally captures rich spatio-temporal information in videos.
Revised: In this paper, we present a new method for finding video CNN architectures that capture rich spatio-temporal information in videos.
Edit intent: clarity
Original:  Previous work, taking advantage of 3D convolutional layers , obtained promising results by manually designing CNN architectures for videos .
Revised:  Previous work, taking advantage of 3D convolutions , obtained promising results by manually designing CNN architectures for videos .
Edit intent: clarity
Original:  Previous work, taking advantage of 3D convolutional layers , obtained promising results by manually designing CNN architectures for videos .
Revised:  Previous work, taking advantage of 3D convolutional layers , obtained promising results by manually designing video CNN architectures .
Edit intent: clarity
Original:  We here develop an evolutionary algorithm that automatically explores models with different types and combinations of space-time convolutional layers to jointly capture various spatial and temporal aspects of video representations.
Revised:  We here develop an evolutionary algorithm that automatically explores models with different types and combinations of layers to jointly capture various spatial and temporal aspects of video representations.
Edit intent: clarity
Original:  We here develop an evolutionary algorithm that automatically explores models with different types and combinations of space-time convolutional layers to jointly capture various spatial and temporal aspects of video representations.
Revised:  We here develop an evolutionary algorithm that automatically explores models with different types and combinations of space-time convolutional layers to jointly learn interactions between spatial and temporal aspects of video representations.
Edit intent: clarity
Original:  We further propose a new key componentin video model evolution , the iTGM layer, which more efficiently utilizes its parameters to allow learning of space-time interactions over longer time horizons.
Revised:  We further propose a new component , the iTGM layer, which more efficiently utilizes its parameters to allow learning of space-time interactions over longer time horizons.
Edit intent: clarity
Original:  This paper deals with the problem of training multilayer feedforward SNNs.
Revised:  This paper deals with the problem of training multi-layer feedforward SNNs.
Edit intent: fluency
Original:  The non-linear integrate-and-fire dynamics employed by spiking neurons make it difficult to train SNNs to output desired spike train in response to a given input.
Revised:  The non-linear integrate-and-fire dynamics employed by spiking neurons make it difficult to train SNNs to generate desired spike trains in response to a given input.
Edit intent: clarity
Original:  To tackle this, first the problem of training a multilayer SNN is formulated as an optimization problem such that its objective function is based on the deviation in membrane potential rather than the spike arrival instants.
Revised:  To tackle this, first the problem of training a multi-layer SNN is formulated as an optimization problem such that its objective function is based on the deviation in membrane potential rather than the spike arrival instants.
Edit intent: fluency
Original:  Next  it is reformulated for a more efficient implementation, which can also be interpreted to be spatio-temporal error backpropagation.
Revised:  Next , it is reformulated for a more efficient implementation, which can also be interpreted to be spatio-temporal error backpropagation.
Edit intent: fluency
Original:  Thus, the new algorithm is a key step towards building deep spiking neural networks capable of  event-triggered learning.
Revised:  Thus, the new algorithm is a key step towards building deep spiking neural networks capable of efficient event-triggered learning.
Edit intent: clarity
Original:  They accelerate protein engineering by learning from information contained in all measured variants and using it to select variants that are likely to be improved.
Revised:  They accelerate protein engineering by learning from information contained in all measured variants and using that information to select sequences that are likely to be improved.
Edit intent: clarity
Original:  We make recommendations at each stage and look to future opportunities for machine learning to enable the discovery of new protein functions and uncover the relationship between protein sequence and function.
Revised:  We make recommendations at each stage and look to future opportunities where ML will enable discovery of new protein functions and uncover the relationship between protein sequence and function.
Edit intent: clarity
Original: In this paper we make progress on the unsupervised task of mining arbitrarily shaped clusters in highly noisy datasets, which is  present in many real-world applications.
Revised: In this paper we make progress on the unsupervised task of mining arbitrarily shaped clusters in highly noisy datasets, which is a task present in many real-world applications.
Edit intent: clarity
Original:  Moreover, AdaWave inherits the ability from the wavelet transform to clustering data in different resolutions.
Revised:  Moreover, AdaWave inherits the ability from the wavelet transform to cluster data in different resolutions.
Edit intent: fluency
Original:  We adopt the `grid labeling' data structure to drastically reduce the memory consumption of the wavelet transform so that AdaWave can be used for relatively high dimensional data.
Revised:  We adopt the "grid labeling" data structure to drastically reduce the memory consumption of the wavelet transform so that AdaWave can be used for relatively high dimensional data.
Edit intent: fluency
Original:  Experiments on synthetic as well as natural datasets demonstrate the effectiveness and efficiency of the proposed method.
Revised:  Experiments on synthetic as well as natural datasets demonstrate the effectiveness and efficiency of our proposed method.
Edit intent: fluency
Original: Large mini-batch parallel SGD is commonly used for distributed training of deep networks . Approaches that use tightly-coupled exact distributed averaging based on AllReduce are sensitive to slow nodes and high-latency communication .
Revised: Distributed data-parallel algorithms aim to accelerate the training of deep networks . Approaches that use tightly-coupled exact distributed averaging based on AllReduce are sensitive to slow nodes and high-latency communication .
Edit intent: clarity
Original: Large mini-batch parallel SGD is commonly used for distributed training of deep networks . Approaches that use tightly-coupled exact distributed averaging based on AllReduce are sensitive to slow nodes and high-latency communication .
Revised: Large mini-batch parallel SGD is commonly used for distributed training of deep networks . Approaches that synchronize nodes using exact distributed averaging based on AllReduce are sensitive to slow nodes and high-latency communication .
Edit intent: clarity
Original: Large mini-batch parallel SGD is commonly used for distributed training of deep networks . Approaches that use tightly-coupled exact distributed averaging based on AllReduce are sensitive to slow nodes and high-latency communication .
Revised: Large mini-batch parallel SGD is commonly used for distributed training of deep networks . Approaches that use tightly-coupled exact distributed averaging (e.g., via AllReduce) are sensitive to slow nodes and high-latency communication .
Edit intent: clarity
Original:  We prove that SGP converges to a stationary point of smooth, non-convex objectives at the same sub-linear rate as SGD,  that all nodes achieve consensus , and that SGP achieves a linear speedup with respect to the number of compute nodes.
Revised:  We prove that SGP converges to a stationary point of smooth, non-convex objectives at the same sub-linear rate as SGD, and that all nodes achieve consensus , and that SGP achieves a linear speedup with respect to the number of compute nodes.
Edit intent: coherence
Original: Deep neural networks (DNNs) provide state-of-the-art results for a multitude of applications, but the use of DNNs for multimodal audiovisual applications is still an unsolved problem.
Revised: Deep neural networks (DNNs) provide state-of-the-art results for a multitude of applications, but the approaches using DNNs for multimodal audiovisual applications is still an unsolved problem.
Edit intent: clarity
Original:  Our experiments with in- and out-of-distribution samples selected from a subset of the Moments-in-Time (MiT) dataset show  more reliable confidence measure as compared to the non-Bayesian baseline  .
Revised:  Our experiments using in- and out-of-distribution samples selected from a subset of the Moments-in-Time (MiT) dataset show more reliable confidence measure as compared to the non-Bayesian baseline .
Edit intent: fluency
Original:  Our experiments with in- and out-of-distribution samples selected from a subset of the Moments-in-Time (MiT) dataset show  more reliable confidence measure as compared to the non-Bayesian baseline  .
Revised:  Our experiments with in- and out-of-distribution samples selected from a subset of Moments-in-Time (MiT) dataset show more reliable confidence measure as compared to the non-Bayesian baseline .
Edit intent: fluency