wanyu/IteraTeR_v2 huggingface dataset:
Original: In this paper we are interested in the quantitative analysis of the compaction ratio for two classical families of trees: recursive trees and plane binary increasing tree .
Revised: In this paper we are interested in the quantitative analysis of the compaction ratio for two classical families of trees: recursive trees and plane binary increasing trees .
Edit intent: fluency
Original:  Once a tree of size n is compacted by keeping only one occurrence of all fringe subtrees appearing in the tree the resulting graph contains only O(n / \log n) nodes.
Revised:  Once a tree of size n is compacted by keeping only one occurrence of all fringe subtrees appearing in the tree the resulting graph contains only O(n / \ln n) nodes.
Edit intent: clarity
Original:  This result must be compared to classical results of compaction in the families of simply generated trees, where the analog result states that the compacted structure is of size of order n / \sqrt{\log n . We end the paper with an experimental quantitative study, based on a prototype implementation of compacted binary search trees, that are modeled by plane binary increasing trees.
Revised:  This result must be compared to classical results of compaction in the families of simply generated trees, where the analogous result states that the compacted structure is of size of order n / \sqrt{\log n . We end the paper with an experimental quantitative study, based on a prototype implementation of compacted binary search trees, that are modeled by plane binary increasing trees.
Edit intent: fluency
Original: In this paper we are interested in the quantitative analysis of the compaction ratio for two classical families of trees: recursive trees and plane binary increasing trees.
Revised: We are interested in the quantitative analysis of the compaction ratio for two classical families of trees: recursive trees and plane binary increasing trees.
Edit intent: coherence
Original:  More formally, asymptotically, for a random tree with n nodes, its depth is of order \ln n.
Edit intent: coherence
Original:  We end the paper with an experimental quantitative study , based on a prototype implementation of compacted binary search trees , that are modeled by plane binary increasing trees.
Revised:  We end the paper with an experimental quantitative study , based on a prototype implementation of compacted binary search trees that are modeled by plane binary increasing trees.
Edit intent: fluency
Original: Different areas of the brain such as the cortex and the prefrontal cortex show a great recurrence in their connections, even in early sensory areas.
Revised: Different areas of the brain such as the cortex and the prefrontal cortex show great recurrence in their connections, even in early sensory areas.
Edit intent: fluency
Original:  It is essential to understand the dynamics behind the models because they are used to build different hypotheses about the functioning of the areas and also to explain experimental results.
Revised:  It is essential to understand the dynamics behind the models because they are used to build different hypotheses about the functioning of brain areas and to explain experimental results.
Edit intent: clarity
Original:  Present work focuses on the study of the dynamics of recurrent neural networks trained to perform Boolean-type operations with temporal stimuli that emulate being sensory signals.
Revised:  Present work focuses on the study of the dynamics of recurrent neural networks trained to perform Boolean-like tasks with temporal stimuli that emulate being sensory signals.
Edit intent: clarity
Original: Different areas of the brain such as the cortex and  the prefrontal cortex  show great recurrence in their connections, even in early sensory areas.
Revised: Different brain areas, such as the cortex and the prefrontal cortex show great recurrence in their connections, even in early sensory areas.
Edit intent: clarity
Original: Different areas of the brain such as the cortex and  the prefrontal cortex  show great recurrence in their connections, even in early sensory areas.
Revised: Different areas of the brain such as the cortex and , more specifically, the prefrontal cortex show great recurrence in their connections, even in early sensory areas.
Edit intent: clarity
Original: Different areas of the brain such as the cortex and  the prefrontal cortex  show great recurrence in their connections, even in early sensory areas.
Revised: Different areas of the brain such as the cortex and the prefrontal cortex , show great recurrence in their connections, even in early sensory areas.
Edit intent: fluency
Original:   Several approaches and methods based on trained networks have been proposed to model and describe these systems .
Revised:  Several approaches and methods based on trained networks have been proposed to model and describe these regions .
Edit intent: clarity
Original:  Present work focuses on the study of the dynamics of recurrent neural networks trained to perform Boolean-like tasks with temporal stimuli that emulate being sensory signals.
Edit intent: coherence
Original:  The patterns in the distribution of the eigenvalues of the recurrent weight matrix ware studied and properly related to the dynamics  .
Revised:  The patterns in the distribution of the eigenvalues of the recurrent weight matrix were studied and properly related to the dynamics .
Edit intent: fluency
Original: We develop a semi-supervised learning (SSL) approach for acoustic source localization based on deep generative modeling . Source localization in reverberant environments remains an open challenge, which machine learning (ML) has shown promise in addressing.
Revised: We propose a semi-supervised learning (SSL) approach for acoustic source localization based on deep generative modeling . Source localization in reverberant environments remains an open challenge, which machine learning (ML) has shown promise in addressing.
Edit intent: clarity
Original: We develop a semi-supervised learning (SSL) approach for acoustic source localization based on deep generative modeling . Source localization in reverberant environments remains an open challenge, which machine learning (ML) has shown promise in addressing.
Revised: We develop a semi-supervised localization approach based on deep generative modeling . Source localization in reverberant environments remains an open challenge, which machine learning (ML) has shown promise in addressing.
Edit intent: clarity
Original: We develop a semi-supervised learning (SSL) approach for acoustic source localization based on deep generative modeling . Source localization in reverberant environments remains an open challenge, which machine learning (ML) has shown promise in addressing.
Revised: We develop a semi-supervised learning (SSL) approach for acoustic source localization based on deep generative modeling . Source localization in reverberant environments remains a challenge, which machine learning (ML) has shown promise in addressing.
Edit intent: clarity
Original:  While there are often large volumes of acoustic data in reverberant environments, the labels available for supervised learning are usually few.
Revised:  Even with large data volumes, the number of labels available for supervised learning are usually few.
Edit intent: clarity
Original:  The VAE is trained to generate the phase of relative transfer functions (RTFs), in parallel with classifier training , on both labelled and unlabeled RTF samples.
Revised:  The VAE is trained to generate the phase of relative transfer functions (RTFs), in parallel with classifier training , on both labeled and unlabeled RTF samples.
Edit intent: fluency
Original: We propose a semi-supervised localization approach based on deep generative modeling with variational autoencoders ( VAE ).
Revised: We propose a semi-supervised localization approach based on deep generative modeling with variational autoencoders ( VAEs ).
Edit intent: fluency
Original:  We address this issue by perform semi-supervised learning (SSL) with convolutional VAEs.
Revised:  We address this issue by performing semi-supervised learning (SSL) with convolutional VAEs.
Edit intent: fluency
Original:  We find that VAE-SLL can outperform both SRP-PHAT and CNN in label-limited scenarios.
Revised:  We find that VAE-SSL can outperform both SRP-PHAT and CNN in label-limited scenarios.
Edit intent: clarity
Original:  To address the above issues, we propose  interpretable and efficient Heterogeneous Graph Convolutional Network (ie-HGCN) to learn representations of nodes in HINs.
Revised:  To address the above issues, we propose an interpretable and efficient Heterogeneous Graph Convolutional Network (ie-HGCN) to learn representations of nodes in HINs.
Edit intent: fluency
Original:  To address the above issues, we propose  interpretable and efficient Heterogeneous Graph Convolutional Network (ie-HGCN) to learn representations of nodes in HINs.
Revised:  To address the above issues, we propose interpretable and efficient Heterogeneous Graph Convolutional Network (ie-HGCN) to learn the representations of objects in HINs.
Edit intent: clarity
Original:  It automatically extracts useful meta-paths for each node from all possible meta-paths (within a length limit determined by the model depth ), which brings good model interpretability.
Revised:  It automatically extracts useful meta-paths for each object from all possible meta-paths (within a length limit determined by the model depth ), which brings good model interpretability.
Edit intent: clarity
Original:  It automatically extracts useful meta-paths for each node from all possible meta-paths (within a length limit determined by the model depth ), which brings good model interpretability.
Revised:  It automatically extracts useful meta-paths for each node from all possible meta-paths (within a length limit ), which brings good model interpretability.
Edit intent: clarity
Original:  It directly takes the entire HIN as input and avoids intermediate HIN transformation .
Revised:  It can also reduce the computational cost by avoiding intermediate HIN transformation .
Edit intent: clarity
Original:  Extensive experimental results on three real-world networks demonstrate the superiority of ie-HGCN over  state-of-the-art methods.
Revised:  Extensive experimental results on three real-world networks demonstrate the superiority of ie-HGCN over the state-of-the-art methods.
Edit intent: fluency
Original:  So far, two policies enforce a robust execution of MAPF plans taken as input , namely, either by forcing agents to synchronize , or by executing plans while preserving temporal dependencies.
Revised:  So far, two policies enforce a robust execution of MAPF plans taken as input : either by forcing agents to synchronize , or by executing plans while preserving temporal dependencies.
Edit intent: coherence
Original:  So far, two policies enforce a robust execution of MAPF plans taken as input , namely, either by forcing agents to synchronize , or by executing plans while preserving temporal dependencies.
Revised:  So far, two policies enforce a robust execution of MAPF plans taken as input , namely, either by forcing agents to synchronize or by executing plans while preserving temporal dependencies.
Edit intent: fluency
Original:  This paper proposes a third approach, called time-independent planning, which is both online and distributed.
Revised:  This paper proposes an alternative approach, called time-independent planning, which is both online and distributed.
Edit intent: clarity
Original:  In reality, users hope to reduce the cost , while keeping the delay in an acceptable range  .
Revised:  In reality, users hope to reduce the cost while keeping the delay in an acceptable range .
Edit intent: fluency
Original:  How to make a proper cost-delay tradeoff according to the user's preference is the key issue in the design of Wi-Fi offloading strategy.
Revised:  How to make a proper cost-delay tradeoff according to the user's preference is the key issue in the design of the offloading strategy.
Edit intent: clarity
Original:  We model this strategy as a three-state M/MMSP/1 queueing system, of which the service process is a Markov modulated service process (MMSP), and obtain the structured solutions by establishing a hybrid embedded Markov chain.
Revised:  We model the strategy as a three-state M/MMSP/1 queueing system, of which the service process is a Markov modulated service process (MMSP), and obtain the structured solutions by establishing a hybrid embedded Markov chain.
Edit intent: fluency
Original:  Our experiments show that our model achieves  28\% relative gain over state-of-the-art sequential models and 2\times higher accuracy than syntactic models that learn to generate the edited code instead of modeling the edits directly.
Revised:  Our experiments show that our model achieves a 28\% relative gain over state-of-the-art sequential models and 2\times higher accuracy than syntactic models that learn to generate the edited code instead of modeling the edits directly.
Edit intent: fluency
Original:  Our experiments show that our model achieves  28\% relative gain over state-of-the-art sequential models and 2\times higher accuracy than syntactic models that learn to generate the edited code instead of modeling the edits directly.
Revised:  Our experiments show that our model achieves 28\% relative gain over state-of-the-art sequential models and 2x higher accuracy than syntactic models that learn to generate the edited code instead of modeling the edits directly.
Edit intent: fluency
Original:  Our experiments show that our model achieves  28\% relative gain over state-of-the-art sequential models and 2\times higher accuracy than syntactic models that learn to generate the edited code instead of modeling the edits directly.
Revised:  Our experiments show that our model achieves 28\% relative gain over state-of-the-art sequential models and 2\times higher accuracy than syntactic models that learn to generate the edited code , as opposed to modeling the edits directly.
Edit intent: clarity
Original:  We make our code, dataset, and trained models publicly available .
Revised:  Our code, dataset, and trained models publicly available .
Edit intent: clarity
Original:  Yet, we show that the time-aggregated representation of such systems over sufficiently large periods can be meaningfully embedded into the hyperbolic space, using existing methods developed for traditional  complex networks.
Revised:  Yet, we show that the time-aggregated representation of such systems over sufficiently large periods can be meaningfully embedded into the hyperbolic space, using methods developed for traditional complex networks.
Edit intent: clarity
Original:  Afterwards, we present a comparative study on seven different distributed deep learning techniques on a 32-GPU cluster with both 10Gbps Ethernet and 100Gbps InfiniBand .
Revised:  Afterwards, we present a comparative study on seven different distributed deep learning techniques on a 32-GPU cluster with 100Gbps InfiniBand .
Edit intent: clarity
Original:  We finally discuss some challenges and open issues for possible future investigations.
Revised:  We finally discuss some challenges and open issues for further investigations.
Edit intent: clarity
Original:  To be clear, the goal of this work is to propose a mechanism for providing an information preserving mapping that users can learn to use to see (or perceive other information) using their auditory system.
Edit intent: coherence
Original:  A generative adversarial network  is then used to find a distance preserving map from this metric space of feature vectors into the metric space defined by a target audio dataset and a mel-frequency cepstrum-based psychoacoustic distance metric.
Revised:  A generative adversarial network (GAN) is then used to find a distance preserving map from this metric space of feature vectors into the metric space defined by a target audio dataset and a mel-frequency cepstrum-based psychoacoustic distance metric.
Edit intent: clarity
Original:  The GAN successfully found a metric preserving mapping, and in human subject tests, users were able to successfully classify images of facesusing only the audio output by our model .
Revised:  The GAN successfully found a metric preserving mapping, and in human subject tests, users were able to accurately classify audio translations of faces .
Edit intent: clarity
Original:  This work describes a novel technique for leveraging machine learned feature embeddings to translate visual (and other types of) information into a perceptual audio domain, allowing users to perceive this information using only their aural faculty.
Revised:  This work describes a novel technique for leveraging machine-learned feature embeddings to translate visual (and other types of) information into a perceptual audio domain, allowing users to perceive this information using only their aural faculty.
Edit intent: fluency
Original:  For both target audio metrics, the GAN successfully found a metric preserving mapping, and in human subject tests, users were able to accurately classify audio translations of faces.
Revised:  For both target audio metrics, the GAN successfully found a metric preserving mapping, and in human subject tests, users were able to accurately classify audio sonifications of faces.
Edit intent: fluency
Original:  Our approach also requires a weighting scheme that allows us to compare different positions .
Revised:  Our approach also requires a weighting scheme to compare different positions .
Edit intent: clarity
Original:  Our approach also requires a weighting scheme that allows us to compare different positions .
Revised:  Our approach also requires a weighting scheme that allows us to compare different achievements .
Edit intent: clarity
Original:  Inequality has not increased among the elite clubs and between the countries , however, it has changed within some national associations .
Revised:  Inequality has not increased among the elite clubs and between the national associations , however, it has changed within some national associations .
Edit intent: clarity
Original: Standard correlation based imaging methods in aeroacoustics assume that the estimated cross correlation matrix is superimposed with additive white noise.
Revised: This article discusses aeroacoustic imaging methods based on correlation measurements in the frequency domain. Standard methods in this field assume that the estimated cross correlation matrix is superimposed with additive white noise.
Edit intent: clarity
Original: Standard correlation based imaging methods in aeroacoustics assume that the estimated cross correlation matrix is superimposed with additive white noise.
Revised: Standard correlation based imaging methods in aeroacoustics assume that the estimated correlation matrix is superimposed with additive white noise.
Edit intent: clarity
Original:  The covariance matrix of correlation data is given in terms of forth order moments.
Revised:  The covariance matrix of correlation data is given in terms of fourth order moments.
Edit intent: fluency
Original: Online manipulation of information has become  prevalent in recent years as  disinformation campaigns seek to  polarize political topics .
Revised: Online manipulation of information has become more prevalent in recent years as disinformation campaigns seek to polarize political topics .
Edit intent: clarity
Original: Online manipulation of information has become  prevalent in recent years as  disinformation campaigns seek to  polarize political topics .
Revised: Online manipulation of information has become prevalent in recent years as disinformation campaigns seek to influence and polarize political topics .
Edit intent: clarity
Original:  We examine the usefulness of these coordination patterns for identifying the activity of a disinformation campaign from other Twitter activity.
Revised:  We examine the usefulness of these coordination patterns for identifying the activity of a disinformation campaign from legitimate Twitter activity.
Edit intent: clarity
Original:  In doing this meta-analysis ,  we show that although coordination patterns could be useful for detecting disinformation activity, further analysis is needed to determine the community's intention .
Revised:  In doing this meta-analysis , we show that while coordination patterns could be useful for detecting disinformation activity, further analysis is needed to determine the community's intention .
Edit intent: coherence
Original:  In doing this meta-analysis ,  we show that although coordination patterns could be useful for detecting disinformation activity, further analysis is needed to determine the community's intention .
Revised:  In doing this meta-analysis , we show that although coordination patterns could be useful for providing evidence of disinformation activity, further analysis is needed to determine the community's intention .
Edit intent: clarity
Original:  In doing this meta-analysis ,  we show that although coordination patterns could be useful for detecting disinformation activity, further analysis is needed to determine the community's intention .
Revised:  In doing this meta-analysis , we show that although coordination patterns could be useful for detecting disinformation activity, further investigation is needed to determine the community's intention .
Edit intent: clarity
Original: We propose a compartmental model based on genetic fitting algorithm to estimate early stage COVID-19 epidemic dynamics in Algeria .
Revised: We propose a compartmental model based on genetic fitting algorithm is proposed to estimate COVID-19 epidemic dynamics in Algeria .
Edit intent: clarity
Original: We propose a compartmental model based on genetic fitting algorithm to estimate early stage COVID-19 epidemic dynamics in Algeria .
Revised: We propose a compartmental model based on genetic fitting algorithm to estimate early stage COVID-19 outbreak dynamics in Algeria .
Edit intent: clarity
Original:  Moreover, we advance approximate nowcast and forecast of the  non-measurable asymptotic infected portion of the susceptible population and the incidence of disease as well as quarantined active cases . Epidemic peak-time is estimated and CFR and IFR are calculated.
Revised:  Moreover, we advance approximate nowcast and forecast of the non-measurable asymptomatic infected portion of the susceptible population and the incidence of disease as well as quarantined active cases . Epidemic peak-time is estimated and CFR and IFR are calculated.
Edit intent: clarity
Original:  Information provided by our model could help establish a realistic assessment of the situation for the time being and near future in order to apply the appropriate public health measures.
Revised:  Information provided by this study could help establish a realistic assessment of the situation for the time being and near future in order to apply the appropriate public health measures.
Edit intent: clarity
Original:  Using a cross-validation method to overcome the overfitting problem , we advance approximate nowcast and forecast of the epidemic evolution including key epidemic parameters and non-measurable asymptomatic infected portion of the susceptible population.
Revised:  Using a cross-validation method to overcome the overfitting problem , we advance approximate nowcast and forecast of epidemic evolution including key epidemic parameters and non-measurable asymptomatic infected portion of the susceptible population.
Edit intent: fluency
Original:   Basic reproduction number on Feb. 25th is estimated to 3.78 (95\% CI 3.033-4.53) and effective reproduction number on May 24th after three months of the outbreak is estimated to 0.651 (95\% CI 0.539 - 0.761 ).
Revised:  Basic reproduction number on Feb. 25th is estimated to 3.78 (95\% CI 3.033-4.53) and effective reproduction number on May 24th after three months of the outbreak is estimated to 0.651 (95\% CI 0.539 -0.761 ).
Edit intent: fluency