wanyu/IteraTeR_v2 huggingface dataset:
Original:  The agent not only receives low-level details but also considers coordination from high levels to obtain global information for increasing operational performance.
Revised:  The agent not only receives low-level details but also considers coordination from high levels to obtain global information for improving the training performance.
Edit intent: clarity
Original:  Our experiment, a two-player tennis competition task performed in the Unity environment , tested the HCA multi-agent framework based on the Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) algorithm .
Revised:  Our experiment, a two-player tennis competition task performed in the Unity environment used to test the HCA framework in the benchmark algorithm, Proximal Policy Optimization (PPO) algorithm .
Edit intent: clarity
Original:  Our experiment, a two-player tennis competition task performed in the Unity environment , tested the HCA multi-agent framework based on the Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) algorithm .
Revised:  Our experiment, a two-player tennis competition task performed in the Unity environment , tested the HCA multi-agent framework based on the Asynchronous Advantage Actor-Critic (A3C) with Proximal Policy Optimization (PPO) .
Edit intent: clarity
Original:  The results showed that the HCA framework outperforms the non-hierarchical critic baseline method on MARL tasks.
Revised:  The results showed that the HCA framework outperforms the benchmark algorithm on three MARL tasks.
Edit intent: clarity
Original: In this study, we investigate the use of global information to speed up the learning process and increase the cumulative rewards of multi-agent reinforcement learning ( MARL) tasks.
Revised: In this study, we investigate the use of global information to speed up the learning process and increase the cumulative rewards of reinforcement learning ( MARL) tasks.
Edit intent: clarity
Original:  In our approach, the agent is allowed to receive the value information from local and global critics in a competition task , indicating that each agent not only receives low-level details but also considers coordination from high levelsto obtain global information for improving the training performance.
Revised:  In our approach, each agent receives value information from local and global critics in a competition task , indicating that each agent not only receives low-level details but also considers coordination from high levelsto obtain global information for improving the training performance.
Edit intent: clarity
Original:  In our approach, the agent is allowed to receive the value information from local and global critics in a competition task , indicating that each agent not only receives low-level details but also considers coordination from high levelsto obtain global information for improving the training performance.
Revised:  In our approach, the agent is allowed to receive the value information from local and global critics regarding a competition task , indicating that each agent not only receives low-level details but also considers coordination from high levelsto obtain global information for improving the training performance.
Edit intent: clarity
Original:  In our approach, the agent is allowed to receive the value information from local and global critics in a competition task , indicating that each agent not only receives low-level details but also considers coordination from high levelsto obtain global information for improving the training performance.
Revised:  In our approach, the agent is allowed to receive the value information from local and global critics in a competition task , indicating that each agent not only receives low-level details but also considers coordination from higher levels, thereby obtaining global information to improve the training performance.
Edit intent: coherence
Original:  Our three experiments from tennis and soccer competition tasks performed in the Unity environment used to test the HCA framework in the  benchmark algorithm, Proximal Policy Optimization (PPO)  .
Revised:  Our three experiments from tennis and soccer competition tasks performed in the Unity environment used to test the HCA framework in the benchmark algorithm, proximal policy optimisation (PPO) .
Edit intent: fluency
Original:  We perform experiments on intracellular lysosomal distributions and Monte Carlo simulations and find good agreement between the asymptotic solution, particle histograms and experiments.
Revised:  We perform experiments on intracellular lysosomal distributions and Monte Carlo simulations and find excellent agreement between the asymptotic solution, particle histograms and experiments.
Edit intent: clarity
Original:   We show that exact recovery can be achieved using a semidefinite programming (SDP) approach .
Revised:  We show that exact inference can be achieved using a semidefinite programming (SDP) approach .
Edit intent: clarity
Original:  Our analysis predicts the experimental correctness of SDP with high accuracy, showing the suitability of our focus on the Karush-Kuhn-Tucker (KKT) conditions and the second minimum eigenvalue of a properly defined matrix  .
Revised:  Our analysis predicts the experimental correctness of SDP with high accuracy, showing the suitability of our focus on the Karush-Kuhn-Tucker (KKT) conditions and the spectrum of a properly defined matrix .
Edit intent: clarity
Original: High-resolution prediction of the home location of people has applications in diverse fields, including agriculture, transportation, and public health.
Revised: Timely and high-resolution estimates of the home location of people has applications in diverse fields, including agriculture, transportation, and public health.
Edit intent: clarity
Original:  The goal here is to obtain an accurate estimate of home locations of a sufficiently large subset of the population to subsequently use in models for the application domain . Conventional data sources, such as census and surveys, have a substantial time-lag and cannot capture seasonal trends.
Revised:  The goal here is to obtain an accurate estimate of home locations of a sufficiently large subset of the population to subsequently use in models for the application domain . Conventional data sources, such as census and surveys, have a substantial time lag and cannot capture seasonal trends.
Edit intent: fluency
Original:  There has been much recent interest in the use of social media data to overcome this limitation .
Revised:  Recently, social media data to overcome this limitation .
Edit intent: coherence
Original:  Due to these constraints , much of previous research has aimed  at a coarse spatial resolution, such as at the time zone, state, and city levels.
Revised:  Due to these constraints , much of previous research has aimed only at a coarse spatial resolution, such as at the time zone, state, and city levels.
Edit intent: clarity
Original:  We believe that ours is the highest accuracy obtained for high-resolution home location prediction from Twitter data for both the entire sample and for its subsets.
Revised:  We believe that ours is the highest accuracy both for the entire sample and for its subsets.
Edit intent: clarity
Original:  We exploit the locality of the unsupervised Spike Timing Dependent Plasticity (STDP) learning rule to target subsets of a segmented Spiking Neural Network (SNN) to adapt to novel information while protecting the information in the remainder of the SNN from catastrophic forgetting.
Revised:  We exploit the locality of the unsupervised Spike Timing Dependent Plasticity (STDP) learning rule to target local representations in a Spiking Neural Network (SNN) to adapt to novel information while protecting the information in the remainder of the SNN from catastrophic forgetting.
Edit intent: clarity
Original:  We exploit the locality of the unsupervised Spike Timing Dependent Plasticity (STDP) learning rule to target subsets of a segmented Spiking Neural Network (SNN) to adapt to novel information while protecting the information in the remainder of the SNN from catastrophic forgetting.
Revised:  We exploit the locality of the unsupervised Spike Timing Dependent Plasticity (STDP) learning rule to target subsets of a segmented Spiking Neural Network (SNN) to adapt to novel information while protecting essential information in the remainder of the SNN from catastrophic forgetting.
Edit intent: clarity
Original:  In our system , novel information triggers stimulated firing  , inspired by biological dopamine signals, to boost STDP in the synapses of neurons associated with outlier information.
Revised:  In our Controlled Forgetting Networks (CFNs) , novel information triggers stimulated firing , inspired by biological dopamine signals, to boost STDP in the synapses of neurons associated with outlier information.
Edit intent: clarity
Original:  Our preliminary results on the MNIST dataset validate the capability of such a system to learn successfully over time from an unknown, changing environment, achieving up to 93.88\% accuracyfor a completely disjoint dataset.
Revised:  Our preliminary results on the MNIST dataset validate the capability of CFNs to learn successfully over time from an unknown, changing environment, achieving up to 93.88\% accuracyfor a completely disjoint dataset.
Edit intent: clarity
Original: Network alignment (NA) aims to find a node mapping between compared networks that uncovers regions of high topological similarity , thus allowing for the transfer of functional knowledge between  aligned nodes.
Revised: Network alignment (NA) aims to find a node mapping between compared networks that uncovers similar network regions , thus allowing for the transfer of functional knowledge between aligned nodes.
Edit intent: clarity
Original: Network alignment (NA) aims to find a node mapping between compared networks that uncovers regions of high topological similarity , thus allowing for the transfer of functional knowledge between  aligned nodes.
Revised: Network alignment (NA) aims to find a node mapping between compared networks that uncovers regions of high topological similarity , thus allowing for transfer of functional knowledge between aligned nodes.
Edit intent: fluency
Original: Network alignment (NA) aims to find a node mapping between compared networks that uncovers regions of high topological similarity , thus allowing for the transfer of functional knowledge between  aligned nodes.
Revised: Network alignment (NA) aims to find a node mapping between compared networks that uncovers regions of high topological similarity , thus allowing for the transfer of functional knowledge between the aligned nodes.
Edit intent: coherence
Original:  A likely reason is that current NA methods assume that topologically similar nodes have high functional relatedness .
Revised:  A likely reason is that they assume it is topologically similar nodes have high functional relatedness .
Edit intent: clarity
Original:  A likely reason is that current NA methods assume that topologically similar nodes have high functional relatedness .
Revised:  A likely reason is that current NA methods assume that topologically similar nodes that are functionally related .
Edit intent: clarity
Original:  However, in this study we provide evidence that this assumption does not hold well.
Revised:  However, we show that this assumption does not hold well.
Edit intent: clarity
Original:  As such , a paradigm shift is needed with how the NA problem is approached.
Revised:  So , a paradigm shift is needed with how the NA problem is approached.
Edit intent: coherence
Original:  We find  TARA is able to make accurate predictions.
Revised:  We find that TARA is able to make accurate predictions.
Edit intent: fluency
Original:  Like traditional NA methods, TARA the uses this alignment for the across-species transfer of functional knowledge.
Revised:  Like traditional NA methods, TARA uses this alignment for the across-species transfer of functional knowledge.
Edit intent: fluency
Original:  In this context, we find that TARA outperforms or complements existing state-of-the-art NA methods WAVE, SANA, and PrimAlign .
Revised:  In this context, we find that TARA outperforms existing state-of-the-art NA methods WAVE, SANA, and PrimAlign .
Edit intent: clarity
Original:  To study the intervention effects on pixel-level feature(s) for causal reasoning, we introduce pixel-wise masking and adversarial perturbation.
Revised:  To study the intervention effects on pixel-level features for causal reasoning, we introduce pixel-wise masking and adversarial perturbation.
Edit intent: fluency
Original:  We further provide a first look into the characteristics of discovered CE of adversarially perturbed images generated by gradient-based methods . Experimental results show that CE is a competitive and robust index for understanding DNNs when compared with conventional methods such as class-activation mappings (CAMs) on the ChestX-ray 14 dataset for human-interpretable feature(s) (e.g., symptom) reasoning.
Revised:  We further provide the first look into the characteristics of discovered CE of adversarially perturbed images generated by gradient-based methods . Experimental results show that CE is a competitive and robust index for understanding DNNs when compared with conventional methods such as class-activation mappings (CAMs) on the ChestX-ray 14 dataset for human-interpretable feature(s) (e.g., symptom) reasoning.
Edit intent: fluency
Original:  We further provide a first look into the characteristics of discovered CE of adversarially perturbed images generated by gradient-based methods . Experimental results show that CE is a competitive and robust index for understanding DNNs when compared with conventional methods such as class-activation mappings (CAMs) on the ChestX-ray 14 dataset for human-interpretable feature(s) (e.g., symptom) reasoning.
Revised:  We further provide a first look into the characteristics of discovered CE of adversarially perturbed images generated by gradient-based methods URL Experimental results show that CE is a competitive and robust index for understanding DNNs when compared with conventional methods such as class-activation mappings (CAMs) on the ChestX-ray 14 dataset for human-interpretable feature(s) (e.g., symptom) reasoning.
Edit intent: fluency
Original:  We further provide a first look into the characteristics of discovered CE of adversarially perturbed images generated by gradient-based methods . Experimental results show that CE is a competitive and robust index for understanding DNNs when compared with conventional methods such as class-activation mappings (CAMs) on the ChestX-ray 14 dataset for human-interpretable feature(s) (e.g., symptom) reasoning.
Revised:  We further provide a first look into the characteristics of discovered CE of adversarially perturbed images generated by gradient-based methods . Experimental results show that CE is a competitive and robust index for understanding DNNs when compared with conventional methods such as class-activation mappings (CAMs) on the Chest X-Ray-14 dataset for human-interpretable feature(s) (e.g., symptom) reasoning.
Edit intent: fluency
Original: Microservice architecture has transformed the way developers are building and deploying applications in  nowadays cloud computing centers.
Revised: Microservice architecture has transformed the way developers are building and deploying applications in the nowadays cloud computing centers.
Edit intent: fluency
Original:  This new approach provides increased scalability, flexibility, manageability  and performance while reduces the complexity of the whole software development life cycle ;
Revised:  This new approach provides increased scalability, flexibility, manageability , and performance while reduces the complexity of the whole software development life cycle ;
Edit intent: fluency
Original:  This new approach provides increased scalability, flexibility, manageability  and performance while reduces the complexity of the whole software development life cycle ;
Revised:  This new approach provides increased scalability, flexibility, manageability and performance while reducing the complexity of the whole software development life cycle ;
Edit intent: fluency
Original:  Various microservice platforms have emerged to facilitate the DevOps of containerized services by providing the ability of continuous integration and delivery.
Revised:  Various microservice platforms have emerged to facilitate the DevOps of containerized services by enabling continuous integration and delivery.
Edit intent: clarity
Original:  In this paper, we study and evaluate the provisioning performance of microservice platforms by incorporating the details of all layers ( ie , both micro and macro layers) in the modeling process.
Revised:  In this paper, we study and evaluate the provisioning performance of microservice platforms by incorporating the details of all layers ( i.e. , both micro and macro layers) in the modeling process.
Edit intent: coherence
Original:  In this paper, we study and evaluate the provisioning performance of microservice platforms by incorporating the details of all layers ( ie , both micro and macro layers) in the modeling process.
Revised:  In this paper, we study and evaluate the provisioning performance of microservice platforms by incorporating the details of all layers ( ie , both micro and macro layers) in the modelling process.
Edit intent: fluency
Original: In this paper, we propose and analyse a new adaptive multilevel stochastic collocation method for randomized elliptic PDEs . A hierarchical sequence of adaptive mesh refinements for the spatial approximation is combined with adaptive anisotropic sparse Smolyak grids in the stochastic space in such a way as to minimize  computational cost.
Revised: We propose and analyse a new adaptive multilevel stochastic collocation method for randomized elliptic PDEs . A hierarchical sequence of adaptive mesh refinements for the spatial approximation is combined with adaptive anisotropic sparse Smolyak grids in the stochastic space in such a way as to minimize computational cost.
Edit intent: clarity
Original: In this paper, we propose and analyse a new adaptive multilevel stochastic collocation method for randomized elliptic PDEs . A hierarchical sequence of adaptive mesh refinements for the spatial approximation is combined with adaptive anisotropic sparse Smolyak grids in the stochastic space in such a way as to minimize  computational cost.
Revised: In this paper, we propose and analyse a new adaptive multilevel stochastic collocation method for randomized elliptic PDEs . A hierarchical sequence of adaptive mesh refinements for the spatial approximation is combined with adaptive anisotropic sparse Smolyak grids in the stochastic space in such a way as to minimize the computational cost.
Edit intent: fluency
Original:  Two numerical examples demonstrate the reliability of an error control by adaptive methods and the significant decrease in complexity versus uniform spatial refinements and single-level stochastic sampling methods .
Revised:  Two numerical examples demonstrate the reliability of the error control and the significant decrease in complexity versus uniform spatial refinements and single-level stochastic sampling methods .
Edit intent: clarity
Original:  Two numerical examples demonstrate the reliability of an error control by adaptive methods and the significant decrease in complexity versus uniform spatial refinements and single-level stochastic sampling methods .
Revised:  Two numerical examples demonstrate the reliability of an error control by adaptive methods and the significant decrease in the complexity that arises when compared to single level algorithms and multilevel algorithms that employ adaptivity solely in the spatial discretisation or in the collocation procedure .
Edit intent: clarity
Original: Classical stochasticity demography predicts that environmental stochasticity reduces population growth rates and, thereby, can increase extinction risk.
Revised: Classical stochastic demography predicts that environmental stochasticity reduces population growth rates and, thereby, can increase extinction risk.
Edit intent: fluency
Original:  We provide a detailed energy-delay performance evaluation of previously proposed BSN designs based on Spin-Transfer-Torque (STT ) MRAM and Spin-Orbit-Torque (SOT ) MRAM employing low barrier circular IMA magnets by SPICE simulations.
Revised:  We provide a detailed energy-delay performance evaluation of previously proposed BSN designs based on Spin-Orbit-Torque (SOT ) MRAM and Spin-Orbit-Torque (SOT ) MRAM employing low barrier circular IMA magnets by SPICE simulations.
Edit intent: clarity
Original:  We provide a detailed energy-delay performance evaluation of previously proposed BSN designs based on Spin-Transfer-Torque (STT ) MRAM and Spin-Orbit-Torque (SOT ) MRAM employing low barrier circular IMA magnets by SPICE simulations.
Revised:  We provide a detailed energy-delay performance evaluation of previously proposed BSN designs based on Spin-Transfer-Torque (STT ) MRAM and Spin-Transfer-Torque (STT ) MRAM employing low barrier circular IMA magnets by SPICE simulations.
Edit intent: clarity
Original:  It is known that the groups n V are an infinite family of infinite, finitely presented, simple groups.
Revised:  It is known that the groups nV are an infinite family of infinite, finitely presented, simple groups.
Edit intent: fluency
Original:  We also prove an EPPA analogue of the main results of J. Hubicka and J. Nesetril: " All those Ramsey classes (Ramsey classes with closures and forbidden homomorphisms) " , thereby establishing a common framework for proving EPPA and the Ramsey property.
Revised:  We also prove an EPPA analogue of the main results of J. Hubicka and J. Nesetril: All those Ramsey classes (Ramsey classes with closures and forbidden homomorphisms) " , thereby establishing a common framework for proving EPPA and the Ramsey property.
Edit intent: fluency
Original:  We also prove an EPPA analogue of the main results of J. Hubicka and J. Nesetril: " All those Ramsey classes (Ramsey classes with closures and forbidden homomorphisms) " , thereby establishing a common framework for proving EPPA and the Ramsey property.
Revised:  We also prove an EPPA analogue of the main results of J. Hubicka and J. Nesetril: " All those Ramsey classes (Ramsey classes with closures and forbidden homomorphisms) , thereby establishing a common framework for proving EPPA and the Ramsey property.
Edit intent: fluency
Original:  While a system of a certain depth is needed, since depth 1 systems only allows to solve problems in \mathbf{P^{\boldsymbol#P , it was until now unclear if a linear depth was, in fact, necessary.
Revised:  While a system of a certain depth is needed, since depth 1 systems only allows to solve problems in \mathbf{P^{\#P , it was until now unclear if a linear depth was, in fact, necessary.
Edit intent: fluency
Original:  The experimental results based on data from a real e-commerce platform demonstrate the effectiveness of the proposed framework .
Revised:  The experimental results based on a real e-commerce platform demonstrate the effectiveness of the proposed framework .
Edit intent: clarity
Original:  In practical recommendation sessions, users will sequentially access multiple scenarios, such as the entrance pages and the item detail pages, and each scenario has its own recommendation strategy .
Revised:  In practical recommendation sessions, users will sequentially access multiple scenarios, such as the entrance pages and the item detail pages, and each scenario has its specific characteristics .
Edit intent: clarity
Original:  We propose a multi-agent reinforcement learning based approach (DeepChain), which can capture the sequential correlation among different scenarios and jointly optimize multiple recommendation strategies.
Revised:  We propose a multi-agent RL-based approach (DeepChain), which can capture the sequential correlation among different scenarios and jointly optimize multiple recommendation strategies.
Edit intent: clarity